How to use CDP to improve your conversion rates

Posted on September 16, 2020 by Arena

Customer Data Platforms can fuel your marketing efforts, help you improve customer experience, and maximize ROI. This post will teach you how to embrace CDPs on daily marketing activities to potentialize results.

Marketing leaders’ job has become more challenging year after year with the rise of new content channels, connected devices, and sales formats. In a competitive scenario, acquiring and retaining requires more than just a good strategy. We live in the age of tailor-made communication, where there is no room for basic and generic marketing anymore.

No wonder companies from all segments have searched for ways to make their marketing approach more personal and cost-effective at the same time, which requires the right tools and best practices for data management.

A report from the CMO Council shows that marketers worldwide see the execution of a data-driven strategy as their primary challenge to have a unified view of customer experience (CX) across different touchpoints, according to 38% of marketers consulted for the study.

According to 30% of respondents, another challenge is to abandon customer data silos, which make data inaccessible across the organization. Even though marketers can count on CRM and DMP platforms to understand some of the customers’ engagement and pain points, the problems above can only be truly solved through robust data management platforms.

In that sense, digitally mature marketers have specifically reached out to Customer Data Platforms (CDPs) in order to understand customers better and offer them a better customer experience.

Ultimately, a CDP can boost brands’ ROI and help them maximize conversion rates. This post will explore the concept of CDP, how it differs from other data platforms, and how marketers can use them to improve their results.

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What is CDP?

A Customer Data Platform (CDP) is software that centralizes customer data from different data systems and customer-facing platforms. It collects quantitative and qualitative information from diverse touchpoints with customers, offering a friendly interface that allows companies to access customer data from different departments easily.

Customer Data Platforms combine customers’ demographic data, buying history, hobbies, transactional data, social media preferences, interactions with call centers, navigation data, and more.

They work mostly with first-party data, crossing information from Customer Relationship Management (CRM) systems, Data Management Platforms (DMPs), and customers’ direct interactions with your brand through support channels, payment methods, social media, and different devices.

The idea is to combine Personally Identifiable Information (PII) and build a unified view of individual customers – also called Unified Customer Profiles. Since the data match is consistent across different platforms, data is even more reliable than other platforms.

A few examples of data collected by CDPs:

Purchases
Renewal dates
Customer and product value
Abandoned baskets
Stage in the conversion funnel
Products and categories searched and browsed
Store and website visits
Content and channel preferences
Social media interactions
Customer support interactions
Email opening rates
Lifestyle preferences
Contact information

These are just a few examples. The possibilities are endless! In reality, your company can choose to plug in any data system to the CDP. All data can then be stitched to the unique customer profile, allowing marketing teams to work on segmentation and personalization.

Typically, CDPs are used with five purposes in mind:

Improving customer identity resolution
Data cleansing and enrichment
Data Centralization and integration
Audience data analytics
Marketing segmentation and optimization

CDP vs. CRM vs. DMP: beware of the difference

The marketing industry has long relied on acronyms to refer to metrics and tools. The data management realm is specifically pervaded by similar acronyms that comprehend entirely different things, such as CDP, DMP, and CRM.

Most marketers will agree that it is essential to manage data through one of these: Data Management Platforms (DMP), Customer Data Platforms (CDP), and Customer Relationship Management (CRM). However, not all of them might understand how each of them works.

All three platforms share a list of common assets: they aim to establish a Single Customer View (SCV), use data for audience activation, and offer reporting, analysis, and optimization tools. Such platforms will often work side-by-side, but CDPs, DMPs, and CRM show many differences despite their similarities.

We have already explained how CDPs work, now let’s explore how DMPs and CRM systems compare.

Data Management Platforms

The DMP is mainly used to drive advertising campaigns, relying almost exclusively on anonymous data from cookies, devices, and IP addresses. It captures generic data such as when users visited your website and how long they spent on the page.

Then, such navigation information is used to target ads according to customer behavior to reach customers who match the brand’s target profiles – a process called probabilistic matching. A DMP can monitor campaign strategies, identify conversion points and personalize campaigns according to them.

Main differences with CDP

CDPs work with both anonymous and known individuals, while DMPs work almost exclusively with anonymous entities and unknown customers
In CDPs, database updates happen in real-time, while DPMs only allow scheduled database updates
CDPs are based on historical integrated customer records, which means you can store customer data for however long. DMPs, however, store data for shorter periods, usually up to 90 days (a cookie’s lifespan) to target ads and build lookalike audiences
DMPs are used only for managing digital advertising, while CDPs can be used across an entire organization, including for sales and customer success

Customer Relationship Management

CRM systems are typically used by sales teams, storing personal information from known customers – such as contacts, demographics, transaction data, notes about customers made by sales, CRM, and customer success teams.

Softwares alike are used to track leads, understand the sales pipeline, and for driving customer engagement. CRMs don’t store anonymous user behavior.

Mains differences with CDPs

CRMs aren’t built to ingest large volumes of data from different sources, like CDPs
CRMs only analyze personal data from known customers, such as name, age, and contacts, but not navigation behavior – something tracked by CDPs
CRMs do not connect customers’ actions through different channels and devices, and so is not able to follow the customer journey like a CDP

Using CDPs to improve marketing ROI

Successful marketing campaigns don’t embrace just a few channels, but a complex constellation of touchpoints with your audience. Acting over this constellation, however, can sometimes be challenging. A survey from the Harvard Business Review shows that only 3% of marketers believe they are able to act on all of the customer data they collect. Another 21% say they can act on very little of it.

As we discussed earlier, CDPs can play a significant role in connecting customers’ fragmented journey. But beyond that, they can help you make smarter investment decisions, improve ROI, conversion rates, and Customer Acquisition Costs (CAC).

Also, CDPs can automate and eliminate repetitive, time-consuming tasks from marketing professionals’ routines, making daily marketing activities more agile.

A few ways a CDP can improve business results:

Accurate personalization

In the age of recommendation algorithms, customers expect personalized experiences everywhere. Marketers should avoid at all costs making wrongful recommendations or serve ads that are not relevant within the user’s journey.

Because CDPs break data silos and integrate marketing efforts across different channels, they help brands to deliver the right messages, at the right time and in the right channels for customers. For instance, you could exclude users that recently bought your products or those who are not likely to engage with your ad campaigns from your targeting strategy, focusing on users who are likely to engage.

Better budget allocation equals better leads

CDPs allow brands to acknowledge what products customers show interest in, their purchase intent, and how likely they are to churn. They can also find out their favorite interaction channels and stage in the customer journey. From there, it gets easier to allocate ad dollars and improve content strategies on every channel.

As a result, CDPs help attract more qualified leads, optimize marketing budgets, reduce customers’ acquisition costs (CAC), and improve conversion rates.

More qualified data

Marketing leaders are shifting their attention from second and third-party data to first-party data. As privacy and compliance regulations become more consolidated, organizations increasingly seek to work with their own, integrated data – something Customer Data Platforms can help them with.

Driving data-driven sales

Customer Data Platforms can help sales teams upsell or cross-sell products based on customers’ recent purchases or search intent. By having access to enriched, accurate data, salespeople can better design retargeting and churn prevention campaigns through email, mobile, and other channels.

More autonomy and agility to marketing professionals

Depending on other departments for reports and insights can be time-consuming and unproductive for marketing teams, since not everyone is on the same page about marketing needs. CDPs are useful to many areas within a company, but every team can shape their use according to specific goals while having access to all kinds of company data.

According to CMO Council, 67% of marketers believe speed is one of the primary benefits of data-driven marketing, resulting in quickly executing their campaigns. Through CDPs, teams can scale marketing efforts and get new processes started faster.

Benefits from CDPs don’t stop there. In this post, you can check 20 ways CDPs can be used in marketing.

Integrations and key assets of CDPs

In a fragmented media and advertising landscape, marketers want tools to give them more control over events in their channels. CDPs allow companies to integrate different systems and deploy data with customers’ profiles to many marketing and customer relationship platforms.

Most Customer Data Platforms typically offer connector marketplaces where marketers can set up integrations in just a few minutes. However, the depth and amount of possible integrations can vary according to the CDP you choose.

Areas of integration offered by CDPs usually include:

Advertising: Integrations to DSPs, Facebook Ads Manager, Google Marketing Platform, and more
Analytics and AB Testing platforms: Google Analytics, Adobe Analytics, Optimizely, MixPannel, etc
Email and marketing automation tools: MailChimp, Hubspot, Sendgrid, Salesforce Marketing Cloud, SMS tools, and others

When connected to other systems, CDPs can deploy customers’ profiles to marketing tools (also called delivery platforms), enabling the planning and distribution of campaigns and personalized messages.

The amount of tools companies will connect to their CDPs will depend on the specifics of their business. Large businesses are likely to connect more tools than small companies, for instance.

Before adopting a CDP, be prepared

Yes, a Customer Data Platform can do wonders for your marketing strategy, but you need to feed it for it to work properly. CDPs won’t effectively integrate customer touch points if they can’t truly access data about the whole customer’s journey.

If you want a seamless, functioning CDP, it has to be fueled with multiple data records from clients – not just a few sources. A Customer Data Platform should gather historical data and freshly-collected data about their interactions with your brand.

That’s how it can create a satisfactory customer profile and identity resolution (when the system matches records from different data sources and connects them to single customers). But why do you need identity resolution?

A customer might interact with your brand through several channels and devices, but sometimes CDPs will interpret different data points as if belonging to other customers.

So, not having enough data or having insufficient data prevents you from having the perfect picture of single customers, resulting in wasted investments, bad customer experience (CX), and poor marketing results.

In a nutshell: the more data sources your CDP can gather, the better. If your company only provides a few data points, your unified customer view might not be so complete, resulting in gaps in customer experience and poor conversion and engagement results.

Want to learn more about CDPs?

As we have seen, Customer Data Platforms are complex, and so is the process of choosing the best one for your company.

If you want to dig deeper into the benefits of CDPs for marketing, we recommend downloading Arena’s “Customer Data Platform 2022” ebook. In this complete ebook, you will find more valuable information about how CDPs work and how they can be incorporated through every step of marketing.

If you want to learn the specifics about Arena’s CDP, feel free to reach out to one of our consultants.

