Using Data Enrichment to Improve Marketing Performance


For brands that seek to put the customer at the center of everything they do, and want to do so at scale, data is the foundation. It all begins with the data set you collect about your customers, directly from your customers. Your all important first party data. In its raw form, however, first party customer data isn’t as useful as marketers need it to be. To make existing data useful, businesses rely on data enrichment.

What is Data Enrichment?

Data enrichment is the enhancement of any data using information from another data source. Enrichment can be conducted by bringing together multiple sources of data from within the organization, to paint a more comprehensive picture of the customer’s behavior within the four walls of the brand.

Data enrichment can also be conducted by appending externally sourced data to your first party data. External sources of enrichment data could be business partners, data syndicators (like Nielsen or GfK), public sources (e.g. Census or Bureau of Labor and Statistics data), or newer sources of digital data (e.g. Google mobility data). This type of enrichment provides a deeper insight into how customers behave outside the four walls of your brand.

How Data Enrichment Differs From Data Cleansing

Data cleansing is typically a prerequisite to data enrichment. In data cleansing, businesses take data that has corrupt, inconsistent, redundant, inaccurate or poorly formatted information and clean up the data quality.

For instance, some legacy systems store customers’ first and last names in a single field with an underscore between the names. A marketer would want to remove the underscore, check for middle names in the mix, and separate first and last name into two separate fields. The name fields would then be ready for use in personalized email marketing tokens.

Additionally, businesses often have differing representations of the same customer across multiple systems. For instance, the same customer may have provided their work email address to a call center rep, but used their personal email address when creating their mobile app account. It’s likely this business does not understand that these two separate email addresses represent the same single customer.

Tackling this challenge is a specialized use case of data cleansing called identity resolution. The output of successful identity resolution is a single identifier across all internal systems for that one customer. Once this data cleansing prerequisite is complete, your business is now positioned to enrich its customer data by bringing together data about the customer from internal and external sources.

(Learn more about why identity resolution is critical to best-practice customer database management).

Why is Data Enrichment Important?

Data enrichment is important because it takes raw data that may not be very useful, and makes that data insightful and actionable.

Here’s a clear-cut example from the consumer lending world of how data enrichment can make data more valuable. When a consumer applies for credit, the lender gathers information directly from the consumer such as name, address, occupation, social security number and more. But based on that information alone, the lender isn’t able to make a decision about lending to the borrower. The information at hand simply isn’t insightful or actionable enough. To make it actionable the lender will seek to enrich the data with information from a third-party credit bureau like Experian, Equifax or Transunion.

Using the borrower’s social security number as the common identifier, the credit bureau will provide data about credit account balances, payment history, inquiries, any derogatory marks and more. They will also provide a credit score. The lender may then append some of that data to the first party they have already gathered about the borrower—it is now enriched with credit information, making it more useful and actionable. Specifically, they leder will use it to decide whether to lend, how much to lend, and under what borrowing terms.

Data Enrichment at a Foundation for Customer Relationship Marketing

The example above brings the power of data enrichment home for just about every consumer. But how can data enrichment benefit marketers?

As we discussed at the opening of this piece, modern marketers seek to put the customer at the center of everything they do. That means creating authentic, personalized experiences informed by everything from the customers’ entire history of interaction with the brand to their in-the-moment behaviors across all the brand’s channels—whether online or offline—as well as characteristics of the customer such as demographic data, psychographics and more.

Data enrichment is the only way to bring these disparate elements of information together so marketers can have the customer insights they need to deliver great experiences, and build the rich segments and 1:1 activation that cements deeper and more loyal customer relationships. 

6 Top Benefits of Data Enrichment

Data enrichment offers marketers and their organizations a range of benefits including:

  • Improved customer segmentation. Enriched data has more attributes by which marketers can define customer segments. This makes it easier for customer experience (CX) professionals in marketing, sales, product, and service teams to organize and scalably manage more tailored interactions and relationships with similar groupings of customers.
  • More effective communications. Data enrichment expands the depth and breadth of insights marketers can access about every customer. This allows marketers to executive pinpoint targeting of offers and content that are more relevant—boosting conversion and brand loyalty.
  • Enhance existing customer experiences. Customers want brands to know who they are, understand their preferences, remember past interactions, and anticipate customer needs and wants. Enriched data provides the insights you need to tailor the helpful, contextual experiences that drive higher customer satisfaction and keep customers engaged with the brand.
  • Precision algorithms. Marketers are increasingly using predictive analytics, machine learning and AI to develop accurate data and model customer behavior and predict wants, needs, propensity to convert and much more. The richer the data fed into these models, the more accurately they can perform.
  • Reduced data management costs. By enriching data in a planned, structured way, brands reduce the need for departments or IT to do one off joins, merges, appends and data integration projects. This reduces costs of data management, and puts insights more readily at the fingertips of the marketers who need them.
  • Increased sales. Enriched customer data enables marketers to better understand the ideal target customer, their potential lifetime value, what offers they’ll respond to, and what will drive them from a first time customer to a loyal repeat customer. This understanding allows marketers to create experiences and campaigns that drive new incremental sales.

Getting Started With the Data Enrichment Process

The first step to customer data enrichment is to assess the sources of customer data that exist within your enterprise.

#1 Begin with your offline and online customer touchpoints which can include:

  • Websites
  • Mobile apps
  • Point of sale
  • Digital commerce
  • Call centers
  • Surveys

#2 Next, examine the systems that manage and store some of the data gathered via your customer touchpoints. These can include:

  • CRM
  • Order management
  • Data warehouses
  • Data lakes
  • Many other systems

#3 Assess the state of data integration and unification within your organization. Is the customer data from the systems and touchpoints above unified within a single customer database? Is that database accessible to marketers in a way that lets them activate the data within? For many organizations, the answer is no (continue to step 4!)

#4 Seeks solutions, tools and approaches for data cleansing and identity resolution. As mentioned above, these are prerequisites to getting started with data enrichment of customer data. Once this process is complete, your data is ready to be unified.

#5 Unify your customer data into a customer database. For many modern marketing departments, a customer data platform (CDP) serves as the point of unification of customer insights, as well as the set of applications through which marketers access and activate customer data.

#6 With the unification process complete, your internal customer data is enriched with all the other internal data sources that richly attribute your customer records, readying them for powerful segmentation, targeting and the deployment of 1:1 experiences.

#7 Now, you’re ready to investigate external data sources that can further enrich your customer data and provide powerful new insights and attributes about your customer profile.

Get Started with Your Data Enrichment Strategy Today

ActionIQ and our industry leading CDP platform can help you plan and execute a data enrichment strategy that moves the needle on your customer relationships and most critical marketing KPIs. For a consultation with one of our customer data and customer experience experts, contact ActionIQ.

Florian Delval
Florian Delval
Director, Technical PMM
For the last decade, Florian’s mission has been to empower enterprise organizations in their digital transformation process via the definition and deployment of a strong Customer Experience Stack. Florian educates enterprise organizations to increase the value of their technology investments in a complex and ever changing environment. Find him on LinkedIn.
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