A home appliances retailer in Pune posts photos of new stock every evening around 7 PM, right when people are scrolling on the way home. Some evenings it works too well: forty comments in under an hour, half of them "price?" and "available in white?", and by the time the store manager clears the counter and opens Instagram the next morning, most of that interest has already cooled.
Nobody on staff is idle. The manager answers what's in front of them, usually whichever comment came in loudest or most recently, not the one from the person who typed their pin code and asked about delivery. Because the reply queue and the buying queue aren't the same thing, the store spends real attention on comments and still loses the customer who was closest to actually paying.
This is the actual argument for combining AI with social media, not the vaguer "be more active online" advice most SMEs have already tried and shelved. AI on the social side does one narrow job well: it reads intent the moment a comment lands. Comments that mention price, location, or availability get an instant, relevant reply; ambiguous ones get flagged for a person instead of buried under the next fifty. LinkedIn alone already carries roughly 80% of B2B social leads industry-wide, and businesses layering AI qualification on top of that traffic report meaningfully higher conversion, not from posting more, from replying faster to the posts they already make.
Where the lead actually gets lost
The same shift matters even more on WhatsApp, which carries more weight in India than almost anywhere else. Over 500 million people here already have the app open, and Meta's own AI-assisted business tools for it launched this year aimed specifically at small businesses, not enterprise accounts. That's the same channel a customer already uses to message their tailor or their electrician, now able to answer a stock question at 11 PM without anyone awake to type it.
None of this works on its own. Bolt AI onto a page with no clear sense of who actually buys, and it just replies faster to the wrong people, which is arguably worse than replying slowly to everyone, since a fast, generic answer can read as more dismissive than no answer at all. The Pune retailer had to sit down first and write out, in plain language, what "ready to buy" meant for that store: in stock, deliverable to the customer's area, asking something specific rather than just typing a heart emoji. That list took an afternoon, not a developer, and every automation rule after it just pointed back to those same three lines. Only once that was written down did the automation have something worth acting on.
Getting the sequence right
The Pune page didn't grow much that month. Its reply time did, from close to a day down to under ten minutes, and that's the number that actually moved sales. If a comment section looks busy but the sales calendar doesn't match it, that ten-minute gap is the place to look first, before spending anything on more posts or a bigger ad budget.