Does the .Store TLD have an advantage for SEO/SEM? A Domain Experiment

Updated on 30 Nov 2023 by Elliott Davidson

Over the last 12 months, we (Contrast) have been commissioned by .Store Domains to run an experiment to compare and see if there are any performance differences in using a .store vs a .com domain for your eCommerce website.

There isn’t any public data available on this so we didn’t know how this would play out.

To test this, we launched two eCommerce sites that were the same, selling the same products, the only major difference being that one used .com and the other used a .store domain name extension.

We wanted to run this as any business owner or creator would want to do for their own store from a resources and knowledge perspective. As such, the stores were built using Shopify and we didn’t invest an excessive amount of time into paid or SEO that couldn't be replicated into a monthly owner's workload.

The main thing here is that, unlike most other experiments like these, these would be actual stores customers could buy from, not just a front as a way to collect the data. This way, the experiment could be as real as possible.

So that search engines and users interpret the sites as unique, we reworded the content. Duplicated content does not perform well from a Search Engine Optimisation (SEO) perspective, hence why we reworded it.

In addition, we used slightly different primary colours, images, and fonts across both websites. This was to reduce the chance of a user confusing one of the experiment websites for another or assuming the sites were duplicates and therefore could be a scam.

We cannot discount these differences that may have impacted our results, however, we have taken measures to minimize these confounding variables.

Another way we controlled the variables within this experiment was that the sites all used brand-new domains, registered at the same time, with no pre-existing history. This ensured the sites were not biased in their performance due to previous domain history.

As part of this test, we decided to look at each site's performance from an indexing, paid search, and SEO perspective.

You can view what each of the websites looked like below as we have created replicates of them for you to view through real-life screenshots of each store.


If you want to receive any organic traffic (SEO) from search engines like Google, your website needs to be crawled and indexed.

With this being a critical part of this experiment, we wanted to see how both stores (brandname. com & performed when crawled and indexed by Google.

Each website started with 34 pages, which were broken down into product, category, and information pages (i.e. About page). We would then track and record this data daily per URL per site.

As these were two brand-new websites, they had never previously been crawled or indexed. Therefore, on the launch of the two websites, we did the following:

For this specific part of the experiment, we decided to split this test into two parts.

Firstly, we decided to only submit the website's sitemaps to Google Search Console (GSC) to see how much natural coverage each site would gain within 15 days.

Secondly, for all pages which were not indexed through step one, we then requested each specific URL to be indexed again through Google Search Console (GSC), this time though it was through their URL inspect tool. Indexing Results

The results show that by day 6, 32/34 (94%) of pages had been indexed without any further manual indexing requests.

Only one URL had to be requested to be crawled and indexed after the 15-day period; this one URL was then indexed the same day. Therefore, this site had full coverage of all 34 URLs in 15 days. Indexing Results

The results show that by day 6, 19/34 (56%) of pages had been crawled and indexed without any further manual indexing requests. One URL had been crawled, though not indexed.

At the 15-day mark, 9 URLs (26%) had to be requested to be indexed. Of these 9 requests, 6 were indexed on the same day the request was submitted. The remaining 3 URLs were indexed between 2-5 days after the submission of the indexing request. All 9 URLs only had to be manually requested once.

Indexing Discussion site was 30% faster in getting the 34 pages fully crawled and indexed compared to the site. This data suggests that Google seems to prioritize crawling and indexing a store on .com as compared to .store.

That said, although had faster indexing, it acquired the least number of impressions over the first 30-day period. totaled 139 impressions, whereas had 154 impressions.

So despite the quicker indexing of the .com TLD store, the .store TLD site got more impressions over the first 30-day period. Ultimately, this is one of the leading metrics from indexing we care about from an SEO perspective.

Paid Search

Do your potential website customers care if you are using a different domain extension to .com?

We wanted to test and measure the level of consumer trust based on actual consumer purchases and the conversion rates of each site.

After launching the stores, we then waited 3 months to introduce this paid search test as part of this wider experiment.

To keep this fair and minimize the variables, we kept the ad accounts the same across both sites. This meant the ad account structures, targeting, URL destinations, budgets and bids were the same for both stores.

