Analyzing product performance is not as simple as just looking at units sold. One factor that is often ignored is the product’s visibility: how many times the product got viewed and the resulting conversions.

Let’s take brick-and-mortar stores as an example. Not all shelves are equal. The ones that guarantee more visibility are more expensive by quite a margin. The more time a product spends in front of customers, the more sales it generates. Eye-level space on shelves is sold at a premium. The same thing applies in online stores: the more a product is shown to clients, the more opportunities it has to make a sale.

Let’s look at an example: We have products A and B. For simplicity, let’s say both have the same costs and price. Product A has generated 100 sales from 10,000 listing impressions, while product B has generated 50 sales from 1,000 listing impressions. Which is more performant? Product A has a 1% conversion rate at the impression level vs 5% for Product B. We have a clear winner: Product B.

Looking at product visibility raises some other questions as well:

• Are there products that have not been viewed by any customer?
• Are there products with high conversion rates from listing, but low conversion rate from the product detail page? Or the other way around?
• Which categories need more impressions for a conversion? If 3 months ago the T-shirt category needed 1000 product impressions to generate a sale and now I need 3000 product impressions to generate a sale, then something has happened to my offering.

Product Impressions

A product impression is triggered when a product is in view for one second as part of a Product Listing Page (PLP).

A PLP is a page on a website that presents a list of products based on a category or search query.
A product is in view when it’s visible on the customer’s screen, not above or below the fold, for at least one second.
A product with 0 impressions means none of your customers have seen your product in any PLP. It’s most probably buried deep in your catalog, deep enough no one browses till there.

Product Detail Page (PDPs)

A product detail page (PDP) is triggered each time a product’s dedicated page is viewed by a customer. This is where all the details are: title, description, specifications, reviews, delivery time estimates, and, of course, the add-to-cart button. A product view is a clear sign of interest from the customer.

A product with zero impressions in any PLP and zero PDP views means that no one knows that this product exists. No need to tell you how wasteful this is.

A product with a high number of impressions and a low number of PDPs means there is a lack of interest in this specific product. We know it has been seen in PLPs due to the high number of impressions, but nobody clicked on it to reach the PDP. To make it easier to see this, we can look at the impression click-through rate.

Impression Click-Through Rate (CTR)

If we take the number of PDPs generated by the number of impressions (times 100) we get the impression click-through rate. This shows how many customers interact with a product from product listing pages. The higher the rate, the more appealing the product is to your customers. The lower the rate, the lower the chances for that product to make a sale.

Impression Conversion Rate (CR)

Transactions generated by browsing PLP for a specific product divided by the number of impressions (times 100) result in the impression CR. This is a shortcut to measure a product’s performance in PLPs. Make sure that you filter the transactions to use only the ones generated by PLPs.

A word of caution: you can have PDPs that are not generated by a PLP. For example, traffic that comes from your Google Search or email that goes directly to your PDP. The traffic has to be filtered, and PDPs need to be taken into account only when generated by PLPs. Here at Datma Analytics, we do it automatically for each Collection. If you’re using another analytics product, make sure to filter your data properly.

We can go a step further and analyze how a specific product category is performing by analyzing its CTR and CR. As a reminder, a product category is defined as a Product Listing Page (PLP), a list of products visible on the same web page. CTR and CR can be applied at any level of your catalog taxonomy. For example, you can analyze the T-shirt category PLP and the Long Sleeve T-shirts and Sport T-shirts sub-categories.

Product Listing Page Conversion Rate (PLP CR)

Take the number of transactions generated by the number of PLP views (times 100) and you get the PLP conversion rate. For example, The T-shirt category has been browsed by your customers 1000 times and generated 10 sales. The CR will be 10/1000 *100 = 0.1%.

Product Listing Page Click-through Rate (PLP CTR)

Take the number of PDP generated and divide by the number of PLP views and you get the PLP click-through rate. For example, The T-shirt category has been browsed by your customers 1000 times and generated 1500 PDPs. The CTR will be 1500/1000 *100 = 150%.

Both rates can be above 100%. Someone visiting a category usually clicks more than 1 product resulting in an above 100% PLP CTR. It can also buy more than one product from the same category, let’s say 2 different T-shirts, resulting in an above 100% PLP CR.

Remember that different product categories have different conversion values by default. It’s not a good idea to compare the Furniture category with the Pillow category conversion rate. The power of measuring PLP CR and CTR is when comparing it with itself at a different moment in time. A 10% increase in PLP CR year on year for your T-Shirt catalog means that the same number of category views have generated 10% more sales. That’s a good improvement.

When looking at the PLP conversion rates make sure to filter the traffic properly and attribute the revenue to the right category. For example, a category has made a sale only if somebody clicked a product when browsing it, added it to the cart from the generated PDP, and finalized the order in the same session. If the PDP has been generated by a newsletter, the revenue should not be attributed to the category containing that product. We’re analyzing the categories from a browsing perspective.

Product Detail Page Conversion Rate (PDP CR)

PDP CR is calculated by dividing the total number of transactions by the total number of PDPs (times 100) generated in a certain period. For example: A keyboard with 5,000 PDPs and 100 transactions will have a (100/5000) * 100 = 2% PDP CR.

It’s best to compare PDP CRs of similar products to find the best ones as there can be justifiable discrepancies. For example, in a category with an Average Product Price (APP) of $20 you may have a $100 product that is only bought by some of your customers. It may have a high PDP CR, but it won’t have the volume of your average-priced products. But comparing two similar-priced products, you can easily determine which one is performing better.