Buyer's guide
In-Store Conversation Intelligence: How It Works, What It Costs, What to Ask a Vendor
In-store conversation intelligence is software that captures the face-to-face conversation between a customer and a sales advisor on a physical shop floor, transcribes it, and scores it against the retailer's sales playbook. Every conversation becomes a lead if a number was shared, a score for the advisor, market signal on competitors and objections, and evidence for coaching. It is the in-person counterpart of the call-recording tools that instrumented phone sales a decade ago, built for a setting those tools cannot reach.
Why the store needs its own category
Conversation intelligence for calls (Gong, Observe.ai and their peers) works on clean digital audio with two speakers, a clear start and end, and consent handled by the dialer. None of that holds on a showroom floor. The audio is noisy and code-switched, a Hindi sentence with an English model name and an EMI figure in the middle. The conversation may be twenty minutes across three display areas. Consent has to be taken in person, under India's Digital Personal Data Protection Act. The basement has no signal. And the thing worth scoring is not talk ratio but whether the advisor did the demo, mentioned the offer and asked for the number.
That is why in-store conversation intelligence is a category of its own rather than a feature of call analytics, and why retrofitted call tools tend to fail on the floor. For the wider category definition, see what is retail conversation intelligence.
How it works, end to end
- Notice and consent. Signage at the entrance and the desk, and a disclosure line from the advisor that is itself a scored playbook step. Recording stays locked until consent is recorded.
- Capture. The advisor taps once to start and once to stop on their own phone. Offline-first, so a dead zone does not lose the conversation. Our guide to capturing in-store conversations covers the five design decisions in detail.
- Transcription. Speech recognition tuned for Indian English, Hindi and Hinglish, with speaker separation. The audio is deleted once the transcript exists.
- Scoring. The transcript is assessed against the retailer's playbook: greeting, need discovery, hero feature, objection handling, offer and finance, close, asking for the number. Each step is covered or missed, with the transcript lines that show it.
- Action. A lead is created if a number was shared, scored for intent, with a follow-up date. Objections, competitors, budget and timeline are extracted as market signal. The advisor and manager see it the same day.
Phone capture or installed hardware?
This is the first fork in the market, and it decides most of what follows.
| Question | Advisor's phone, one tap | Installed sensor or microphone |
|---|---|---|
| Hardware to buy and maintain | None | Per counter, per store |
| Start and end of a conversation | Explicit | Inferred from continuous audio |
| Overlapping conversations | One per recording | Must be separated by software |
| Consent basis | Taken in the conversation, evidenced | Signage only |
| Works outside the store (home visits, events) | Yes | No |
| Depends on advisor adoption | Yes, and non-recording is visible | No |
Phone capture wins on cost, consent and audio quality, and loses only on the adoption question, which is answered by making non-recording visible: the advisor who captured nothing is a named row on the coverage report before the store opens.
What it measures
- Capture rate. Consented conversations recorded per advisor per day, against footfall.
- Playbook adherence. Each scored step, per conversation, per advisor, per store, trended over time.
- Intent. A buying-intent score for every customer who shared a number, so follow-up is prioritised.
- Market signal. Competitors named against which model, objections by city and week, stated budgets, unmet demand.
- Follow-up discipline. Whether the agreed follow-up happened on the agreed date.
- Conversion on captured leads. The number that ties the rest to revenue.
Who buys it
Any business where the decision is made in a face-to-face conversation with a trained advisor: automobile dealerships, telecom stores, consumer durables and electronics, furniture and mattresses, jewellery, real estate, and education counselling. The common thread is a high-value, considered purchase and a walk-in that leaves no data behind.
What drives the cost
Pricing is almost always per store per year, with a paid pilot first. Underneath, two costs dominate: speech recognition per minute of audio and AI analysis per conversation. Both have fallen sharply and keep falling, which is why scoring every conversation rather than a sample became affordable in the last two years. Beware of quotes that hide hardware, installation or per-user app fees.
Questions to ask any vendor
- Show me the transcript lines behind one score. If every number cannot be traced to the conversation, the scoring is a black box.
- Play me a Hinglish showroom recording and its transcript. Not a demo file; a noisy one.
- What happens to the audio, and when is it deleted? Ask for the timestamp.
- How is consent taken, and where is the evidence stored for a DPDP audit?
- What happens when the store has no network?
- Can the playbook be ours, per vertical and per store type, or is it a fixed rubric?
- Which of your claims are live today and which are on the roadmap?
Related reading
- Sales interaction monitoring in retail: mystery shopping, floor walks, CCTV and conversation intelligence compared.
- Best retail conversation intelligence tools in India: which platforms are built for the floor.
- Borentis vs Gong: the retail floor versus the sales call.
Frequently asked questions
What is in-store conversation intelligence?
Software that captures the face-to-face conversation between a customer and a sales advisor on a physical shop floor, transcribes it, and scores it against the retailer's sales playbook. The output is a lead, a score for the advisor, market signal (competitors, objections, budget) and coaching evidence, for every conversation rather than a sample.
How is it different from conversation intelligence tools like Gong?
Call conversation intelligence works on digital audio: phone, Zoom, dialer. In-store conversation intelligence has to capture speech in a noisy showroom, in code-switched Indian languages, with in-person consent, often with no network. The analysis is also different: a store visit is scored on floor behaviours such as the demo, the offer and asking for the number, not on talk ratio and call length.
Does it need microphones installed in the store?
No. The advisor's own phone is the device: one tap to start, one tap to stop. Installed sensors and always-on microphones exist as an alternative, but they capture overlapping conversations, have no clear start and end, and rest on signage-only consent, which is a weaker legal footing in India.
Is it legal in India?
Yes, with notice and consent. Under the Digital Personal Data Protection Act the retailer is the Data Fiduciary and must give notice and obtain consent for the stated purpose. The cleanest design takes consent before capture starts, deletes the audio after transcription, and retains the transcript only for an agreed window.
What does it cost?
Most vendors price per store per year. The two largest cost drivers are speech recognition and per-conversation AI analysis, both of which fall every year. Expect a paid pilot of eight to twelve weeks before any network-wide contract.
Where Borentis applies this
- Playbook Adherence: Your playbook, finally observed.
- Execution Scorecards: See the floor before the P&L does.
- Walk-in Recovery: The customer who left is still yours.
Borentis is in-store conversation intelligence built for Indian retail floors: one-tap, offline-first capture on the advisor's phone, Hinglish-ready transcription, playbook scoring with an evidence trail behind every number, leads created automatically, and audio deleted after transcription.