Most experimentation and conversion rate optimization (CRO) folks will tell you that optimizing on the homepage is the most important thing you can do, followed by your category page. But what if I told you that actually, it’s your product page?
Rishi Rawat talks about this on his website, Frictionless-Commerce, and gives the example of two people looking at a product page on a website and how the description of that product is exactly the same for each buyer and how there is a lost opportunity there to personalize it based on the viewer’s preference. He posits that in years of testing various elements on product pages such as layout, design, and description, the thing that made the biggest difference was the product’s description.
If you really think about it, as marketers we often try to write a broad enough message so that it covers 80% of the people seeing it, especially when it’s a promotion. However, that’s not the way consumers want you to think about it anymore. According to Salesforce research, 66% of consumers expect brands to understand their unique needs and expectations and 52% expect offers to always be personalized. This validates that brands need to leverage data and insights to determine what a customer wants.
When consumers visit your site they are in one of a few consumer type buckets:
- They’re either newly exposed to the product you’re selling and want to learn more about it.
- They’re somewhat familiar with the product you’re selling and are curious about your specific product that they probably found while doing their product research.
- They have extensive knowledge about the type of product and know what they are looking for.
- They’re just browsing your site, maybe because of an ad they saw about a sitewide sale or dumbscrolling at the doctor’s office.
The point is, all of these types of consumers would convert better if the product description was tailored to their specific needs, interests, and desires. Now this may sound like a lot of work, but it doesn’t have to be. Keep reading to find out more.
Regardless of of consumer type, you need to understand these questions:
- Are they price sensitive?
- Have they arrived due to a need, desire, or interest?
- Are they shopping for themselves, someone else, or is it a gift?
- How did they arrive on the site? Was it from an ad, email, SMS, direct mailer, something else?
- Are they shopping with intent/purpose, or are they just browsing?
When a salesperson meets a consumer in person in your store they can very quickly assess answers to many of these questions. In fact, it’s often part of their sales pitch. But online, we seem to ignore the sales qualification process, and we never really get the answers to those questions. Hence, we wind up with product pages that are a one-size-fits-all, when in fact, we know they are not.
How to optimize for the product detail page description
The most important thing you need to do in order to properly understand their consumer type is understand how they found your website. Do you have this first or third party data available so you can pull into your testing tool? Can your CRO or personalization tool identify it for you with AI or machine learning?
Many retailers feel that the consumer needs to be logged in or self-identify in some way for them to gather all of the consumer touchpoints to serve up a personalized relevant experience. But that’s no longer true.
At the most basic level, AI can help you identify where someone came from so you can instantly understand things about that consumer that can help you tailor the product description to their wants, desires, or needs. For example, if you could know how they arrived on your site, whether they saw an ad or email or received an SMS from you promoting a discount, that could alert you they might be a ‘deal shopper.’ Or if you knew that a consumer had been on your site before, but perhaps didn’t buy anything and now they’re back again and you can see what other pages they’ve searched on your site. Did they research similar products previously? Has one of them dropped in price recently? Understanding what they’ve clicked on and how they’ve browsed your site allows you to tailor the description to their specific needs.
Where AI is the most powerful is that it can dynamically change the product description based on the information it has from where the person came from so that it is a frictionless, targeted shopping experience.
Your goal is to get down to a segment of one and do first page personalization. The more data you have, the easier that is to get to. If you don’t have a lot of data it’s not the end of the world, you’ll just be experimenting with writing the description for one to many, which is still better than one to all.
For example, on any product page you may ask the consumer for information prior to showing them the product description such as, maybe size, color, best sellers, or items under a certain dollar amount.
Let’s look at Allbirds. From the moment I land on the homepage they can deduce my gender, from there they can deduce in real-time whether I am looking for things that are trendy if I click on ‘Best Sellers’ or if I’m price conscious and click on ‘Gifts under $75’. The data capture can keep going.
Another example is when a consumer books a hotel stay. The data they input in the selectors will tell you a lot about what you should show them and can also help you tailor the description to that particular consumer’s wants, needs, and desires. If they select AAA/CAA or Lowest Rate then you know they are a discount shopper and looking for the best deal. Perhaps you show them a promotion. If they select Senior Discount you now know their age bracket and can draw conclusions on things like type of bed to amenities on what might be important to them, such as hotels with restaurants on property or within a short walking distance.
There are many examples like this, you just need to have the right data capture and conversion tools in place to understand your buyer’s signals.
Understanding your buyer’s signals
When an anonymous user comes to your site directly and clicks around but doesn’t buy anything, you have very little information about them. We often chalk that up as a non-conversion. However, you do have some information. You know what time of day they came to your site. You know what day of the week it was. You know their geo-location. You know they typed in your brand’s website directly into their browser so you know they are familiar with your brand because they either saw an ad or a billboard or heard a radio/podcast advertisement or heard from a friend. You also know what site they went to after they left yours. The point is, you know something about these anonymous people which should allow you to tailor the product description somewhat. You also now have information that you can store for when they come back again and possibly serve them up an even more tailored product description, or better yet, use that data to retarget those folks in an ad.
Known and Repeat visitors
If you have their email address, you know them from some marketing activity or you researched them to target them in your marketing efforts. Every touchpoint is a chance to collect data and information about that visitor so that you can properly use that information to change up the product description.
For example, this pre-holiday season I went to visit Frontgate.com, a site from which I have purchased a few outdoor items in the past year. Even when not logged in, instead of greeting me with a generic “Joyful Together” holiday promotion, I get the “A Cozy Outdoor Christmas” promotion. Now that’s Frontgate using data they already have on me. Now imagine taking that to the next level to the product description.
As you make enhancements to your ecommerce playbooks for next year, take the time to reassess your data inputs and your tools to see what you can pull into each experience to make it more relevant for each web visitor. AI is your friend, and data-driven personalization is what will set you apart from your competitors.
~ Tracy Sestili, VP of Marketing
Tracy Sestili is a tenured marketing executive leading teams at Intellimize, Fountain, SparkPost (acquired by MessageBird), Cisco, and TiVo. She has previously served on the board of Women for WineSense, and co-founded a nonprofit for lung cancer, for which she received a Bay Area Jefferson Award.