How Customer Data Platform is reinventing customer relations

Posted on July 29, 2020 by Natalia Gaal

Using a Customer Data Platform is helping companies to focus obsessively on their customers and benefit from their engagement.

You need to know your customers—this isn’t any news. It doesn’t matter if you want to make them more engaged, optimize your budget for campaigns, or improve your ROI.

Customer accurate information is at the heart of every company and should be treated correctly to generate powerful outcomes from your marketing efforts.

If you don’t have a consistent understanding of your consumers, then all your strategies will likely go down the drain.

But how exactly do you get to act like you know your customers? The answer is simple: by managing their data.

To treat data thoroughly and reach your customer relationship goals, you might come across the need to use the right technologies. This is when the Customer Data Platform (CDP) walks in.

A customer data platform monitors and tracks multiple data sources to bring relevant information to a single hub that is easy to access and understand.

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Once implemented, CDPs collect, integrate, manage, and analyze customer data continuously. These automated processes help many teams to focus on solving complex problems that require a human brain. At the same time, a Customer Data Platform brings current, real-time data to be leveraged and turned into marketing master plans.

Why do companies use Customer Data Platforms?

Is there a reason why companies implement a Customer Data Platform in their business models? Yes, many.

According to Gartner, plenty of marketers look to customer data-driven strategies to deliver growth. For example, marketers invested two-thirds of their budget in supporting relationships with their customers in 2017 and 2018.

Still, they have found the technology they were using to be frustrating—until CDP’s unique upshots came out as a solution to their problems.

A Customer Data Platform reaches out for several channels and concentrates real-time data in a single place your team can access whenever it is convenient.

This stimulates a collaborative work environment and speeds the pace of operational routines. Customer Data Platforms are also known for making marketers’ lives less complicated since automating workflows would take too many working hours to be accomplished.

The other reason companies use Customer Data Platforms is that they are much more than a simple database. According to the CDP Institute, the ideal Customer Data Platform should contain five essential capabilities:

Absorb data from any source
Give full details of ingested data
Store data without end and frequently
Create unified profiles (such as personas)
Share data with any system that needs it

All of the five skills above drive brands into having a vigorous understanding of their customer base by collecting and analyzing reliable data across their marketing channels.

What types of data does a Customer Data Platform assess?

The types of customer data assessed by a CDP can be quantitative and qualitative.

In other words, by using a CDP, you will be able to figure out:

How to identify your customers, using personal data
How to interact with your customers, using interactional data
How customers expect to be impacted by experiences, using behavioral data
How your customers perceive your brand, using attitudinal data

The datasets above are being generated at all times in any digital environment and should be combined to create an unbeatable and absolute customer understanding.

But how do CDPs gather such different information?

They reach out to analytics reports, engagement measures, support occurrences, eCommerce metrics, and customer feedback (to quote a few), to maximize your knowledge and equip you with fast, accurate moves.

This is the main reason why CDPs are revolutionizing the way brands communicate with customers and vice-versa. They are an unlimited and underlying base for companies to create remarkable customer experiences and increase customer engagement in a way we have never seen before.

The effects of CDP in customer experience

A Customer Data Platform grants companies an invincible competitive advantage: passionate customers who keep being fed with reasons to remain brand loyal.

Historically, we can see customers have adopted technologies faster than the brands they interact with. This made companies try to embrace digital transformation technologies focused on customer experience to reach out to consumers where they are and how they want.

Expanding your brand’s online presence to talk to customers in multiple channels isn’t enough, in any case. Any company can create an Instagram account and interact with its audience then and there, right?

However, the ones that truly stand out are focused on delivering personalized, relevant, well-designed interactions that take place as soon as customers want.

Tailored customer interactions should happen anywhere, at any time. This is the main reason why organizations around the world are digitizing their business models. According to the Boston Consulting Group Research, personalization will drive an $800 billion revenue shift to the top 15% of companies that work best on it, in only three industries.

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I know what you’re thinking: that’s much profit for a small number of companies—and yes, it is. Even so, it sounds like a warning: companies that aren’t ready to turn personalization ordinary in their marketing campaigns, will be left stranded.

As you know, doing a great job on personalization is all about knowing everything there is to know about your customers and quickly activating your knowledge when needed.

Can you notice any coincidences between this goal and the usage of a CDP?

How CDPs are reinventing customer relations

Suppose you’re leading digital initiatives to deepen the relationship between your customers and your brand. In that case, you should pay attention to the changes CDPs are leading in customer management and how it differs from other popular marketing tools.

A Customer Data Platform is way more complete than a Customer Relationship Management (CRM) software.

CRM will tell you how to personalize and improve existing customer relationships. Meanwhile, a CDP will do that and indicate how you can promote products and services and what you should do to attract new customers.

With the new untapped potential CDPs unleash, companies are increasingly confident in meeting market changes and customers’ preferences. Hesitating in our competitive world is no longer an option, and data-driven marketing plays a vital role in feeding companies with unequivocal customer interactions.

Ahead, we have numbered a few ways Customer Data Platforms reinvent customer relations to inspire you and your team.

1. CDP enables segmentation opportunities

While it simultaneously optimizes strategies, a CDP provides companies with a 360-degree view of customers to act on an essential customer experience requirement: segmentation.

Segmenting customers by specific traits, behaviors, attitudes, and others is a fantastic opportunity to create tailored marketing touchpoints throughout their journey and attract them with meaningful content.

When based on data, segmentation is an unmatched growth engine that encourages customer loyalty and enhances profitability.

2. A CDP gives your interactions a personal touch

Similarly, you can not spell personalization without customer data.

Owning a Customer Data Platform will help you quickly access reliable information to customize customer interactions, making your consumers feel special, and long-term relationships feasible.

Many companies are using CDP for Customer Data Management. See below how their tactics connect with top-level personalization:

3. A CDP enriches customer relationships

There isn’t enough emphasis on how knowing your customers is essential for customer relations.

People expect to be treated accordingly to their visions as much as they wish to connect emotionally with brands. A single miscommunication can harm brand-customer relationships irreparably.

As soon as you have a panoramic view of your customers’ habits, preferences, needs, and issues, you should feel more confident in building specific touchpoints that elevate the customer journey and make customers want to hang around you for longer.

Owning a Customer Data Platform will also measure your customer loyalty programs’ effectiveness and help you find what groups of customers deserve attention according to their life cycle.

4. A CDP is agile

Agile methodologies are the perfect response to a world that is changing every day, every hour. CDPs consider our ever-changing environment and let your team access specific data whenever it needs, contributing to an agility mindset.

Agility layers can be used to shape CDP frameworks that adjust to your company’s infrastructure, turning data sharing into a reality. CDPs also absorb data from other internal systems, like CRMs and Data Management Platforms (DMPs), you might already have.

Apart from that, CDPs update in real-time. This allows you to assess micro-moments data and instantly operationalize it.

5. A CDP ingests data from any source

Your customers are everywhere these days, right? You can find them on social media, navigate your website, read your emails, download your app, and take a look at your physical store. The interaction possibilities between your customer and your brand are countless.

If truth be told, it truly doesn’t matter where your customers are and what they’re doing. Whether they’re reading your blog or using your chatbot, data is being generated at all times, collected from simple interactions to complex operations.

A Customer Data Platform reaches out to any source of information, from Live Chats to SEO, from blogging to Twitter, from customer loyalty to affiliate marketing programs to provide your company with everything you know about your potential and current consumers.

6. A CDP elevates digital transformation

Simply, a digital transformation process should rely on—and a lot!—on a Customer Data Platform.

By watching digital-native organizations, it becomes clear that many technologies can be embedded to digitize businesses.

However, it is worthless to implement technologies that don’t accurately connect with customers’ needs. Digital transformation starts and ends with the customer, transcending traditional marketing, sales, and customer service roles.

That being said, without a reliable Customer Data Platform, companies who are digitizing their operations will mostly fail to unleash the real potential of a digital transformation.

Digital-native companies have already built their business model based on data collection and responding to customers’ needs with high-level experiences.

These companies combine traditional marketing strategies, such as loyalty programs, with groundbreaking digital initiatives that connect with customers in real-time and engross their engagement.

Remember: It is crucial to direct your digital transformation efforts into interactions that engage your audience, and a Customer Data Platform is intimately related to that.

It taps into your databases to unify relevant information and operationalize customer knowledge, delivering targeted experiences that will delight and retain your customers.

It should also be stated that CDPs assist companies in taking a step back and revisiting their processes to leverage technology cleverly.

For example, Netflix was quick to turn its service into a scalable streaming platform that replies to customers’ demands. The now-sector-leading company could only reinvent itself because it took a very attentive look at customer data and responded accordingly.

Align your digital initiatives with the power of a Customer Data Platform

While IT staff has been skeptical for a while, digital leaders worldwide have been engrossing CDP in their workflows and getting amazing results from data management automation.

Not only has perfect treating data been helping these leaders come up with customer-centric solutions, but it has optimized their budget and turned manual work more effective.

Forbes Insights highlighted that 44% of surveyed organizations stated a Customer Data Platform is helping drive customer loyalty and increase ROI.

Arena serves customers from 120 different countries and sees firsthand how the fast-paced digital environment influences global market changes day after day.

That is why we work to build awareness for digital leaders and marketers to embrace Customer Data Platforms in their full potential and boost customer engagement.

In case you need to further your research towards the CDP role for the upcoming years, download our Customer Data Platform 2020: the future of marketing and sales ebook and take a deeper dive.

30 reasons to use Customer Data Platform for eCommerce

Posted on July 28, 2020 by Arena

Information is king, and businesses are constantly on the lookout for tools that can provide a richer understanding of their customers and the journey they embark upon. Customer Data Platforms (CDP) have emerged as crucial tools, particularly for the burgeoning realm of eCommerce.

30 Reasons To Use A CDP

Here’s a deep dive into why CDPs should be at the heart of your digital strategy:

1. Seamless Automation

Trust in a CDP to transform complex data streams into easily digestible and actionable insights, automating processes that would otherwise drain resources.

2. Eliminating Operational Silos

Facilitate efficient information-sharing across departments with a CDP, creating a unified vision for your business.

