The Enterprise Marketer’s Guide to Customer Data Platforms

Today’s customer journeys are more complex than ever. 

The majority of shoppers follow a zig-zagging path through a wealth of touchpoints, both online and offline. They might stumble across a company’s social media post, which directs them to a blog, before finally landing on the eCommerce site or visiting the business in-store. 

Customers have high expectations from the brands they engage with, and expect personalisation across all touch points; in fact, Salesforce reports that 80% of customers value the brand experience as much as the products themselves.

With such unpredictable journeys, how can businesses keep track of their customers? And how can they deliver personalised experiences across an ever-expanding set of touchpoints?

The answer: a Customer Data Platform (CDP)

At a high level, CDPs offer a broad range of benefits, including:

  • Delivering unified views of customers and their interactions across every touchpoint 
  • Maintaining strict compliance and privacy standards in the handling of customer data
  • Creating the ability to act on customer data to deliver personalised experiences across every marketing and service channel 

But beyond these benefits are a world of critical challenges and considerations to address before committing to a CDP. To name a few:

  • Does your business need a CDP?
  • If so, do you have a thorough understanding of how a CDP works?
  • What specific challenges is your team aiming to solve with a CDP?
  • How do you choose the right CDP for your business?

In this guide, uncover the top characteristics and considerations when investing in a Customer Data Platform: including what a CDP is (and isn’t), the range and complexity of the data sources that power it, and the most important capabilities you should look for when weighing your options.

What Is A Customer Data Platform (CDP)?

CDPs are a type of software that aggregate customer data collected from a variety of sources, structure it into central customer profiles, and then allow that data to be accessed by other pieces of software. 

CDPs build these customer profiles by combining data from a variety of stores across different data types, including first, second and third-party sources. That means that they can collect and organise data from your CRM, DMP, data lakes or warehouses, websites or mobile apps, and/or POS systems. 

With these profiles created, users can then create audience segments (sometimes even based on machine learning), and activate them across other channels such as paid media,  SMS marketing, customer service tools and even website personalisation. 

The end result is the ability to not only manage data in a compliant and structured way, but also to be able to efficiently deliver targeted, personalised experiences at scale across the whole of the customer journey. 

What Is Customer Data?

Customer data is the currency of modern business. It’s what marketers and brands need to know in order for their products or services to be successful, which is why CDPs have become an essential piece of software for modern businesses.

When we talk about customer data, we’re referring to the bits of information consumers leave behind when they interact with a company. Online examples include commenting on social media sites, such as Facebook and Twitter, using an app that requires login credentials, or cookies left behind from a site visit. Offline, a business may collect data from phone numbers or email addresses from customers who fill out contact forms in-store.

The Data Sources That Power A Customer Data Platform

CDPs collect a wealth of data from different sources and platforms including event-based data and transactional data.

Commonly, the data that enters a CDP can be categorised into 4 main types:

1. Identity Data

Identity data makes up the foundation of each customer profile in a CDP. Identity data enables businesses to identify customers from each other, creating single customer profiles without producing replicas. Identity data as a whole covers information like:

  • First and last names
  • Demographics like age and gender (descriptive data)
  • Locations such as addresses, cities, countries
  • Contact information like phone numbers and email addresses
  • Social platform information, like Instagram or Twitter handles or LinkedIn addresses
  • Professional details, such as job title and company
  • Company account details, like business-specific user IDs or account numbers

2. Descriptive Data

Descriptive data layers onto identity data, expanding it to produce a more comprehensive picture of a customer. Descriptive data categories will vary depending on the industry in which the business is in.

For example, children’s toy sellers would likely collect information about how many young children are in their customers’ families, whereas a sports apparel ecommerce store may collect information about a customers’ gym membership.

Descriptive data usually includes information regarding:

  • Careers, like employers, industry, income, and job descriptions
  • Lifestyles, like the type of home, pet or vehicle
  • Families, like the number of household members
  • Hobbies, like memberships or subscriptions

3. Quantitative Data

Quantitative data gives businesses more information regarding how customers interact with them through actions like click-throughs, their reactions to things like discounts, or their transactions. 

