AI — A Personalization Engine On Steroids

Marketing has come a long way since the days of John Wanamaker and his famous complaint that he didnt know which half of his marketing spend was useful and which wasn’t, but, as senior Forbes contributor, George Bradt, contends in his article, Wanamaker Was Wrong — The Vast Majority Of Advertising Is Wasted, attribution is extremely difficult to measure and brands would be smarter to try to spot their most loyal customers rather than try to figure out the exact steps that should be attributed to a purchase. Although there are plenty of tools available to collect purchasing behavior, piecing together a somewhat reliable path-to-purchase is not easy and Bradt believes the money is better spent both finding loyal customers and providing those customers with a personalized experience they will learn to covet.

Today, personalization has become the optimum word in a radically new customer experience environment. In her article 3 AI-driven strategies for retailers in 2019, Giselle Abramovich states “Personalization is table stakes for today’s retailers, who are increasingly competing to be relevant in the hearts and minds of shoppers.” Many brands agree. Personalization requires a substantial investment in CRM, multi-channel marketing, analytics, and social media, but brands are also recognizing this is a price that must be paid because highly sophisticated customers expect an exceptional shopping experience every time they go out and they aren’t shy of jumping between competitors if they aren’t happy either with a purchase or a buying experience. “The battle to win customer hearts and minds is no longer simply about a product, it’s about experience because that’s what motivates loyal patronage,” says Adobe Sensei Team in their AI: Your behind-the-scenes marketing companion.

In his article Study finds marketers are prioritizing personalization…but are further behind than they realize, Andrew Jones claims “most marketers today are working with customer data that is decentralized, spread across the organization, in multiple databases that are updated in batch processes.” Success for marketers, contends Jones, is in consolidating data into a single database. In order to create successful customer experiences, “marketers must strategically collect and utilize customer data, including real-time signals of intent, which are typically not captured today,” says Jones.

To compete on experience, companies must understand both what customers currently want as well as anticipate what their next actions will be, contends the Adobe Sensei Team. Because customers are inundated with choices, there’s not a lot of time to get it right. But there is a lot of data and it’s growing exponentially and it has to be dealt with in real-time. Unfortunately, as the Adobe Sensei Team points out, “the knowledge you need to personalize interactions and compel customers to act is locked up in huge amounts of data.” This means the data has to be analyzed for patterns, trends, and profiles, so insights can be quickly acted upon. The deluge of data in CRM, Multi-Channel Marketing, analytics, and social media systems is too much data for a human to comprehend and that’s where AI and machine learning come in.

Searchandising

Because of COVID, U.S. ecommerce grew in by $183 billion as consumers flocked online to purchase everything from groceries to medical items to cleaning products, toys and games, even electronics, all in an effort to stay indoors and mitigate the spread of the virus. A lot of businesses quickly followed suit, adjusting their models to include digital commerce.

In his blog Adobe announces new solutions to improve ecommerce experience for Adobe Commerce, Jason Woosley notes the latest AI developments in the Adobe suite of marketing products are focused on helping customers find the products they are searching for online. Powered by Sensei, Adobe’s AI and machine learning technology, Live Search grants merchants ‘searchandising’ capabilities to provide customers with fast, personalized search-as-you-type results that get smarter over time, based on constantly running AI-driven analytics, explains Woosley. Because Live Search utilizes the same product catalog metadata as Adobe’s Product Recommendations feature, many merchants will find it an easy add-on.

“Live Search also offers robust reporting on search queries to help with merchandising. For example, analysis of popular or top searches can help inform the merchant on what future products or bundling of existing products to offer in their storefront,” says Woosley. This is a powerful and extremely useful feature as social media and search drive so many purchase decisions these days. Customer demand is as important to commerce as supply and knowing there is limited demand for a product helps with inventory control. According to Woosley, for search queries that don’t get any product results, the merchant will be able to update the algorithm to recommend other catalog products that might be more fitting to a customer running a search.

