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Imagine you are the PM in charge of Reactions on Facebook - the new way to interact with posts by using “love”, “haha”, “wow”, “sad”, and “angry” reactions. What would success look like in terms of number of non-like reactions per post at launch and how do you come up with this? Would this number differ by reaction? Why or why not?​

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You launched a new feature that determines whether a Facebook message was read by a recipient. What metrics would you collect? How would you know the feature was a success?

 

So by reactions, you mean instead of just giving a like, I am able to react with different emojies right?

 

Yes you are right.

 

Also, could you remind me the reactions it is like, funny, sad and angry right?

 

Yes, but we also have wow and love.

 

Ok thanks for that. So what I will be doing is, before starting directly with metrics, I will summarize this features goal and how it helps FB mission. Then from the user perspective, I will speculate on the why users are using this reactions, so I would be able to think about product health metrics. Finally I will try to think about whether it has a negative effect on FB also any risks involved and how would I measure it if any.

 

Then I think we will end up having a lot of metrics so I will try to choose 2-3 top metrics to look for.

 

Ok sounds good, go ahead.

 

So first the mission and the goal.

 

FB's mission is bringing people together closer and I can actually see how reactions help with that, beucase with reactions you are communicating with the poster and the other viewers in an effective way. So let me write down:

M -> Reactions is easy communication

 

And from the users perspective, I can see that having reactions really enhances the ux. Because before reactions I think people were hesitated to like a sad post, because it does not really convey the meaning. So from the users side this is a good problem to be solved. Since reactions do not have a complex structure, I will not go down the customer journey here.

 

Ok is that all?

 

Before going through metrics, I would like to talk a bit about the possible negative sides of this feature actually. I think there is a good chance that reactions will decrease the number of comments that is being written, and comments might be a very critical thing here since it provokes a conversation, compared to the reaction. I see like feature in the raeactions so there is no need to think about it in terms of cannibalization.

 

So having all this assumptions in front of me I will go with these metrics:

 

For company misssion:

 

# of people reacting to story -> this should be growing because we want to understand if we are helping people to connect more

 

# of unique reactors / DAU (daily basis of couse) -> This is also a good indicator of understanding passive users vs active users, because we want people to react

 

For user pain points

 

  • Avg. reactions per post -> I would expect this to increase compared to likes actually.

  • Distribution of reactions -> This will also give me a good understanding overal sentiment around facebook, I do not want it to be a sad place :)

    • It is possible to deep dive to this by type of posts or type of post owner too but this will be a detailed metric

  • It is also a good metic to look at people in different groups like high reactors, medium reactors and low reactors -> This will help me understand how the reactions used

 

For the risks:

  • Number of comments made would be usefeul

  • Also number of people (unique) commenting per week would be useful

  • Avg number of comments per post could also be an indicator.

 

If I were to prioritize I would go with:

  • # of people reacting to story -> To see how I help company mission

  • Avg. reactions per post -> I want this to be increasing too

  • avg # of comments would be useful so I can compare it

 

 

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C: Clarify the Question

Who are the reactions for?
What are the goals of reactions?
Why was it trimmed to the said 5?

I: Identify the Customers

The two main customers for this feature that I see are businesses who need this information, and people who have been resorting to the like button to respond to posts. Who does it add more value to? I would think this would add more value to businesses as it can directly lead to a more efficient monetization with this additional layer of understanding of a user's sentiment. 

There are two aspects of success

1. (Users) Market Adoption and Engagement due to the reactions. Will people post more, respond more, now that there is an option of an appropriate response?

2. (Businesses) How much more efficient can this information make market targeting?

  • Market Adoption
    • Hypothesis: Does the availability of different response options increase the post engagement of the users?
      • Avg count of reactions per post daily pre-launch of non-like reactions
      • Avg count of reactions per post daily post-launch of non-like reactions (hope to see an increase)
      • Avg count of reactions per 7 days (assuming weekends have a spike of activity) pre-launch of non-like reactions
      • Avg count of reactions per 7 days post-launch of non-like reactions
    • Does the availability of different response options instigate people to share more news?
      • Avg number of posts per day pre-launch
      • Avg number of posts per day post-launch
    • Does biasing to positive emotions garner more engagement with the user?
      • Correlation of distribution of categorized posts according to the non-like reaction vs Avg engagements per post.
  • Business Monetization
    • Does targeting using non-like reactions lead to more engagement with the user?
      • Avg count of single clicks on targeted posts
      • Avg count of two-level clicks on targeted posts
      • Avg count of responses (comment, shares, reactions) on targeted posts
Would this number differ by reaction?
I believe that the reaction type is only important for the businesses to understand how to target their products or subjects, but to Facebook it does not make much of a difference. A user is likely to engage in a post that makes them mad, sad, happy, funny etc. Being mad about a cause is not necessarily a bad thing. Sympathizing with a sad cause isn't either. I believe success would differ due to the mixture of each reaction-garnering post, not the reaction themselves. 
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First of all, I'd probably need some sort of clarification about what "at launch" means. Are we looking at the performance the very next day after the feature is launched or are we giving ourselves a few weeks to see how things are going to play out? I assume it's the latter and we are going to be evaluating success two weeks after launch.

