How much do you really know about your customers? Do you know if more of them are homeowners or renters? How many children do they have? How many of them have parents who live with them? Do they want new products from you or will they be just as happy with an enhanced one?
Believe it or not, your customers have a story to tell you that can help you expand your business. If all you know from your own customer database is where they live or work, how to reach them via phone or online, and what they’ve bought in the past, you’re missing out on the amazing story with meaningful details you can use to improve your relationship with them. In other words, you now have access to information that tells you how likely your customers will repeatedly purchase from you or whether or not it’s a good idea to expand into a new market segment based on the behaviors of your current customer base.
Thanks to a highly complex process called data analytics, you can now take your existing customer database and put a new spin on how you market to them by simply using that data to identify the common attributes of your audience. We can take your data set and give you a rich profile of the most common attributes your customers share and provide you with demographical data that will help you radically improve your marketing strategies, service offerings and build customer loyalty in a way you’ve never seen before.
What are Data Analytics
Using data aggregation and data mining methods, it’s possible to organize your data to identify patterns and relationships that you would not otherwise see just by maintaining your own list. Through data analytics, you can perform several types of analysis that offer up profiles that succinctly describe your current clients, which you can ultimately use to develop new ones. However, it’s important to remember that the best customers are the ones you already have—here are three types of data analytics you can use to learn more from your own customer list:
Descriptive Analytics: This is data that gives you insight into the past. You can use this data to understand your customers based on their past purchases and leverage that history to develop a robust profile what your customers have in common. For example, you can learn their education experience, income, the kinds of cars they drive, the number of children they have, their race and gender—all of these attributes you can use to further inform your choices to develop new products as well as how to attract new clients who share similar demographics.
Predictive Analytics: This is data you can use to understand the future. Imagine being able to use your current customer data to gain insights on how likely they are to buy again in the future. These statistics take the data you have and give you a more scientific “best guess” to forecast customer behavior and purchasing patterns.
Prescriptive Analytics: This data is all about providing advice and allows you to take your customer data and quantify the effect of future decisions in order to advise on possible outcomes before the decisions are actually made. Sounds kind of strange, doesn’t it? What this means is that you can use your customer data to assess possible outcomes, which means you can develop products and services at the right time based on your customers’ future needs!
We’ve been using these tools with our clients for a while now and it amazes me how you can take a customer list and within minutes uncover a treasure trove of information that makes it easier to develop marketing and print campaigns that lead to much stronger responses and increased revenues! If it sounds like I’m simplifying how all this works, I am. There are a lot of complex equations and calculations made to render this kind of report, but imagine how you can instantly improve your relationship with your clients by learning more about them within seconds after running their list through some of our algorithms and mining tools.
This is such a rich and fascinating way to rethink how you can market and sell to your customers that I plan to expand on these types of analysis in future entries. In fact, my next entry will focus on how the non-profit sector can use these tools to strengthen their relationships with their donors in new and innovative ways!
If you’d like to learn more as to how to apply data analytics and develop a robust profile of your current clients, click here and we’ll schedule a call to explain how our process works!