3. Enriching the Customer Journey

Harness CDPs to unlock a comprehensive understanding of your customer’s interactions, ensuring you’re always delivering value.

4. Intelligent Marketing Segmentation

Harness the power of AI to sift through varied data, empowering you to create precisely targeted marketing campaigns.

5. Tailored Communication

Today’s consumer demands personalization. With a CDP, ensure every touchpoint resonates and builds loyalty.

6. Crafting Memorable Experiences

Use data-driven insights to craft seamless experiences, both online and offline, enhancing customer satisfaction.

7. Metrics that Matter

Deploy CDPs to get an eagle’s eye view on the efficacy of your eCommerce strategies, refining them as you grow.

8. Real-time Relevance

In an ever-changing market landscape, CDPs ensure you’re always a step ahead, thanks to real-time data updates.

9. 360-Degree Customer View

Break down the barriers between online and offline data to truly understand your customer’s journey.

10. Unified Customer Profiles

Leverage a CDP to get an in-depth understanding of your audience personas, refining your marketing strategies.

11. Stand Out from the Crowd

Responsive data-driven strategies ensure you’re always ahead of the curve, a must in today’s competitive marketplace.

12. Maximizing Customer Lifetime Value

Invest in understanding your current customers’ needs and behaviors, ensuring they remain loyal advocates.

13. Merging Digital and Physical

Achieve true omnichannel success by merging online and offline data streams.

14. Refining Offerings

Listen to your customers. Let their feedback guide improvements in your products and services.

15. Attracting Ready Buyers

Precision-target your messaging to capture those on the cusp of purchase.

16. Deep Customer Engagement

Leverage CDP insights to truly engage customers across every touchpoint, building loyalty and trust.

17. Enhancing Marketing Tools

Amplify the efficiency of your current marketing tools by integrating them with a powerful CDP.

18. Spotting and Addressing Anomalies

Ensure your strategy is always on track by identifying and rectifying any anomalies.

19. Anticipating Customer Behavior

Predict future customer actions and behaviors, refining your strategies for maximum impact.

20. Optimized Operational Efficiency

Drive efficiency by streamlining data processes, freeing up resources for strategic action.

21. Strategic Pricing

Ensure your pricing remains competitive and appealing by gauging customer sentiment and market trends.

22. Effective Supplier Negotiations

Utilize historical data to drive better deals and collaborations with suppliers.

23. Never Miss Feedback

Continuous monitoring ensures you’re always in the loop, adjusting strategies based on real-time feedback.

24. Minimize Cart Abandonment

Dive deep into the reasons behind cart abandonment, ensuring your checkout process is as smooth as possible.

25. Addressing Checkout Drop-offs

Investigate and rectify factors causing customers to abandon checkouts, maximizing conversions.

26. Tackling Churn Rates

Unearth the reasons behind dwindling customer loyalty and rectify them, building a lasting relationship.

27. Boosting Conversion Rates

Harness data insights to optimize your site’s usability and messaging, driving higher conversions.

28. Driving Organic Traffic

Strategically leverage live content and social media to naturally increase site visitors.

29. Elevating Social Media Engagement

Deepen customer relationships by engaging them on social platforms, turning followers into loyal customers.

30. Embrace the Future

Data is the future of marketing and sales. Integrate a CDP into your strategy and ensure your brand remains at the forefront.

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For a comprehensive understanding of the transformative power of CDPs, delve into Arena’s ebook Diving Into The Customer Journey In Live Ecommerce. The insights within can be the key to unlocking the full potential of your eCommerce strategy.

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An essential guide to Customer Data

Posted on June 30, 2020 by Paola Magni

Customer data is the key to understand customers beyond the confines of your own strategy, which makes you avoid dangerous assumptions to create relevant products and experiences.

Continuously data analysis will help you to come up with strategies that cover the market’s lacking points and elevate your marketing to a more meaningful approach.

We are witnessing a new customer era. Every company’s engines work daily to think, develop, and incorporate business and marketing strategies that put customers at the center of everything they do.

This new approach does not strike the market as a surprise. For the past years, with so much information in the palm of their hands, customers became more demanding and more willing to connect with brands that make proper use of their information to deliver more than just basic products and services.

If you have been paying attention, you already know customers value experiences more than anything else these days. This means true engagement will only be achieved by a remarkable customer experience that elevates your brand and creates a sense of connection with your audience. However, planning an exceptional customer experience takes a wide understanding and a sharp knowledge of how to solve consumers’ issues.

That is why customer data is definitely here to stay.

What is customer data and why does it matter?

Customer data is all the information a company gets from consumers whenever they interact with it. Whether it is personal, psychological, or demographic, customer data help companies clarify facts and avoid assumptions when thinking and refining business strategies related to customer experience.

The importance of customer data is related to the incessant need to build a strong customer understanding. Many organizations have already noticed that, by using data as a pillar, their operations draw near customer satisfaction and proper marketing approaches that return investments and reduces waste. On the other hand, without concise information about their customer base, companies fail to engage their audience and make sense of the many market opportunities datasets provide.

Customer experiences are tremendously affected by customer data, which means the right data extraction, validation and analysis are crucial to generate accurate outcomes that will enhance marketing and business plans. Customer data matters so many companies have embarked on customer data management (CDM) to correctly address data in their goals and daily work.

With trustworthy data at the palm of your hand, you will feel more confident in tactics to contact, acquire, and retain your customers, keeping their interest, and offering them exceptional engaging interactions. Customer data will also support your financial decisions, assisting you in where and when to allocate your budget.

How is customer data created?

As you read, a massive amount of data is being created. All around the world, people are navigating desktop and mobile devices. It doesn’t matter if they are shopping, replying to an online survey, or filling a lead form to get in touch with a software development company. Each of their digital interactions with brands creates data — which continuously provides the basis for algorithms to produce more data.

According to Deloitte in its Global Marketing Trends 2020 report, 90% of all global data were produced in the last two years, considering more than 26 billion smart devices circulating the globe.

Aware of data potential, the market has amended digital initiatives to maximize data collection, extraction, and validation methods. Big data analytics have been embedded to extract useful information from huge datasets, such as CRMs, that can’t be manually validated. Simultaneously, data scientists have been growing as popular as the need to adopt a data-driven culture.

These market signs alone are an extremely important indication that data is everywhere, and companies that don’t welcome it proactively will be in a tight spot.

Types of Customer Data

Customer data is separated into four main categories. In their own way, these categories will help you enhance the customer experience in different and empowering perspectives.

Personal data

Also known as identity and basic data, this type of information allows customers to be recognized by individual details and is divided into linked and linkable information.

Every information that can be used to identify a person without extra details is linked personal data — full names and emails, for example. Date of birth, physical address, and phone numbers are linked personal data too.

Now, linkable information doesn’t identify on its own. Still, when combined with other pieces of information, it is useful to draw a bigger picture. ZIP codes, age, gender, job titles, education level, marital status, and number of children are examples of linkable personal data.

Interaction data

If you ever wondered how your customers behave on your website, or how they interact with your emails and your social media accounts, interaction data will answer all of your questions.

Sometimes known as engagement data, interaction data brings a meaningful and solid viewpoint of how customers interact with your brand’s touchpoints.

Examples of interaction data are: Time spent on your website, page views, social media engagement, traffic sources, customer service feedback, and paid ad conversions.

Behavioral data

If you want to know how customers respond to experiences with your products and services, pay attention to behavioral data.

This type of data assists you to have a deeper understanding of behavior patterns your customers have throughout the purchase journey. This means interaction data may or not be considered behavioral data — it depends on the big picture and the goals you wish to achieve.

Some examples of behavioral information you can track are: Previous purchases, website heat-maps, customer loyalty program usage, repeated actions related to your products, and CTAs clicked.

Attitudinal data

The fourth and last type of customer data is related to how consumers perceive your brand. Unlike metrics you can easily measure, such as product purchases, click rates, website visits, and social network interactions, attitudinal data refers to emotions and individual opinions. It embraces feelings, which makes them highly subjective — that explains why this type of data is also referred to as qualitative data.

Continuously mining through attitudinal data will get you closer to proactively responding to consumers’ issues and anticipating trends they might be interested in. This is the perfect chance to get to know your consumers’ individual preferences and their point of view towards topics that interest you.

Attitudinal data examples are: Customer lifestyle, motivations, pain points, sentiments, and desirability. Customer reviews are excellent to gauge this sort of information.

Collecting customer data

As we have already emphasized, digital transformation has made every channel a powerful source of customer data. If your customers are interacting with your marketing and shopping channels, you can easily extract customer data from them using Customer Data Platforms (CDP).

There are several ways to collect customer data from distinct data points, and they depend on your goals.

That being said, before jumping to conclusions on which channel is the best to collect data from, make sure you address your data goals first. Is it to accelerate revenue? Develop new products? Get a more precise understanding if you ought to invest in a new marketing campaign? Start with the why, and then move forward.

More than predicting upcoming trends, recall that customer data should be highly attached to things that happened in the past. Past customer sales, buying decision patterns, abandonment rates (and much more) can be extracted from customer data to develop better strategies that respond directly to what your consumers did and said months, weeks, and days ago.

We have compiled some collecting data options ahead.

1. Website Analytics

Web analytics reports are excellent to understand what is resonating with your audience and how they are talking back to you.

When investigating this type of report, remember behavioral data insights can be extracted from heat-maps, bounce rate, page views, and even the devices your target market uses the most.

2. Social media engagement

Social media-based data can tell you a lot of things. Shares, likes, and comments on social media are basic engaging metrics you can measure to understand what customers think about your brand and what type of message they enjoy. You will likely get a good amount of data from social media analytics to make sense of customers’ sentiment towards you.

We highly recommend you to go even further and run social listening while analyzing social media insights. This will guarantee you interpret your customers’ interactions more accurately.

3. Customer interviews and feedback surveys

Feedback is crucial. Whether customers love what you’re doing or criticize it, you need to be available to take their considerations and opinions into account.

When done right, customer interviews, and feedback surveys will gather your audience’s interests, opinions, preferences, and how you can improve your products and services to serve them better.

Another data collection suggestion is to investigate customer churn. This explains the reason why some customers buy from you for a while and then leave. What affected their experience so they felt like not coming back? Is there anything you can do to improve this experience and avoid other customers from turning their backs on you?

