- Personalized incentive recommendations and usage predictions
AI systems can analyze your campaign launch lists and customer database to identify which contacts are more likely to purchase when offered a certain incentive, and then assign the most efficient incentive to each one.
Personalized Incentive Recommendations and Usage Predictions for AI in eCommerce
While some customers require higher incentives, others will buy without any. Algorithms can determine who needs what, then send the most appropriate offer.
Incentive recommendations are a simple but effective strategy that can add value and increase ROI for marketers. Marketing teams simply upload a series of incentives (in the form of images or code snippets) to their automation platform, assigning a value to each one. Through machine learning and artificial intelligence, AI platforms can also predict a customer’s most likely response.
Customer Lifecycle, Prediction, & Automation
AI predicts when customers are about to churn, become inactive or intend to make a purchase… and it uses embedded knowledge to automate the delivery of the best content at the best time. This is really the bread and butter of AI in eCommerce.
- Likelihood to purchase
With a strikingly high level of accuracy, AI can predict who is likely to buy or convert. Based on past purchases and other behavioral data, self-learning systems can “sense” (to make things a little more human) who will buy.
Similarly, AI also understands which sets of customers are likely to remain inactive or defect, and can anticipate which defective contacts are most likely to return.
- First- to second-time buyers
Many marketers are challenged to get customers buying again and again. Too often, people make one purchase from a brand and then never return. Losing customers to the abyss after they make one purchase is not an ideal lifecycle!
The solution, which AI can handle, is to identify first-time buyers who are likely to convert and encourage the second purchase with an offer. AI can also identify active buyers who are likely to convert, then provide an offer most likely to secure the purchase and increase the cart value.
In their First- to Second-Time Buyer campaign, BrandAlley saw an immediate increase in open rates, average basket value (10% increase), and revenue.
- Likely to churn customers
Traditionally, marketers have missed out on ripe opportunities with churning segments. For example, marketers might see that a customer has gone inactive or has discontinued their subscription, and then decide they need to send an email to re-engage them. But by that time, it’s already too late.
AI flips that on its head by identifying – before the fact – who is likely to churn, and then sends them the right message(s) to prevent it from happening in the first place.
- Next cart value
AI predicts, at a one-to-one level, what an individual’s next cart value is going to be. With AI, marketing teams can actually say:
“Customer A will likely spend $60 on her next purchase.”
“Customer B will buy every 60 days whereas Customer C will buy every 3 weeks.”
“Customer D, who used to be a high-value customer, is going to churn in the next 30 days unless he/she receives offer X.”
- Predict customer lifetime value
AI takes all data points and variables into account to determine an individual customer’s lifelong value to the business.
My favorite athletic apparel brand, for instance, with whom I do quite a lot of business would be able to take all of my data – contact info, preferences, behavior in-store, in real-time in their app and website, catalog views and buys, and all my purchases – to paint a complete picture of my anticipated profitability.
Customer lifetime value is arguably the most crucial long-term metric to get right for eCommerce marketers. Why? It helps brands understand which customers are worth more to them… so they can prioritize communications, incentives, and VIP-like treatment to these segments.
Conclusion
For brands on the leading edge, AI in eCommerce is helping unlock new dimensions of their marketing, optimize resources, anticipate how customer behavior will impact the business, and make decisions on what to do about it in advance.
As many forward-thinking early adopters have stated, it isn’t a question of “if” AI will augment marketing, but of “how” and to what degree. This sentiment is slowly soaking into the collective marketing sphere, too. 85% of marketers believe AI will have a “significant impact on the marketing industry” in the next five years.
As we approach the dawn of a new decade, the time is now for eCommerce and retail companies to take action and begin piloting, adopting, and integrating smart systems.
