Most social listening tools were built for a communications team. They answer questions a CMO asks once a quarter: what's our share of voice, is sentiment up, are we trending anywhere we shouldn't be.
An ad team needs something narrower and more useful: the sentences people actually use, sorted by the objection they contain, close enough to hand to a copywriter on Monday.
Same raw material, completely different output. This guide sorts the tools by which of those two jobs they're really built for, and shows what listening looks like once it reaches the ad.
What an ad team needs from listening
| Requirement | Why | Most tools |
|---|---|---|
| Verbatims, not summaries | "Sentiment is 62% positive" writes no hooks | Lead with dashboards |
| Comments on ads — yours and rivals' | The objection is stated where the buying happens | Rarely covered |
| Review platforms that matter locally | Play Store, Google Maps, Amazon, Flipkart | Patchy outside the West |
| Indian-language and Hinglish handling | Half the useful comments aren't in English | Frequently poor |
| Grouping by objection, not topic | "Price" is a topic; "will it work on my skin" is a brief | Topic clustering only |
| A path to the creative | Listening that ends in a PDF changes nothing | Ends in a report |
Read that column on the right before you buy. Most of the market is excellent at the thing you don't need.
The categories
| Category | Examples | Built for | Ad-team fit |
|---|---|---|---|
| Enterprise suites | Brandwatch, Sprinklr, Meltwater, Talkwalker | Brand health, crisis, PR measurement | Powerful, slow, priced for a comms budget |
| Mid-market monitors | Brand24, Mention, Hootsuite | Mentions and alerts for smaller teams | Good value, thin on review platforms |
| India-focused CX platforms | Konnect Insights, Locobuzz | Omnichannel support plus listening | Strong on Indian channels and languages |
| Review and app-store miners | App-store analytics tools | Product feedback | Narrow, but the highest-intent language |
| Ad-native listening | Marxx | Turning comments into personas and hooks | Purpose-built for creative, not for PR |
Nobody needs all five. The question is whether your bottleneck is knowing what people say about the brand or knowing what to put in the next ad.
What listening looks like when it reaches the ad
Here's the test: can you tell, from the creative alone, that someone read the comments? These eleven ads pass it, and the run lengths tell you which kinds of listening pay off hardest.
Start with the most literal version of the idea — printing the sceptic's comment instead of arguing with it.
Is this just a trendy online gut fix? Or it really works? That is not a brand's sentence. The grammar is wrong in exactly the way a real comment's grammar is wrong, and leaving it unfixed is the whole point. It ran 4 days with three near-identical copies running alongside it — a brand testing the same harvested objection three ways at once, which is what you do when you believe the sentence rather than the execution.
Then the version that borrows the words, not the sentence.
No white cast. No jhanjhat. Two complaints lifted from sunscreen reviews, one in English and one not, and it ran 17 days — four times the Two Brothers run. "Jhanjhat" is the line worth studying in this entire post: it does not survive translation into a report, it cannot be produced by a sentiment model, and it is precisely the word that makes the ad feel like it came from someone who has actually worn sunscreen through an Indian summer. A dashboard would have logged this as "negative sentiment, texture".
The third pattern is harder and rarer: saying the thing customers imply but never write.
You stopped buying chips for your kids — but the aloo in tonight's sabzi came off the same chemically grown farm. Ran 9 days. No customer has ever typed that sentence. It's assembled from two separate things they do say: that packaged snacks are poison, and that home food is safe. Listening gets you the raw material; someone still has to notice the contradiction between two buckets.
Back to verbatim, in a category where the question arrives by DM.
Is there really no way to hide stretch marks once I have them? Ran 10 days, and the platform classifies its own format as a social-comments ad — the brand isn't imitating the look of a comment, it's using one. The discount, 35% plus 20%, sits well below the question. Hook first, offer later.
A myth-versus-fact card on whether your fruit is actually clean after one wash. Ran 6 days. This is what an FAQ becomes when one question gets asked so often it stops being support and becomes positioning. The format is dull; the selection is the work.
Astrotalk's chat screenshots, used as the proof itself. Ran 3 days in this execution — but the pattern is where the brand lives, and the next ad shows why.
The same mechanism in Kannada, with a crucial difference: the comment it screenshots is a sceptic challenging the service, answered with a specific prediction. It ran 34 days — more than ten times the previous execution, with siblings at 34 and 30 days. That is the clearest finding in this post. Harvesting praise got them 3 days. Harvesting doubt, and answering it in the comment thread itself, got them a month.
The lesson generalises, and a UK lender proves it twice in the same quarter.
Scared to check funding eligibility in case it damages my credit score — is this a real risk? Ran 13 days. One objection, in the customer's voice, with the answer as the headline.
The same objection, reworded — worried applying for business funding will trash my credit score — is this true? — and this one is still running, live 19 days. Two ads, one fear, both long-lived. That is what "count the repeats" looks like once it reaches production: the sentence got said enough times that the brand built two ads out of it rather than one, and both are outliving its offer creative.
Praise is worth harvesting too, as long as you pick the strange compliment rather than the flattering one.
A customer telling Bombay Shaving Company it should charge more, because the product is that good. Ran 11 days. No brand would write this line about itself without sounding insufferable. In a customer's mouth it handles the price objection and the quality objection simultaneously, which is why you keep a "praise" bucket at all.
And the channel most Indian brands under-mine entirely.
A Reddit thread — can one person ship a SaaS product solo, without really coding — screenshotted and used as the hook. Ran 20 days. Reddit and Quora are where the real comparison happens between strangers with nothing to sell, which makes them the highest-quality language available and the least used.
