Why Long Tail SEO Matters for eCommerce Marketing
You’ve likely heard about long tail SEO or #VoiceSearch but aren’t sure how to apply to your business. See how!
Long tail SEO. Optimizing for Voice Search (i.e. Alexa, Google Home, etc). You may have questioned investing in the effort — because it doesn’t provide an immediate ROI.
In my experience this has been the norm for a large majority of eCommerce businesses. The good news is that you control your own destiny to make this change without having to invest tens of thousands of dollars.
Your own data is likely showing you a trend of web-based keyword search queries continuing to shift towards long tail. Couple this with the adoption rate of voice assistants — Alexa, Siri, Google Home — and it’s not far fetched that we’ll see long tail continue to take a significant chunk of overall search percentage.
“Alexa, where can I find black handbags with silver hardware? Oh … On sale too.”
“You can find black handbags with silver hardware at Macy’s and Rebecca Minkoff. Would you like me to show what I’ve found on your phone? Or would you like to buy this Rebecca Minkoff Mini M.A.C. Crossbody I found for 20% off?”
“I love it! Can you purchase and ship to my home address?”
“No problem, Brad. It will arrive Thursday morning.”
The potential here is almost endless. The current advancement of in-store fitting room experiences means they’ll likely come to homes soon, which would only continue to drive this voice-based search experience.
Character Counts On the Rise
What happens when you compare the keyword query length for sites over time? Here’s one example for an eCommerce site comparing organic keyword length in Q3 2015 to Q3 2016.
Measure your own shift with Google Analytics and some “Excel-ry”:
- Go to Acquisition > Campaigns > Organic Traffic and pick your own date range comparison (e.g. September – November, 2016 versus 2015).
- Export as a CSV and import into Excel or Google Docs.
- Add a new Column A called ‘Keyword Length’ and set the formula of A2 to be =LEN(B2) targeting your keyword query cell. Copy this for the entire column. This gives a count of characters for each keyword.
- Filter your date range and keyword column to perform your own analysis (if you’d like a Google doc with this already setup, leave a comment, and I’ll send you one).
For this particular site I analyzed, period-over-period organic traffic was within 2% — so the sample size was very close. Quite the difference in keyword query length in a year!
Taking a Step Back
Before digging deeper, let’s review the difference between keyword query types with examples so we’re speaking the same language.
(Fat) Head Terms
These are short, popular, and generally take years to build rank in. Your home page and primary category pages are examples of where head terms are generally utilized.
Examples are “cell phones,” “dresses,” or “handbags.” See the 368,000 monthly searches:
As you’d expect this is slightly more specific than our head terms. Examples are “black handbags” or “blue dresses.” These are usually your category pages and ideally with SEO-friendly faceted/layered navigation filters applied.
You’ll see below the volume for something like “blue dresses” is 74,000 (the upper end of the Chunky Middle).
These keyword queries contain at least 3–4 words and are the largest opportunity for spreading a wide net to rank on thousands of keyword combinations. Examples are “black handbags with silver hardware” or “mint green converse high tops.”
The search volume is considerably less.
How Can You Start Today?
First, build out a plan with your team that you can execute on together. I’ll cover a few tips below for category pages and go more in depth on site-wide enhancements in part 2 of this series.
The most logical place to start is your layered navigation filtering. Each filter selected should update where each of the items below contain the category + filter name + filter option(s) selected:
- title tag
- h1 tag
- canonical URL
Without focusing on this enhancement, your filters applied are either
- non-existent because the filtering ajax refreshes the product list
- numeric or random string values like this: https://www.simmsfishing.com/shop/t-shirts.html?simms_size=474
Alexa can’t map “simms_size=474” to a real size like “Large”. So in this example, www.simmsfishing.com is not likely to reap the benefits of a “where can I find a fishing hoodie in size large”.
Have a sitemap that is updated with filtering permutations that you’d like indexed and utilizing the rel=prev/rel=next tags for paginated content.
And for really advanced users, you can utilize Google’s query parameter search console tool to help manage the total number of permutations that can be crawled from your filters.
Here is an example implementing long tail friendly layered navigation well:
Here are two site search results comparing the search query “michael kors cocktail dresses”:
Nordstrom wins in this example, ranking higher than Macy’s for “Michael Kors Cocktail Dresses”, however both sites are on the first page of results!
eCommerce category pages have historically been really solid at fathead or maybe even “chunky middle” search queries. By implementing a solid long tail SEO strategy to your category pages and layered navigation, you should help put yourself in position as #voicesearch optimized and ahead of your competition.
If you would like specific platform tips on how to take enhance your own category pages, let me know in the comments or email me at firstname.lastname@example.org.
I’ve used this module from Amasty many times on Magento, which works pretty well out of the box.
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