Our AI-Built Niche Site: 1,160 Visits in 15 Days
TL;DR results
Period: 18 September to 2 October 2026 (15 days), counted from the site's own server logs with bots filtered out
- Visits in 15 days
- 1,160
- Pages listed for search engines
- 543
- Product pages with price history
- 500
- Side-by-side comparison pages
- 20
The home page is the top landing page every day; the rest of the visits are spread across many product pages, each one built around a real price history.
What we did
We built a product price comparison site with AI helping at every step: picking the niche, designing the page templates and writing the code. The niche is everyday household products: kitchen tools, small appliances, cleaning gear and similar things people compare before buying.
We picked it for one reason: we could collect data nobody else shows. We record each product's price every day, so a page can answer the question a shopper actually types into a search box, which is "is this a good time to buy?" A generic review cannot answer that. A price history can.
Between 18 September and 2 October 2026 the site logged 1,160 visits (unique visitors per day, added up over 15 days, bots removed). As of 3 October 2026 it lists 543 pages for search engines: 500 product pages, 20 side-by-side comparison pages, plus category, best-of and policy pages.
The steps
- Choose a niche with a changing number. Prices, stock, ratings or specs that move over time give you fresh, unique content every day without rewriting anything.
- Collect the data on a schedule. Store one row per product per day. The history is the asset; the pages are just views of it.
- Make one page answer one question. Each product gets its own clean address, the product name in the title, a short verdict ("lowest price in the last 90 days" or similar) and a table of dated prices.
- Put the content in the HTML. Our first version drew products with JavaScript, so search crawlers saw an empty page. We switched to pages rendered on the server, with the name, verdict and price table in the page itself.
- Only open pages that earn it. A product gets a page once it has at least 10 days of price data and at least 3 different prices. Anything below that bar is not indexed.
- Generate the sitemap from the database. A hand-written sitemap listed zero product pages. Now the sitemap is built from the same data as the pages, so new pages appear automatically.
- Add structured data carefully. Product pages carry product and offer markup so search engines understand them, plus canonical and social preview tags.
- Add comparison pages for close pairs. When two similar products compete for the same buyer, a side-by-side page answers "which one should I buy?" in one place.
How we keep pages fresh and honest
- Every price shows the date it was last checked.
- If a price has not been rechecked for 3 days, the verdict changes to say so instead of calling an old price "current".
- Pages with old prices drop their offer markup, so a search result never shows a stale price as today's price.
- Pages that are not changing are listed in the sitemap as monthly rather than daily, so crawlers spend their time on pages that did change.
What brought visitors
- The home page is the biggest single entry point. It was the top landing page on every one of the 15 days, which tells us people come looking for the site itself as well as for single products.
- Individual product pages are the long tail. Almost every day a handful of visits land directly on a specific product's page, a few per page, spread across many different products.
- Search referrals show up daily. Visits from a local search engine arrived on 13 of the 15 days.
The lesson: a site like this does not get one big hit. It gets many small ones, spread across hundreds of pages, and each page only has to win one narrow search.
What we would do next
- Open the next batch of pages once indexing looks healthy, by lowering the minimum price history from 10 days, and raise the bar instead if too few pages get indexed.
- Add more comparison pages for the pairs people already land on.
- Track which product pages are entry pages week by week, and write better verdicts for the ones that bring visits.
- Keep counting visitors from server logs so the numbers on this page stay honest as the site grows.
Free tools for this: Word Counter
Frequently asked questions
How do you count visitors?
From the web server's own access logs, not a browser script, so ad blockers do not hide anyone. We drop bots, crawlers, our own test tools and vulnerability scanners, count unique visitors per day, then add the days up. The 1,160 figure is that daily count summed over 18 September to 2 October 2026.
Why not make a page for every product?
Search engines filter out pages that differ by a single value, and too many thin pages can drag the whole site down. We only open a page when we have at least 10 days of price data and at least 3 different prices, so every page has something worth reading.
Did AI write the pages?
AI helped design the page templates, the rules for which products get a page and the checks that keep pages honest. The page content itself is data: product names, collected prices and a plain-language verdict built from that data.
Can I copy this for my own niche?
Yes. The method works for any niche where a number changes over time and people search for it: prices, availability, ratings or specs. The steps below are the ones we followed.