October 13, 2020

How to Improve Ad Relevance

It’s happened to all of us. You finally found a great deal on a product you’ve been wanting to buy and pulled the trigger. The package is on its way from Amazon, Wish, or some other retailer.

You open another browser window to check the news, and are surprised to see advertisements for the exact same object you just purchased flooding the screen. As you’ve already purchased the product, you rightfully ignore these advertisements and go on with your day, slightly miffed at the obliviousness of advertisers.

If you offer online products or run an online marketplace, there’s a good chance this is happening to you regularly. Ad relevance is a powerful tool when used properly, presenting users with options similar to items that they’ve already purchased. The intent is to encourage a click by advertising items the user has already expressed interest in, either through a click on an ad or a purchase on a website. However, the efficacy of this approach changes once the user has actually completed the purchase. 

Let’s take a brief look at ad relevance. We’ll explore some of the pitfalls of using ad relevance naively, and discuss how we can improve relevance – and click-through rates – with a slight shift of focus.

What Is Ad Relevance?

Ad relevance refers to how closely your ad matches your customer’s interests, behaviors, and needs. Relevant, high-quality ads can increase engagement and revenue, since they appeal directly to each buyer’s unique situation. As SmarterHQ reported, 72% of consumers say they will only engage with marketing content if it’s personalized and customized to their interests.

Ad relevance can also refer to how closely your ad matches your landing page. If your ad copy teases the features of your mobile app, for example, you want your landing page to include more information about those features and a download link for that app – creating a seamless, intuitive experience for the customer.

Stating the Problem

You are likely participating in a number of ad networks spread around the web. These ads, if properly implemented, should be driving clicks on your products that result in higher traffic on your site – and accordingly, higher sales. The key to successful ad campaigns in this style is to present potentially relevant items to the consumers, encouraging them to make a purchase based on items they’ve already expressed an interest in.

The most common approach here – what we’ll call the “naïve” approach – is to present the user with products similar to those they have already purchased. If a user has purchased a red dress, for example, one might “naively” conclude that they are interested in purchasing more dresses. 

The user continues to browse the web and, in accordance with the above, they promptly see advertisements for red dresses in a similar style, blue dresses, green dresses, and other similar big-ticket items that they’ve already demonstrated a willingness to purchase. All is well in the world. Well, except for your click-through rates.

The Problem With the Naïve Approach

The problem with the naïve approach above rests in a faulty assumption. The base assumption is that if a user has purchased one item, they are likely to be interested in – and purchase – similar items. Someone who purchases a red dress may also be interested in another red dress, or may be interested in a blue dress with a similar neckline. While this approach seems logical at a glance, it ignores user behavior.

Put yourself in the shoes of a user shopping for a red dress. The user likely already has a closet full of other clothes, and is purchasing the dress to bolster their existing collection. While it is likely that they may purchase additional dresses in the future, odds are that they’re not interested in purchasing a big ticket item like a dress in bulk. This is a difference between the act of shopping, where you want to be presented with a range of similar options so you can make a decision, and the act of buying, which is driven by the underlying purpose that drove you to shopping online in the first place. 

The “naïve” approach optimizes for the action of shopping, but ignores that most of these ads are not being seen on your marketplace – in fact, once the user has clicked through to your site, they no longer need to have the related products shown to them as ads. They’ve expressed an interest in purchasing this item from you, which means they’ve necessarily shifted their mindset from “purchase” to “buy”.

Improving Clickthrough Metrics

Once the user swaps their mindset from “purchase” to “buy”, the naïve approach to advertising above immediately loses its efficacy. The user has just bought a red dress – there is not much of a chance they need two red dresses. The key here is to recognize that the switch from a “purchase” mindset to a “buy” mindset changes the desires of the shopper. They’ve completed their primary goal – buy a red dress – and have moved on to the original driving goal of building a wardrobe that includes a red dress.

To get around this misunderstanding, you’ll need to expand your definition of related products. A user who has bought a red dress likely doesn’t want another red dress. However, they probably are very interested in a red handbag, red shoes, or any other item that would be fashionable with their new garment. Bolstering this is the place where the user is actually seeing your advertisements. 

Once they’ve purchased an item from you, they’ve probably already left your website to continue their day. This means they’re seeing your “relevant” ads on other websites, either browsing the news, searching the web for additional products, or while checking in with friends and family. By changing the ads at this point to show items related to the red dress, you can once again capture their attention and drive them back to your site.

How to Improve Ad Relevance

There’s one key ingredient to improving ad relevance: customer data. Once you understand which channels your customers use and which content they engage with, you can create high-quality ad copy that reaches them in the right place at the right time — with just the right messaging.

Learn more about multichannel advertising here.

Take the finance and investing advice site, The Motley Fool. They use a multichannel approach, building unique strategies for demographics across email, search, social, and display advertising. For example, they can launch ads in email newsletters from premium publishers in their industry. When users click on an ad, they’re taken to a relevant article or video, and can choose to sign up for The Motley Fool’s special offer email series. The publication then nurtures these new leads with previews of their premium subscription offerings.

Why does this work so well? Because The Motley Fool has the data to improve ad relevance and understand its target audience: Baby Boomers aged 55+, more than half of whom are likely to click on email ads for relevant content. As a result, the publisher drove hundreds of new subscribers each month and optimized its cost per acquisition.


Simply put, once a sale has been made, advertising that shows similar items to the user loses all efficacy. The user has made their purchase, and moved on to other things. If you want to capture that user’s attention, you’ll want to present the user with items related to their purchase, but not similar. By focusing on user behavior data, and the factors driving their purchase decision, you can revolutionize your advertising and improve clickthrough rates, providing ads that are more relevant to the user and more beneficial to your bottom line.

Learn more about multi-channel messaging here.