MULTI BUYER ANALYTICS FOR MORE CUSTOMER LOYALTY

Intensive customer loyalty

But before we get to the analytics, let’s take a quick look at the bigger picture: Acquiring new customers is costly and requires significantly more effort than intensifying an existing customer relationship. This has been proven by many studies and surveys. And this experience applies not only to the sale of energy bars, wine or travel to end customers, but also in B2B business. For example, tradesmen who have good experiences with their suppliers buy regularly and usually also larger baskets of goods. So let’s intensify customer loyalty!

“Mmmh-delicious-moments” or: Knowing customers in order to bind them specifically

Customer loyalty is hugely important, as my Buddy illustrates. After all, satisfied regular customers are loyal, tolerant of mistakes, and they recommend products authentically to friends or colleagues. In the age of social media, this also means that loyal customers recommend a product to a large number of people in their social network. How do you win over loyal customers and create these “Mmmh-köstlich moments”? How do companies increase customer loyalty and turn single buyers into multiple buyers? Of course, a good product range is a basic prerequisite. But beyond that, it’s crucial to know your customers intimately. Knowing what moves them, what excites them, and what motivates them to make repeat purchases. The key: Multi Buyer Analytics.

Evaluate purchases with Multi Buyer Analytics

Companies that use multi-buyer analytics are significantly more successful than their competitors. This is proven, among others, by a power bar manufacturer and Schober customer who uses Multi Buyer Analytics based on our universal data platform (udo) with great success. The first thing to do is to get a solid overview of purchases and buying habits.

Which customers buy only once and then disappear from the radius of marketing measures? Which customers, on the other hand, buy multiple times? With the answers, segments for subsequent measures can already be created in a first approximation. If you add the time intervals between purchases and the product groups purchased in each case, the view of the customers quickly becomes complete.

It can be seen, for example, that a so-called persona of multiple buyers prefers to buy a certain product in larger quantities, but then does not order anything else for a longer period of time. Another, however, orders small quantities more frequently, but these come from different product areas – energy bars, protein shakes and isotonic sports drinks.

Product mix analysis

Product mix analyses go deeper, allowing the correlations of individual offerings to be determined at the product level. In the case of the power bar manufacturer, for example, flavor, price and container size are related. For other Schober customers, such as the water specialist bevo, it is water pipes, connecting sleeves, special adhesives and hoses. Whatever the product portfolio, a product mix analysis of purchases reveals valuable synergies for existing customer care. Of course, it is precisely these correlations that must first be drawn from the data through analysis. To make this possible even without a degree in mathematics, udo offers
udo
offers intuitive ready-to-use analytics.

Targeting customer loyalty measures

Targeted analysis of purchase and customer data as part of multi-buyer analytics provides crucial knowledge about customers. Single and multiple buyers with their respective preferences can be precisely identified, so that marketing and sales can use targeted communication measures to stimulate customer loyalty and new purchases. The right triggers and purchase motivations can then be set along the customer journey: The targeted development of existing customers can begin – from single to multiple buyers, from loyal customers to brand ambassadors. Of course, many factors – market, target customers, budget, creativity and others – play a role in the measures. The right mix of measures is therefore always individual.
We have compiled five key success factors and reasons for multi-buyer analytics in a checklist that you can download for free below.

Back to the gym

But let’s get back to the power bar manufacturer and its case. The company used multi-buyer analytics to first target and segment buyers of its products and cluster them by buyer group. One key finding: the number of multiple buyers can be expanded particularly quickly through targeted cross-selling. From the product mix analysis, it was clear that energy bars are a low-threshold, “fast-turnaround” offering and sell very well along with energy gels in the gym environment.