Quantitative data will include information like:

  • Transactional, like the type or number of purchased or returned products, abandoned carts, or order dates 
  • Communicational, like email opens, click-throughs and responses
  • Online activity, such as the number of website visits, click-throughs, product views, and social media engagements
  • Customer service access, like query details, help initiation dates and service representative details

4. Qualitative Data

Qualitative data is a type of data that layers contextual information into customer profiles because it can give a customer profile a ‘personality’. This is because qualitative data collects information about attitudes, beliefs, motivations, opinions and values whether those are relevant to the company or not.

To that end, qualitative data will collect information regarding: 

  • Consumer motivation, regarding how the customer found the business, why they chose to purchase and why a particular product over others
  • Personal opinion, which could give insight into how a consumer rates the product, customer service or business 
  • Personal attitudes and preferences, like a consumer’s favourite colour or material

Why an Enterprise Marketer Needs a Customer Data Platform (4 Key Benefits)

CDPs strengthen your customer relationships, empower your marketing efforts and help your business to reach its objectives. CDPs are capable of doing all this because they provide, among others, the following three benefits:

CDPs break down down data silos

In a business, customer data is typically held and organised by different departments for example, customer service, sales and marketing. Because all three of those departments need different information to complete their tasks, the individual collections of data grow into separate data silos that become fragmented and may use different taxonomies. 

For example, the customer service department may have information about a customer, such as their recent queries, whilst the marketing department may have contextual information on the same customer, such as their purchasing habits. By failing to marry this information due to data existing in different silos, a 360-degree view of a customer becomes increasingly difficult to construct. 

Aside from being an organisational nightmare, this has a direct impact on the customer. For example, a customer who has recently submitted a complaint to customer services might still be targeted by marketing emails or trigger SMS messages asking for referrals. Or a customer who’s recently made a purchase might continue to be retargeted with ads for the product they just bought. 

This failure to build a holistic customer view, as well as the lack of efficiency and transparency that data silos create, has a measurable impact on core business metrics such as: 

  • ROI on acquisition campaigns → Existing customers aren’t excluded from acquisition campaigns, leading to a waste of budget 
  • Customer lifetime value Identifying and acting on key upsell opportunities is challenging 
  • Churn and attrition rates It becomes nearly impossible to understand and act on churn signals

How a CDP addresses this challenge

CDPs aggregate and organise customer data collected from a variety of sources, structuring it into individualised and central customer profiles also often referred to as a ‘single customer view’. This data can then be actioned across the whole stack: for example, connecting a customer’s journey on marketing channels to their customer experience records.

CDPs deliver personalisation at scale

Personalisation across the full customer journey is vital as a table-stakes expectation for a competitive customer experience. However, creating rewarding customer experiences with personalised touchpoints along the user journey is easier said than done. 

How a CDP addresses this challenge

A good CDP not only creates a single customer view to enable accurate personalisation based on the ‘full customer picture’, but integrates with your full marketing stack in order to deliver personalised experiences based on this data in real-time. For example, triggering emails from your ESP based on a customer’s recent in-store transaction. 

CDPs enable customer data compliance

Ever since the introduction of new customer data regulations like GDPR, marketers have been faced with a huge challenge in how they capture, store and use customer data in a way that doesn’t fall foul of the law. 

The problem is that the ‘consent journey’ is just as complex as the customer journey. Consent can be captured in multiple ways across multiple channels, consent preferences may differ based on those different communication types and channels, and may be subject to different regulations depending on geography. 

Without a unified way of viewing customer consent, meeting the compliance needs for processing and activating through marketing becomes a minefield, and inhibits scalable marketing and personalisation.

How a CDP addresses this challenge

Important: not every CDP is equipped to solve this challenge, as most are created for North America (where data compliance regulations are considerably more relaxed). However, good CDPs will have consent mastering (the ability to unify cross-channel consent preferences for an individual) and consent orchestration (the ability to scalably reflect consent in activating data) built-in.

