How Sieora built 400 retail store owner prospects in one hour for an AI security monitoring company
The client provides AI-powered CCTV monitoring for retailers. Stores in major shopping centres were a practical starting point for its foot-traffic use case, but standard prospecting tools could not filter for the owners of stores in those centres.
Headline results
The challenge
A manual search would have meant opening mall directories, checking each store and researching its ownership one business at a time.
The workflow
Perplexity
Identify major shopping centres across South Africa. Examples shown: Sandton City, V&A Waterfront, Gateway Theatre of Shopping, Canal Walk.
Apify
Extract store names and websites from mall directories. Examples: ZARA, Cotton On, Pick n Pay Clothing, Superdry, The Body Shop.
Claude + Apollo + Clay
Search for store, business and franchise owners: owner, franchisee and director roles.
The result
In one hour, the workflow produced a focused list of 400 retail owner prospects. It turned scattered mall directory data into a usable starting audience for targeted outreach.
400 leads in 1 hour: from mall directories to a focused owner prospect list.
The principle
When the audience does not exist as a prospecting filter, build it from the underlying market data.
Measurement note
Shopping-centre presence is a targeting signal, not verified store foot traffic. This case study measures list building; it does not claim outreach, meeting or sales results.