Twelve workflows that new users run in their first week. Each one starts with a single filter and ends with a list you can act on.
Every owner wants to know what the leaders in their category do. Start from a category or a keyword and rank the result by any of 20+ metrics.
Pick a subcategory such as Baby Health. That one returns more than 250 stores.
"Skateboard" returns around 900 stores selling skateboard products.
Set maximum domain age to 5 years and sort by authority.
Click the plus sign for the store's full profile and technologies.
Stores that earn links faster than their age suggests usually sell something people talk about.
In the skateboard example, the top results all sold innovative electric boards.
Pick Pets and Animal Supplies, filter to the US, order by average price.
See the Shopify store database and rising online stores pages.
The recommender learned from 4,000+ technologies across millions of websites. It tells you which tools stores like yours run that you do not.
Search your domain. Recommendations show in a green box on its profile.
Type the tools you use, for example a session recorder, a live chat and your store platform. You get up to 1,000 recommendations.
Send up to 500 domains. We return recommendations for each one.
Each recommendation names the tool you already run that most drove it. You see why, not just what.

Higher prices usually mean higher margins. Three routes lead to them.
Pick a detail level and get 50 high-ticket niches per request from a pool of 40,000. We add 2,000 a month.
Enter your products or keywords. Get the high-ticket niches closest to what you already sell.
Browse 60,000+ groups built from 32 million products, each with price, demand and difficulty.
Beyond the obvious pinball machines, laptops and smart TVs, the list surfaces niches few sellers have spotted.
The recommender works like a retail "customers also bought" engine. It recommends technologies to websites, based on what they already run.
Type a technology, for example a live chat tool. Get stores most likely to adopt it.
The same recommendations for non-ecommerce sites worldwide.
Sites in categories where your technology over-indexes but which do not use it yet.
Shopify is used 8.1 times more in Style & Fashion than that category's share of all domains would predict.
Shopping, Food & Drink, Hobbies & Interests, Pets, Sports and Home & Garden also sit above 1.0.
See the AI lead recommender and AI cold email pages.
Type any of 4,000+ technologies. Get the stores that run it, each with 20+ metrics.
Country and language.
Vertical and category.
Average price and number of products.
Domain age, authority and popularity rank.
See websites using any technology and competitor customer lists.
The five million most popular websites, each placed in the IAB taxonomy, with authority, domain age and technologies.
Run the same recipe on any of the other 439 categories, or export to Excel, Sheets or CSV for your own analysis.
Combine category data with technology data. Target the categories where your type of tool is used above average.
Or the category leader you compete with.
Categories above 1.0 are your natural market.
The recommender names tools often used alongside yours.
Sites in strong categories, running complements, without your tool.
Style & Fashion, Shopping and Food & Drink lead. That matches what an ecommerce platform should show.
Three more lenses on any technology: domain age, site popularity and country.
Apache skews to older domains, Nginx to younger ones. A rising tool wins the new sites first.
Analytics tools skew older; ad monetization skews younger.
The top 1M sites in groups of 100,000. React peaks in the top tier and falls with rank.
Bootstrap spreads evenly; Apache rises lower down.
About 1 million stores carry a country. Nginx, for example, is very popular with stores in India.
Put five live chat tools on one chart and spot audience gaps between you and rivals.
For every one of 60,000 product keywords we measure the average authority of the top ten ranking sites. Low means beatable.
Each of about 60,000 product groups carries a 5-year search trend. Sort descending inside any category.
The top of the list shows what buyers want more of every year.
Pick an ad technology, list every site running it, filter by category. Personal Finance alone returns many thousands.
Two independent signals tell you which accounts need attention first.
Customers in categories that use your type of tool far below baseline are less anchored to it.
Shopify example: Style & Beauty is about 8 times baseline, Books & Literature sits below it.
The recommender spots when your tool is unlikely to sit alongside a customer's other tools.
Output: your customers ranked by churn likelihood.
See churn prediction.
Both plans include all twelve workflows. Enterprise adds larger reports and more seats.