The platform for actionable customer feedback in the AI era.
Most companies say they listen to customers. Very few actually read the answers. The open-ended box at the bottom of a survey - the one where someone types what they really think - usually fills up faster than anyone can process it, then sits untouched in a spreadsheet. Zonka Feedback was built for the pile nobody reads.
The company started in 2014 in Gurugram, a satellite city outside Delhi, collecting feedback on tablets propped up at restaurant counters and hospital reception desks. It has spent the years since turning that simple idea - ask the customer, right where they are - into a broad customer-experience platform. Today more than 1,000 businesses run surveys through it, including Samsung, American Express, EY and Swiggy. The team that serves them numbers around 33 people. The venture funding raised to get there is zero.
That combination is the interesting part. Customer-experience software is a category dominated by names that raised hundreds of millions - Qualtrics, Medallia, SurveyMonkey. Zonka Feedback plays in the same field with a bootstrapped balance sheet and a founder who talks openly about building software businesses without outside capital.
At its core, Zonka Feedback is survey software - but the word "survey" undersells it. The platform measures the three metrics that customer-experience teams live by: NPS (would you recommend us?), CSAT (were you satisfied?) and CES (how much effort did that take?). The harder problem it takes on is delivery. A customer will answer a one-tap question inside an app but ignore an email; another will reply to a WhatsApp message but never open a link. So Zonka spreads the same survey across email, SMS, WhatsApp, web, in-app widgets, physical kiosks and offline modes, and meets people wherever they will actually respond.
Once the answers come back, the platform routes them. A poor score can open a case, assign it to a person and track whether anyone followed up. This is the part that turns feedback from a report into an action - the "close the loop" step that most tools leave as an exercise for the reader. Zonka layers reputation management on top, pulling public reviews into the same view, and hangs role-based dashboards over all of it so a support lead and a product manager each see the slice that matters to them.
It helps to be concrete about the three letters everyone in this business throws around. NPS asks one question - how likely are you to recommend us - and sorts people into promoters, passives and detractors. CSAT asks whether a specific interaction landed well, usually right after it happens. CES asks how hard the customer had to work, on the theory that effort predicts churn better than delight. A team running all three learns different things: NPS tracks the relationship over time, CSAT catches the bad Tuesday, CES finds the friction. Zonka's job is to make collecting and comparing them boring and repeatable, so the interesting work - fixing what the numbers expose - is where the human hours go.
In 2024 the company shipped Zonka Feedback 3.0 and rebuilt the platform around AI. The pitch is aimed squarely at that untouched pile of open-ended responses. Instead of a human skimming a few hundred comments and guessing at patterns, the AI layer groups feedback into themes, scores sentiment, tracks which products or features get named, and estimates which issues actually move the numbers. The company's own framing is blunt about the target it is aiming at.
"Not another dashboard" is a pointed line in a category that has sold dashboards for two decades. The bet is that teams are not short on charts; they are short on knowing what to do next. Whether the AI delivers on that consistently is the open question every buyer in this market is now asking - but the direction is clear, and it is where the product is being pushed.
There is a practical reason the timing works. A company running surveys across eight channels ends up with more free-text feedback than a support team can ever read - thousands of sentences a week for a busy brand, most of them never opened. That backlog was a liability when a human had to sort it and is an asset the moment software can. The same volume that made feedback unreadable is exactly what makes the theme-and-sentiment approach worth building. Zonka's advantage is that it already sits on twelve years of that data flow; the AI layer is less a new business than a new way to use the one it has.
The customer list runs across industries: Samsung and Nikon in electronics, American Express and Simpl in finance, EY and BCG in services, Swiggy and Purplle in consumer, plus healthcare providers, retailers and universities. A recurring public example is SmartBuyGlasses, an eyewear retailer that reports raising its NPS by 30% after using the platform to close the loop on customer complaints - the kind of number that gets a case study written.
What ties such different buyers together is less the industry than the shape of the problem. A hospital wants to know if patients felt heard at discharge; a food-delivery app wants to know why a rider got a one-star rating; a bank wants to catch a frustrated cardholder before they call to cancel. Different questions, same mechanic: ask at the right moment, on the channel the person will answer, then get the answer to whoever can act on it before the moment passes. Zonka sells the plumbing for that mechanic, which is why a kiosk in a clinic and an in-app prompt inside a fintech can run on one account.
The model is straightforward B2B SaaS: monthly subscriptions that scale with feedback volume and features. Public pricing puts feedback management in the low hundreds of dollars a month, with the AI intelligence tier running higher, and custom enterprise contracts above that. Distribution comes from three directions - direct sales, a deep bench of 50+ integrations that put Zonka inside tools teams already use, and lifetime deals on marketplaces like AppSumo that seeded the early small-business base.
| Tier | Roughly | For |
|---|---|---|
| Feedback Mgmt | ~$199/mo | Surveys, NPS/CSAT/CES, workflows |
| AI Intelligence | ~$999/mo | Themes, sentiment, impact analysis |
| Enterprise | Custom | Scale, compliance, support |
Figures are approximate and drawn from public pricing; actual costs vary with volume.
The integration list does real work here. Native connections to Salesforce, HubSpot, Intercom and Zendesk mean a survey can fire automatically when a support ticket closes or a deal moves, and the response flows straight back into the CRM. For a small team, being embedded in bigger platforms is how you reach customers you could never sell to directly.
The competitive map is crowded. At the top sit Qualtrics and Medallia, enterprise suites with enterprise price tags. In the middle are SurveyMonkey, Typeform and SurveySparrow. Nearer Zonka's positioning are focused feedback tools like Delighted, Retently and AskNicely. Zonka's claim to a spot is breadth at a mid-market price - omnichannel collection, closed-loop workflows and an AI layer, without the seven-figure commitment the top tier expects. Capterra reviewers have rated it 4.8 out of 5 and flagged it as strong on value, which is the exact ground a bootstrapped challenger wants to hold.
There is also the discipline the funding story imposes. A company that has raised nothing has to be profitable to exist, and profitability tends to keep a product honest - features get built because customers pay for them, not because a board wants a growth chart. Founder and CEO Rajiv Mehta, who has started several companies, is public about preferring that path. Co-founder Sonika Mehta leads product. The compliance posture - ISO 27001, GDPR, HIPAA - is the unglamorous groundwork that lets a 33-person shop sell to a Samsung or an American Express in the first place.
Bootstrapping cuts both ways, and it is worth being honest about the tradeoff. A self-funded team cannot outspend Qualtrics on sales or match Medallia's services army. It wins, when it wins, on price, on breadth of channels, and on being quick to answer a support ticket - the things a small team can do better than a large one, not the things it can do bigger. Public revenue estimates put Zonka in the low millions, which is a rounding error next to the incumbents and a comfortable living for 33 people. Those are two different games, and the company seems clear about which one it is playing.
Strip away the AI branding and the integration count, and Zonka Feedback has been answering one question for twelve years: what are your customers actually telling you, and are you doing anything about it? The tablet at the counter in 2014 and the AI theme engine in 2026 are two answers to the same question. The company's wager is that the answer keeps getting more valuable as the volume of feedback grows past what any human can read - and that a small, self-funded team can keep being the one that reads it.