5 Things To Consider When Choosing A Customer Data Platform

There are a number of different CDP providers out there, so once you decide to invest you’ll need to make sure you’re choosing the right one for your business. While there are other factors to consider, here are 5 criteria to watch for as you start to weigh your options:

1. Extensive data integrations

The right CDP should serve as the layer of technology that unites all of your martech and adtech stacks. This means the CDP you choose must allow you to ingest customer data from wherever it’s held, activate that data wherever it’s needed, and repeat this process on an ongoing basis. 

2. Accurate identity resolution

A Customer Data Platform must be able to accurately unify customer identities – without it, the single customer view can’t be created and many functions of the CDP are rendered obsolete. 

3. Custom audience segmentation

If your goal is to drive personalisation with your customer data platform (CDP), make sure that you can create custom audiences based on any data points. Your audience can then be used across multiple channels like email, social media ad campaigns or even within apps themselves through deep linking features, which allow users a seamless transition between platforms.

4. Machine learning-powered segmentation 

Marketers have long known that traditional rule-based segmentation can lead to inefficiencies and wasted spend. However, the ability to generate machine-learned audiences has long required support from Data Science specialists. This support has been difficult to access for many marketers, and impossible for others. 

To maximise time and effort, consider a CDP that offers the ability to create machine-learned segments without the help of a Data Scientist.

5. Rigorous security and privacy compliance

Especially in the more stringent privacy environment of Europe, it’s vital that your Customer Data Platform is completely watertight when it comes to privacy and security standards. Look for international privacy and security certifications, such as ISO 27001, ISO27017, ISO27018, CSA Star and GDPR Seal.

How To Choose The Right Customer Data Platform for Your Business

Finding the right CDP for your company is not a decision that should be taken lightly. 

After all, your CDP has access to sensitive customer data, unifying it from several different departments and delivering it to multiple areas of the business. Making a decision is a process that can therefore get complicated by nature – to make it simpler (without making mistakes), follow these guidelines:

1. Assemble your buying team

While the decision is yours, you’ll need to involve other stakeholders. This is because the data the CDP will be handling is from different departments within your company, so it’s important for everyone to agree on what type of service they need and how much access they’ll have. 

Consider having representation from the following: 

  • Data Protection (DPO) or Legal (to ensure compliance is up to code)
  • Sales (their CRM platform may store customer information to be brought into the CDP)
  • Customer Experience (they also use tools that handle customer data) 

2. Define all your challenges

If you want to know what CDP is best for your business, think first about how the system will be used. Defining your challenges (or use cases) ahead of time will help you find the right solution. In addition to the use cases we outlined in an earlier section, examples could include:

  • Decreasing abandonment rates
  • Increasing engagement with loyalty programmes
  • Identifying and prioritising high-value customers

Take some time to think about what you want your CDP to accomplish and then talk with other stakeholders for their input. Once these ideal use cases are identified, evaluating vendors becomes a lot easier.

3. Know what integrations you need

Next, make a list of all tools used or integrated with your customer (e.g., website software, CRM systems like Salesforce, realtime live chat with Zendesk) before making any decisions on which pieces should be included in the new project.

Businesses most often start with:

  • An analytics tools like Google Analytics
  • An advertising tool like Facebook Ad Manager
  • CRMs 
  • Customer success and/or live chat tools like Intercom
  • Business intelligence tools
  • Data warehouses 

Get an in-depth look at the top characteristics of an investment-worthy CDP

Before a CDP can offer solutions, you’ll need to ask the right questions. The factors outlined above are a step in the right direction, but there are other attributes that should be considered when weighing your options. 

Download The Enterprise Marketer’s Guide to Customer Data Platforms for an in-depth look at the many layers of a Customer Data Platform, including:

    • Why an Enterprise Marketer needs a CDP (and how other Enterprise Marketers use them)
    • Additional data sources that power a CDP
    • A detailed ‘CDP shopping list’ including the top 10 considerations for success
    • A complete overview of how to choose the right CDP for you