Services company: 2× qualified leads at the same budget

The problem

The forms worked and the volume was there. The sales team was spending its day on enquiries that were never going to buy, and the ones that would buy waited behind them.

What we did

Lead scoring on inbound requests, nurturing sequences for the ones that are early rather than wrong, and a direct integration from the forms into CRM so context arrives with the lead instead of being retyped.

Result

Qualified leads per month doubled over five months with no increase in advertising budget. NDA project: industry and trend, no brand.

Method: AI speeds up handling, it does not create demand

A model does not produce new demand. It shortens the gap between an enquiry and a human, and it takes the routine off the rep: context, qualification from the thread, a draft reply.

Context before the first call. Publicly available information is gathered and condensed in advance so the conversation starts on substance.

Qualification from the thread. Answers the rep forgot to log are extracted from the conversation and written into fields.

Draft written, human sends. Automatic sending in the company's name is the fastest way to damage a reputation. A checked draft is not.

Routing by fit. The enquiry reaches whoever closes that kind of deal, with the next step attached.

We measure first-response time and the share of qualified conversations — those are what automation actually changes, unlike the number of messages sent.

Services used on this project: AI automation.

Relative metrics only: these projects are under NDA, so the industry, the timeframe and the direction of change are published and the brand and absolute volumes are not. On a call we walk through the same structure applied to your market: baseline, work, expected metric.