What is a customer data platform (CDP)? Definition, key features and implementation best practices

Data is arguably one of the world’s most valuable resources. Most companies understand the need to collect customer data, but they must act on this information for it to be of any use. A customer data platform can help them start that journey.

While many organizations today are constantly trying to capture more customer data, they can also struggle to make sense of it. It can be challenging to understand customers across all touchpoints and lifecycles. CDPs give businesses the tools they need to overcome these obstacles.

What is a customer data platform?

At its simplest level, customer data platforms consolidate all of a company’s customer data into a single place. These software packages pull information from various sources, including social media, mobile apps, emails and company databases. They then organize it into one place where teams can view and act on it.

CDPs use this data to create customer profiles, often called single customer views (SCVs). These SCVs can become a source of truth for anything the company needs to know about a specific client. That way, it’s easier to personalize marketing campaigns, to understand the market, and to avoid confusion.

Customer data platforms work by first connecting to data sources, which can be anything from social media profiles to customer service records. Then, they verify and combine this data — including removing repetition — to form comprehensive SCVs. As they get new information, they’ll update SCVs accordingly to provide consistent, up-to-date records.

Benefits for enterprises

Nearly every consumer is more interested in buying from brands that recognize them. CDPs make it easier for businesses to personalize customer interactions and achieve those improvements. The primary way these platforms do that is by providing a more complete picture of each customer.

Different data sources may tell you alternate things about people. Combining this disparate information through a CDP gives you the whole picture, letting you personalize marketing or message content to a greater extent. Being able to see all this data from one place also streamlines the process.

CDPs also make it easier to run effective multichannel marketing campaigns. With all customer data in one place, businesses can ensure advertising strategies are consistent across all channels, converting leads into customers faster. Other benefits include:

• Making data easily accessible for all teams
• Making data easier to secure
• Enabling more automation
• Integrating with other IT tools

CDP use cases and examples

The customer data platform market was worth $3.5 billion in 2021 and could increase almost five-fold to $15.3 billion by 2026. Consequently, businesses have many CDP solutions to choose from. Some of the most popular options include Bloomreach, Insider, Segment, Totango, Emarsys and Tealium.

Since customer data can influence many operations, CDPs have many potential use cases. Personalized marketing is perhaps the most straightforward one. Marketers can use SCVs to tailor marketing materials to individual users’ preferences and personalities, making these efforts more effective.

Similarly, some companies use customer data platforms to segment their markets. With so much information in one place, teams can easily sort their customers into different demographics to understand how they reach various markets. Alternatively, companies can look at how SCVs change to understand customer churn or other behaviors.

Also read: What is customer data? Definition, types, collection methods and analysis best practices

Types of customer data platforms

Customer data platforms come in a few different types, too. Generally speaking, these platforms fall under four categories:

• Data CDPs
• Analytics CDPs
• Campaign CDPs
• Delivery CDPs

Data CDPs are the most basic of the four types. These platforms collect data from multiple sources and consolidate it into a single system, making it available to other systems but not much else.

Analytics CDPs perform all the same functions but take things a step further. As their name implies, they also include analytics functions, helping automate some processes. That can consist of automatic customer segmentation, predictive modeling or mapping the customer journey.

Campaign CDPs are similar but can distinguish between individual customers’ specific treatments. On top of analyzing market segments, they can manage unique marketing materials, messages and interactions for each user. Delivery CDPs include all those functions but add message-delivery systems to reach out to these customers.

Must-have features to look for while selecting a CDP

Whichever of the four types of CDP businesses are looking for, they should watch out for some key features. Some — like data ingestion and identity resolution — are core functions of CDPs, so you’ll see them in every solution. Others may not be standard but can make a significant difference.

One of the most important of these is data cleansing. Data cleansing features remove redundancies and incomplete information and standardize data formats, ensuring their records are more accurate. Considering that poor-quality data costs companies $100 per correction, cleansing data before acting on it is crucial.

A similar feature to look for is data enrichment, which complements first-party data with information from outside sources, making SCVs more comprehensive. Automatic segmentation — especially real-time segmentation — is also essential. Other vital features to consider include:

• Predictive modeling
• Email and marketing automation
• Multiple third-party integrations
• Business intelligence

Top 7 best practices for implementing CDPs in 2022

While customer data platforms have a lot of potential, they don’t deliver on it automatically. Like the data itself, these tools require the proper application to show their full value.

To make the most of CDPs or any other tool, businesses must understand how to pick, adjust and apply them. With that in mind, here are seven best practices for implementing CDPs in 2022.

1. Define your goals and needs

Before businesses even look at available CDP solutions, they need to ask what they want from them. The best platform for a company depends on its specific use cases, goals and technical requirements. Consequently, teams need to determine what these are before they can make an informed decision.

