Data Life Cycle in Customer Experience Journey
Rohit Prabhakar
Chief Digital Officer ? Strategy→ Transformation→ Revenue Growth ? Digital, Marketing, Ecommerce, CX, MarTech, Data Analytics, AI ? FIS, McKesson, Thomson Reuters, Visa
Working on customer experience we focus on touchpoints – the single transactional points where a customer interacts with different facets of the business and its various offerings. It is quite logical, these touchpoints represent critical points in the customer life cycle that must be understood and served very well. Data and Technology are key enablers but unfortunately most of our enterprises struggle with disconnected data and not-so-well integrated technology stacks. Even companies that may have integrated MarTech stacks struggle with silos of data.
As we solve the data and MarTech silos, it is critical that we also understand the concept of Data Life Cycle in Customer Experience Journey. Yes data has it’s own lifecycle! It is not the integrated data or MarTech that can build great experiences but ability to use right data at right stage in combination with integrated tech that can execute just-in-time. Four main types of data that enable Data Life Cycle in Customer Experience Journey are:
- Intent Data: Collection of behavioral signals from Deep Web that help interpret purchase or renewal intent.
- Behavioral Data: Data that reveals new insights into the behavior of customers on the web, eCommerce platforms, online games, mobile applications, and IoT.
- Customer Data: Wide variety of data like demographic, personal information collected by businesses to understand, communicate and engage with customers.
- Product Usage Data: Data that helps to understand how how-often users interact with your product and their behavior while using the product
It is connected and comprehensive data-driven, outside-in approach to deliver an outstanding, seamless, and rich customer experience that wins both the game of customer experience and business growth. Mapping entire customer experience journey with the right type of data at each customer journey phase helps understand customers’ experience and delivery an amazing experience at every touchpoint. You can read the details especially what data is available at what stage in detailed article.
Looking forward to hear your thoughts on the types of data, availability of that data at various stages, practical use of that data and results you may have seen. Please feel free to comment and share what I may have missed. Appreciate your help in making this more usable information for the community.
Recommended Content: Read about the various technical systems like DMP, CDP and Data Lake that will help your enterprise to connect and use these data types.
Chief Product and Technology Officer, Chatham Financial
2 年Rohit, I think the data gap I see most commonly on the customer journey, is the failure to apply customer behavioural data in their support cycle against future engagement. Most of us focus hard on marketing and content site analytics, and then turn to application usage data after that. Customer Care/Support data can tell us what's blocking or missing from the customer journey, it can enable strategies around future customer engagement, as well as new feature and journey ideation. Don't underestimate the value of support data!
OG of Revenue Marketing, Change Agent for Marketing & MarketingOps, Passionate Speaker, Content Creator
3 年Ok...adding to the conversation. Grt idea on the data journey. While getting the right data at the right time is a big problem for many companies, often the bigger issues are politics, fiefdoms and old organizations models.
OG of Revenue Marketing, Change Agent for Marketing & MarketingOps, Passionate Speaker, Content Creator
3 年Rohit...thanks for sending. I will review and provide feedback...if it needs any!
Chief Strategy Officer | Consultant | Advisor
3 年Great post Rohit. Few reactions...first, seeing more companies really trying to understand how to bring in new customers and how that journey looks different from existing customers. Think new to a category or changing the way they use a category. Secondly, using data that is part of a primary research effort from qual to quant. Most data points collected tell us what an individual did and not what they thought. This gap needs to be better understood and more often.
Head of Retail Deposits | Chief Marketing & Digital Officer | Board Advisor | Strategy, Growth, Transformation | Business Leader |
3 年Rohit Prabhakar Great post! The big question is data integration is still not in the DNA of either marketers, product or technologists. Most people struggle to build it as part of their customer journeys. How do you make it easy so that it is simply plug and play vs. Integration?