The goal of reactions feature is to give users more freedom in expressing how they feel about content that gets posted on Facebook. This feature should be particularly appealing to users whose primary method of engagement on FB is via the like button, which, I assume, is going to be the vast majority of FB's userbase.

First, to set some baseline metrics I can look at the historic data to estimate things like 

  1. number of likes over the span of 2 weeks
  2. number of posts over the span of 2 weeks 
  3. avg. number of likes per post
  4. avg. number of likes per user

Second, I can look at the distribution of the sentiment of facebook comments. I am pretty sure this data will already be available because that's probably how they came up with these 5 reactions to begin with. Let's say the distribution looks like this: neutral (50%), funny (30%), sad (15%), surprised (10%), angry (5%). I'd say it's a pretty safe bet that reactions are going to follow pretty similar distribution. 

Next, I am going to make a few assumptions:

  1. Given how these reactions got implemented (you need to hover before they pop up), not all users are going to immediately become aware that this option even exists
  2. In the first two weeks, I'd expect that only around 25th percentile of facebook active users are going to engage with the feature and it'll take the rest of the users more that two weeks to get fully on board

I think these assumptions matter because it is pretty unrealistting to expect 100% of our active users to immediately jump on board of the reactions train. We'll be setting ourselves up for failure if we don't adjust our launch goals accordingly.

Keeping our assumptions and sentimetn distribution in mind, we can proceed to do some math for reaction vs likes volume two weeks after launch. For ease of math, I'll assume that the expected number of likes over 2 week period based on our historic data is 10million. After we roll out reactions 75% of users are going to continue relying on likes to react to post because they are not yet on board with the new feature, so that's 7.5million likes. 25% of the users are going to use reactions instead of likes whenevere appropriate. Based on our sentiment distribution data, we can expect 1.25million likes, 750k haha, 375k sad, 250k surprised, 125k angry reactions. After summing everything up we end up with the following number of likes and reactions per post:

Likes: 8.75million / # of posts
Haha: 750K / # of posts
Sad: 375k / # of posts
Surprised: 250k / # of posts
Angry: 125k / # of posts

I'd expect the numbers of reactions grow and likes decline as more and more people are becoming aware of the feature, but ultimately we are likely to end up fairly close to the distribution of general user sentiment. Unless we continue adding more types of reactions, I think "like" is going to continue being the most popular way of engaging with the post, just because it is the default and the most relevant reaction for the majority of posts.  One thing to note is that these calculations did not accout for the fact that many users were most likely not liking posts that were making them sad or angry, so I think our average number of reactions + likes per user is going to go up due to this and so will the percentage of reactions vs likes.

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I think this response was an interesting take to the question, and actually answers it. Thanks!

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Let me start to answer this Facebook metrics PM interview question with a few questions of my own:

1. How're we doing it right now? --> Users have an option to 'Like' the post

2. Why did we launch 'Likes' in the first place? --> What do you feel?

Let me think about it. First off, let me segment the different users:

1. Heavy Posters --> These are the 1% of the users who are always active on Facebook. They're posting all the time, adding new friends, commenting, etc. They're are the content creator!

2. Frequent Posters --> These are the 9% of the users, who sometimes participate on daily FB's activities. 

3. Occasional Posters/Lurkers --> These are the 90% of the user who usually lurks around

As a FB PM, I would have seen this pattern and wanted more participation/engagement from all user segments. --> Seems fair assumptions

Let me list the needs/pain-points of each segment:

1. Heavy/Frequent Posters  --> When others don't engage on their posts, they lose motivation to produce content/posts and thereby they come less on FB, and FB loses its power of having an engaging community. 

2. Lurkers --> They like the posts but don't want to comment, they want an easy way to show their appreciation.

Looking at the above problems, 'Likes' seems to be the solution. 10% of users posting and 90% 'Liking'

Now, extending the above analogy, I see we can have more emotions - “love”, “haha”, “wow”, “sad”, and “angry” catering to the distribution of the 90% of the users as not all 90% will have a need to 'Like', they have other emotions like “love”, “haha”, “wow”, “sad”, and “angry”

So, from the above hypothesis, I see # of posts having only 'Likes' will < #posts having 'reactions'

Other Success metrics will be:

1. # of posts with reactions / # posts without reactions

2. Reactions leading to more posts --> # reactions / # total posts --> Cohorts of posts before and after reactions can be measured

3. Reactions leading to more active users --> # unique users before and after reactions

4. Reactions leading to other activities --> 'Add Friends', 'Comments', and 'Chats'

 

To summarize, I feel reaction will increase overall engagement as we're targeting a larger distribution of user and their emotions, and an ability to portray these emotions will lead to an increase in engagement

 

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I'll start by laying out FB's overall Mission and goals: 

FB is focussed on bringing people together and creating community. 
There are two tabgible outcomes that I can distill from there: creating connections and fostering meaningful interactions between them. 
Knowing where FB is in its lifycycle, I would assume FB is currently focussed on Engagement/Retention and Revenue. 
 
