+2 votes

You are a Growth Marketing Analyst at FB and  you have been tasked to identify reasons as to why users signing up from a country are not returning to FB after 30 days.

What will be your hypothesis? 

What data/metrics will you look at prove or disapprove each of the hypothesis

How will you prioritize your problem to solve?

How will you measure success of your change?

asked in Problem Solving by (14 points) | 1.5k views

3 Answers

+1 vote

Clarifying questions

  1. is this a new country for FB?
  2. if not, has this started happening recently? how long has it been happening?

Assumption: FB has been in this country for a long time. This started happening recently 3-4 months

[repeat question now] Ok, so the change is recent and the new users who are signing up are not returning after 30 days

Let me think about what a new user needs on FB
- New user is looking to socialize with their friends and engage with meaningful content on the platform

>> Hypothesis #1: they may not be finding enough friends to connect and thus the platform may not be engaging to them

>> Hypothesis #2: New user is looking for content to engage with and there not finding enough engaging content

Data that I will look for: 

  1. # of connections made per new user per month in that country: 
    1. I will compare it within the country before this drop started occuring and also to other similar countries 
    2. I will also look at % of times People You may know (PYMK) feature was shown to the user in their newsfeed and % of connections user made from the feature. This will help me verify if FB showed enough friends and whther the firends were relevant or not. Based on % times this feature was shown, I can devise an A/B test to show this feature more and validate further if it helps improve 
  2. % of non-friend content shown to new user in the newsfeed:
    1. I will again compare it within the country before this drop started occuring and also to other similar countries 
    2. I will like to conduct an A/B test by showing relevant pages or groups to them in the newsfeed (based on their demographic, FB can gues their interest; since they are new users FB may not have enough info about their interests) and by showing the pages, we can guide them to find new content. We see if the test group stays with FB compared to control to validate the hypothesis. 

I will measure the success of the tests in terms of improvement in 30 day retention. Since this is metric we were concerend about, we will measure the improvement in the metric

answered by (15 points)
0 votes

Understand the bell curve for product growth.

Whether the product is in initial, growth, saturation, stagnation(decline) phase in that country.

Assumption #1: Assuming the product is in growth phase.

Analyse whether the user is signing up for facebook or for using some other applicatons (using sign up with facebook).

Assumption #2: Assuming the user is using facebook app.

Analyse which of the user engagement metrics is declining : fb chat, fb groups, fb pages, user posts or quiz/fb apps based posts.

 Analyse the last activity that the user spends time upon before leaving the page.

Solving the problem:

  1. If the fb posts feature is getting less engaging: Engage the users more by showing the posts by dividing into several groups and applying A/B tests: Posts by direct friends, posts by mutual friends, trending posts etc.
  2. If fb pages or fb groups are getting less engaging: Encourage more group posts in the main feed of the users who're the top commentors/ medium commentors/ less commentors.
  3. If quiz/ fb-app posts are less engaging : Suggest(Incentivise) the app developers to create more new /innovative/ trending apps.

Measuring the Success:

Analyse the results of the hypothesis over a month and apply the appropriate changes over the next months and observe the user engagement/ the rate of users coming back within 30 days. 

answered by (38 points)
0 votes

Assumption: users use FB mainly for socializing with their friends. 

This is an on-going existing problem, which was not caused by specific events or incident.

Hypothesis 1: The new user has not formed a specific habit of using the app or she forgot to use the app. 

Hypothesis 2: After the user registered, she does not feel the need of going back to the app

Hypothesis 3: the user is simply not a target user. The user kept going back to the competitor app such as snapchat for social networking. 

Data to be collected:

(1) demographics data about these group of users to understand if they fit into FB's majority user profile. For example, age is an important factor. Teenagers tend to use snapchat. Younger age implies that the users are simply not the target users for FB. Therefore, the solution should be more at the strategic level - whether or not FB should study the competitor's features and customers and enter new territory by developing new features/products/buying other apps

(2) Study those users' friends' usage of FB and separate them into different buckets. If the user has a group of highly actively friends on FB, the user might just forget to use the app or need a little bit more influence from their friends. A reminder email to the user or even remind the user's friend on FB to say hi or interact with the user on FB might help solve the problem.

If the user's friends are not active on FB, then, in general, the user might find FB is not necessary for her to socialize with her friend. Therefore, FB might want to target other than socializing features such as pushing random news or random interesting content to get the user's attention on FB's other functions. 


Post launch of the solutions, tracking user's login behavior, CTR of reminder emails, content they tended to consume, features they use most, interactions with their FB friends, growth of FB friends etc.

answered by (13 points)

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