Improving E-Commerce Conversion Rates: How to Automatically Merchandise Your Content

To personalize or not to personalize: Coveo CMO, Mark Floisand explains why the data signals from both your business and your users need to merge for your digital strategy.

You are shopping online and come across the perfect watch. The color and model you want is in stock, and it has countless 5-star reviews. You add it to your cart, check out and have it shipped to your home all at no cost to you. A free watch of your choice sent directly to your doorstep would truly be the ultimate customer experience

THE MODERN CONTENT MARKETER’S BUYER GUIDE

Welcome to the 2019 edition of The Modern Content Marketer’s Buyer Guide. About 10 years ago, marketers realized that content is a critical piece of their pie, and have since been working overtime to generate content to help win the prospect’s attention.

Download

As a customer, this would be nirvana: a highly personalized, relevant shopping experience, that costs me nothing.

The “free watch” experience would most certainly delight any shopper. However, this would be absolutely terrible for any business. It is an extreme example, but it highlights a valuable point:  only taking the customer wants and insights into account means nothing if you don’t also incorporate business value into the mix. A conversion is only as valuable as what it returns.

Personalization provides a powerful opportunity for differentiation in low-barrier-to-entry markets that are increasingly competitive. It gives customers the tailored treatment they want in a way that also generates loyalty beyond the product or service alone. But it has to make business sense, too.

Also Read: Losing Customers Before Conversion? Here’s Why

A Balancing Act

A great customer experience alone is not enough for the success of a company. Balance between customer delight and business objectives must be struck, and this requires merchandising products  that meet the needs and desires of the shopper, and contribute to the bottom line.

You need to take into account all the buyer’s information and signals inside your own business that affect the contribution margin of the products you are offering - in real time. Product gross profit margins are a valuable starting point from within your catalog. But there are a host of other signals that affect profitability, too. The frequency of product returns, the number of complaints generated in your contact center, and the negative sentiments being expressed by dissatisfied customers are all important to consider.

In our wristwatch example, Watch A might be exactly what a customer is looking to find. It is black with a square digital face, GPS capabilities, and an alarm. On the other hand, Watch B is similarly priced, with the only difference being that it has a grey stripe down the band, but has $100 more gross margin. Watch A might be a perfect match for the shopper, but B brings in more profit for the company. Why not recommend it?

In this case, it would be best to push Watch B to the top of the product results. It meets the customer’s needs while also meeting those of the company - there is more value in this conversion. An exceptional customer experience is indeed about satisfying the customer, but it must be done in a way that builds business value, too. After all, your ability to continue to provide for customers is entirely contingent upon your ability to sustain your business. Delight is fleeting, but profit will ensure that it is enduring.

Many merchandising teams still undergo this entire process by hand. However, it is impossible for business outcomes to be fully optimized when balancing is manually configured. There is room for error and it isn’t scalable - only a few products can be taken on at a time.

Also Read: 5 Personalization Myths to Ignore in 2019

The Machine Learning Advantage

Machine learning can take on every product and automatically merchandise your content. After determining the classification of different products, ML is able to surface them in a logical and relevant way. On one side, this comes from dynamically changing facets and filters so customers can find exactly what they want. Findability does help to improve your conversion rate, but it is not enough to ensure that there is business value in that development.

However, with ML there is the added ability to draw signals from together from disparate silos to  jointly consider customer insights and business indicators. Through this unified lens, it is able to find the optimal balance between all signals instantly and tailor product recommendations to match. In this case, Watch B is pushed to the top because it gives the customer a product that makes sense for them at a margin that makes sense for the company. This is what makes findability profitable.

Not only does Machine Learning have the capacity to determine what to merchandise and how, but also when to stop merchandising certain items. A popular watch that is sold in large quantities may look profitable, but if is being returned en masse, then it is not truly a successful product. ML would be able to capture both sides of that dynamic, cease displaying that watch and automatically start merchandising a similar watch with a lower return frequency.

In automatically merchandising your content with ML, conversion rates will meaningfully increase because customers will successfully find products that maximize returns. This comes from both prioritizing truly profitable items as well as lowering the visibility of those that only appear to be.

Personalization may lead to a great experience one time, but giving customers exactly what they want, every time, is not sustainable. Producing great experiences over time comes from meeting customer needs, but also from delivering business results. Employing ML is the only way to find the optimal balance between these priorities.

How are you applying AI to make the customer experience work for you?