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Matching video enquiries to the right business, automatically

How a lead generation business automated transcribing VideoAsk responses and matching each enquirer to the right business, over a nine-month engagement.

client
A lead generation and client-matching business
industry
Lead generation
duration
9 months
Lead matching from video responses. Before: five manual steps from watching a video to logging the match. After: VideoAsk, Make and Google Sheets transcribe, match and log it.before: 5 manual stepsWatch the videoTranscribe itNote the needFind a matchLog in the sheetafter: one automated pathVideo responseVideoAskMakeSheetsMatched and loggedLead matching from video responses. Before: five manual steps from watching a video to logging the match. After: VideoAsk, Make and Google Sheets transcribe, match and log it.before: 5 manual stepsWatch the videoTranscribe itNote the needFind a matchLog in the sheetafter: one automated pathVideo responseVideoAskMakeSheetsMatched and logged
lead matching, before and after

This client matches people who need a service with businesses that provide it. People describe what they need in a video answer through VideoAsk, which is personal and slow to process. Someone had to watch each video, transcribe it and decide which business fitted, and the matching was inconsistent.

Over nine months we built and refined a Make system that does it instead:

  1. Each VideoAsk response is transcribed automatically.
  2. Rules read the transcript and pick out what the person needs.
  3. The person is matched to a business that fits that need.
  4. The match and the details go into Google Sheets.

Enquiries are now processed as they arrive, and matching follows the same rules every time, so it’s more accurate. The client handles more leads in less time without adding people.

Stack used

  • Make
  • VideoAsk
  • Google Sheets

Related: make consulting and business process automation

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