This ensured that no one account had been given preference, so how well the accounts performed was fully down to their individual performance.

From this, we then looked at the individual sites' conversion rates to evaluate if there was a preference to a specific TLD. This was done by looking at Google Ads data cross-referenced against conversion data in the Shopify stores.

We ran this PPC test for long enough to get enough data so we’d be able to see if statistically one site or the other was or was not performing better. In our case we actually ran these ads for 5 months straight. PPC Performance

Over the 5 month period where the paid Google search ads were live, accumulated 2,229 clicks, 21,547 impressions, and 33 sales.

Additionally, had a conversion rate of 1.48% and an average CAC (customer acquisition cost) of £39.59. PPC Performance

Over the 5 month period where the paid Google search ads were live, accumulated 2,229 clicks, 21,547 impressions, and 33 sales.

Additionally, had a conversion rate of 1.48% and an average CAC (customer acquisition cost) of £39.59.

PPC Performance Comparison














Click-through rate (CTR)



Avg. CPC



Conv. rate



Cost / conv



Paid Search Discussion

First, we need to mention that although the paid search campaigns were identical, the PPC spend varied across the two paid accounts, causing an inability to actualize the data to campaign spend levels and creating uncertainty as to whether the results were affected.

This issue would have arisen whether an equal budget was maintained between site campaigns or whether we’d paused both campaigns when one site ran through its budget.

From a variables perspective, the former is preferable, and that’s what we did. It just so happened that better spent through its daily budget more consistently, resulting in a higher PPC campaign spend but a cheaper average CAC (customer acquisition cost).

However, this doesn’t directly correlate to the number of conversions relative to spend. Ultimately, experiments aren’t perfect and we controlled the variables as best we could.

The hypothesis we had was would there be a difference in trust from a consumer in wanting to buy from a .com domain vs .store TLD. had a 12.12% increase in conversion rate over (1.48% vs 1.32%).

Additionally, the conversion rates might look similar but if you forecast this out to running an eCommerce store doing $100,000s if not $1,000,000s, this small difference of 0.16% could be worth $10,000s.

Equally the CAC (customer acquisition cost) was cheaper for at £39.59 vs £44.45 for site

CAC and conversion rates tend to be one of the most important KPIs for eCommerce businesses and as you can see, the outperformed the on all fronts through this paid test.

Organic SEO

From an SEO perspective, after the initial indexing phase we tessted, we left both sites alone for 3 months to see how things naturally played out from an SEO perspective.

After this we started to write and post blog content. In total we published 34 blog posts to both sites, just reworded. Each targets one of the 3 different stages of a customer's journey to encourage potential customers to place an order. The blog content is a mix of reviews, comparisons, ‘best of’ posts, and industry guides.

To help build up the authority of the websites, we built a total of 15 backlinks which pointed back to 15 individual articles. When identifying the guest posting opportunity for the experiment websites, we made sure to use industry relevant websites. Each of the external websites linked back to both experimental websites, therefore the guest post content was slightly different to avoid a duplicate content issue.

Both the blog content and the links didn’t just go live all at once, we drip fed them over the course of the next several months. This was so it was all natural and replicable for a website owner workingl on their own with limited time and budget. SEO Performance

It took 10 months, 20 days (324 days) for to earn its first 100 clicks. Shortly after at 11 months, 25 days (359 days) received a total of 20,000 impressions, with these continuing to increase as the experiment continued. It wasn’t until the last 30 day period of the experiment that achieved its first 250 organic clicks during a 30 day window.

Over the 12 months of the project, the website gained a total of 24,822 impressions and 333 clicks. SEO Performance

It took 8 months, 19 days (264 days) for to earn its first 100 clicks. Additionally, the site gained 20,000 impressions by 9 months, 23 days (296 days). It wasn’t until the last 30 day period of the experiment that achieved its first 250 organic clicks during a 30 day window.

Since the start of the project, the website gained a total of 49,939 impressions and 623 clicks.