If you’re looking for ways to extract behavioral and attitudinal data, consider searching for customer feedback and combine this information with other data to get a bigger picture.

4. Contact information

Contact information is vital to customer data. If you wish to communicate with your consumers, you should know where to find them according to the stage of their journey.

From phones to physical addresses and social media, contact information is needed to build a good amount of personal data you can rely on.

5. Customer service

Customer service is related to feedback but contains high potential itself. It is critical to allow customers to reach out to customer service software enabled to bring useful data your way.

As a consequence, customers can quickly seek help for big and small issues and solve their problems more easily all while providing you with more information.

Validating customer data

As vital as it is, customer data is useful when you are ready to properly extract and validate it. This means you need to find actual helpful information from your data sources, and pull them out to understand how valuable they are. This is what we call data extraction — and it will prevent you from swimming in a random sea of data.

Data extraction uses the right tools to streamline data from customer experience to marketing, and makes sure the information provided is useful for your teams to make better decisions.

To avoid wasting all the money, time, and effort you put into collecting data, there are some essential considerations about customer data validation you should pay attention to:

Customer data must be a source of truth and facts about your audience: Above all things, remember customer data is supposed to assist you in using factual information to come up with fitting solutions. For this reason, the data you extract must be reliable and revolve around your clients. If the data you’re extracting isn’t customer-centric, you better reconsider why it is important.

Customer data must be goal-oriented: Exploring multi-channels to extract data from without a clear goal in mind might lead you to conclusions that don’t make much sense. Make sure you know what your goals are from the beginning and set milestones to measure your progress. This will help you visualize how much data is affecting your operations and what else can be done.

Customer data must be integrated: Thanks to technology, data can now be transferred from one channel to another in a matter of seconds — and that is essential to every company that needs fresh information to anticipate opportunities and maximize their potential. By using customer data integration (CDI) tools, you ensure information gets to the right people and set a pattern to collect, organize, unify, and visualize customer data wholesomely. Best of all, CDI automates these processes and cuts down routines that take time. This means your human resources will have more time to focus on what they’re good at: Finding perfect responses to all the data software and algorithms have extracted and assembled for you.

Customer data must be contextualized: In-house data, also known as first-party data, should be combined with external data to give the information you’re putting your hands in a more precise context. There are two types of external data you can blend with your in-house insights to ensure a broader understanding: second party data and third party data. The second party data is the information provided by another company towards the audience that interests you — this type of data is usually shared between partners. In the meantime, third party data is collected by companies that don’t have a link to customers and sell information to other organizations. These data types can enrich your first-party data and elevate your insights.

Customer Data Analysis

Customer data analysis is crucial to any customer data strategy. Wrong data analysis might cause disconnected and poor responses from brands to erupt and bother customers with interactions they don’t need nor asked for.

As complex as it might sound to gather validated data to be analyzed, some special technologies can help the process be smoother and more efficient. Data mining is one of them. By mixing machine learning, statistics, and artificial intelligence (AI), data mining can analyze loads of data using sharp techniques —and the greatest thing about it is that its analysis is automatic.

Analyzing quantitative data

When it comes to quantitative data, you might come across the need to categorize it according to some classifications and segmentations. Or, perhaps, you will notice it is necessary to relate different data points and comprehend how specific characteristics affect the customer experience. Luckily, data mining provides many programmatic settings that can be adjusted to return the insights you are looking for.

If you’re willing to fragment customers to create more dynamic and creative ads, customer data analysis will help you find segmentation opportunities. If your team needs to associate behavioral patterns to develop a new campaign, customer data analysis will gather helpful information to predict how people will respond to your strategy. The opportunities are countless.

Analyzing qualitative data

On the other side, when we talk about qualitative data, many companies face the challenge of making sense of subjective information, such as sentiment. People’s emotions and feelings vary individually, and being stuck in the middle of so many variations is an uncertain place for your company to be at. If you’re wondering how to absorb valuable insights from this context, we have good news for you: there are ways technology can track important keywords to translate qualitative data into actionable decisions.

When analyzing qualitative data, pay attention to patterns that might make the situation clearer. Are your customers using the same keywords when they give feedback? Are the stories they tell somehow similar? Are there common elements in the ideas they communicate that can help you create a further sense of how they feel about your brand?

Take advantage of what customers say to you in feedback interviews, surveys, and methods of the sort, to gather enough data and take action.

Benefits of Customer Data Analysis

Relying on customer data will benefit you in countless ways. To help you understand how, we’ve listed some benefits in-detail right ahead:

1. Segmentation

Segmenting your customers is a smart way to get a broader view of what their issues are and how you can reach out to them more effectively. Separating them by age, demographics, gender, job title, and more makes it easier to plan specific marketing campaigns that will straightforwardly attract them, whether your goal is to attract them, engage them or make them buy more.

2. Personalization

People no longer wish to be contacted with general messages that lack a personal touch. Customer experience is a synonym of personalization and, if you don’t use data-based strategies to customize interactions with your consumers, it is highly likely that they will get frustrated by irrelevant content and mass communication. In contrast, personalization increases service quality and customer satisfaction.

3. Deeper audience understanding

Data is becoming the centerpiece of companies that desire is to remain relevant in customers’ minds. This happens because, without a detailed and precise understanding of their audience, companies will hardly add value to their customer base.

Customer data is the key to understand customers beyond the confines of your own strategy, which makes you avoid dangerous assumptions to create relevant products and experiences. Continuously data analysis will help you to come up with solutions around creative, data, and media — the right combination to empower your marketing and business approaches.

4. Revenue

When used correctly, customer data helps you understand how to increase your consumers’ loyalty and lifetime value, reducing churn at the same time. It also gives you a better understanding of where to invest in valuable campaigns and trends that will bring you more ROI.

5. Humanization

Human connection isn’t just another trend. The fact customers need to embrace companies with a purpose is changing their relationships with brands. People don’t want to be treated as a transaction. On the contrary, they expect companies to act authentically and be transparent in what they believe in, treating them individually. Pulling the right customer data contributes to humanize your brand so it corresponds to these expectations. It also frees your team to have more time to focus on how to genuinely engage customers.

Data-base your decisions

Now that you’ve come to the end of this article, you know there isn’t space for assumptions to guide your brand’s decisions anymore. More than ever, new ideas and improvements need to connect with customers’ expectations. In this context, embracing the right technologies to collect, extract, validate, and analyze data is crucial.

To find out more advantages that the use of Customer Data can provide for your company, contact one of our consultants, and resolve any doubts on the subject.

Customer Data Platforms vs. Data Management Platforms: Definitive Guide

Posted on June 30, 2020 by Paola Magni

Customer Data Platforms (CDPs) and Data Management Platforms (DMPs) might look similar, but each plays a different role in marketing. In this post, you will learn their main differences and applications.

Connecting the dots between your customers and the dozens of touchpoints with your brand is not an easy assignment. There are multiple roads that lead customers to your channels, and, in the best scenario, to buying your products.

If you were to map the physical and digital interactions that guide your customer through the conversion funnel, you would probably find ad pieces, search queries, social media and proprietary content channels, interactions with customer support, and so on.

With so many channels in mind, your team has to make sure your brand’s message is unified across all of them. You want the path to your content and your products to be as seamless as it can be, right? In order to do that, you need good tools for customer data management.

A report from research company Forrester found that data-driven businesses grow on average 30% more yearly than those ones that don’t systematically harness data within the organization. Data-driven companies are also expected to drive $1.8 trillion by 2021.

Historically, companies have relied on Data Management Platforms (DMPs) and Customer Relationship Management systems (CRM) to gather insights, and shape marketing campaigns, and content strategies.

But what if you could complement these tools and engage your customers with even more compelling and personalized messages? That is possible with the emergence of Customer Data Platforms (CDPs), a prominent type of data management system.

In this guide, we will explain exactly how Data Management Platforms and Customer Data Platforms work, their differences, and similarities, and how you can use each of them to leverage data-driven marketing in your organization.

Integrating Customer Data Platforms and Data Management Platforms is crucial for your marketing strategy

Customer Data Platforms (CDP): Definition and Examples

A Customer Data Platform (CDP) is software capable of unifying customer data from different data systems and customer-facing platforms. It gathers quantitative and qualitative information from several touchpoints with customers, regardless of whether they are recurring customers, new customers, or prospects.

Customer Data Platforms collect all sorts of data in a granular way, combining customer’s demographic data, buying history, social media preferences, call centers, and navigation data.

Basically, CDPs cross data from CRM systems, DMPs, customer support channels, payment methods, social media interactions, and different devices, allowing marketers to build a holistic view of customers and their pain points.

They also gather behavioral information, such as customer’s lifestyles and hobbies, transactional data from the company’s web site, mobile apps, advertising channels, social listening, and email marketing tools.

Here are specific examples of data collected by customer data platforms:

Transactional and order data: Exact purchases, renewal dates, customer and product value, abandoned baskets, and stage in the conversion funnel.
Behavioral data from web and mobile: Products and categories browsed, clicks, store visits, interaction data, and number of pages visited.
Profile data: Contacts and opt-in data and psychographic data points, like details about lifestyle, context, content, and channel preferences.

As marketing executives are expected to keep track of all customer interactions, another great news is those customer data platforms makes its unified customer database accessible to other systems – and even other departments. Wouldn’t it be great to connect marketing, sales, and customer success data, for example?

Unified customer profiles

You might still be wondering how exactly CDPs can capture so much data. That happens because the software facilitates customer data integration, filtering the data through algorithms to determine unified customer profiles.

These profiles are based on navigation patterns from your real customers and prospects, because they are mostly based on first-party data – Personal Identified Information (PII) that comes from customers navigating your own channels.

Such accurate profiles make it a lot easier for marketers to build personas and segment campaigns. Since the data match is consistent across different platforms, CDP is known for offering deterministic matching.

As the processing of data happens in real-time, CDPs also make it possible for you to quickly spot changes in customer behavior.

Data Management Platforms (DMP): Definitions and Use Cases

While leading marketing at a large organization, the least you should have is a data management platform to orchestrate your digital marketing efforts. The Data Management Platform (DMP) market size is expected to drive $3 billion a year by 2023, with a Compound Annual Growth Rate (CAGR) of 15% between 2017 and 2023.

