Predicting and Personalizing; The Future of Ecommerce Marketing

The Future of Ecommerce Marketing

Predictive Analytics in Action 

Have you ever wondered how some brands seem to know exactly what their customers want, sometimes even before they do? It’s not magic, and it’s certainly not businesses eavesdropping on phone conversations. It’s all about predictive analytics. Brands can utilize their first-party data to fine-tune product offerings and marketing strategies to better identify and meet the needs of their customers. While there are multiple ways this can be done, one of the most advanced is what customer data and analytics platform Decile is doing with their AI models. Decile is able to provide marketers with predictive metrics on their customers with limited purchase history. This includes identifying which customers are “most valuable”, defined as those with the highest lifetime value (LTV), as well as what products a customer might purchase next and when based on purchase behavior of similar customers. “This information can be invaluable in properly targeting the right customers with the right message,” says Decile. 

Seeing the Future Clearly

Putting together marketing strategies without the use of predictive analytics is like playing golf with your eyes closed – the chances of a hole in one are slim. Predictive analytics can give brands a clear view of not only the hole, but which club to use to reach it. Utilizing enriched data, which combines buying behavior data of similar customers, along with statistical algorithms and machine learning techniques, brands can now predict what’s going to happen next in their customers’ journey. This helps businesses make smarter decisions, like knowing which products to recommend for a future purchase as well as what kind of marketing messages will have the greatest impact and when to send them.

Cary Lawrence, CEO of Decile stated in a recent Q&A that “leveraging machine learning for predictive models (i.e. High propensity to Purchase, Personas, Predicted LTV) [can] advance the way marketers both acquire and retain their customers. This added layer of sophistication allows marketers to focus on growing profitably, not just growing topline revenue.”

First-party data remains the gold standard of data collection that fuels predictive analytics. It’s transparent and mutually beneficial, unlike third-party cookies, which are on their way out. More and more customers are willing to share their preferences and behaviors with their favorite brands, in exchange for a more personalized shopping experience. Marketers must continue to leverage this opportunity when communicating with customers and keep up their end of the bargain. 

Everyone Has a Persona

In today’s dynamic marketing landscape, understanding your audience is paramount. It’s no longer enough to put customers into broad categories. Crafting a message or product that connects with customers involves delving into their behaviors, preferences, and motivations. 

AI-generated personas leverage first-party data enriched with demographic, psychographic, and behavioral attributes to create a detailed and complete customer profile. The AI processes millions of data points, from purchasing behavior to age, and everything in between, to identify patterns and clusters of similar traits among customers. This modeling goes far beyond the standard grouping of “Google analytics” and allows brands to build and retain a more loyal customer base by speaking more directly to subsets, inform product optimization strategies and drive more personalized marketing campaigns to ultimately help that brand to grow profitably.

Predicting What Will Move the Needle

Sure, understanding your customer is a major part of marketing to them, but even more paramount is learning what will increase their lifetime value (i.e. make them a repeat purchaser, etc). This is especially important when looking at surges of one-time purchasers, says Decile, for instance in the case of a “viral moment.” A Decile customer recently experienced just that, where they had a viral moment on TikTok and experienced the associated surge in purchases for the viral product. While a surge in sales can be great, the brand needed to understand how to turn these new customers into repeat customers. This is where predictive analytics can offer marketers exactly the info they need to capitalize on that viral moment. 

With enriched data and predictive analytics, the brand was able to identify who of these new customers had the highest propensity to repurchase and who of them would most likely be of the highest value. Instead of just target marketing the new customer base in mass, the brand took an individual approach to personalize marketing campaigns to those customers who met those criteria and were able to retain a significant set of these viral buyers. 

When thinking of what will “move the needle”, marketers need to consider things like price sensitivity (should you or should you not offer a customer group a discount), their average purchase frequency (when to target a marketing message), their product affinity (what products they are likely to purchase next), and their channel preference (where a customer wants to be reached). Insights into consumer behavior such as these can drastically improve a marketing program and given the rise in AI and modeling, looking forward at these in a predictive way, versus waiting on historical data, can be the difference between outgrowing the competition and being left in the past.  

Implementing Predictive Analytics into Your Marketing Strategy

It’s not just about gathering data, but about leveraging the right technologies of the future to enrich that data and make it actionable. “More precise and predictive data is the key to personalized marketing and the cornerstone to a well-rounded and successful marketing program. Not all customers are the same and they should not be treated as such by brands,” says Lawrence. The marketer of the future is one that is looking to the future, by properly analyzing data and identifying patterns and common traits among customers to develop better strategies retaining customers. And while more and more marketers are becoming data nerds more than creatives, new and emerging technologies continue to make the job of properly using data just a little bit easier. 

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