Organic Search Performance Comparison


Impressions (GSC)



Clicks (GSC)



Average click-through rate (CTR) (GSC)



Average position (GSC)



All page views (ex direct) (GA4)



Only organic page views (GA4)



All website page views (excluding direct) are broken down into the following: products (28.05%), categories (26.07%), blog posts (9.08%), home page (33.26%), information pages i.e. about page (1.65%), and miscellaneous i.e. policies, cart, account, search, checkout, and orders (1.64%).

Presented below is keyword data from Google Search Console. It shows the total keyword footprint as well as the section performance of the blog vs non-blog content which we categorized.


Non-Blog Keywords

Blog Keywords

Total Keywords







Organic SEO Discussion

The data from the 12 month project is large enough to conduct significance tests which show the TLD consistently organically outperforms the TLD. This is shown through constantly higher clicks, impressions, and click through rate.

  • domain gained the first 100 clicks 80 days before

  • acquired the first 20,000 impressions 63 days before

  • had the largest keyword footprint, 49.01% larger than

  • TLD gained 250 organic clicks in any 30 day period 4 days before

  • gained the first 100 clicks, received 20,000 impressions and achieved 250 clicks in a 30 day window the fastest

  • This suggests Google preferred the domain over the TLD.

Statistical Testing

This is the nerdy section for those who want to understand the testing behind this experiment. The significance testing was conducted with code generated in the software MATLAB.

Significance testing involves using measures such as the mean and standard deviation (spread of the data) to identify small differences across a large set of data. The significant differences between the sites and their corresponding metrics are indicated in green.

Significance testing goes beyond comparing the means. It assesses if the differences across the metrics were brought about by chance, or instead a manipulation of variables. The green indicates there was enough evidence across the time period of the experiment to indicate a significant difference of the two websites. Therefore, it is implied that the manipulation of variables (differing TLDs) contributed to the significant difference.

On the other hand, the red indicates where there was not sufficient evidence across the time period to indicate a significant difference between the metrics.

Paid Search

Mean values

Clicks per day


CTR per day

Avg. CPC


Conversions per day













Significance testing: vs




Avg. CPC


Conversions per day

p value







Organic Search

Mean Values

Clicks per day

Impressions per day

Average CTR per day







Significance testing: vs Branded.store1




p value





What does E stand for? E-06 = 0.000006 (6 zeros)

p < 0.05

Significant difference between the two sites using the corresponding metric

p > 0.05

NO significant difference between the two sites using the corresponding metric

Statistical Significance Summary

We cannot use measures of statistical significance to compare totals or means. Significance testing requires a moderate amount of daily data to find significant differences in trends across a spread of data. This means we cannot use significance testing to measure the difference between the total number of conversions, cost per conversion, or conversion rate because these are singular figures. This is also due to the fact that the daily data isn’t sizable and consistent enough to make these statistical conclusions.

Even though we can’t measure the statistical significance of cost per acquisition and conversion two KPIs (key performance indicators), we were able to do so for all of the other KPIs and outperformance on clicks, CTR (click-through rate), average cost per click, and cost.

The data from the organic SEO aspect of this project is large enough to conduct significance tests which show the TLD consistently organically outperforms the TLD. This is shown through constant higher clicks, impressions, and click-through rate making data statistically significant.

Experiment Summary

Speaking honestly from my professional perspective the results came as a surprise to me. If anything, I would have thought things would have been equal, if not weighted towards the .com vs .store TLD. I wouldn’t have thought that the .store site would statistically outperforme the .com site in nearly all KPIs.

We saw that outperformed on initial indexing. Though following this, from an overall paid search and SEO perspective, the statistically outperformed the counterpart site on all but one measurable KPI.

In Google’s own guidelines documentation they say “Overall, our systems treat new gTLDs like other gTLDs (like .com and .org).”. We can safely say that this is true. The new gTLDs (like .store) are not looked at or weighted against in a negative way that would affect your site performance, in our case, it was only positive.

Whether or not we like to admit it, customers know the TLD extension .com and this sentiment isn’t going away anytime soon. That said, I’d now consider a .store TLD.

Additionally, from securing and locking down IP when registering domain names as a brand, you should be purchasing this so no one else has the opportunity to buy it and launch a store to compete against your current site.

Finally, if you just want to launch your own store and keep it separate from your main website, I see no reason why you wouldn’t do this on a .store TLD.