If you are still not familiar with Data Management Platforms, it’s time to get acquainted with them. DMPs are intelligent data warehouses that are majorly used to drive customer segmentation and retargeting campaigns.

Their main objective is to increase audience engagement and make your ad targeting more effective. A DMP will monitor campaign strategies, identify conversion points and personalize campaigns according to them.

Segmentation on the Data Management Platform (DMP) can be done according to different data types, sources, end-users, and geolocalization.

These platforms focus on third-party, anonymized data collected through navigation cookies; device IDs, and IP addresses. Since the information captured is anonymous, DMPs automatically select data for marketing campaigns based on a process called probabilistic matching or lookalike modeling – when the system finds customers that are more likely to match your target audience by having similar qualities and behavior.

Here are a few specific examples of data collected by Data Management Platforms:

Web and app data: General information about customers who visit your website and app, like age, gender, location, browsing, and purchasing history.
Data from second and third-party sources: Anonymous data from partner sites and apps and databases bought from other providers.
Data from first-party systems: Sometimes, DMPs can include valuable, but highly sensitive information like customer’s name, address, email address.
Data from advertising campaigns: Visualization and navigation data related to search-engine-optimization (SEO) marketing and display advertising campaigns.

The methods for data collection through DMPs also may vary by vendor and industry, but generally, the system gathers information via JavaScript tags, server-to-server integration, and an application programming interface (API).

If a major publisher wants to send its website data to its DMP, for instance, it can use tags. An e-commerce platform, on the other hand, might choose to send data from marketing automation tools.

CDPs vs. DMPs: Key Differences Explained

If you are just starting to dive into marketing data solutions, it is almost inevitable to mistake DMPs for CDPs. Although they share some similarities, they show far more differences when it comes to managing data. The CDP Institute, a platform-agnostic organization in the realm of data platforms, uses a simple quote to explain the distinction between CDPs vs. DMPs. They describe:

“CDPs work with both anonymous and known individuals, storing personally identifiable information’ (PII) such as names, postal addresses, email addresses, and phone numbers, while DMPs work almost exclusively with anonymous entities such as cookies, devices, and IP addresses”.

Yes, the main distinction between DMPs and CDPs is about the type of data they rely on. However, other important data platform differences impact how they are used. Let’s explore them in detail.

Types of Data

As the CDP Institute describes, the greatest difference between CDPs and DMPs lies in their use of Personally Identifiable Information (PII) – or data related to customers’ identity. In marketing terms, a PII is a combination of data used to identify a specific customer.

The logic behind CDPs is that you’ll be targeting individuals: the more data you collect about a single customer, the better will be the experience your brand will provide to him, specifically. It can help you analyze if the user can be converted to a customer or understand content affinity based on the customer’s inclination to visit articles, for instance.

DMPs, on the other hand, rely on anonymous data – from cookies, devices, and IP addresses – in hopes to reach customers who match their target profiles. DMPs are useful in capturing generic data, such as noting when a particular user visited a website and how long they spent on the page.

Data Retention

Another major difference between customer data platforms and data management platforms has to do with how long they store data. CDPs are based on historical records, which means you can store customer data for how long you think it will be useful. You could choose to maintain customers’ records for a long period to build in-depth, accurate customer profiles and nurture relationships. Or, you could set a time limit for it, but having a long record about customers make it easier for you to analyze their lifetime value, for instance.

DMPs, however, store data for shorter periods of time, usually up to 90 days (a cookie’s lifespan) to target ads and build lookalike audiences. That’s not always good because it prevents marketers from having the bigger picture of the customer data over time.

Use Cases

Customer Data Platforms are used to gather customer data in their organic form and deploy insights to other marketing platforms. Marketers can use CDPs to coordinate different marketing strategies across different devices and channels. Beyond advertising, CDPs can be used to leverage the integration of marketing teams with other areas, from sales to customer experience (CX). In this post, you can check 20 ways CDPs can be used in marketing.

DMPs, on the other hand, are often constrained to digital advertising activities. They help marketers coordinate campaign optimization, audience modeling, cross-channel segmentation, and retargeting.

Data updates

In CDPs, database updates happen in real-time, while DPMs only allow scheduled database updates. It doesn’t mean that one model is better than the other, once the way you access and activate data will depend on your strategy.

Marketers can lean on CDPs for ongoing marketing efforts with single customers while relying on DMPs to potentialize specific campaigns and track their performance periodically.

What DMPs and CDPs Have in Common?

CDPs and DMPs do not necessarily replace one another. CDPs, specifically, can act as a complementary asset for DMPs. That means that the data gathered by CDPs can be enriched for better segmentation in DMPs, creating better lookalike audience segments. Therefore, you could choose either one or both of these platforms according to your marketing needs.

Generally, DMPs and CDPs will work side by side with customer relationship management systems (CRMs), which store data based on historical and general information such as contact, demographics, and notes about customers made by CRM teams.

Now, to set a common ground between DMPs and CDPs, we made a list of the assets they have in common.

Both CDPs and DMPs aim to establish a Single Customer View (SCV) or a 360-degree view to help businesses understand their customers.
Both platforms use data for audience activation and for delivering personalized user experiences.
Both platforms offer reporting, analysis, and optimization tools

3 Reasons Why a Customer Data Platform (CDP) is the Best Choice for Marketers

While different management platforms are always welcome, many marketers are turning their attention to Customer Data Platforms. Despite the growth of data and spend on marketing technology, many CMOs still struggle to demonstrate the revenue impact of their marketing activities on the business.

In this scenario, CPD emerges as a promising tool to centralize valuable insights, automate marketing integrations, and track performance precisely. A study by Forbes shows that 53% of marketing executives are using CDPs to engage with customer’s needs.

To finish this guide, we made a list of 3 ways your marketing team could benefit from a CDP:

1. Accurate personalization

In this day and age, not having a CDP can actually result in a poor experience for your customers. You can’t take the risk of making wrongful recommendations or serve ads that are not relevant within the user’s journey. Because it breaks data silos in organizations, CDPs are generally more effective than DMPs in attracting qualified leads, optimizing marketing budget, and reducing customers’ acquisition costs (CAC).

A CDP allows you to acknowledge what products customers show interest in lately, as well as their purchase intent and how likely they are to churn. You can also find out their favorite interaction channels and stages in the customer journey. From there, you can come up with predictive models and improve content strategies for every channel.

2. Better data quality

The focus of marketing leaders is also shifting from third-party data and anonymous data to first-party, single-customer data, which also addresses CDPs’ importance. As data privacy and compliance regulations become more consolidated, organizations increasingly seek to work with their own, integrated data.

3. Integration to other software

CDPs can be integrated into different touchpoints called “delivery platforms” or “engagement platforms”. These can be, for instance, your company’s email marketing or marketing automation software, website, or social media management platform.

Delivery systems interact with the platform to send out messages and collect engagement data that will feedback into the system. These integrations enable the planning of campaigns and the set of messages.

Next Steps

We know that there are many data management solutions in the market. But now that you have learned a bit more about DMPs and CDPs applications, maybe it’s worth strengthening your marketing data solutions.

We recommend you check out Arena’s customer data platform blog section to learn more about the potential of CDPs. You can also click here to get in touch with one of Arena’s consultants and learn the specifics of our CDP.

What is and how to do Customer Data Management CDM

Posted on June 30, 2020 by Arena

This guide will teach you how to use data frameworks to offer differentiated customer experiences and optimize marketing ROI.

It has been a few years since the buzz around “Big Data” started. Working with marketing in the media space, you probably hear your peers bragging about their data-driven strategies a lot. Do you consider yourself a data-driven marketer too?

Beyond marketing, modern CMOs have had to assimilate abilities in information technology and customer data management. In 2020, you should expect most marketing teams to effectively use customer data to drive growth and customer satisfaction.

Getting there can be quite a journey, though. Research from the Dentsu Aegis Network from 2018, made with 1,000 CMOs, shows that to two-thirds agree that while there is increasingly more consumer data available, it’s harder to extract insight from it.

Another report from Harvard Business Review shows that less than half of an organization’s structured data is actively used in making decisions, while less than 1% of its unstructured data is analyzed or used at all.

Historically, companies have relied on excel sheets and on manually storing and analyzing customer data through different software, with little to no integration. No offense to excel and isolated systems, but things have changed.

The amount of customer data flowing to companies’ databases continues to rise through new channels and platforms, and that’s where customer data management comes to play. More than ever, organizations need a complete set of practices and automation tools to help them manage customer information.

In this article, we will talk about the importance of having customer data management on top of the marketing agenda. We’ll also explore the types of data, best practices for data management, and the role of different data software in data management.

What is customer data management?

Customer Data Management, shortly known as CDM, is the framework in which companies collect, track, organize, analyze and share customer data throughout the organization.

The term “Customer Data Management” was coined in the 1990s, initially as a way to describe software that replaced disc-based or paper-based data storage. Such software was often used independently by departments within companies.

The concept of CDM evolved along with the Software as a Service (SaaS) industry and nowadays embraces a wide array of cloud computing applications that centralize access to customer data. It also embraces a set of methodologies that help marketers to locate, cross-analyze, and act on customer data.

Why marketers should invest in customer data management?

In a scenario where customers interact with brands through dozens of channels, there is almost no room for guessing and gut-feeling in marketing. Having a good hunch about what will engage audiences is not enough, and so the role of customer data management is to provide companies with accurate and actionable insights.

It reduces your chances of making mistakes, since mismanaging your customer data can lead to actions that will ultimately reduce engagement and profitability. Additionally, using customers’ data in a biased, inaccurate way can lead to poor customer experience (CX) and harm your brand.

Good customer data management is key to building a data-driven culture and bolstering customer-centricity in marketing. Isn’t it everything you wish for?

Data Management strategies can bring marketers a holistic view of customers’ journeys, connecting the dots between different channels, and offering cues to enhance their experience.

