Comparing Uber and Lyft Using Google’s Sentiment Analysis API

In this competitive world, competition is seen in almost every field. So as the cab services. Uber and Lyft are the leading competitors in the ridesharing industry in the US market. These two companies are offering their best in order to attract users, then retain the existing customers and then to gain their loyalty.

Evaluating the services of both these companies will let us know how Uber and Lyft users are feeling about the respective brands. For this, one need not perform a lengthy survey rather one can adopt some simple ways to check out the things.

You must be waiting to know what would be that simple way to know and compare various parameters of two different companies. Google has provided a simple way of finding these with the help of its Sentiment analysis API. With the help of this Google’s sentiment analysis API, user’s view can be collected via a single API call. Now, let us know more about it

Analysis of API Result
The first factor which is taken into consideration is the uber app and lyft app reviews from iTunes as both the ridesharing companies are operating via mobile app, so it would be viable to consider the reviews and based on that a sentiment value is assigned for each. Also, the best part of this API is that it is not purely based on star rating, but it is based on the actual content of the review.
In comparison with Uber, Lyft has got better ratings and reviews. Uber ratings count for about 2.7 on a scale of 5, and the graph of Uber is slightly falling overtime on the basis of small sample survey. On the other hand, Lyft’s ratings were stable over the last five hundred users and its graph is stable without any inclination. Even it is interesting to note that the Uber’s highest score across the 500 recent reviews was in a match with the Lyft’s lowest average score during the same period.

Next, to app reviews, Twitters was chosen to be basic for evaluation for two reasons, of which the first one is it allows more number of data points than iTunes and secondly, Twitter is known for business communications when any issues are there with them. These two reasons may it’s a viable source to extract more accurate analysis.
Based on 8000 tweets published on this platform @uber and @lyft hashtags, the results were almost struggling for both the companies. And these two companies were witnessing decreased scores over a period of time and this may account for the following reasons

• Recent app releases had some bugs or a sluggish app performance which has an impact on brand reputation
• Issues of unsatisfied customers were not met completely.

Putting in simple words, Lyft is getting better reviews than the uber. But it is interesting to note that Uber is running more profitable than Lyft right now. But the Lyft owing to its better review may captivate in the long run. That is why the number of customers migrating to this ridesharing company is on raise.
Another noticeable thing about Google Sentiment API is that internationally operating businesses always keep a watch on happening trends across the world which helps sentiment analysis as per country-specific breakdowns.
In terms of country-specific analysis, Lyft which operates via collaboration with local ridesharing agencies is having an upper hand over Uber. Lyft data is collected from its major occupancy countries, i.e., US and Singapore, whereas Uber’s data is collected from India and Singapore.

Technical Analysis

The above results were found interesting, now let us know how the analysis of these
API supports the following three kinds of analysis of text

• Entities
• Syntax
• Sentiment

1. Entities
The entities API documentation provides the following description
Named entities in text, saliences, entity types, mentions in each entity, and other such properties
This will helps in understanding the capabilities and also it clearly identifies all the entities in the statement. It also links to Wikipedia articles.
2. Syntax
This allows a deeper understanding of the contextual information. This will help in understanding the document and provides a full set of annotations like syntactic, semantic and sentiment information.
For example, if any text statement is provided, then it’s deeper understanding not leaving grammar part also. It checks for each and every minute thing for providing a deeper understanding of it.
3. Sentiment Analysis
Sentiment analysis is very powerful and API can deduce it from the arbitrary text. API is by nature is a straight forward one.
Applying this to the Uber and/or Lyft reviews, it takes into account not just the rating or review texts, but it provides a deeper understanding of the reviews or the rating provided based on various parameters like country, reviews given on various platforms, etc.
For analysing the data, the reviews from different platforms from their respective links (from their respective country link, rather than just generalizing). This makes it the difference between the analysis of Google Sentiment analysis and App store ratings. The best part of Google sentiment analysis is that it helps in overcoming user’s bias in ratings and the true description of the reviews. It is not just based on any of the single parameters, but is considered the tweets on twitters and other forums for getting the complete analysis.
Valuable sentiment analysis can be obtained by following the below set up
Twitter Stream ---> Google NL API ---> Google BigQuery ---> Google Data Studio
Conclusion:
Above write up provides you with an in-depth understanding of how Google Sentiment Analysis, API operates for finding the capabilities of two famous ridesharing companies, i.e, Uber vs Lyft
The API gives true and accurate information about company executions, by considering the company’s engagement at various geographical locations. Also, it will allow to let users know about the brand perception which is critical for the success of the respective brand.
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