Step 1: Understand the problem:

1) What type of apps get 5 star rating vs 1 star rating. Are they from specific company or is the difference in the type of the app?

2) Are these apps targeted towards the same user segment e.g. apps with rating 5 are targetted towards self learning vs. apps with rating 1 were gaming apps targeted at millenials

3) Were all these apps launched during the same time?

4) How are these apps classified based on monetization viz. free vs a cost basis

Step 2: Internal and External issues

Internal issues:

1) Differences in the user experience of the app

2) Paid vs Free App. Higher expectations from a paid app

3) Type of app e.g. targeted at an older user segment gets better rating than a younger user segment

4) Total number of ratings- Apps with higher ratings have lot of reviews and hence averages our bad rating

5) Changes in the quality control policies at Google

External Issues:

1) Lot of similar apps in the market leading to high expectations from the user base

2) Change in education and economic demographics due to which the app features are no longer relevant

3) General perceptions type of app e.g. right sided news, conservative news etc.

4) Availability of investments in the market in apps

Step 3- Hypothesis:

1) Older apps benefit from high number of reviews thereby averaging few bad reviews vs newer apps getting skewed with few number of bad reviews

2) Acceptance policies on app stores have changed with focus only on quality of code vs usability of app

Step 4: Action items

1) Do not compute average score for apps < say 1000 reviews. Just show total review and number of 4+ reviews

2) Update App acceptance policies to consider a usability test done by a certified company. These companies use a crowd similar to the targeted user base of the app and provide feedback.

40% of users giving 1 star rating is a big concern and it could be because of issues with basic function of the app. I am assuming that the reviews are genuine. My overall approach would be as follows

1. Understand the scope of the issue / concern:
   1. Is this recent or has been happening for a while.
   2. If there are old negative reviews whose concerns are already addressed, reach out to the impacted users to revisit their rating if they are happy.
   3. If there are issues, check if it is from a particular platform – Android / ioS or desktop etc.,
   4. Any specific geography
   5. Any specific devices / handset

1. Try to understand the root cause contributing to the 1 star rating.
   1. Check if any drop in the internal metrics coincides with the timeline of the 1 star reviews (no of installations, DAU, WAU etc.,)
   2. Check what is the common issue pointed out in these reviews with 1 star rating.
   3. As there are several comments / concerns, try to do word cloud analysis on the comments and list out the common words associated with the negative comments

1. Is a Quick fix possible:
   1. If the issue is recent and if it is caused by any internal factors (any new feature launch, deployments etc.,) – check if it is possible to revert the recent changes and restore the app
   2. Communicate to all impacted users on the resolution
   3. Do a root cause analysis with the engineering team to understand the issue with the recent release and fix it.

1. Categorize the issue and prioritize the concerns based on the impact:
   1. The issue pointed out in the highest number of comments will take the highest priority and so on.
   2. Categorize the issues into functional, UI, perception etc.,

1. Identify solutions and prioritise them based on the impact and effort needed.
   1. Check if the issue is actually needs fix or it is a perception problem – maybe a communication or info bar on how to use a feature might help
   2. A short term solution or quick fix to resolve the issue for time being if possible.
   3. Evaluate a long term solution considering the root cause of the concerns

1. PR / User Communication
   1. After understanding the issues (after point-2), reply to the user comments in the playstore that we are already working on the issue to avoid more negative reviews.
   2. Also, keep them updated on the timeline of the fix / feature launch – even a tentative timeline will do

To summarize, my approach will be to understand if the reviews are recent or happening for a while. For the recent issues, I will try to narrow down the major root causes contributing to negative reviews. Explore possible quick fixes and also long term solutions based on user impact. Also manage PR in parallel to prevent more negative reviews.

let me test my understanding on Google Hangout product first.

“Google Hangouts is a cross-platform instant messaging service developed by Google. It is a communication platform from Google. With it, you can not only send messages to other users online but also make video calls, phone calls, and send texts to real phones. And, like other online meeting tools, you can conduct meetings or host web conferences using Google Hangouts“

Lets look at main objective of Google hangout – its is to let users use the products and share data with Google to genrate trageted ads on other platform of Google for same user.

Clarifying questions:

1) is it possible to know if ratings are bad on desktop experience or Mobile experience? – Lets assume its same

2) is it possible to know a particular segment of users which has provided bad ratings like School/Universities students (Chatting/Video/Phone), Working professionals (Web conference/Meetings/Chat/Phone) or Others? Lets assume its a common phenomenon on all users segments

3) Or can we split the user ratings by gender or by age group to get more insights

4) Can we segregate reviews by region to see if a certain region is providing a bad rating vs others? Lets assume its majorly across US

5) Are there any common themes across bad ratings and good ratings like video experience, chatting, Phone, sharing of data, Advertisement etc 

6) can i also understand if there are any trends in ratings like it is going from bad to good (Then no problem) or Good to worse (i believe its the latter) – Assume lot of bad ratings in last couple of quarters

7) is it also possible to understand if those users are using the Hangout on Apple OS or Android OS or Windows OS? Assume its on Competition OS

majorly Apple OS on Mobile and Windows OS on Desktop.

to Summarize, The ratings have gone bad over last couple of quarters on Windows/Apple OS in US across different age-groups and user segments

Now, we will look at factors that can be Internal and external and solutions

Internal:

1) Any latest UI, product feature or bug or improper advertisements coming that is causing ratings to go bad? (Can be decoded through reviews like video hang, app crash, No-free ads etc)

Recommendation – Work with Engineering team to provide the hotfix or roll-back feature or check search algorithm on targetted ads

2) Any recent lawsuit on hangout which causes bad impression to users – could be like sharing of data , leaks of user data base. 

Recommendation – Work with legal team to clear the air on the same and provide necessary communication to users

3) is Google hangout taking lot of memory or battery on Phone/Desktop vs Competition?

Recommendation – work with engineering team on what has changed, can bring Hangout lite feature and use cloud if necessary

4) is Google hangout changed certain features as not-free and caused users to leave bad rating?

Recommendation – Check on reviews and bring the discounted/free feature with competition

External:

1) Are friends/Workspace (Universities or Work professional) moving to competition platform like whatsapp, Zoom, Teams causing bad ratings

Recommendation – Work with sales team to identify the root cause of movement and see how we can winback competition and provide best experience

2) is recent update on Apple OS or Windows OS making the experience on hangout bad?

Recommendation – Work wiht engineering team to identify the root cause and work with Apple and Windows ecosystem to drive the right experience

3) Are those ratings legit, check if competition is driving or a hack is driving the ratings down?

Recommendation – check with validation team on evaluating the legit of ratings

4) is there particular region in US or government movement causing ratings to go bad? (Porbably, not a reason as Google is headquartered in US)

Success-metrics:

1) % of ratings improvement over next 3 qurters

2) Provide a survey to users to see if they are happy with new experience to validate the success of solutions and in return rpovide an entry to lucky draw, or free montly service on Google cloud etc