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.

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.

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.