Eleven ads, and the pattern across them is not sentiment. Each is one sentence a real person wrote, promoted to the hook — and the ones that lasted longest were the ones built on doubt rather than praise: 34 days on a sceptic's challenge, 19 and 13 on a credit-score fear, against 3 days on a wall of happy screenshots. A share-of-voice dashboard will never produce any of them.
The channels that matter in India
Western tool coverage skews to X, Reddit and news. For an Indian consumer brand the ranked list looks different:
| Channel | What you get |
|---|---|
| Comments on your ads and rivals' | Objections at the point of purchase, in the platform's own language |
| Play Store and App Store reviews | Churn reasons and feature requests, dated and versioned |
| Google Maps reviews | Location-level complaints, invaluable for anything with outlets |
| Instagram and YouTube comments | Hinglish, slang, and the words people use for the category |
| Amazon and Flipkart reviews | Purchase-stage doubts, often more specific than your own site's |
| Reddit and Quora | Long-form advice between strangers, where the real comparison happens |
| WhatsApp and DMs | The highest-intent questions, and the hardest to mine at scale |
Ask any vendor which of these they actually index for India, and how they handle Hinglish. The answers vary far more than the marketing pages suggest.
Ten questions for the demo
- Show me raw verbatims, not a sentiment score.
- Do you index comments on ads, including competitors' ads?
- Which Indian review platforms do you cover, and how fresh is the data?
- How do you handle Hinglish and transliterated text?
- Can I group by objection rather than by topic?
- Can I filter to one product, one city, one time window?
- What's the export — can a copywriter use it without you?
- How do findings reach a brief or a creative?
- What's the per-seat versus per-workspace pricing at my team size?
- What happens to my data, and can I delete it?
Question five is the sorting hat. Topic clustering gives you "price, delivery, quality". Objection clustering gives you "too expensive for a trial size", "arrived leaking", "didn't work on oily skin" — three different ads.
How to run listening without buying anything yet
- Pull 200–300 comments from your last month of ads, plus your two closest rivals'.
- Add your Play Store and Google reviews, one-star and five-star first.
- Sort into four buckets: pain points, questions, feature requests, praise.
- Keep the exact words. No cleaning up, no translating the Hinglish.
- Count repeats. Anything said three times is a hook; anything said ten times is a campaign.
- Start with the doubts, not the compliments. On the evidence above, the sceptic's sentence outran the happy screenshots by a factor of ten.
- Write three ads from the three most repeated sentences, and run them against your current control.
If that produces a winner, you've learned what to buy a tool for. If it doesn't, no tool would have saved you.
Where Marxx fits
Marxx isn't a PR listening suite and doesn't try to be. It reads the channels in the table above — comments under your ads and your competitors' ads, App Store and Play Store reviews, Google and review-site feedback, the subreddits your category lives in, your own site — and turns them into personas rather than dashboards.
Each persona is built from what people wrote, and every line stays traceable to the comment it came from. Nothing is invented from a demographic description. The buckets are the four above, and the output is meant to be briefed from: pain points become hooks, FAQs become objection handling, praise becomes proof, feature requests become the next angle.
Then the persona goes to the production canvas and becomes an ad, which is the step most listening tools leave to you.
Demo: personas built from your own reviews and ad comments
Bring your ad account and one review link. On a 30-minute call we'll pull comments from your ads and your competitors', mine your app and Google reviews, and build two personas from what's actually written there — each with the verbatim quotes behind it.
Book a demo, or see how the creative intelligence layer decodes what your category is already saying.
FAQs
What are the best social listening tools in 2026?
For brand health and PR, the enterprise suites — Brandwatch, Sprinklr, Meltwater, Talkwalker. For smaller teams, Brand24 or Mention. For Indian omnichannel coverage, platforms like Konnect Insights and Locobuzz. For turning comments into ad creative, an ad-native tool is a better fit than any of them.
What's the difference between social listening and social monitoring?
Monitoring tracks mentions and alerts you. Listening looks for patterns across them. For an ad team, the useful version is narrower still: collecting the exact sentences that reveal an objection.
Can social listening tools read comments on Facebook and Instagram ads?
Some can, many can't — and it's the single most valuable source for a performance team, because the objection is written at the point of purchase. Ask specifically, and ask whether competitors' ads are included.
Do these tools work for Hinglish and Indian languages?
Coverage varies sharply. Sentiment models trained on English often misread transliterated Hindi entirely. If your comments are Hinglish, test the tool on your own last month of comments before signing anything — and note that the longest-running ad in this post is in Kannada, which most Western tools will not read at all.
How much do social listening tools cost?
Enterprise suites are typically annual contracts priced for a comms budget; mid-market monitors start far lower on a monthly plan. Published pricing moves constantly, so treat any figure you read as a shape and ask for a quote at your volume.
Which comments are worth turning into ads?
The doubts first. Across the eleven ads above, the executions built on a sceptic's challenge or a specific fear ran 34, 19 and 13 days; the one built on a wall of positive screenshots ran 3. Objections are more durable than praise because they keep being held by people who haven't seen the answer yet.
How do I turn listening into ads?
Sort verbatims into pain points, questions, feature requests and praise; count repeats; promote the most repeated sentence to a hook, keeping the customer's exact words — including the ones that don't translate. The eleven ads above are what that looks like when it's done properly.
Sources: Brand24's tool comparison, Meltwater's 2026 list, Konnect Insights on enterprise listening