Tag Archives: customer acquisition

What is and how to do Customer Data Management CDM

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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

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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:

  1. What message will you tell them?
  2. How will you communicate with them?
  3. When will you reach out to them?
  4. Where will you find them?

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

  1. Goals and pain points;
  2. How they behave;
  3. The best timing according to their routine;
  4. 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.