How to Work with Loyalty Program Data
If you have a loyalty program and the data it produces, what are you supposed to do with it? As a data miner, it’s your role to provide decision makers with analysis that supports the business. Some executives understand loyalty programs and may request specific information, perhaps more of it than you have hours to provide. But many others don’t ask.
Some executives don’t trust data, some don’t like it, and many don’t understand it, but the most common reason why executives don’t ask you for information is that they just have a lot of other things on their minds. When management isn’t asking for analysis, don’t sit around waiting for a call. This is a good opportunity to take a proactive role. It’s more than an opportunity; it’s a necessity!
Your organization may have many executives, but you must treat each one as an individual. Your company may make 101 kinds of snacks, but the person in charge of corn chips only wants to hear about corn chips. He doesn’t have authority to make decisions about chocolate, crackers, or fruit rolls, and he doesn’t have time to think about them, either.
Focus on something that’s important to a particular decision maker. If you don’t know the executive’s priorities already, here’s how you can figure it out. Start by getting an understanding of the executive’s responsibilities. These may be defined by elements such as specific product lines or geography. The executive will have specific strategic goals, and you need to know what they are.
Next, find out what metrics are most important to the executive’s survival. Executive compensation, for example, is often tied to business performance metrics. When you know what metrics define the executive’s pay, you’ll know exactly where to focus your data-mining efforts.
Consider that you want to provide some useful analysis for the executive in charge of marketing corn chips in Canada. You’ve narrowed the scope a lot just by knowing these responsibilities; you have no need to consider any product lines except corn chips, or any geography except Canada. Next, look at goals. Maybe the executive has a goal to increase sales by 7 percent this year.
Here’s the key: Executives already know what has happened, and they need you to show them how they can influence what happens next.
So don’t go to the executive and explain that corn chip sales are up 4 percent so far this year. Somebody else has already done that. Instead, mine the data for clues about what actions could increase sales. Become your decision maker’s data-miner hero by discovering actionable information such as
Characteristics of customers who buy large quantities of a product
Characteristics of customers who are increasing the amount they buy
Growing customer segments
Combinations of products that are often bought together
Promotions that work better than others
Marketing channels that are more cost-effective than others
Shopper behavior patterns (in-store and online) that affect sales
Unexpected factors (or combinations of factors) that influence sales