Customer Data Management is important for:

Customer acquisition
Increasing retention and engagement rates
Knowing customers in detail and in real-time, from individuals to clusters
Increasing data quality by breaking data silos
Simplifying customer relationship management (CRM)
Drive higher revenue

How customer data management is connected to customer lifetime value (CLV)

Having well-structured customer data management practices is what allows marketing teams to follow up on important indicators, like the Customer Lifetime Value (CLV).

Amidst a seemingly chaotic user journey – with different channels, devices, and purposes – customer data management can help marketers understand customers and guide them through the conversion funnel.

Collecting and organizing relevant customer data will allow you to better segment your audience, find out behavior and buying trends, and drive personalized campaigns. As a result, marketers can ultimately attract more qualified leads and reduce customer acquisition costs (CAC) – improving overall marketing ROI.

But customer data management is useful only for marketing. It can help sales, IT, and customer success manages customer touchpoints. The great news is that every department can have access to the same data and deliver a consistent, unfragmented user experience.

Four Types of Data to pay attention to

Before trying to set up a data management framework, your team should have a roadmap of data types and specific information that can enrich your strategy, according to your business goals.

We will now explore four data types and a few examples for each.

1) Identity Data

Identity data is collected through micro-transactions and interactions in the company’s channels – when a customer signs up for a newsletter or enters their payment information on the checkout page.

By collecting customers’ identity data, marketers have the minimum amount of information to start a conversation (and hopefully a long relationship) with the customer. Such information is also helpful to help companies build brand personas.

Examples of identity data: Name; Personal data (date of birth, region, gender, etc); Address; Contacts; Social media profiles; Account data.

2) Quantitative Data

Quantitative data is mostly related to the customer’s decision making process as they interact with your brand. Such data covers different channels throughout the customer lifecycle, from emails and customer support channels to purchase transactions and social media.

The idea is to understand the specifics of how customers are interacting with your brand through important operational data. You could use quantitative data to find out details about channel interactions and steps that led customers to convert.

Examples of quantitative data: Transactional data, such as the number of purchases, time of purchase and subscription value; Order dates; Cart abandonment and Bounce info; Click-through-Rates; Website visits; Product views; Number of Interactions.

3) Descriptive Data

Descriptive data comprehend additional lifestyle information that complements customer personas. Collecting this type of data typically requires doing deeper research and interviews with customers in order to dive into individual buying behavior. Such data is pretty helpful if you want to use predictive analytics in your marketing strategy.

Examples of descriptive data: Family Data such as marital status and number of children; Lifestyle data, like hobbies and interests; Education and career data.

4) Qualitative Data

Qualitative data should describe the motivations behind the customer’s actions. Gathering such insights might be more time-consuming and expensive than simply collecting quantitative data, but it is worth it. After all, tackling into customers’ deepest motivations is how you’ll captivate them.

This type of data is better collected on a one-to-one basis, mainly through the marketing teams’ interpretations of customers’ opinions throughout their journey – through analyzing CRM notes or reviews in websites, social listening tools, feedback questions, and Net Promoter Score (NPS) systems.

Best practices in customer data management

An effective customer data management framework requires marketers to make human and tech investments, have well-defined processes and priorities. We have picked a few key practices involved CDM:

Data collection

A lot of the data within enterprises go unused, and so data collection is the first step in building an integrated customer data management strategy. There are millions of data streams coming into companies’ systems from many touchpoints, and so marketers need to make sure relevant data doesn’t go to waste.

It’s important to understand what data needs to be ingested. Ask yourself: What goals do I want to achieve with my marketing strategy? Which data points are directly or indirectly related to my Key Performance Indicators (KPIs)? From there, you can start filtering your sources of data and the indicators you will track.

Data Integration

Centralizing all company’s data into a central system is also vital for customer data management. That enables the “ETL Process”, which stands for “Extracting, Transforming and Loading” data. This stage is where you will check your data integrity, filter it, and validate it.

A good data system will ingest relevant data, convert it in necessary formats and load it into different tools such as a data warehouse, a customer data platform (CDP), a data management platform (DMP), a customer relationship management (CRM) or any other system. The result? You will have a single hub for all the data you need.

Data management

This is where you connect the dots between data points to build robust, unified profiles of individual customers or segments. This could mean using statistic models to create identity graphs, applying data governance to make sure you integrate consent to customer data, or anonymizing data to be used through a data management platform (DMP).

Data analysis and activation

Data management tools: the difference between CRM, DMP, and CDP

Although customer Data Management can be described as a framework, it requires companies to have the right technologies.

Your data software stack could be more or less complex depending on the size of your business and the number of touchpoints with the customer, but, essentially, your CDM strategy will require a combination these platforms: a Customer Relationship Platform (CRM), Data management Platform (DMP) and Customer Data Platform (CDP).

Each one of them plays a role in your strategy. But what is the difference between them?

The basis of data management starts with customer relationship management systems (CRM), which are built to engage with customers by tracking their relationship with your company. They only store data if the customer has interacted with the brand in some way, and they are based on historical and general information such as contact, demographics, and notes made by CRM teams.

Data management platforms (DMPs), on the other hand, have been widely used by marketers to serve ads and lead digital campaigns. These platforms focus on third-party anonymized data collected through cookies (that typically expire after 90 days), device IDs, and IP addresses.

In a different model, a Customer Data Platform (CDP) is a software capable of unifying customer data from various sources, internal or external, gathering quantitative and qualitative information from multiple touchpoints between a company and its customer base. It allows you to build a holistic view of customers and their pain points in a granular way.

Why CDPs are the ultimate trend in customer data management

Although CRM systems, DMPs and CDPs share similarities, they are different when it comes to managing data. Customer data platforms, specifically, have increasingly been used as an integration hub for data systems because they are built to ingest large volumes of data from multiple sources – unlike CRM systems and DMPs.

There were days when marketing segmentation based on DMP persona segments and CRM was enough, but today, brands are expected to personalize every step in the customer journey – which is only possible through CDPs.

A study by Forbes shows that 53% of marketing executives are using CDPs to engage with existing customer’s needs, increasing the likelihood that they will become recurring clients.

The focus of CMOs is also shifting from third-party data and anonymous data to first-party, single customer data, which also underlines CDPs’ importance. As data privacy and compliance regulations arise, organizations also seek to work with their own, integrated data.

CDPs are capable of providing marketers with a historical record of identified customers that can be used not only for advertising but for other purposes as well. By centralizing information in a single platform, companies can optimize resources and avoid having to rework their data over and over through different systems.

Bonus tips for successful data management

Make data widely available to different teams: The Harvard Business Review study we mentioned before reveals that 80% of a data analyst’s time is spent on just discovering and preparing data. Customer data can be an important asset across departments, so it’s important to centralize access to it instead of storing it in separate departments and warehouses. Let the data flow!

Always keep data governance in mind: Understand the privacy policies of your data tools and ensure consent is integrated into all of your data collection, while also respected in marketing campaigns.

Don’t over-collect data: Understand exactly why you’re collecting the data your collecting, and which questions your company is trying to answer with them. Resist the impulse to gather too much data “just in case” you need it, without a proper purpose.

Create rules for data categorization: Set up file formats you’ll be using, standards for tags, file-naming, and timestamps. Such standards will make it easier for your team to navigate through the data.

Beware of new data sources: Pay attention to emerging data types, such as those from voice activation devices, geo-localization in smart devices, Internet of Things, Augmented and virtual reality platforms, etc. New data points will eventually require new processing and marketing frameworks.

Still want help defining your customer data management strategy?

Now that you have learned a bit more about customer data management, maybe your next step will be to study data management solutions.

If that is the case, we recommend you check out Arena’s customer data platform blog section to dive deeper into the subject. You can also get in touch with one of Arena’s consultants and learn the specifics about our CDP.

Data-driven marketing: learn how to work it with your customers

Posted on June 25, 2020 by Paola Magni

Data-driven marketing belongs to a new customer service approach that unleashes companies’ potential to make better, scalable marketing decisions and benefit from higher marketing ROI. It represents the future of customer experience and meaningful branding messages.

You already know what people say: Knowledge is power. Facts, information, and skills acquired through experiences are gold mines for every company that wishes to stand out and stay relevant in their customers’ minds.

Customer data platforms tells marketers everything they need to know about their target audiences. Through digitalization and its multi-channels, it became possible to trace people’s actions across the digital and physical worlds to optimize the process of offering customized products and services that match individual needs.

However, these days, data must be smooth to access and easy to visualize. This happens because customers want quick responses, which timing and effectiveness are highly affected by delays and assumptions.

In this unforgiving environment, are you confident that your marketing decisions are based on facts? When important events on your field take place, how quickly can you respond to them? How many customized experiences do you actually deliver to your customers?

If the answers to those questions concern you, you’re at the right place, at the right time. Get ready to know how data-driven marketing can take you closer to the answers you wish you could give.

In this article, you’ll find out:

What is data-driven marketing;
Data-driven marketing benefits;
Impacts on customer experience;
How to work data-driven in consumer segmentation;
And examples of data-driven culture.

With that in mind, let’s move forward.

What is data-driven marketing?

Data-driven marketing is a strategy that uses customers’ reliable information to personalize whole marketing communications and experiences. From buying journeys to targeted media and in-store service, data-driven marketing accesses massive information to leverage decisions and make the right judgment about what customers need. This helps marketers to refine strategies based on facts, not guesswork.

But where does data-driven marketing get all the information from?

When you use your phone’s mobile apps or desktop devices to web navigate, you’re leaving traces all around the internet. The applications you use are designed to send data to companies so they know what websites you access, with who you’re interacting with, the locations you have been to, and more relevant information that clarifies your individual preferences and lifestyle.

Many organizations are already worried about data, but we must call attention to the fact that data-driven marketing goes beyond data itself.

The many devices, platforms, and other types of media you use are surely whispering into marketers’ ears over and over to help them build fact-based decisions that match your expectations. Even so, data-driven strategies merge a high-powered amount of digital and offline channels to give context, collect information, and arrange it in ways that are easy to visualize. Data-driven marketing aims at amazingly-designed customer experiences, but influences internal operations in ways companies have never seen before.

With so much information being generated at all times, data-driven marketing unites the right tools to track, segment, and optimize strategies. When used right, this groundbreaking approach will help you to invest in the right interactions to increase customer retention and bring you more marketing ROI.

