The task
The payment provider was looking for prospective clients among IT companies. The logic is simple: if a company runs ads, it has budgets and an active, operating business, so payment solutions can be pitched to it. The job was to find everyone advertising in search across IT topics and turn that into a database for the sales team.
What we did and what data we collected
We built a broad keyword set for the IT niche and ran ad monitoring in search results: who is advertising (the advertiser), which ads they run, and which landing pages they point to. From the advertisers and their websites we compiled a list of companies — prospective clients; competing payment services, aggregators and irrelevant niches were removed from the list. The data was kept as a time series to also catch new advertisers who had just started buying traffic.
Challenges and how we solved them
First, coverage. Ads are tied to queries, so a broad keyword set was critical to catch as many advertisers as possible; more on collecting and clustering keywords in our articles on keyword scraping and scraping Google queries.
Second, ads are personalized and rotate: different users, geos and times of day see different ads. We captured SERPs for the target countries, frequently enough to catch the rotation rather than a single snapshot — otherwise some advertisers would simply never show up.
Third, search engines defend against automated queries. Collection ran in distributed mode, with proxy rotation: otherwise the data would be incomplete at that volume.
The result
The client got a regularly updated database of IT-niche advertisers — a list of active companies with budgets, ready to use as a prospecting database for selling payment solutions. The history is visible too: who started advertising and when, which shows whom to approach first.
Services in this case study: Ad Monitoring · SERP scraping · Data for Marketing and Sales · Data Search and Enrichment