The recently announced Adobe Journey Optimizer is Adobe’s newest tool in their customer experience canon. It “combines a variety of data types, including behavioral, transactional, and operational data across multiple touchpoints into a single, centralized customer profile that is constantly updated,” explains Sundeep Parsa in his article Adobe unveils new application to help brands personalize customer journey. Parsa offers a hypothetical to describe what the system does: a clothing store recognizes, due to unforeseen circumstances, that customer satisfaction surveys should be held as some customers who had made recent purchases might be affected by a shipping delay and they shouldn’t be contacted. The store decides to send out a personalized email apologizing for the delay, along with a discount code with product recommendations based on the customer’s past purchases. Additionally, any consumer with the brand’s loyalty app on their mobile device who is within a short distance of a store location would be sent a real-time offer based on inventory available at that particular location. “With Adobe Journey Optimizer, artificial intelligence (AI) and machine learning (ML) based intelligence is an integral part of the application. Brands can apply intelligence, learning, and predictive insights to automate the process of deciding what communications to send on which channels and when in order to produce the best outcomes for individual customers,” says Parsa.

Morphing is another way for brands to personalize the shopping experience. In their article Website Morphing, Hauser et al. claim “‘Morphing’ involves automatically matching the basic ‘look and feel’ of a website, not just the content, to cognitive styles.” Hauser et al. use Bayesian updating to infer cognitive styles from a company’s clickstream data. In today’s highly competitive e-commerce environment, website design can become a major profit driver, contend Hauser et al. They argue “Websites that match the preferences and information needs of visitors are efficient; those that do not forego potential profit and may be driven from the market.”

Hauser et al. propose ’morphing’ a website automatically by matching website characteristics to customers’ cognitive styles,” which is “a person’s preferred way of gathering, processing, and evaluating information” As Witkin et al. define it, cognitive styles can be identified as “individual differences in how we perceive, think, solve problems, learn and relate to others.” The “goal is to morph the website’s basic structure (site backbone) and other functional characteristics in real time,” says Hauser et al. Cognitive styles dimensions “might include impulsive (makes decisions quickly) versus deliberative (explores options in depth before making a decision), visual (prefers images) versus verbal (prefers text and numbers), or analytic (wants all details) versus holistic (just the bottom line).” A website can morph in a hundred different ways, through a hundred different decision trees by changing the graph-to-pictures-to-text ratio, reducing the number of options available to the browser, or by carefully curating the information and pictures presented on a webpage. There are countless ways to customize and personalize a website to better serve customers who expect personalized service and AI has to be an integral part of this process simply because of the enormous amount of data involved.

Conclusion

Customers will always prefer the human touch in their brand interactions, claims the Adobe Sensei Team. Brands should think of AI and machine learning as a behind-the-scenes marketing assistant who provides deep customer understanding as well as a forecasting tool that predicts trends and monitors unusual activity, all while giving brands the time they need to make the right decision or offer for the right customer on the right channel.

According to an Epsilon survey, 80 percent of consumers say they’re more likely to do business with companies offering personalized experiences. That number won’t be declining anytime soon. Once people start receiving proper personalized service, they won’t want to give it up. On top of that, many brands see personalization as an important competitive differentiator, and they spend small fortunes on systems that deliver personalization marketing. Hyper-personalization will soon be the norm for large corporations, let alone simply personalization.

As far as Wanamaker’s famous quote on marketing spend goes, we might be headed in the wrong direction of attribution, which is hard to believe as there seem to be endless ways in which to discover a customer’s path to purchase. However, like a dog that finally catches a car and suddenly realizes it doesn’t know what to do with the car, attribution might turn out to be an expensive bet placed when understanding a customer’s lifetime value might be a better long-term investment. Whether personalization is a table stakes ante tossed in to simply join the game or a process that results in a pot of gold at the end of a marketing rainbow, it behooves executive to keep in mind the words of Shep Hyken, the customer service, and experience expert, who said, “The best advertising you can have is a loyal customer spreading the word about how incredible your business is.” With AI and machine learning’s ability to understand, analyze, and communicate with customers on a deep, intimate level, there really are no more excuses for companies to avoid joining the AI revolution. If they don’t join now, they may forever be left behind.