frequent1y @sked questi0ns

What is TheReviewIndex all about?

TheReviewIndex is an independent site that aspires to simplify online shopping, by organizing and summarizing user reviews from various online sources. All user reviews, from across sources, are summarized and presented as an unbiased, feature-wise summary to make reading reviews more efficient. Not just that, you can also use the search engine to discover products based on your specific feature requirements. Lastly, the engine compares the prices for products across all the online stores, to help determine the most cost effective offering.

How does it work?

We crawl various sources on the internet, aggregate and reconcile user reviews for products. Leveraging machine learning algorithms, we detect fine-grained topics and implicit sentiment, after blacklisting potentially fraudulant content. This information is churned and presented as an unbiased, feature-wise summary scorecard of the aggregate opinion, along with the relevant pros and cons. A search engine sits on top of this insights layer, enabling discovery based on specific feature requirements.

Where does TheReviewIndex get the data?

TheReviewIndex requires data such as product catalogs, reviews, specifications, etc. We crawl and aggregate all available information from across various public webpages. This data is then churned to get presentable insights.

How do you calculate the overall product rating?

First, a score is computed for each feature (e.g battery, display, etc) of the product by taking into account factors such as - volume of opinion, split of positive vs negative opinion, strength of sentiment, etc - and stack ranking them against all other products in the category. Then, all the individual feature scores are combined, giving due importance to critical features, to get the overall rating. This rating is converted to a percentile view and presented.

I noticed some discrepencies in the data quality? What do I do?

We use machine learning algorithms to perform activities such as detecting topics of discussion and sentiment in review sentences. It is possible that there will be a few cases of incorrect classification.
Having said that, we constantly monitor the quality of algorithms and data to maximize accuracy and ensure that these outliers do not influence the eventual outcome or recommendation.
After taking above points into consideration, if you still think that there are large discrepencies, you can provide feedback using the link provided in the site or write to us at with the details and we will take these inputs into consideration while tweaking our algorithms.

How can I trust TheReviewIndex? How do I know that the evaluation is fair?

We have deliberated over this question from the very beginning. Since building and keeping trust with you is very important to us, we have designed the product to ensure that every recommendation is strongly supported by solid evidence, in case you choose to drill deeper. If you choose to, you can drill down and read all individual user comments that contributes toward the score of each feature. Not just that, all these comments are properly attributed and linked back to the origin.

How does the site make money?

We make money via affiliate partnerships with online stores where payout is a percentage of the sale value to the referring site. This means that every time a visitor uses our site to research and decide on a product and then goes on to purchase the item from any of our partner ecommerce stores (by clicking on the links provided on our site), we make a small commission of the sale value. This doesn’t at all change the price the user pays.

Why is XYZ product missing?

We try to keep the site as updated as possible. But sometimes due to various reasons, in rare situations, some products can be missing in our database. If you notice a product missing, please drop a note to and we’ll try our best to rectify!

You do not have the category that I am looking for. What do I do?

We will soon expand to include all major electronic and appliance categories. If you do not want to wait, shoot out a request at Who knows, maybe we will be able to prioritize your request.

How do you deal with review spam?

One of the major concerns of online opinions is the problem of spam and incentivized reviews. Although, a single spammy review does not receive too much importance (since we rely on mass opinion for making our judgements), several spammy reviews can be misleading, often drowning actual user opinion.

We think that spam, much like any other crime, will leave behind a trail. This is true especially when spamming is done at scale. We try to identify these and in the spirit of transparency (like rest of the site), we are starting to expose the underlying data points that contributed to our decision.

Right now we expose only a couple of signals out, but we will be rolling out a more comprehensive set of signals in the near future.


Have more questions? Send them out to and we will revert as soon as possible.