In our last post, we compared the manual process of compiling customer data across many different sources to baking a complicated recipe from scratch for the first time. The recipe was for a Chocolate Babka, and the idea was that assembling a bunch of ingredients and fumbling your way through a recipe is difficult, time consuming and risky, while buying the Babka pre-made from a store is easy, quick and reliable.
The store bought Babka in our example is a metaphor for a complete, 360 degree profile view of your customers, packaged up nicely without any manual effort from you or your teams. Ready to eat, if you will!
But let’s take that a step further. You now have a centralized view of all of your customer data from across all of your systems, but this is of no use to you without insights that tell you how to use it. It’s like getting the taste, the energy and sustenance from the food. We have to consume and digest it to assume any of those benefits.
Everyone is Asking…
Once all of the data is in one place, the next step is to answer key questions about customer behavior. The answers to those questions will impact decisions around marketing, segmentation, retargeting, budgeting, forecasting, and more. For a few examples, here are some of the top questions we hear from our customers:
On the topic of…Customer Data
- Who are my best customers? How do I know who they are?
- Which customers are at risk of churning and how can I tell?
On the topic of….Loyalty Programs
- How do I make sure the program won’t just dilute my margins?
- How good does a reward need to be in order to incentivize consumer behavior?
On the topic of….Communication
- How often should I communicate with my customers?
- How do I know which channel will work the best?
The reason these questions are so common across the board is because everyone is trying to understand how to increase their likelihood of success, however that is defined. Success in a micro sense might include the open rates for an email, the number of clicks on a retargeting ad, sales from a social media campaign, or the performance of one segment over another. Success in a macro sense is often the combined result of a lot of those smaller efforts – and might be the impact on margin for the business as a whole.
At the end of the day, finding answers to the questions that will impact business success is not the job of one or two people, or a marketing team, or even a data analyst. Technology is essential to do some of the heavy lifting, and has given rise to a plethora of new and innovative approaches to managing customer data from different sources.
But the job of an intelligent customer data platform goes beyond aggregating data: the platform should also be able to provide answers to key business questions like those we shared in this article. By layering on machine learning, predictive modeling, and forecasting capabilities, these platforms can make data usable and understandable by any member of the organization. Furthermore, this shared level of knowledge will increase the likelihood of success exponentially.
Stay tuned for our next article where we’ll talk about how a customer data platform works to answer key business questions.