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5 frequently asked questions about Customer Data Platforms answered

5 Frequently Asked Questions about Customer Data Platforms

Over the past three years, there has been a lot of confusion about what a Customer Data Platforms (CDP) can and can't do, and subsequently what benefits a CDP can bring to a company. Here are the 5 most frequently asked questions about Customer Data Platforms:

1. Can I use our home grown solution to create CDP-like benefits?

A Customer Data Platform (CDP) will typically be controlled and used solely by the marketing team, so the information stored will be customer-related (contact information, customer activities/behaviors and transactions). Its raison d’être is to create a Single Customer View (SCV) by normalizing the customer data collected from marketing and operational systems across the business, and drawing together all known information about the customer into one ‘Golden Record’. During the Single Customer View creation process the CDP will cleanse the data, correct incorrect or inconsistent formatting, and merge duplicate entries. The data is also persistent, which means that it is retained indefinitely (unless required to be removed by law), including every change or process, which is then timestamped for 100% traceability.

A CDP is purpose-built for the Marketing Department and is designed to remove their reliance on internal departments (IT for example) or 3rd party agencies for the processing of customer data, or the need to employ dedicated people to cleanse data for every campaign. The IT Team also benefits from the purchase of a CDP, as they will no longer need to process data queries for the Marketing Department.

A ‘home grown solution’ will commonly be a mixture of tools and processes revolving around a Data Warehouse or Data Lake, created with multiple use cases in mind and designed to store historical information (not necessarily related to customers) from different departments across the business. For example, a non-marketing related use case that I’ve seen before was to better regulate the heating of a multi storey office to save money and become more eco-friendly. That's certainly not the foremost thought of the marketer!

The ability to formulate customer matching rules, create real-time connectors to marketing automation tools and conduct customer data enhancements is not usually a key requirement of a Data Warehouse or Data Lake. Therefore, the common marketing use cases for a CDP purchase, such as improved targeting of marketing campaigns or better personalization of offers, are usually not in scope. Extracting data from the Data Warehouse can also require the creation of special queries, and therefore advanced technical knowledge. So, IT will need to manage the warehouse and marketing queries will go through them. Again, a primary use case for a CDP is that the reliance on IT or 3rd parties should be reduced, enabling easier access to data for the Marketing Team.BlueVenn-Galaxy-2.0-2019-FINAL-outlinedx2

A final differentiation is that a ‘home grown solution’ will require building and maintenance. By using ETL and piecing together some manual processes with various technologies and technical processes, you can probably achieve the same benefits as a CDP. However, this will entail long projects and continual maintenance, while a CDP is purpose-built for Marketing and is continually updated and developed by the vendor for its customer.

2. Will a CDP improve our data quality?

The CDP Institute has a list of 5 criteria that must be met for a customer data management system to be certified as a 'RealCDP', namely it must be able to:

  • ingest data from any source
  • capture full detail of ingested data
  • store ingested data indefinitely (subject to privacy constraints)
  • create unified profiles of identified individuals
  • share data with any system that needs it.

As you can see, the integrity or quality of the data is not explicitly mentioned, although you could argue that the creation of unified profiles should include cleansing, de-duplication and normalization. However, there are CDPs on the market that don’t do it!

That being the case, data optimization is something you’ll want to ask about in your Request for Information (RFI) if cleaner data is a key requirement for your organization. The CDP Institute argues that such optimization is not a core requirement in all CDP purchases, but we struggle to see why that would be. After all, if your data is inaccurate or out of date, then any insights or marketing campaigns you execute from that data will be too.

A Marketer’s Guide to Customer Data Platforms eBook


Download our eBook for more CDP advice, to learn how a CDP differs from other data management technologies, or to find out about the different types of CDPs and what to look out for when researching technology vendors.

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3. Can a CDP handle our marketing automation requirements?

Most CDPs will offer a means of activating your data to power marketing automation, personalization, mobile marketing and other marketing campaign requirements. Some provide marketing automation functionality within the solution itself. Commonly, you will find CDPs that provide a real-time personalization front-end, while some exclusively provide tag management. There is a growing prominence, however, of ‘campaign CDPs’, which provide multi-channel campaign orchestration capabilities within the platform itself.

More recently, CDPs have started to be categorized into the different activation buckets of ‘personalization CDPs’, ‘tag management CDPs’, ‘campaign CDPs’ and ‘pure CDPs’.

So, yes, a CDP can solve your marketing automation needs as well, but you need to choose the right CDP that matches those needs or requirements.

One thing to check with a CDP that offers ‘journey orchestration’, ‘marketing automation’ or ‘cross-channel campaign management’ is whether it simply provides segments of customers to your marketing automation channels, or whether the ability to create the campaign workflow itself is enabled within the CDP. If the latter, then you will be able to coordinate all your online and offline channels from one campaign workflow, rather than relying on separate systems to manage campaigns in silos.

This CDPs and Multi-Channel Campaign Management webinar is a useful resource to help you understand the benefits of having a campaign management workflow within your CDP, capable of combining unified data with unified marketing decisions.

