Framework to drive a successful Customer Data Platform (CDP)
By Madhusudhana G K
In today’s digital modernization services, every enterprise is aspiring to adopt CDP to deliver hyper-personalized services, which would allow them to retain their existing customer base and acquire new consumers.
Over the past few years, I have seen success and failure models of CDP adoption, enablement, and success measurements. In one of the enterprise engagements, one of the products was chosen as CDP services, but they were unable to measure the success of CDP in their business even after 6 months. There are many gaps in the way it’s been thought through and designed. Their existing systems (content, analytics, and campaigns) were not maturely designed to capture the required data.
There were many aspects to think through and design for the success measurements of CDP services.
While being part of customer conversations and solution propositions, here is one of the frameworks for measuring the success of CDP enablement.
1. As a consultant, ask these questions before proposing a CDP solution.
· What are those key challenges driving a hyper-personalized experience in the current business echo system.
· Are current systems (IT Landscape) matured enough to derive those behaviors and touch points?
· What values are derived through CDP adoption?
· What can CDP do for my business?
· How does CDP help drive hyper-personalization in the cookie and cookie-less worlds?
· What are my business goals and vision for adopting CDP in my business?
· What use-case scenarios drive and build our customer 360 profile?
2. Goals and Measurements
One should define the goals that would drive measurement and success.
For example, in the given business, we know what type of user profile data we have in our distributed systems. To start with, define not more than 2 to 3 use-cases, which would set a base framework and a platform. Define the parameters that would collect as much data as possible across the user journey across the channels. Based on the collected journey-based data, define the hype-personalization one would define and transform, which would allow one to retain existing consumers and acquire new ones.
3. Discovery Framework
Knowing the business models and distributions across the markets, it is not wise to define and propose a one-shot CDP solution (platform or product). I have seen such solutions fail literally and am unable to measure the success even after 6 months. The best way is:
· Understand how current systems are mature in reaching their AdTech and MarTech systems to reach their consumers.
· Understand the existing system landscape and the type of data being collected (1st party).
· See if the collected data is relevant to connecting user behaviors, transactions, emotions, and interactions across channels (over the Web, mobile, POS/Call call center, etc.).
· Collect and analyze 3rd party data in relevance to 1st party data and define a kind of co-relationship.
· Its very critical to understand the analytics system capturing the user behavior data. At times, we have redefined the whole analytics model by the way it collects the data at its core.
· Understand the way businesses reach out to their consumers, whether through their own campaign systems or third-party systems.
· Understand their content and personalization strategy.
4. Use-case Framework
The use-cases strategy is very crucial and should be well thought through to address their current and future business models across markets and channels. Ask some of the basic questions, like:
· What personalization use case would drive cross-channel behaviors?
· What would be the use case for driving real-time journey-based marketing?
· Search-based marketing to drive consumer values.
· Real-time sentimental analysis (e.g., call center interactions, online chat, service-based calls, etc.)
· Personalization based on historic behaviors
· Driving personalization through social behaviors and third-party interactions
5. Product assessment and Recommendations
Right platform selection is one of those key phases in the whole CDP adoption. There are various platforms available on the market. It is important to choose the right CDP with the TCO model. This is one of those deep exercises to deal with.
6. Conception Approach (Implementation Framework)
This is a very critical phase where we define the success of CDP enablement and rollouts. We account for three mainstreams of conception.
1.Business strategy and foundation (information inventory, systems maturity, requirements blueprints, journey blueprints, business priorities)
2. MVP — Global reference architecture (platform landscape, reference architecture, integration pipeline, data and processing pipeline, segmentation, channel enablement, pilot implementation, ROI mapping, and measurement)
3. Enablement (activations and market specific customizations)
I have seen that these elements contribute to a well-defined framework to enable, activate, and measure the success of any CDP initiatives. To be honest, we have filled some of these gaps while we try to fix some of the failed implementations.
