✏️ Get the most out of the product check: insights & best practices

More and more webshops are seeing customers land directly on their product detail pages (PDPs) through advertisements. These customers have different needs compared to visitors who enter a webshop through the homepage or product listing page to browse products. Rather than wanting to know which product suits them, they want to know whether the specific product they're viewing is the right choice. In early 2024, we developed the product check specifically for these webshop visitors.

The product check is a feature you can use when you want to place your product finder on a PDP. It ensures that the advice is presented differently: Aiden recognizes the URL of the PDP where the customer is located and then shows in the advice whether this product matches the customer's needs, along with potential alternatives.

After extensive testing and feedback from various webshops, we've gathered valuable insights about optimally implementing the product check. (Curious about the initial commercial results? Click here!). In this article, we share the most important best practices for implementing this feature. What works best? And what should you pay attention to? Let’s take a look.

The number of questions

We often get asked about the ideal number of questions for a product finder. The answer is simple: it doesn't matter. In the data from more than 1,500 product finders, we see that adding more questions doesn't cause more people to drop off. There's only one condition: the questions must be relevant. For each question, the customer needs to understand that the answer is useful for the final advice.

With the product check, it's different: more questions work better. Why? The product check evaluates one specific product and must determine if it's a good match for the customer. And a product is only considered a good match when at least 80% of the answers match neutrally or positively. In other words: up to 20% of the answers can be a poor match. This percentage has direct consequences for the optimal number of questions. With 4 questions, for example, every answer must match perfect, good, or neutral - one bad match (25%) is already too much. With 5 questions, only one question may match poorly (20%) in order to appear in the advice. In short: the more questions you ask, the smaller the impact of one bad match becomes.

Of course, you don't want to overwhelm the customer with questions either. We know that each question must ultimately be relevant. Our advice: aim for at least 6 relevant questions per flow.

Matching

Is it difficult to come up with more questions? Or do you often see empty advices appear in Test & Tweak? Then neutral matches might offer the solution.

Neutral matches? we hear you thinking. We hardly ever talk about this. And when we do, we say something like: don't use them, unless it's for a no preference-answer (such as "I don't know," "No preference," or "Doesn't matter"). But there are exceptions!

Let’s look at an example. In a product finder for vacuum cleaners we ask 4 questions (too few of course, but we want to make a point here). The vacuum cleaner that the customer wants to "check" on the PDP matches perfectly on 3 of the 4 answers given. The only characteristic that doesn't match is the color: the customer indicates wanting a black vacuum cleaner, but this specific vacuum cleaner is red. 25% of the answers therefore match poorly, which means: this product is not a good match. There aren’t any alternatives either: there simply isn't a vacuum cleaner in the catalogue that meets these strict requirements. The result? An empty advice.

It's a shame to reject this vacuum cleaner just because of the color. In every other aspect, it’s a perfect fit. By setting the matching for 'remaining products' to neutral instead of bad, this characteristic no longer influences the final recommendation. This way, you prevent a product that is otherwise a perfect match from being rejected based on a less important feature.

After setting neutral matching on remaining products, there's no more bad matching on color. Color is now simply not taken into consideration in the advice - only if it matches the customer's wishes. Result: more products are suitable, and the empty advice is resolved.

This is a small, simple trick to make more products align with customer wishes. But be careful: use this only as a last resort, when coming up with more questions is truly impossible.

The order of the questions

The order of questions is also important in the product check. Especially when you offer products that can be divided into different segments, such as basic and premium products.

Imagine: a customer is looking for a basic product and is viewing such a product on a PDP. While filling out the product check, the customer is presented with questions about cool, technical features and advanced functions (Wow, sounds awesome, the customer thinks. Obviously!). After completing the product check, it turns out that the best-matching product is much more expensive than the customer had in mind. This super expensive product suits me best? They think, disappointed. Never mind. Customer gone.

You can prevent such a situation by determining the customer segment early in the conversation flow:

• Ask about the experience the customer has with the product (basic, average, expert), and add price indications in the info texts.
• Pinpoint the customer’s budget and clearly indicate in the info texts what type of product they can expect for each budget.

This approach creates two advantages: you manage customer expectations, and you can ask more targeted follow-up questions that fit that specific segment. The result? Relevant products in the advice that match the customer's wishes, and that they can afford.

Secondary sorting

Customers look for confirmation and recognizable options when making a choice. When they do the product check on a product page, they not only see whether the viewed product is suitable for them, but they also see some alternatives. It's important to think carefully about how you present these alternatives.

Therefore, use secondary sorting strategically. This sorting is applied when multiple products get the same advice score. Maybe you've set it to margin (because you want to push certain products. Understandable). But it might be beneficial to set the secondary sorting to popularity instead. You probably show popular products on multiple places on your website, so it's possible that the customer has come across this product before and has already formed an opinion about it. Does the customer see a product that they have already rejected as an alternative in the advice? This can strengthen their confidence in their current choice.

Tip: you can also set secondary sorting based on review scores. You can also show these with the recommended products. Nothing as reassuring as the positive experiences of other customers!

Placement

The placement of the product check is also essential for its success. A clear proposition that directly appeals to the customer is most important. A button with only 'product check' or 'product finder' is not enough - customers need to immediately understand what to expect when they click the button.

The most effective approach is asking a question that directly addresses the customer's potential doubt. A good example is: "Not sure if these headphones are the right fit? Do the check!" Display the text with the product check button next to it. In an eye-catching color, of course.

Planning to place a banner? Watch out for banner blindness: your visitors tend to automatically ignore advertisement-like elements. Use visual elements that make the banner feel like part of the website, such as images with standout features that grab attention and convey authenticity. It's also good to include the specific product in the proposition.

In summary: when implementing a product check, it is essential to critically evaluate the placement, the number of questions, and their order. Remember, the product check always starts from a product page, with the central question of the customer being: does this product suit me? All testing and optimizations of your product check should be centered around this question.

Do you have questions about implementing the product check or want to share your experiences? Our team is ready to help, and we're always interested in your insights and test results!