To understand your data, start with reporting.
If you’re trying to set up a customer data platform, or any system that collects data, my standard advice is to start with your use cases. That is, what do you want to do?
Another way to approach the issue is to ask “what do I want my reports to look like”? Or, “what questions do I want to ask?”
Let’s start with profit per customer.
You’ll need some basic things, like customer ID, order ID, order amount, and profit margin. But it’s pretty likely that your profit margin will vary by product, so you’ll also have to know which products are in each order, and you’ll have to calculate the net profit margin for all the products in that order.
Then you’ll have some complicating factors like discounts.
Here’s the next step. Imagine you’re presenting this information at a board meeting. What hard questions are people going to ask? For example,
- What are the drivers of customer profitability?
- How can we identify and attract the most profitable customers?
- Are there any customer segments that we should target more heavily? (Or ignore.)
- How can we improve customer profitability?
- Can we predict long-term profitability for any given segment of customers?
What kind of data do you need to answer these questions?
You’ll need recency, frequency, and velocity data for different customer segments.
You’ll want demographic information on all your customers.
You might want some information on competitive factors that affect different products or customer segments.
All those things will inform how you set up your customer data platform so you can be sure you’re collecting the information you need to answer these questions.
But we’re not done yet. That’s just one KPI (key performance indicator). You’ll need to go through the same exercise for …
- Gross margins on sales
- Sales forecasting by month
- Inventory projections
- Profit and loss analysis
But that’s all just e-commerce stuff. If you’re a media company, you’re going to worry about audience engagement, ad revenue, subscriber growth, customer satisfaction, and so on. And for each one of those you’ll have to go through the same exercise. How are you going to report on it, what data do you need for those reports, and what hard questions is management going to ask you?
The point here is that thinking ahead of time about what you want to get out of your data will help you know what to collect and how to structure it, and that’s crucial for success with a customer data platform.