Data-driven marketing benefits

Now that you know the importance of data-driven and how it is revolutionizing marketing strategies, it is time to highlight some of its many benefits.

Segmentation

Data-driven marketing is the key to build marvelous customer experiences based on well-designed segmentation. The first step is to select the right customer segment to drive marketing efforts into. After that, you will be prepared to work on specific, tailored tactics to sharpen your customer touchpoints, whether they’re potential or not.

By segmenting a target market, it gets easier to develop products, solutions, and approaches that will attract the right people to your brand. Segmentation also provides transparency when you wish to know how your campaigns are resonating with the public and gives you a better understanding of particular users’ behavior.

Customer acquisition

Four essential questions must be answered very carefully when you decide to attract target audiences and contact potential customers:

What message will you tell them?
How will you communicate with them?
When will you reach out to them?
Where will you find them?

In a data-driven approach, all of these questions will be respectively answered based on:

Goals and pain points;
How they behave;
The best timing according to their routine;
And the digital and physical places you’re more likely to meet them.

Even if you have a large number of customers, it is possible to combine data to deliver special, tailored touchpoints that match their behavior and preference. It could be an e-mail, or an SMS, or a live event. Possibilities are countless, but you will surely pick the best ones once you know what customers expect from you and how to engage them.

Data-driven marketing works efficiently when it comes to continuously deliver interactions to match customers’ expectations throughout their journey. With so much information at the palm of your hand, you will be ready to transmit the right message (what) at the right time (when) and place (where).

Revenue

Every company director loves it when technology saves the day by cutting costs and returning investment. Gladly, this is pretty much the case with data-driven marketing.

According to the Forrester report “Insights-Driven Businesses Set the Pace for Global Growth“, data-driven organizations grow 30% per year more than companies that don’t base their strategies on data.

When we take a good look at different markets, it gets even clearer that data-driven strategies embody assertive communication that makes ROI possible.

Custom-made marketing campaigns reach proper audiences, which leads to customer acquisition, which leads to customer engagement – and ROI is coming back to you in each one of these stages. Not to mention the revenue currency that comes from these approaches.

Revenue is also possible by cutting costs, reducing churn, and democratizing information through different companies’ sectors.

Upgrade your marketing strategy

Automation was already a buzz when CRMs arrived to transform the way marketers dealt with customer data. From purchase details to personal information and preferences, CRM was and still is prepared to collect digital data at higher levels. This allows big data to play a more predominant role in marketing: Data is now at its core, deciding the directions companies should take to reach their goals.

It must be said that collecting data became a more complex task, especially when you take the number of multi-channels available these days. Still, this complexity isn’t an excuse: If brands don’t automate operations related to those channels, they will lose way too much time putting effort into what can be automatic, and marketers won’t be able to strengthen their creative side and propose remarkable tactics.

Fortunately, there is a considerable amount of data-driven tools that optimize, clean, and filter important data from multiple sources, whether they’re 1st (directly extracted from customers) or 3rd party (found in the market).

Data-driven marketing automation saves you time, money, and free your team to focus on more important tasks that require human abilities, such as creativity. That is how you truly upgrade your marketing strategy: By quickly analyzing qualitative data and returning a creative response to customers’ issues.

This means a wider customer reach, more relatable content, targeted ads, and personalized customer journeys – to only quote a few.

Don’t forget that numbers and reports play a crucial role in data, but the outcome will only be useful if the human eye analyzing them gets the right insights and develops accurate replies to get closer to customers.

Impacts on customer experience

Lincoln Murphy, known as the Customer Success guru, says that Customer Success is only achieved by combining what customers need to an appropriate experience while delivering the right interactions. As you know now, this has everything to do with data-driven.

Data-driven marketing is a new shift in customer care. It prioritizes customer experience in smart and strategic ways, such as we have never seen before.

Many marketers around the world have embedded data-driven strategies into their routines, taking their time to analyze information that will drive to ideal customer experience. With so many benefits, data-based decisions impact consumers on profuse levels. Take a look at some of the impacts:

Personalize customer interactions

Needless to say, real engagement is closely related to giving customers a personal touch in everything you do.

Irrelevant content, general messages, and ordinary offers will only frustrate the current consumer. People expect brands to customize every touchpoint and suit them to previous steps of their consumer journey. This means companies need to enrich and individualize communications that work in a one-to-one approach to get in touch with customers and prospects.

While 74% of consumers feel frustrated by irrelevant content, 56% of them would reward personalization with a purchase.

Data-driven tactics are the perfect response to this personalization requirement. It allows you to incorporate consumers’ inclinations, pain points, and attitudes to deliver personalized experiences both in digital and physical fields.

Content personalization also turns your communication more persuasive, improves customer conversions, and boosts engagement.

Improve products and services

Products and services can also be personalized and better designed to respond to buyers’ expectations. Analyzing clear data will help you understand whether you need to develop a new product or give an existing one new functionalities to match your customers’ needs. This kind of information also guides you to make the right decisions on when to invest in innovation and when to change small details that make a difference.

Besides, data-driven marketing ensures companies always keep an eye on the market to launch tailored, untried products. Data will assist you in when to launch something new, to know how much people are willing to pay for your products and services, and what can be enhanced to increase customer satisfaction.

Ask for feedback

Another way data-driven marketing impacts customer experience is via feedback. Remember that people use social media to discuss brands and experiences, and when they talk about your company, you should be the first to know. Practices like social listening will help you monitor what people say on social media networks and collect precise data to gather feedback and insights into what’s working and what needs refinement.

Predict customer trends and market changes

Customers are avid for brands that can communicate and act based both on their individual preferences and what’s going on around the globe. Sustainability, social responsibility, storytelling… These are all actual trends that brands should pay attention to while planning their year. Closing your eyes to the market and only focusing on customer behavior is dangerous, as the external environment can dictate what trends will create buzz and what you can do to make people more interested in your brand.

Data-based predictions are important to keep you one step ahead of your competition, especially in times of change. Timing is crucial: Losing the chance to reply quickly to changes and real-time events might harm your brand in ways you never thought possible. With that in mind, make sure you use data to be prepared for change.

Reach customers where they are

Uncovering the best channels for promoting your brand can be a challenge, but data-driven marketing clarifies what those channels are and how your customers use them. This will prevent you from investing unnecessarily in channels that have bad ROI and planning media usage poorly.

With a more concise understanding of trends, you may get a broader view of channels’ tendencies to use them correctly, building more responsive communications. Batches of customers will also benefit from an enhanced content distribution from your part.

Make customers more engaged

Data automation is the ultimate principle to direct creativity into engaging strategies. In the past, marketers could only deliver a few types of customer service — versions back then didn’t vary, and general communication was even acceptable. Nowadays, though, our hectic and ever-changing routine requires more from brands. If you want to truly engage customers and make them loyal to your brand, you better start seeing data as the main resource to achieve better engagement rates.

More interested in experiences than in products, customers these days expect to be listened to and empowered by appropriate brand responses. Not only people are willing to pay more for better experiences — engaged customers are ready to invest emotionally in brands, and this is vital to any long term customer relationship.

Besides making you relevant in consumers’ minds, engagement pays your bills. Companies that have improved engagement increase purchase frequency and order sizes. This keeps revenue coming in and customers satisfied with relevant buying and connection experiences.

How to work data-driven in consumer segmentation

To apply data-driven marketing in your company, you need to be ready to extract, treat, compare, and analyze digital information from multi-channels, transforming it into knowledge.

We know this multi-channel information means millions and millions of data coming from social media, website analytics, cookies, CRMs, consultancies, market data, competitors, and more. But, thanks to technology and digital transformation, data-driven companies use analytics and algorithms to filter and select types of data that matter the most to them.

There are data-driven solutions — software and methods — that will help you segment your customers and visualize information in intuitive reports. With the advances of machine learning and artificial intelligence, machines gather data around and bring it to you whenever you need it.

One of these tools is the Customer Data Platform, also known as CDP. A CDP should provide you with the right insights to create personas, attract and qualify leads, create new content strategies, and develop customer relationships.

Be aware that marketing segmentation is a key-strategy when it comes to the data-driven mindset. Separating customers by interests, job titles, age, location, gender, and more is an amazing strategy for companies that wish to come up with outstanding marketing strategies instead of sending mass emails and trying to acquire leads through general advertising. Segmentation will pull you closer to generate real-time audience engagement.

For example, in 2015 Very.co.uk combined customer preferences with data about the weather to create personalized homepages to attract consumers to their e-commerce. In the process, 1.2 million versions of the website could be displayed, matching customers’ interest. For example, if you were looking for homeware, your homepage would bring special promotional messages that had everything to do with the products you were looking for. It is completely personalized — and that was only possible because Very.co.uk data scientists created complex algorithms to predict customer behavior.

Nubank, the largest Fintech in Latin American, is another company that embraces data-driven marketing to customize the customer experience. Nubank created ‘wows’, the name given to specific gifts customers receive when assistants feel a special type of connection while serving them.

Every gift is designed especially to the customer, considering their preferences and context. Nubank recently gave a consumer that owns 85 dogs a box full of dog toys, bone-shaped letters (written to the customer herself), and a device that throws dog treats in the air.

Examples of data-driven culture

Data-driven marketing has been so relevant it is leading a policy of its own, known as data-driven culture.

Data-driven culture allows organizations to replace opinions and guesswork with data-derived facts. Here, data is the main resource for collecting and leveraging insights in every company’s department. For this reason, all operations and routines will revolve around it, creating a new decision framework that relies on collaboration to move, integrate, and combine data more efficiently.

This means information must flow effortlessly through people, processes, and solutions so decisions can be made in a matter of seconds. There is no time for waiting: Business intelligence, technology, sales, product, marketing, and many other teams must have quick access to data to enhance customer interactions as swiftly as possible.

To give you a real case example, The Coca-Cola Company in Brazil assembles a data-driven culture to machine learning and AI to analyze its market and consumers. From three to three months, Coca-Cola employees set goals based on data and measure their progress through indicators and continuous information exchange.

It is also interesting to mention that Coca-Cola uses digital as a leading measurement tool and values people diversity to boost collective learning.

