As you can see, all these positive reviews talk about the budget. Yes, this phone has great specs at this price range. If you are looking for a cheap smartphone and don’t mind it being a little slow, this is a great choice.

Some other interesting insights from these reviews:

Some people who have given 4 and 5 star ratings also wrote about cons, which means there are some bad things about the phone which they are ok with, as pros outweigh cons for them.

Few people even suggested other phones which are comparable to this phone.

Essentially, the whole point is, I should be able to know what is good and what is bad about a product before making a purchase decision; because what is bad for others may not necessarily be bad for me; what is good for others may not be a major concern for me. Each individual is different and has different needs. We are shelling out our hard earned money to buy these products. We have a right to take the right decision!

How do we solve this problem?

Solution #1

Tripadvisor asks people to rate hotels on different parameters as shown in this screenshot. So, if I am a traveler who is most bothered about location, I may go ahead with this hotel even if it scores a little less in other areas. This can be replicated for ecommerce sites where people can rate a product on certain pre-defined parameters for that product category. For instance, a mobile phone can be rated on Performance, Battery, Features, Camera, Storage and Value for Money. However, this may not be a scalable solution because of the wide range of products and product categories.

Solution #2

Imagine if we can perform Natural Language Processing (NLP) and pluck out positive stuff from happy customers and negative stuff from unhappy customers and show them on the ratings, it will help us decide what features of the product made people happy and what made them sad.

NLP can not only categorize positive and negative reviews but also detect the level of positivity and negativity in each.

It can also be used to suggest other products and do better cross selling.

One can even explore a different navigation pattern for showing a list of products based on customer preferences. This is particularly useful for people who don’t have a specific product in mind but just have a rough idea of what they want in the product.

It can also be used to create buying guides for cameras, speakers, ACs etc. Obviously, there is so much more that we can do with NLP on customer reviews.

To extend this further, lets say you selected a phone but you want to know more about battery life and heating issues. So, you may want to read reviews of people on these particular attributes of the product to take a call.