A woman unboxing a new product packaged in a red gift box. She is looking inside with anticipation of something great. AI and product discovery concept
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This is part 2 of a 4 part series on customer experience, sponsored by Contentserv.

In order to keep consumers engaged and buying, brands need to provide them with outstanding product experiences. In fact, 87 percent of consumers say they’d stop doing business with a company that provides inaccurate product information, and 30 percent of consumers abandon purchases due to lack of product content.

But not just any content or image will do. Consumers expect consistently rich, relevant, emotional product experiences whenever and wherever they shop. At the same time, with so many products, channels, languages and target groups, managing these variables to deliver the right product information to your audience is too much for any one person to handle.

The AI capabilities of a product experience platform (PXP) can help. Going a step beyond the traditional product information management (PIM) system, a PXP can help you get just the right product in front of a consumer, at the very time she’s ready to buy.

Related Article: Five Reasons Why Fantastic Customer Experiences Start with Great Product Content

How AI Gets Products Right


1. Helps You Use Customer Data Efficiently

Personalization software and IP tracking can help you find out what a customer has purchased, where they’re located, what time of day it is, and other factors that help you get to know more about them. But many times, that information sits unused because organizations aren’t sure how to best use it.

The right product experience platform can alleviate these concerns, elevating the built-in functionalities of master data management (MDM) and product information management (PIM) with AI. A PXP stores, categorizes, tags and manages personalized information at the product level, helping you understand and actually use your customer data. As a result, consumers consistently have the product information they need to make better buying decisions.

Let’s look at a real-life personalization example – me! I’m a runner, and I always buy the same brand of running shoes. About every six months I go online to buy a new pair. Because my favorite brand knows my buying habits, where I live and what I’m interested in, I’m presented with an array of options beyond just variations of a shoe. I see running shorts, shirts, hats, and even lightweight jackets that are necessary for trail running in the mountains, which they must know I do because the person in the image on my screen is running on a trail. While I came just to buy a pair of shoes, I added a new hat and saved a couple of other articles of clothing to look into another day.

A personalized online experience like that is only possible with software that has the ability to retain and use data in such a way that can bring not just my buying habits to life, but my running habit to life, as well.

Which segues nicely into the next point...

Related Article: 4 Ways to Connect Your Product Information with Customer Experience

2) Recommends the Right Product

While providing product recommendations based on buyer data like demographics and browsing behaviors is a start, imagine how delighted a customer would be if you also based their experience around their moods and interests, or some other relevant attribute?

For example, imagine you have two customers shopping for wine and dinner on your site. Susan is cooking for her friends, and wants top-quality salmon for her famous recipe, and the best wine she can afford. Josh, on the other hand, has invited a date over for dinner, but doesn’t cook. He chooses a lower-priced smoked salmon, and a $30 wine one of his friends said would taste fine.

At checkout, instead of recommending the same product to both buyers, AI goes to work and provides personalized recommendations based on mood and interest data. Because the system knows that Susan likes cooking and enjoys fine wines, at checkout she’s presented with a recommendation and offer for a wine country tour and cooking class. Josh gets a recommendation for caviar — a no-cook way to help him impress his date.

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3) Personalizes Product Presentation

According to an Infosys study, 74 percent of consumers get frustrated with product information that’s not personalized. Brands are leaving a lot of money on the table by displaying the same product the same way to two different people.

Imagine a 50-year-old woman who is looking for just the right white button-down shirt to wear with her new suit. After looking at several styles, she decides on one she likes and visits the product page for details. According to the product description, the style is right – tapered fit, two pockets, stretch fabric. However, the product image doesn’t appeal to her at all.

While she tries to her imagine how the shirt would look with her formal suit, the image shows a young woman in her 20s wearing the shirt with a pair of worn jeans in a casual setting. Sensing that the shirt isn’t a good fit, she moves on to another brand.

When it comes to product content, one size definitely does not fit all. Tailor content to your visitors using the persona attributes, buying behaviors and customer journey data you’ve already collected. Present the same product in various settings and contexts in both images and text so you can connect with a variety of customers and increase your sales.

4) Solves the Consumer’s Problem

AI can help you solve consumer problems by bundling products into solutions rather than just offering individual products. For example, if a shopper is looking for puppy food, they likely have a new family member. In that case, you can present a bundle that includes a food subscription, dog bed, chew toys, and a package of obedience classes. The same person the next week might be looking for rug shampoo and also might appreciate a bundle or recommendations for a carpet cleaning machine rental, stain remover, deodorizer and a carpet cleaning workshop.

By recommending bundled products, services and experiences, shoppers will save time searching for those extra items, and will feel like you’ve delivered a lot more value at a discounted price. Offering product substitutions or complementary offerings can also show customers that you understand their needs and value their business.

The Perfect Product Awaits

If your customers don’t know that you have products they need, then you’re doing them and yourself a disservice. Is the customer data you’ve collected being used, or is it sitting in a database collecting dust? Are you going beyond persona attributes to inform your product recommendations? How about that white button-down? Are you presenting it in the proper context based on who’s buying? And finally, are you solving a consumer problem by bundling solutions, instead of presenting individual products?

If you’re getting any of these questions wrong, it’s time to put AI to work for you. Offering a great online customer experience isn’t just for the behemoth retailers of the world. It’s for everyone, but it takes the right software!

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