Artificial intelligence has already impacted the customer experience across a wide range of industries. Although the workings are mostly transparent, with the data analysis AI is commonly leveraged for occurring largely behind the scenes, for some services, the effect is front and center.
Consider, for example, the list of “movies you might like” that are automatically generated by Netflix, or the customized playlists produced by Spotify. These highlighted items and titles are drawn from AI analysis of not just your own browsing, watching, or listening behavior, but also the combined habits of other users who have similar tastes, creating an aggregate data set that delicately balances personalization with the wisdom of the crowd.
This type of AI wizardry is about to take a major step forward and impact the retail space as much as it has shaped the world of digital content delivery. Let’s take a look at what shape the future of personalized customer experience will take in the months and years to come.
Personalization plays an increasingly important role in where consumers choose to shop. Consider the numerous ways in which predictive personalization (that is to say, being presented with products after having made a purchase, or browsed an online retailer) already makes an impact. Amazon, for example, has been guiding customers to items it thinks they want to buy for years, using the same type of aggregate data analysis employed by Spotify and Netflix.
In the past, online storefronts had to rely primarily on user tracking via cookies, and restricted customer categorization to a small number of basic category identifiers that it would then attempt to market to. Modern strategies, however, adopt a search-based model where in-the-moment browsing habits and product searches continue to refine the products that are presented in real-time.
It’s here that machine learning steps in and works to present buying options that are predicted to meet the customer needs. By combining live search behavior with past results (if a returning customer) and the crowd-sourced results (applicable to all buyers), rather than simply listing inventory, AI can actually steer buyers toward the products they are most likely to purchase.
It’s not just the customer experience at the retail level that is being impacted by AI’s predictive capability. Advertising is another frontier where individual customer profiles, compiled by artificial intelligence, are dramatically changing what’s on offer.
Targeted advertising presents individualized offers to consumers based on their own preferences, which are in turn derived from the AI data analysis that powers search-based predictions. These ads aren’t just found at the point of purchase, but are also used in email and social media campaigns to entice buyers to return to a retailer.
Even less-sophisticated personalized advertising campaigns from years past have been proven to deliver substantially better results (up to 6 times higher revenues) than traditional advertising. These types of campaigns also serve more than one purpose: they can drive traffic to an online portal just as easily as they can push a consumer to visit a brick and mortar location for the same brand.
Conceptually, it’s really a small step from recommending a playlist to putting together a stack of products a customer may want to buy. Artificial intelligence transforms that concept into a reality by presenting businesses with the tools required to truly understand their customers at an individual level, and then take action.