4. Does the CDP have a User Interface (UI) for managing data?

Very few CDPs actually do. You could argue that a data management UI should be a RealCDP requirement, in accordance with the CDP Institute’s statement that “a Customer Data Platform is packaged software that creates a persistent, unified customer database that is accessible to other systems". However, the data layer within most CDPs cannot be accessed, so leveraging it is one of the ‘services’ that come with the CDP purchase.

We have heard on the grapevine that, in some cases, this results in a long database project with high cost and risk, one of the very issues that CDPs are meant to eradicate. This intention is confirmed by the CDP Institute’s statement that, “the CDP is a pre-built system that is configured to meet the needs of each client. Some technical resources will be required to set up and maintain the CDP, but it does not require the level of technical skill of a typical Data Warehouse project. This reduces the time, cost, and risk and gives business users more control over the system, even though they may still need some technical assistance.”

A data management UI within the CDP hands more control to the user, meaning less cost for additional services, and creates a transparency to how your data is being processed in the CDP. The UI enables non-technical users to load data or connect to 3rd party systems to ingest it, facilitating the continual maintenance of the CDP over time, without a reliance on the vendor or a third party for ‘technical assistance’. Similarly, a UI enables users to choose the data processes and matching rules that will control the way the data is cleansed, merged, de-duplicated and enhanced, so that they can maintain the integrity of that data without needing external help.

Download The Business Case for a CDP infographic now.

Customer Data Excellence Report

Respondents at organizations with CDPs are at least three times more likely than those at other companies to agree firmly that they have the following attributes:

  • A Single Customer View.
  • Ability to execute multi-channel campaigns from a single platform.
  • Use attribution beyond first/last-click to improve paid media performance.
  • Use machine learning for data analytics and real-time decisions.

To download the infographic as a PDF, simply click on the download button. 

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5. What types of identity resolution does a CDP do?

Identity resolution means determining whether two or more records belong to the same person, company or device, then using matching rules to group them together in an automated way and merge the information to create a single view of that customer. The matching rules, and the way the data is processed, can be as complex or as simple as required, but for precision marketing ID resolution is an absolute necessity. All CDPs should undertake identity resolution and use matching rules to create a unified customer profile, but they do not all do it the same way, so the methodology is a useful topic to drill into when researching CDP vendors.

A good eBook to get you thinking about matching rules and how to define them for your business is How Many Customers Do I Have?

There are three main types of identity resolution and a CDP may do some or all of them. Some CDPs provide out-of-the-box, one-size-fits-all matching rules, while others provide rules that you can choose and prioritize. So, it’s worth checking what each specific model can do when speaking to vendors, and then associating the capabilities back to what you need your CDP to do.

Possible methods of ID resolution are:

  • Fuzzy matching

    fuzzy-matchingThis term describes a set of matching rules that identifies similarities between multiple data elements. The fuzzy matching rules will look to see if two records include the same name, same email, same address or postal code, and make a decision to match them if there is sufficient similarity across the data fields. The criteria for matching these multiple records may be ranked. For example, a postcode is more likely to be unique and accurate than a first and last name, and therefore a matched postcode will supersede the name fields. Equally, a cell phone number might be even more likely to determine a unique match and supersede the postal code. Determining the software’s rules for fuzzy matching should be a crucial part of your CDP selection.

  • Exact matching

    exact-matchingSimpler than fuzzy matching is exact matching. This technique is often used for updating client source data. A Social Security Number, email address, customer reference number or other unique identifier from another source system will enable the CDP to create a direct match if that identifier is already stored in the system. When data is first loaded into the CDP, a Global Unique Identifier (GUID) is assigned to each record, as well as the unique ID from the original source system. Retaining the original source system ID ensures exact matching in the future when the data is refreshed or loaded again, whilst any new records are also added and new GUIDs are created for those records.

  • Cross-device matching

    cross-device-matchingThis is the process of identifying that two devices are owned by the same person. You may not know who that person is, but this technique is used to build up anonymous profiles of user activity before the user authenticates with the brand (i.e. completes a form submission or makes a purchase). CDP vendors will often use an integration to 3rd party data providers that collect huge volumes of device data and connect devices to individuals using an Identity Graph. Doing so will enable you to identify anonymous users in your CDP without them authenticating. This use of 3rd party data matching is not always legal in parts of the world where device IDs, cookies or IP addresses are defined as ‘personal data’ or ‘personally identifiable information (PII)’, so must be undertaken with caution when holding data on citizens that falls within laws such as the GDPR. However, such matching helps organizations to start to identify huge volumes of anonymous browsers from their digital channels or understand when an existing customer is using a device that was previously unknown.

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  • Use predictive analytics to make real-time decisions that positively affect the customer journey
  • Improve targeting of campaigns using customer segmentation and RFV analysis
  • Use real-time personalization to better engage customers
  • Integrate online and offline channels into the BlueVenn Customer Data Platform to create a true Single Customer View
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Topics: Marketing Data Enhancement data management customer data Data Quality Customer Data Platform marketing automation data unification marketing database cdp