Before my time at Indix, I was a SEO consultant for an online marketing agency that worked with some of the largest ecommerce companies in the country. I focused on canonical tags, duplicate pages, and optimized page titles, but it wasn’t until I started at Indix that I began to fully understand just how arduous ecommerce SEO can truly be. While you can do all of the technical SEO correctly, it doesn’t matter if you don’t have the right product attributes – a difficult problem to solve considering the internet is a dirty place. Neither product SEO nor product data alone can win the ecommerce battle; the two have to be married for ultimate ecommerce success.
Ecommerce SEO is all about optimizing product pages in order for them to be discovered by potential customers as they search for a product to buy. That’s nothing new. This can only work, though, if you have accurate product information on the pages that will match searches. Most retailers rely on manufacturers for this information, but it’s oftentimes incomplete and can even be outdated or inaccurate. Unfortunately, retailers tend to trust the product information they’re given and bulk upload it into the system, which populates the product page.
The SEO implications for when you have incomplete or bad product information are vast. Firstly, say you only have a UPC; UPCs are not unique—manufacturers can reuse them 3-4 years after they discontinue a product. If you base the product information off that bad UPC, the automated information pulled in could identify a baby blanket as some other product, like a pacifier. The actual product, the baby blanket, won’t be found by “baby blanket” keyword searches because Google has no way of knowing that this is actually a blanket and not a pacifier. Your sales for the baby blanket will suffer.
Secondly, if this result ends up ranking for pacifier but the product is actually a baby blanket, people will visit the page only to bounce when they find that it is not the product they were expecting. Google uses machine learning, in the form of RankBrain, to optimize and organize the content you see when you search their engines. When a subset of users that search for a product click on a result only to immediately return to the search results page and choose another option, Google’s machine learning begins to recognize a trend suggesting that this specific piece of content doesn’t satisfy users’ query. This will cause Google to demote your page, hurting your rankings and potential customers’ ability to find and buy your products. You need quality product information to ensure your products are discoverable by the right searches.
Beyond the aforementioned SEO reason as to why you need good product information, there’s also the keyword perspective. When you have all the proper product attributes, you can optimize your product page for the long-tail search. Let’s explore an example. Say this was your product:
If you have the most basic product information, you might have a product title along the lines of “dress” or “blue dress.” Think about how many blue dresses there are out there in the world, and therefore how much competition you’ll have in search results for the term. Even with 49,500 people in the US searching for “blue dress” every month and 90,500 searches each month around the globe, there are 266,000,000 results– in this case your competitors–trying to fight for first page presence.
If you have proper product information, you have enough to write a long-tail product page title. While “long, strapless blue dress with horse pattern” might not have any monthly searches, you’re suddenly relevant for “long blue dress,” “strapless blue dress,” “horse dress,” and other similar searches. Not only does your product have the chance of being surfaced in more search results, there’s usually less competition among these long-tail searches.
What’s more is that long-tail searches usually indicate bottom of the funnel intent; the searchers know exactly what they want and are now in the comparison and selection process. Therefore, if someone searched “long, strapless blue dress with a horse pattern” and you are able to return a long, blue, strapless dress with horses on it, your searchers are going to be pleased to find exactly what they’re looking for and will be more likely to buy from you.
This keyword-to-funnel mapping doesn’t only apply to long-tail searches, however. In the book, Advanced Google AdWords: Third Edition, Brad Geddes explains how different kinds of keywords are used at different stages of the buying funnel. When you get to the final stage, the buying stage, you’ve already done all of the research that you need to determine what you’re going to buy. “At this point, the only question left to answer is where to buy the plasma TV …. These keywords are often product part numbers or company names: Jim’s accounting service or Samsung UN55D6000 55 1080P LED TV,” writes Brad Geddes. In other words, if you don’t have all of the specific attributes like UPC and MPN on your product page, you won’t surface when bottom-of-the-funnel customers are ready to buy. That’s easy money out the window.
It’s easy to think that ecommerce SEO will fix all of your problems, but it will only do so if you have the correct product information. When the two are combined, you have lower bounce rates, better long-tail and bottom of the funnel relevance, and higher conversions. All of that means more money for your company; it’s just a matter of investing in both SEO and product data first.
Also published on Medium.