Why do some business people waste their time doing something that may not work, and even if it does, it might not significantly improve their situation?
The most important thing you can do with data is use it to understand your customers. More important, you can use it to identify and understand your best and worst customers.
I know this sounds rudimentary. Yet too many major corporations and smaller businesses still haven’t taken this important first step with their data.
How Much Do They Spend?
There are some extremely simple steps you can take to identify your best customers. Ask yourself “What qualifies a customer as ‘high value’? Is it someone who purchases $100 a year? $100 a month? $100 ever? If you don’t know the answer, look at a histogram of total customer purchases made within different time frames. That will give you a picture of what customers are doing. Your most valuable customers are in the upper echelons of these graphs.
What Do They Look Like?
Once you identify and flag these people in your database, conduct a profile analysis to determine what those customers look like. What are their demographics? Where do they live? How many kids do they have? What education level do they have? What income level do they have?
This can be accomplished through basic statistical analysis, including looking at means, medians, and graphical output, such as histograms of age and income.
What Do They Do?
Next, look at what your best customers do. Do they use your Web site? Do they use it disproportionally? How did they find your site or business? What media do they frequent? Which Web sites? Which newspapers or radio stations?
What Do They Purchase?
Know what your best customers buy. Use this information to focus your site and business offerings on those products. Again, this may sound rudimentary, but I’ve know million-dollar companies that don’t know what their best customers purchase. And I’ve seen some that do know but didn’t make any changes, not even the obvious ones.
How Do They Differ From Other Customers?
A very important and immediate follow-up question is, “How do my best customers differ from my other customers?” You now know what your best customers look like, but you must understand the differences between them and your other customers. What are the differences in look, behavior, and purchases?
Identify Your Worst Customers
Some businesses are able to identify their best customers. Identifying your worst customers can be just as lucrative. Do any customers actually cost you money? Many financial institutions have done a good job of identifying customers that cost them money and have taken steps to diminish the number or convert them into profitable ones.
The same questions that apply to your best customers apply to your worst. What are their characteristics? Where do they come from? How do they differ from your other customers?
Conducting the analysis described above is something every company with data can do. It’s basic block-and-tackle analysis. It’s easy, can be extremely beneficial to the company.
Identify your best customers by their demographics and other non-purchase data, then search your customer files to see which customers look like your best customers but don’t purchase at their levels. Conduct marketing campaigns targeted to these people with the goal of increasing their spending levels.
Use the non-purchase information to conduct a customer acquisition campaign as well, targeted to prospects with the same demographic makeup as your best customers. The campaign will yield a list of prospects much more likely to be high-value customers, resulting in a higher campaign return on investment (ROI).
Marketers create personas to better understand their target audience and what it looks like. If marketers can understand potential buyer behaviors, and where they spend their time online, then content can be targeted more effectively.
What’s behind a successful data-driven marketing strategy?
One of the major challenges in the martech industry is getting the attention of prospects in a world where they are bombarded by content and emails on all sides.
Facebook is addressing one of the biggest missing pieces of its chatbot offering: analytics.