People typically go into business to sell things that they like – or skills that they are good at — to their customers. Keeping those customers happy — and willing to part with their money — is the lifeblood of any successful business.
So how do you know if they are really happy?
Data analytics can help, if you’re gathering the right information and using the right tools to analyze it.
Here’s how:
Who Are Your High Value Customers?
Customer profitability analysis allows you to learn which customers buy the most goods and services from you and at the greatest profit – and which have not purchased from you recently. This knowledge can help you know which calls to make and when. Plus, you just might find regions and products that are underserved.
How it’s done:
-
Assemble lists of customers, sales, projects, and costs.
-
Calculate revenue, cost and profit for each customer.
-
Rank customers by profit, and note the last few interactions with those customers.
-
Find the customers that account for most of your sales and reach out to them – or find products and regions that are underserved, and launch a new marketing campaign.
Why Are Your Customers Leaving?
Keeping customers is cheaper than finding new ones, and keeping customers happy is an art that often separate successful business owners and managers from the unsuccessful ones. But business owners and managers can’t be on every customer call. Instead, through customer retention analytics, managers can understand what portions of their business are creating happy customers, spot high-value customers that are in danger or leaving, and take steps to keep them.
How it’s done:
-
Assemble a list of all your customer sales – and records of customer interactions.
-
Calculate a Customer Attrition Rate for categories that make sense to your business
-
Look for products, regions, stores, managers, or other events that have higher – or lower- attrition and figure out why.
-
Review the detail and develop a computer model that predicts which high value customers are likely to leave in the future, and make sure that your best team members work to keep them satisfied.
Are You Missing Opportunities to Sell Them More?
Ever notice that handy feature on big-time online stores that suggests other items that would go *perfectly* with the thing you were looking at? And those reviews that suggest that the slightly more expensive items is what you *really* need?
It’s called cross-selling and upselling. Here’s the difference: Cross-selling is convincing a customer who visits your store to buy a hammer and selling them a bundle of nails and a box of bandaids to go with it. Upselling is sending him home with a nail gun.
Data analytics can help you do both more effectively.
How it’s done:
-
Review your product catalog to ensure that related products are placed in the same categories.
-
Review your sales history, and through a technique called “Market basket analysis,” determine which “rules” lead to more sales – and more profit by looking at existing sales. For example: “Customers who buy hammers also buy nails”
-
Place those goods next to each other in your store, or prompt an online user to consider additional purchases.
How are you using data analytics to increase the value of your customer interactions?
DataClear is a Baton Rouge data consultancy firm. Contact Us for a free 30-minute consultation and discover how your company can profit from data-driven decision making using tools that won’t break your budget.