ECommerce Trend Focus: Predictive Analysis of Customer Purchases

Ecommerce success requires efficient business processes, and MPO Global is helping merchants that are our business partners take advantage of advanced modeling to predict demand.

Predictive analysis is an ecommerce trend that is quickly growing in popularity among merchants and retailers. Predictive analytics uses a variety of statistical techniques to analyze current and past facts to predict future and otherwise unknown events. MPO’s merchant partners are using predictive analysis to understand purchasing habits and preferences. By sorting through and analyzing the collected data from interactions, behavior trends and customer profiles, predictive analysis can even suggest the consumers’ next purchases to drive sales.

Using Predictive Analysis alters Retailers’ Marketing Strategies

With the massive presence of social media, merchants are presented with the task of weighing the advantages of paid search against social media advertising. By using predictive analytic technology, merchants can determine the value of the new “social” consumers versus their paid search shoppers, and can then determine which is the more profitable acquisition channel to invest in.

Retailers acquire new shoppers during the lucrative holiday season, and by January, predictive analysis can develop a more accurate forecast of their new shoppers’ spending habits. Traditionally, retailers turning to historical analytics from previous years are limiting their market, as promotions, trends and marketing tactics are constantly evolving from year to year. MPO Global recommends combining predictive analysis results with additional acquired data, such as demographic make-up, purchasing trends and what channels they were acquired from, so retailers can make the most of their holiday haul of new customers.

Merchants are aiming to invest in a lifecycle marketing campaign that deepens their relationships with their customers. Previously, product recommendations would be mostly based on what a customer has already purchased. In contrast, a predictive approach attempts to identify which products to recommend based on what the customer is likely to buy next. An example of one of MPO’s retail partners using this approach is the recommendation of car polishing accessories to a customer who has previously bought a microfiber cloth.

AgilOne, Windsor Circle, Emcien and Rich Relevance are a few examples of the predictive analysis technologies available on certain eCommerce platforms. Let’s take a look at an example of how other companies are taking advantage of this process: DAVID’s TEA, a loose-leaf tea retailer, used AgilOne to segment their customers by purchase type and by creating a sampling for each group. AgilOne helped the company to realize that a new customer who did not return within 30 days was lost, and from there DAVID’s TEA optimized its email communication strategy to confirm purchasing trends in advance. Their predictive analysis technology had the ability to double their conversions by offering the right customer the perfect product for them, at the right time in the right way. This particular analytical approach resulted in an increase in new customers converting to repeat customers who have made their second purchase within 30 days.

Predictive analysis is quickly becoming one of the most successful ways for MPO Global to proactively market our partners products to consumers through the internet. Merchants can take advantage of the huge competitive advantage that predictive analysis offers and are able to use this eCommerce trend to grow their sales among new and repeat customers.