Ecommerce product-recommendation technology is blurring the lines among merchandising techniques, making it difficult to know cross-selling from personalization.
We are in the midst of a software revolution. Machine learning and, especially, generative artificial intelligence have gone from the realm of data scientists to the commonplace in what feels like barely a year, and these technologies are changing how ecommerce websites work.
Since ChatGPT was released on November 30, 2022, generative AI has become so ordinary that it can be found in almost every online editor, app, or search result. It has even made its way into ecommerce product recommendations, with the bleeding-edge AI tools on the cusp of adjusting the copy used to describe a product to match what it knows about a shopper’s navigation history.
This level of personalization is amazing. But does it change what it means to merchandise an ecommerce store? If every recommendation, every part of navigation, and even the products shown as the result of a search are AI-personalized and manipulated, does cross-selling have meaning?
To answer, consider how cross-selling and ecommerce personalization were defined before the widespread use of machine learning and AI.
Cross-selling is a merchandising technique wherein a website offers shoppers complementary items as they navigate and visit product detail pages.
Classic examples are offering batteries with electronics or a case with a laptop computer. Thus ecommerce cross-selling often makes suggestions based on items frequently purchased together or what may logically complement the primary product.
Even before AI’s rise, cross-selling suggestions could be tailored to the individual’s interests or behavior.
Cross-selling was usually in a “frequently also bought with” section low on a product detail page or during the checkout process.
From the merchant’s perspective, cross-selling aims to increase the average order value by encouraging customers to buy more during a single transaction.
Personalization changes the shopping experience to suit an individual customer. Ecommerce personalization is based on that shopper’s unique preferences, past behavior, and data.
While most marketers employ personalization to boost profit, the tactic should make a shopper feel understood and valued. Customers who are happy and comfortable with the buying journey will likely purchase repeatedly and, therefore, have a relatively higher lifetime value.
Personalization requires data collection and analysis. It then uses algorithms and AI to understand customer behavior patterns, preferences, and potential needs. Personalization can manifest anywhere on an ecommerce site, including navigation, category pages, search results pages, and product detail pages.
Cross-selling and ecommerce personalization both require analytics, although personalization relies on a deeper analysis. And cross-selling can be a form of personalization when the recommendations are based on individual user data.
The better AI becomes, the more blurry the line, although one might argue that cross-selling is more transactional, focusing on increasing the immediate value of a purchase, while personalization is about fostering a long-term relationship.
An increase in average order size can measure the success of cross-selling. In contrast, many or most ecommerce marketers measure personalization over time through metrics such as customer retention rates, repeat purchase rates, and lifetime value.
Thus cross-selling can be seen as a point-of-sale strategy, while personalization is a comprehensive approach that influences every interaction with the customer.
AI-powered ecommerce recommendation software circa 2023 already powers both cross-selling and personalization for many or even most online stores. From an ecommerce merchandiser’s perspective, there’s little difference between the two.
So why even bother making a distinction? It is this.
- Different metrics. While both cross-selling and ecommerce personalization aim to improve the shopping experience and boost revenue, the techniques operate on different principles and have different metrics.
- Single-order vs. overall relationship. Cross-selling increases the value of a single order, and personalization deepens the customer relationship over time.
- Mix of both. An effective ecommerce strategy often combines both, leveraging their unique advantages to maximize immediate and long-term gains.
Marketers should not put on-site merchandising on auto-pilot and permit an AI to take over. Doing so could have short-term benefits, but when every ecommerce shop has AI running personalization, personalization will no longer be a competitive advantage.
In fact, the more automatic algorithms and AI become, the more important is the art of marketing — as opposed to the science of it.
Understanding the nuance of cross-selling versus personalized product recommendations could lead one to know that cross-selling should not be personalized in some cases.
It is still a good idea to offer batteries with a toy car that needs them or a case with a laptop computer than it is to offer something completely unrelated based on behavior.