Figure out what users want, fast.
Chat with software reviews to understand what users like, what bothers them, and what they're looking for in a product.
- 180,000+ SaaS products analyzed
- Access to more than 5 million reviews
- 10x faster than doing interviews
7-day free trial. Cancel anytime.
Battle-tested by Indie hackers
As seen on
A better way to do research
Reviewradar thoroughly analyzes SaaS reviews to tell you EXACTLY what users like or dislike. Start right off the bat, no prep work needed.
before
Conventional methods
- Tedious and time-consuming
- Need to find participants for surveys or interviews
- Extremely difficult to scale
- Only partially relevant to your needs (e.g. industry reports)
- Hard to accurately assess nuances
after
Review analysis
- Rapid insights at the click of a button
- Talk to users without actually talking to users
- 5 million reviews right at your fingertips
- 100% tailored to your specific needs and requirements
- Built-in sentiment analysis
“Very interesting tool! Research usually ranks low on most people’s popularity scale, but this makes it far more manageable.It’s fast, efficient, and saves you from the tedious task of sifting through endless resources.”
How it works
Reviewradar is a simple RAG-chatbot designed to deliver review-based insights about customer preferences and expectations. Ask questions, gather intel, and ship faster.
1 • Inquiry
Ask any question
Tell the LLM what’s on your mind. For best results, ask questions that mention specific products (e.g. competitors), explain what problem you are trying to solve and highlight specific features or use cases you are particularly interested in. Add as much details as you wish.
2 • Context
We'll find the best reviews
Reviewradar utilizes a state-of-the-art vector database to semantically search through a vast amount of feedback to identify the best, most insightful reviews for analysis. Integrating this context is crucial for delivering valuable insights into user expectations and preferences.
3 • Insights
Your fast track towards product-market fit
Our LLM then analyzes the most relevant reviews and starts spitting out tons of useful insights in a matter of seconds. Get a detailed breakdown of what users mentioned in the reviews, and effectively research what your target audience wants and how they use similar products.
Join for FREE
Test Reviewradar free for 7 days. If you subscribe to an annual plan you’ll get 4 months for free!
Hell yeah“Love the fact that this includes direct references to reviews! We've primarily used it to monitor our competitors and get a clearer picture of which features are highly praised and which ones receive criticism.”
Take a look inside
Watch the 5-minute on-demand demo to get a better feeling of how this works and whether Reviewradar is right for you.
“We’ve been using this daily for quick sanity checks and to assess feasibility of various product ideas. It’s been incredibly effective and significantly faster than manual desk research.”
Pricing
Pick the right plan for you
Pick the plan that’s right for you and start your free 7-day trial. Cancel anytime.
Battle-tested by Indie hackers
LITE
$12$139 per yearper month
If you're just getting started.
- Unlimited chats
- Query 5 million SaaS reviews
- 100 message credits per month
PRO
$19$219 per yearper month
Most bang for your buck.
- Unlimited chats
- Query 5 million SaaS reviews
- 500 message credits per month
ULTIMATE
$32$392 per yearper month
If you want to go absolutely bonkers.
- Unlimited chats
- Query 5 million SaaS reviews
- 1000 message credits per month
“After discovering that reviews contain a whole lot of useful information, this has been my go-to source for gathering intel about users and what feedback they’ve given on comparable products.”
Frequently asked questions
Can't find the answer you are looking for?Drop us a message at: [email protected]
Who is this for?
Reviewradar was primarily built for independent software developers and product managers at tech startups who want to gain a deeper understanding of their competitive landscape as well as their customers' needs and preferences.
How does this work?
Once you submit your prompt, we will embed your query and ship it off to our database to fetch the most relevant reviews (semantic search). These reviews are then injected into the conversation as hidden context and serve as the main subject for the bot’s analysis. Furthermore we instruct the model to take the findings from the reviews and explore it’s ‘latent space’ to unearth even more profound insights.
How is this different from ChatGPT?
ChatGPT lacks context from software reviews. While it undoubtedly has incredible out-of-the-box capabilities already, knowing what customers have expressed about particular software products is vital to enhance its market research abilities.
What kind of questions can I ask?
As long as it is broadly related to software review analysis, there is really no limit to the type of questions you can ask. We put guardrails onto the model to not engage in tasks that aren’t related to its mission but apart from that there’s aren’t any limits to particular types of question you can ask.
We’ve seen the best and most insightful results when you mention a specific product (e.g. a competitor), or a particular type of software (e.g. CRM tools) along with a somewhat clear objective.
We’ve seen the best and most insightful results when you mention a specific product (e.g. a competitor), or a particular type of software (e.g. CRM tools) along with a somewhat clear objective.
How do I get access?
Enter your email and subscribe to one of our plans. We offer a 7-day free trial.
Does it work for physical products as well?
No. Our database only consists of SaaS products to keep the focus on this particular use case. While general capabilities of the model would certainly allow for a broader application of this research methodology, we decided to narrow its focus on SaaS to achieve the best possible results in this niche.
How much does it cost?
Each plan will give you a certain number of monthly message credits. Each response from the model will deduct one of these credits. It is important to note that only messages from Reviewradar are counted here. In a nutshell think of these message credits as a number of responses you get back from the model.