Worldwide, Coca-Cola is also known for its successful data-driven campaigns and agile mindset. In practice, data helped Coca-Cola deliver the Cherry Sprite flavor, which was inspired by the fact many customers mixed their drinks in self-service drink fountains. It also drove the company to create personalized AI assistants for vending machines that can behave differently and allow consumers to personalize drinks.

To mention one more example, Coca-Cola has been using data-driven marketing to track photographs of its drinks on social media, using image-recognition technology — this allows the company to target customers and deliver more efficient adverts, considering their consumption behavior.

At the end of the day, it’s clear to see that companies that have absorbed data-driven culture are completely different from companies that haven’t. Data-driven companies achieve tremendous results by dealing with complex multimedia channels — like videos, social media, ads, email, and liveblogs; — to reach customers with the right message at the right time. This ability is closely tied to automation and analytical approaches, which permits operations to be optimized, and audiences to be attracted more effortlessly.

Data-driven marketing is the future

We know making the best marketing decisions is a challenge as much as it is a basic requirement. Moreover, facts tell us the future of organizations will be decided by the ability to use data wisely — and we know you don’t want to be left behind.

Arena helps media companies all around the world to encourage engagement and streamline customer data to smart marketing campaigns.

If you’re willing to be assisted by a Customer Data Platform to boost your audience and work data-driven marketing with your customers, get to know more about how we can create powerful experiences for your users.

The Difference Between Data Management Platform (DMP) and a Customer Management Platform (CDP)

Posted on June 22, 2020 by Paola Magni

A data management platform works as a warehouse, collecting, organizing and activating third-party data in a single place. Keep up and find out how to benefit from it!

Data is a crucial resource in this business era. However, it can be useless if the company doesn’t know how to professionally manage all that amount of information, wasting thousands of dollars advertising to an incomplete or insufficient database usage.

In a digital world of first, second and third-party information, a Data Management Platform, also known as DMP, can transform piles of databases into profitable resources. Take a look!

What is a Data Management Platform (DMP)

Customer experience is not a linear walk. They will leave crumbs of information all the way along their relationship journey with a company. That process results in the accumulation millions of data throughout the years from multiple sources.

Most times, those data can seem random, incoherent or fragmented. That may happen when there is no right management of it.

Then, some questions become trivial:

Who are the visitors on my website?
What are they looking for?
How can you have direct contact with them?
Why they are not making deals with me?

A data management platform (DMP) is a tool to filter all those pieces of information into organized profiles for audience segmentation or insights for decision-making.

After that, your company will know exactly who they supposed to talk to; how these audiences behave; what is the best approach along the sales funnel to them; if the investment made in advertisement campaigns has the appropriate segment and more.

You can even create cross-media analysis, which is when multiple platforms, on and offline, can support the same campaign.

How Does a DMP Work?

Operating as a central intelligence system for digital marketing, a DMP creates a perfect definition of your ideal customer by organizing millions of information into demographic, consuming habits, interests and so on.

You can obtain new forms of segmentation through DMP, such as a non-dependent on the context or content one. This new segment is now based on the profile of the audience, regardless of the advertisement subject or the platform displayed.

To function, a data management platform operates in four steps:

Collect

It all begins with data collection, third-party information acquired by relevant partners with similar or identical market spaces. These data can be provided from CRMs, customers’ registration, e-mails, website data, previous purchases and whatever more relevant material is available.

Even though DMP is made to operate third-party data, it also supports some first-party data to improve the information given.

Organize

In this step, the DMP classify the info into categories, grouping them as clusters. Clusters are a type of audience segmentation that combines customers with similar marketing sales behaviors in one file.

For example, it is possible to create a group of customers who has made most of their purchases by ad clicks, or those who spent a certain amount of money in a product or service related to yours, who has more visits in a specific category in a website that might fit your business, etc.

Activate

Now, it is crucial that the data management platform used is agnostic, which means it will be compatible with any digital platform. So, if the company wants to run a campaign for the brand in social media, websites, search engines, etc, it will be just fine. The activation itself happens when the campaign is on.

Learn

By analyzing the return over the investments made on the ads, it will be possible to understand the depth of cluster segmentation. The company will have more domain over the results acquired since the data is much more precise than any other type.

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What Can You Do With a Data Management Platform?

One of the main benefits a DMP provides is the cluster: high-detailed information about customers so you can create hyper-targeted ad campaigns, delivering more conversion rates and increasing the ROI of your company.

Using a DMP, you’ll be able to create accurate segmentation, making the proper usage of your third-party data by giving your audience the right message.

Practical Example

Imagine you run a dental clinic and want to expand your qualified leads base for a specific segment, let’s say dental implants. That is one of the most expensive procedures you have and it is not salable to any type of customer.

Typically, you would create a campaign based on people interested in dentistry or dental implants in a wide range, fitted in average age, near your clinic.

With a DMP, the depth of your segmentation reaches this: men and women, from 40 to 70 years old, who have downloaded some white papers about dental implants, researched a number of keywords that demonstrate the need for professional information and live within 5 km of the clinic.

Here are some possibilities your company can reach with this type of segmentation:

Retargeting: easily implement personalized retargeting campaigns based on specific activities and behaviors online.
Prospecting: integrate with third-party data sources for the acquisition of anonymous data, achieving greater precision and scale in online campaigns.
Website optimization: use your own or third-party data to provide customized content to different consumers when they come to your page.
Audience intelligence: cross your first-party data with other third-party to learn more about your audience and reach the people most likely to convert.
Better ROI: use an analytics tool that centralizes online campaign performance data to determine which audience segment performed best and where to focus your efforts in the future.
Productivity increase: eliminate the bottleneck of needing IT to reach out for your data and have all your teams able to take them out, ready to use.

DMP Benefits for Companies

So far, we have seen in order to escalate your business, having the right audience to talk to is fundamental. This is market intelligence. Your company can no longer have a vague idea of who their customer is. It is necessary to personalize and amplify to get the following benefits:

Cost-Effective Advertising Campaigns

When you have this level of audience segmentation, you can spend every dollar of your budget on better-targeted prospects. Get the return on the investment you need to.

Lower Technology Investments

To run a DMP, you won’t need an extra support. Your whole team, from customer success to follow-up sales, can easily operate the system. As we mentioned before, there is no need for IT.

First, Second, and Third-Party Data Combined

No data is left behind. Even a messy pile of customer information can turn into gold here. As this platform gathers and organizes party data, every piece of a database is important, nothing is wasted.

No Data, No Success

Regardless of the type of industry you are in, uncountable amounts of information are huddled and enter your company through different doors: billing spreadsheets, sales reports, feedback offered by different media, social networks, loss or conquest of new markets, CRM, etc.

Such a thing must be used to leverage business marketing strategies. That is the reason why it is so important to generate an efficient information collection, organization and analysis on a daily basis of a company, as DMP does.

From this, a strategy can be developed over decisions based on information, including those related to strategic and operational marketing. That is the Data-Driven Marketing.

Data-Driven Marketing

Data-Driven Marketing helps, for example, to create a guideline for campaigns using DMP clusters. Besides highlighting the features/benefits/quality/etc of a product or service, it enables a work of relevant engagement with your consumers, delivering exactly what they want.

As a result, communication is enhanced by user experience and becomes more aligned with the needs of its audience.

Strategies will be able to still cohesive and aligned even when using a larger number of channels. Marketing campaigns have been running more frequently in social networks, which is the place where interaction has a leading role.

It keeps getting more essential to own proper knowledge of the market slice you are in. Its audience and characteristics indicate the way your company should brand, advertise and sell their product.

Big Data

When we reach for the definition of Big Data, we find a true technological revolution, making more possible to qualify the results obtained. Big data is a master process of analyzing and interpreting a great volume of data stored somewhere remotely.

Information is available everywhere online in a non-confidential way. No matter how large the amount of information is, Big Data can reach and group them according to interests.

Big data can be used in several business routines. However, to use it properly, it is mandatory to have not only knowledge about the technology, but also to identify which are the touchpoints in your company that will be impacted by its implementation.

By that, it will be possible to make a more efficient allocation of resources and increase the return over the investment in those data analysis solutions. And that is how a Data Driven culture is established.

Thus, the company must act so all teams understand the importance of data integration in the definition of strategies and work based on that!

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How a DMP Can Boost Marketing and Sales Results

Marketing and sales work as the core of the data management platform. This is where it starts, through hyper-segmented audiences. One of the biggest mistakes –– and frequent too! –– of digital marketing campaigns is having an incorrect or too wide segmentation.

Besides impacting those who are not part of your true audience –– and might cause a bad reputation for you ––, there is going to be a significant waste of your marketing budget that may harm your ROI.

Every click or scroll on the screen can generate data. When your marketing strategy is aligned to DMP guidance, you hand over to sales team customers ready to spend their money.

DMP and Sales

At this stage, sales have a unified perspective over the data and better cards to play, such as real-time interactions.

This is a priority in marketing and sales now. A high-performance sales team, which are those with the upper sales amount, increase the chances of achieving their mark by real-time interactions with the customer.

But we are not talking about aggressive and unprepared approaches here. Sales’ strategy must contemplate the best ways to do it based on who is the audience. By that, the integration of the DMP with marketing and sales is crucial for higher performances.

The Main Differences Between DMP and CDP

There are a lot of similarities between Data Management Platform (DMP) and Customer Data Platform (CDP). But there are also some very specific characteristics we need to keep them well established. Here they are:

Data Collection

One of the main differences between CDP and DMP is that DMP uses cookies to track users’ movement and target marketing strategies more efficiently. DMP was developed to search for data on advertising networks.

On the other side, CDP is a technological advance that gathers customer data from different sources and use it to generate more appropriate content, email marketing or offers.

Objective

DMP was designed to create deeper segmentations for the marketing strategy. CDP focuses on improving conversion rates and customer engagement, creating a richer consumer profile with more information.

CDP is also able to capture information from different channels and devices, in an automated way.

Therefore, investing in a CDP or DMP allows you to transform your company, employing more resources and intelligence to the business, and promoting your brand to a great and higher level of reference and success in the market.

How about starting now? Arena has a Customer Data Platform solution for your company. Build your clusters, make better advertisements, and talk straight forward to the audience you need. Click here and visit Arena’s CDP page!