Why We Don't Buy Reviews (And Why You Should Care)

The Uncomfortable Truth About Online Reviews

There is a multi-billion pound industry built around fake reviews. Research from the Competition and Markets Authority (CMA) estimates that 15-30% of online reviews across major platforms are fabricated. For SaaS products specifically, the problem is worse.

Here is how it works. A company pays a review agency between $5 and $50 per review. The agency distributes the request to freelancers who create accounts on Trustpilot, G2, Capterra, or Google Reviews. They write plausible five-star reviews that read like genuine customer feedback. Some agencies even rotate IP addresses and stagger posting dates to avoid detection.

We know this because we were pitched by three of these agencies within our first month of launching Aditya Labs.

We said no. Here is why.

The Business Case for Fake Reviews Is Real

Let us be honest: fake reviews work. A Harvard Business School study found that a one-star increase on Yelp leads to a 5-9% increase in revenue for restaurants. Similar effects have been observed across industries.

For a new SaaS product like ours, the pressure is intense. You launch with zero reviews. Potential customers see an empty Trustpilot page and think either "nobody uses this" or "they are too new to trust." Meanwhile, competitors with 500 five-star reviews (some bought, some earned) dominate the comparison pages.

The temptation to buy even 20 or 30 "seed" reviews to get the ball rolling is enormous. Every growth playbook on the internet suggests it. Some even frame it as standard practice.

We still said no.

Why We Refuse

### 1. It Contradicts Everything We Claim to Be

Our entire product is built on the promise that we are honest about what AI can and cannot do. Our methodology page lists six things we explicitly do not do. The first item is: "We never fabricate case studies or testimonials."

Buying reviews would make that statement a lie. And once you compromise on one integrity claim, every other claim becomes suspect. If we bought reviews, why would you believe our performance metrics? Our ROI projections? Our data sources?

Trust is not a feature you can bolt on. It is either in the foundation or it is not.

### 2. Fake Reviews Are Detectable (And Getting Easier to Spot)

Trustpilot uses machine learning to identify suspicious review patterns. Google has removed tens of millions of fake reviews since 2022. The CMA has taken enforcement action against companies for fake reviews under consumer protection law.

But more importantly, your customers are getting smarter. A study by BrightLocal found that 62% of consumers believe they have seen a fake review in the past year, and 44% say they can usually tell when a review is not genuine. The hallmarks are recognisable: vague praise, no specific details, suspiciously similar language across reviews.

If a sceptical law firm partner or dental practice owner lands on our Trustpilot page and sees 50 generic five-star reviews from accounts created last month, they will not think "this product must be good." They will think "this company buys reviews." And they will close the tab.

### 3. It Creates a Dependency

Once you start buying reviews, you cannot stop. Your review count becomes artificially inflated. Your average rating is artificially high. Any real negative review has an outsized impact because it contrasts with the bought ones. So you buy more to dilute it. The cycle continues.

We would rather have 5 genuine reviews averaging 4.2 stars than 200 fake reviews averaging 4.9 stars. The 4.2 is believable. The 4.9 is not.

What We Do Instead

Since we cannot ethically manufacture social proof, we fill the gap with what we call **technical proof** — verifiable evidence that does not require you to trust anonymous strangers on the internet.

### Sourced Statistics

Every number on our website links to its original research. When we say dental practices miss 30-35% of inbound calls, we cite Weave and Dental Intelligence. When we mention response time impact on conversion, we cite the MIT/InsideSales.com lead response study. You can check every claim yourself.

### Transparent Methodology

Our [methodology page](/methodology) explains how we build, test, and deploy AI agents. It also explains how we source and verify statistics, including our automated staleness detection that flags any data point not re-verified within six months.

### Public Roadmap

Our [transparency page](/transparency) shows exactly where we are today. Which features are live, which are in development, and which are planned. We do not hide behind vague "coming soon" promises.

### Confidence Levels

We label our data with confidence indicators. If a statistic comes from a peer-reviewed study, it gets a "high" confidence tag. If it is based on our projections or limited data, we say so clearly.

### The AI Identifies Itself

Our website chat agent opens with: "I am Aditya, an AI assistant (not a human) for Aditya Labs." We do not pretend our AI is a person. We do not use deceptive language to blur the line. This is not just ethical practice — it is a legal requirement under the EU AI Act Article 50.

The Long Game

We are a new company. We have zero Trustpilot reviews as of this writing. That is uncomfortable. Every week we get emails from review agencies offering to fix that for $500 to $2,000.

But here is our calculation: we are building a product for industries where trust matters enormously. Dental practices trust us with patient data. Law firms trust us with confidential enquiries. Healthcare providers trust us with sensitive information.

These are not impulse purchases. The people evaluating our product are professionals who do due diligence. They will find this blog post. They will check our claims. They will notice if our reviews look manufactured.

We would rather earn trust slowly than manufacture it quickly.

What You Can Do

If you are evaluating AI agent platforms, here are three things to check beyond the star rating:

If you have used Aditya Labs and want to leave an honest review — positive or negative — we would genuinely appreciate it. We do not offer incentives, discounts, or gifts for reviews. We just ask that you share your real experience.

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