Six steps to Data Maturity: A Maturity Model for Data Management while adopting a CDP
A Customer Data Platform (CDP) helps create a unified customer database from customer data gathered from various sources. This way, a coherent picture is created of the customer, and data can be used in a real-time format. Research has shown that the global CDP market will grow from $903.7 million in 2018 to $3.3 Billion by 2023 with a CAGR of 29.3%. However, given the range, breadth, and flexibility offered by CDP, it is essential to analyze the kind of data one has and what sort of CDP would suit the same. Organizations must be aware of how to harness the data in their customer data platform for better customer experiences and improved business performance.
Importance of the Data Maturity Model:
According to BlueVenn in a report titled Customer Data Excellence[i], a data maturity analysis can help organizations understand how to deal with their data. Such understanding allows for:
- Defining and prioritizing the customer experience requirements
- Rigorously translate the customer experience into customer data requirements.
- Audit the current capabilities
- Define a data and technology roadmap aligned to the business goals
- Adopt an integrated approach to leveraging (and monetizing) customer data
- Identify and unlock synergies across the marketing programs.
Data Maturity Stages:
There are six stages in the Data Maturity Model[i] Which determines at what stage the data is in and how it can be used. Let us address each of the stages:
1. Define: At this stage, we define the data management protocols on the parameters to determine the customer experiences to collect the right data. This ensures that the right type of data and the right parameters are collected every time. Also, all the data integrations, which tool to use, and the desired output are defined. Data dictionaries are made to determine a meaning to every data collected, and Dashboards are created. One needs to ensure the data is transformed to the right visualization and provide the most interactive insights.
2. Protect: At this stage, we need to define the right data governance policies and usage protocols to ensure the data is not misused. The right amount of control is required for both the users of the organization and the users from whom the data is collected to ensure every aspect of shared or used data has the right usage policy defined.
3. Understand: At this stage, it is crucial to leverage the power of Big Data analytics, powerful insights, Business intelligence, and all the associated capabilities. A good organization knows what kind of BI & Big Data analytics would suit their data and adopt a CDP model accordingly.
4. Activate: At this stage, the organization should think about data analytics to derive insights and think about designing custom Audiences campaign and Personalized marketing for every customer. The data should give enough insight to target every individual customer and do so personally and different channels, thus providing Multi-Channel capability. At this stage, the CDP should provide a holistic view of individual customers/ target group with personal customer profiles (purchase history, site activity, product recommendations) for every person called a single Unified view of the customer.[ii]
5. Optimize: It is essential to bring all the stages together and optimize the user experience to deliver seamless experiences across all channels (online and offline), Ex: contact centre, POS, customer services.
6. Predict: The CDP should support real-time personalized digital experiences using AI/ML models that respond and predict customer actions, e.g. dynamic merchandising based on search terms, site navigation, and conversion events on the website.
Way Forward:
A Customer Data Maturity Model helps organizations assess their customer experience requirements and define a strategic roadmap for the ongoing development and optimization of their CDP investments. A CDP is always a significant expenditure. It is imperative to analyze the returns that a CDP is expected to generate, both for the customers (through enhanced experiences) and the brand (incremental growth and ROI).
REFERENCES:
[i] https://www.bluevenn.com/hubfs/Customer-Data-Excellence-Report-London-BlueVenn.pdf
[ii] Single customer view (SCV) overview for 2020; Accessible at https://exponea.com/blog/single-customer-view/