First, they should decide what they want to accomplish with their CDP, whether that’s reducing customer churn, improving marketing spending or something else. Once teams know that, they can determine how they’ll use it and highlight which features they need. It’s best to leave room to expand CDP usage, too.

It’s also important to consider technical integrations and support. The average organization uses 110 software applications, which doesn’t even include potential data sources like social media. With so many different programs, making sure your CDP works with what you already use is crucial.

2. Compare vendors

Once companies know what they need and want, they can make a more informed decision about specific CDP vendors. The shopping process should start by eliminating options that don’t have critical features. Teams can use the filters on software comparison sites to help narrow down their options.

Since the CDP market is so large, businesses will likely end up with a shortlist that isn’t exactly short. They can narrow their results further by looking at their budgetary concerns and eliminating any that are too expensive. Factoring in future growth is essential here.

Next, teams should ask vendors about any free trials or demos they offer. These will provide hands-on proof of how each platform could meet their needs and how user-friendly they are. After this process, a frontrunner should emerge and companies can pick the right CDP solution for their needs.

3. Determine what data you need

When businesses are ready to implement their customer data platform, they should consider what they feed into it. The natural reaction may be to gather as much information as possible, but this isn’t always the ideal solution. Some data may not be relevant to the specific use case at hand.

Teams should evaluate what they want to accomplish and determine what data is the most relevant from there. That means leaving out irrelevant information and considering additional data sources they may need. The more closely they can align their data with their goals, the better results they’ll get.

Keeping regulations like the General Data Protection Regulation in mind is also vital. Laws and regulations tend to update frequently, so teams should regularly review these considerations. There may be some restrictions on the types of data they can collect or how they can use it.

4. Clean the data

Once businesses have the right information, they need to clean it before using it. Ideally, the CDP in question will have built-in cleansing features, which companies should pay attention to. If not, they should use other software to clean and organize their data before running it through their CDP.

Data cleansing combines duplicate information, standardizes file formats, verifies information and removes outdated data. While this adds another step into the process, it’s crucial as it ensures the information companies use is reliable. Analytics is only helpful if the data is accurate and easy to understand, which cleansing provides.

Cleaning data before analyzing it will also help streamline the process, as better organization fosters faster analysis. If any legal regulations require businesses to remove some identifiers from their data, cleansing can do that as well.

5. Implement reliable security measures

Any process that involves customer information should include strong security. As helpful as customer data platforms are, they’re tempting targets for cybercriminals since they store so much in one place. Companies need reliable cybersecurity if they don’t want to face substantial legal trouble, reputation damage and business losses.

Compromised credentials are the most common cause of data breaches, so strong password management and two-factor authentication are essential. It’s also best to encrypt all the data you use, both in transit and at rest. That way, if anything leaks, it still won’t reveal any sensitive details.

While CDPs can be valuable to many different teams, it’s best to restrict access to them and their information. Only people who need it to do their jobs should have access — and the same goes for other programs and devices. This will minimize the spaces where vulnerabilities could arise.

6. Act on CDP insights

Once teams start using CDPs to consolidate and organize their data, they need to act on it. These insights can be a huge help, but only if companies do something with them.

This step should come naturally if businesses follow the previous best practices listed here. Teams using the CDP to personalize marketing strategies should look at SCVs to see what resonates best with different demographics. They should then tailor their ads accordingly and monitor any changes.

Alternatively, if teams want to reduce churn, they should look for trends among customers that leave. If there are any commonalities, they should change those factors. CDPs make it easier to do all of this by organizing the relevant information, but they won’t do it all themselves.

7. Set benchmarks and monitor performance

If teams want to make the most of their CDP, they need to benchmark its performance. U.S. marketers spent $19.9 billion on data in 2019. With expenses that high, it’s critical to make sure teams are using their data tools to their fullest potential.

Companies should have set goals before selecting a CDP solution and they can use these for their initial benchmarks. After altering strategies based on CDP insights, they can review their performance concerning these goals. If they exceed them, they can set new ones — if not, question why.

CDP success is often a matter of how businesses use it more than the platform itself. Still, the software may not meet teams’ specific needs, so it’s important to ask whether any issues stem from usage or misalignment of goals and features.

Make the most of customer data platforms

Many types of customer data come from many locations and it could all help businesses. Customer data platforms can help companies understand and act on this wealth of information, regardless of what that looks like in practice.

Knowing what CDPs do, how they do it and what features to consider can help teams fully capitalize on these helpful tools. They can then take their businesses into the future, using customer data to fuel ongoing improvements.

Read next: What is customer data management (CDM)? Definition, process and strategy best practices