What is a CDP?
A Customer Data Platform (CDP) is software that allows you to leverage what you know about your customers to create experiences that are more compelling and relevant to them.
A CDP integrates all your (relevant) customer data into a central database and unifies that data to create a single view of your customer. You then use that holistic, 360-degree view (complemented with AI/ML) to better understand your customer—who they are, what they like, their shopping history and habits, etc. With that enhanced understanding, you can then engage with them on a 1:1 level.
What a CDP is NOT
- Before we dive into the features, use cases, and benefits of a CDP, we should clarify what a CDP is NOT.
- It’s not a Customer Relationship Management (CRM) tool; a CRM focuses on the sales cycle, whereas a CDP has a broader lens and application.
- It’s not a Data Management Platform (DMP); a DMP is used heavily in advertising and relies on third-party data to build anonymous audiences.
- It’s not a Personalization tool; a CDP can enable personalization and some CDPs have personalization capabilities, but a CDP does much much more.
Key Features of a CDP
With that said, let’s dive deeper and examine the four key features that define and differentiate a CDP from other types of platforms.
1. Data Integration – A CDP ingests your data—wherever it’s stored and in whatever format—and stores it in a central data store. It’s critical that the data you feed into CDP is
- your customer data (i.e. first-party data),
- data that can enrich your customer profiles (i.e. second and third-party data),
- and data from all your marketing channels (e.g. web, mobile, social, catalog, content, transaction, call center, POS, IoT, etc). Feeding only one channel of data (e.g. only web) into a CDP defeats the purpose of using a CDP.
Once ingested, cleansed, and enriched (using that second and third party data), the data is available for resolving into user and/or account profiles, to feed machine learning models, for analysis, and for internal/external sharing.
2. Identity Resolution – A CDP uses the cleansed and enriched data, along with a set of identity rules and AI/ML, to create unified user and/or account profiles. Session and device stitching play a big part in this step, especially in resolving unknown to known users. This is where the promise of a “Single View of the Customer” is fulfilled.
Profiles can contain attributes related to demographic, geography, loyalty, transaction, and much more, but it also should include preference information related to privacy, etc. It can contain content, and should flag/hide sensitive/secure information.
3. Segmentation – A CDP uses the unified profiles to create segments/audiences based on various strategies, e.g., demographic, lookalike, interest-based, purchase history. Segments can be built manually or generated with the help of AI. Note: Data science (AI/ML) is a foundational capability of a CDP, enabling and enhancing almost every function within the CDP. With Segmentation, AI helps identify segments that may not be found manually.
4. Activation – A CDP pushes audience information into external systems that can use that information to more intelligently orchestrate their marketing campaigns. Some CDPs have tight integrations with key channels like web, mobile app, and email, such that they’re able to activate directly. (link forthcoming)
Use Cases for a CDP
So, with all this, why use a CDP? There are several use cases, though this is by no means an exhaustive list.
1. Personalization – With everything you know about your customer (current behavior, past behavior, propensity to purchase, etc.), you can create truly personalized experiences for them, manually and/or leveraging AI.
2. Optimization – CDP’s utilize ML as well as traditional experimentation methodologies (a/b and multivariate hypothesis-driven testing) to optimize cross-channel customer experiences—whether that’s content, media, product recommendations, etc.
3. Mapping the Customer Journey – Combine and analyze data across touchpoints to map your customer’s journey and inform attribution.
4. Reporting & Analysis – Leverage all of the data in the CDP, including activation results, to make better, data-driven decisions and optimize your customer experiences.
These use cases can manifest in real-world applications, such as recommending products/services on the web, sending push notification of offers and products on your mobile app, sharing the next best offer (NBO) to your customers via email or your call-center personnel, retargeting inactive customers, upselling/cross-selling, identifying the next best action, recommending similar music/shows/books/articles, analyzing usage data to indicate new products or services, etc.
Benefits of a CDP
With these key features laid out, it’s clear that the benefits of a CDP are
- A central customer data hub (consisting of cleansed, unified, and enriched data)
- 360 degree views of your customers
- A better understanding of your customers i.e. their behaviors, affinities, preferences, etc.
- The ability to utilize that enhanced understanding and share it with your key marketing systems, so that you can deliver the right content, at the right time, to the right person, in the right channel
- Data democratization
- The ability to coordinate marketing efforts across channels
- The ability to make data-driven decisions
- The ability to do continuous optimization
- A competitive advantage that can be acted on in real-time
How do you know if you need a CDP and which of the many platforms out there is the right one for your organization?
If you find yourself still not truly knowing who your customers are or what they want, sifting through data in siloed systems from siloed channels, making marketing decisions based on a single channel vs. your customer’s cross-channel behavior, and not taking advantage of ML/AI to create experiences that progress your customer along the customer journey, then you most likely could benefit from implementing a CDP.
If you don’t know where to start or need assistance in selecting the right CDP for your organization, Search Discovery can help. Here’s the process we follow to help our clients evaluate and select a CDP:
1. Gather/Define your Requirements and Use Cases – Start with the challenges that your organization is facing, what your marketing goals are, your key use cases, and your must-have requirements.
2. Create a Short-list of CDPs – Determine which platforms may be good candidates for your organization by evaluating them and matching them to your requirements.
3. Conduct Vendor Demonstrations – Reach out the vendors on the short-list, share your requirements and use cases, and ask them to demonstrate how their CDP can fulfill those requirements.
4. Evaluate potential risk/challenges – With the additional information you will have received from the demos, you can assess potential risks and challenges for each platform, as well as TCO.
5. Select a platform – Make the final decision based on all the information.
With a platform selected, the next step is implementation. More on that to come in future articles, but note, as beneficial as a CDP is, it’s not a trivial system to implement and requires solid people and process to complement the technology. Search Discovery’s CDP services take a holistic approach, focusing on strategy and organizational enablement, in addition to implementing the technology.
As you can see, we really see the value of a CDP. Implemented and rolled out correctly, it can bring you closer to customer marketing nirvana: reaching the right person, at the right time, in the right channel, with the right content!