Why E-Commerce Merchandisers Should Care About Personalization

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Ideas and Strategies for Real-Time Personalization
Why E-Commerce Merchandisers Should Care About Personalization

April 18, 2017 by

These days, consumers expect personalized digital experiences. Forrester found that 77% of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience. And according to Infosys, 59% of customers say that personalization influences their shopping decisions.

When many think about e-commerce personalization, they think about product recommendations. If you’re a merchandiser, you and your team have probably already invested in product recommendations for your e-commerce site. But how personal are those recommendations? Are they unique to each person’s individual preferences? Do you feel you have control over them? And have you considered what other aspects of your site you can personalize beyond product recommendations? Your search bar, search results, site navigation, homepage experience, and more can all be personalized with machine-learning algorithms. With that in mind, how much of your site can you actually consider “personalized”?

These questions are important for any merchandiser. Here are a few ways in which personalization can help your site be relevant to each shopper to increase conversions and grow basket size.

Provide Recommendations at the Individual Level

While I don’t think I need to convince any merchandiser about the importance of recommendations, many retailers are not providing recommendations that are truly tailored to each shopper. In those instances, recommendations rely on “the wisdom of the crowd” to suggest products to one person that other shoppers browsed or bought. While this approach is a good start, wisdom of the crowd recommendations don’t leverage what is actually relevant to each person and they don’t treat each person like a unique individual.

An advanced personalization platform can track each individual’s actions on your site, analyze the context of those actions, and determine each person’s affinities and in-the-moment intent. You can use that data to deliver recommendations that are truly unique to each person based on all you know about them. It may not appear to be a dramatic difference to the shopper, but it can make all the difference between a shopper leaving your site after viewing one PDP or continuing on to browse another one or, better yet, convert.

Exercise Control Over Your Algorithms

You know your products better than anyone, so it can be unsettling to put such a critical decision about which products to display on your site in the hands of an algorithm. You may have a number of different reasons to want to control which products, categories or brands you promote across your site. You may want to promote higher margin products in designated locations on your site or during specific times, or push certain overstocked inventory. Or, you may have a vendor that won’t allow a competitor’s products to be promoted on the PDPs for its products.

An advanced personalization engine will give you control over your own algorithms, rather than treating them as a “black box.” Exclude a brand from appearing on a rival brand’s product pages, boost higher-priced or high margins items, even include some level of variability so your recommendations don’t become stale. With this approach, you can ensure your visitors see recommendations that are relevant to each individual while still exercising control when you need to. To learn more about how to build and customize an algorithm, check out The Marketer’s Guide to Machine-Learning vs. Rule-Based Personalization.

Grow Basket Size

It’s expensive to acquire new customers, so you probably have several initiatives in place to grow the lifetime value of the shoppers you have already acquired. One way to do that is to encourage visitors to shop multiple categories, rather than just one. For example, if a visitor only shops shoes on your site, he may only buy two or three pairs of shoes a year. But if you can encourage him to shop apparel too, you can increase his lifetime value.

Smarter recommendations can help you there too, allowing you to display them across predetermined categories in a “bundle.” For apparel, you can encourage shoppers to “complete the look” and drive them to shop other categories they may not have considered. With the right approach, you can encourage cross-sells and grow basket size (such as in the office supply example below) while still leveraging the individual preferences of each person.   

personalization for merchandisers

Sort by True Relevance

In-store merchandisers put a lot of thought into the order of products in store aisles, but they obviously can’t personalize how products are sorted in the aisle for each shopper without physically rearranging them each time a new person walks into the store!

But online, you can sort your products on your category pages or sort results by actual relevance to each person. Leverage each person’s preferences for certain brands, colors, styles, price ranges, and more to show the products most likely to interest them. The faster you can show relevant products to your shoppers, the more likely they will be to keep shopping on the site.

Control for Out-of-Stock Inventory

You or your team spends a lot of time planning your inventory to ensure that you have the right quantities to match the demand. You work hard to ensure that you don’t run out of a popular product, resulting in lost revenue. Unfortunately, out-of-stocks do happen, and in that case, you can use personalization to recover.

A personalization engine that is truly real-time will be able to recognize when a product is out of stock and immediately stop recommending it. If someone happens to see an out-of-stock product anyway, you can recommend similar products that are still relevant to their interests.

Use the Data

You undoubtedly know how much data you need to do your job effectively. A good personalization solution provides a lot of data in real time about shoppers, allowing you to dig into real-time analytics on customer preferences and shopping patterns. You could even rely on machine learning and predictive analytics to surface optimization opportunities as well as potential issues for you.

For example, you can immediately discover if a product is out of stock and the expected impact that will have on your business. Identify when interest in a product is lower than anticipated and take action quickly. This allows you to make the most of your data.

Final Thoughts

Consumers expect personalized experiences, and those expectations go beyond basic product recommendations. Your entire site can be personalized to incorporate each person’s preferences and affinities, while still allowing you to control what is shown. For more information about how Evergage can help you individualize your e-commerce experience, request a demo today.

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