The modern world seems really fast and dynamic with a multitude of new products being launched. Marketing agencies are making fortune by monitoring the markets and delivering reports on consumers’ opinions. For today, the feedback analysis is a separate area, let’s say a growing industry with an array of products and services. And the prices for those services are pretty exorbitant.
So, do vendors have a chance to cut down expenses?
Without any doubts, there’s always an opportunity to start personal volcanic activities on feedback collection and analysis. Opinion-polls, online surveys – we all know how it works…
However, in this case let’s bring to notice one unengaged resource. As a rule, all the products are being discussed in social networks. People post photos of their purchases, share impressions and exchange views by making written comments. This information is highly valuable, as it is:
R11; relatively unbiased;
– free and open to public.
How can vendors use this resource in an effective way?
The challenge is somewhat complicated, but possible to respond to. In any case, the vendor is to mull over obtaining a personal app to analyze the feedback or integrate some new tools into the existing CRM thanks to some smart e-commerce solutions.
So, what is the procedure of managing and analyzing data?
1. Information aggregation
In the first place, it’s a must to put all the opinions, comments and mentions into one data base. Here we need help of such tools as Twitter API, Facebook API, and Instagram API. Thanks to these social networks, third party apps have always had access to public information and a free search. All in all, there’s always a search engines API that is able to make a list of web pages that mention the product or service we need.
2. Sentiment analysis
The information collection is just an initial step. This info should be thoroughly analyzed by defining assessments. In computer linguistics this process can be named Sentiments. The system we need to create has to seek emotional judgments that will be kind of triggers for an analytic system.
A great piece of news is that here we’ll avoid creating artificial intelligence. It will be enough to use the existing cloud solutions in the computer linguistics sphere. To cite an example, we can see available solutions from such giants as IBM (Alchemy), Microsoft (Cognitive Services), and Google (Natural Language API). Sometimes, it seems reasonable to think over less ambitious providers that also feature a sentiment analyzer.
What’s the process of analyzing the stored information?
Here we need a theoretical explanation. First of all, a linguistic API allows getting opinion objects. In fact, these are objects or some object component parts that are commented and discussed by people. Component parts are of a particular interest. As for mobiles, a sentiment analyzer lets compose such a list:
– body frame;
– ergonomic aspects;
– UI, etc.
As you can see, these are evaluation categories and topics touched by users. This info is accompanied with sentiments values, forming positive and negative reviews. So, the vendor is granted a possibility to evaluate the degree and frequency of people’s emotionality, let it be positive or negative comments on one or another object in focus.
But for vendors, assessment phrases are of avid interest, i.e. they want to know what exactly people write about one or another assessment object. The Sentiment analyzer divides all the assessment phrases into positive and negative ones, that’s why the vendor sees the exact pros and cons of his/her product. In regards to mobiles assessment, phrases can be the following:
The stored data should be compiled into updatable reports. Vendors will be interested in tracking opinion changes with the course of time. Furthermore, fresh info is also needed during the new product launch, advertising campaigns or special offers.
Thus, the abovementioned programs/apps and their tools are perfect for analyzing users’ opinions and reviews and detecting product/service advantages and disadvantages. Moreover, their usage seems more comfortable, effective, and cost-efficient compared with the process of recruiting a third party company for tracking product mentions and reporting users’ feedback.
About the author:
Yana Yelina is a website design and development expert at EffectiveSoft, a custom software development company with 250+ specialists who boast expertise in different business domains. You can reach the author at: [email protected]