With that context, I'll get into the Reactions feature and first frame the problem is solves for different user groups involved (focusing on non-like reactions):
This features expands the range of emotions one can express or receive on FB, there by connecting various user groups involved at a more personal level, improving overall user satisfaction/engagement. There are 2 broad user groups: 
1) User that is reacting 
2) Content creator who receives reactions on their content 
In line with overall company mission, it would be important to ensure that both of these user groups are gaining value from this feature to ensure there is strong network effect, that it turn improves overall Engagement/Retention. There is also an indirect revenue component to this as user react to Ad content.
 
If I were to capture the overall objective in a North Star metric for this feature, it would be % of Posts with Non-Like Reactions / Day with the assumption that non-like reactions are a deeper form of engagement than a Like, which is a little less personal.
 
I will now break that down into different categories of metrics based on user journeys:
User Group 1) User that is reacting
Awareness: User discovers that he or she can now react in ways beyond Like 
Activation/Conversion: User explores and clicks on a Non-Like reaction for a post
Engagement: User continues to use the feature and also engage in other ways post reacting - comments, shares 
Retention: User loves the feature and continues to use FB more as a result
 
Since this is at launch, I will prioritize Awareness and Activation/Conversion as my top success goals (Priority 1), while ensuring I have proper Counter Metrics identified. Engagement will be my priority 3, followed by Retention and Revenue, which I will measure but not necessarily prioritize for Day 1. I will also set up an A/B test at launch to cleanly determine incrementality. 
 
I will now identify metrics for these categories, prioritize KRs and then move on to the next User Group. Prioritized KR's are in bold. 
 
Awareness
  • % of users (in the Test group) that become aware of Non-Like Reactions / D,W,M (measured by impressions for any onboarding placements) - I will prioritize this as my top KR in this category as I see it as having maximum Impact on our NS at launch
  • # of users that that become aware of Non-Like Reactions (measured by impressions for any onboarding placements)
  • # Impressions for onboarding placements (split by placement)
 
Activation / Conversion
  • % of users (in the Test group) that press and hold Like button to view Non-Like reactions per Session, D, W
  • Base Conversion Rate for Non-Like Reactions per Session, D, (% of users that ultimately choose one of the Non-Like reactions) - This metric will again Impact the NS significantly by ensure users are finding the feature valuable the reacting 
  • I will segment this by Type of Reaction to understand if one or more reactions are getting more traction than the others. At launch, I dont think I will optmize or set Goals by reaction. I will look to understand what users are taking to and optimize from there. 
  • I will also segment by Type of Content, demography, channel, geography
  • At launch my goal will be push Base Conversion Rate so more and more people can "try" the feature. 
Engagement:
  • # Non -Like reactions / user / Session, D, W - segment by Reaction Type 
  • Activity Level per user in the form of # of Reactions per Session, D, W - I will further look to move users from Low Activity Level (2 or less reactions in the form of Likes per session today) to Medium Activity Level (3-5 reactions per week) and from Medium Activity Level (3-5 reactions in the form of Likes today) to High Activity Level (8 or more reactions per week) 
  • % of users that go on comment or share after reacting 
  • Time spent on FB / user/ Session, D, W - Segment by Newsfeed, Timeline
  • # App logins / user / D, W 
  • DAU, WAU, MAU in the user segment that uses non-like reactions
  • DAU/WAU in the user segment that uses non-like reactions
  • Segment these metrics by Type of content, demography, channel, geography
Retention
I will begin to identify which actions correlate well with longer time engagement with FB. E.g. 
% users that use a non-like reaction at least 3 times in their first ween after activation (assuming this metric correlates well with long term retention / stickiness)
 
Monetization
I will be measuring enagement with Ad content for launch but not deem it a goal metric.
 
Counter Metrics
Base Conversion Rate for Reactions overall including Like per Session, D, W 
% of users that go on comment or share after reacting 
%Churn - % users that rapidly disengag with FB (reduced time spent, app loging) after the launch of this feature
 
User Group 2: Content Creators
 
Awareness
  • % users that become aware of non-like reactions prior to posting content (measured by impressions for any onboarding placements) - segment by User Type (individual, business, public figure etc) - I will prioritize this so this group can get an opportunity to create content that is geared towards generating these higher levels of engagement from users
  • # Impressions for onboarding placements 
 
Activation/Conversion: 
  • % users that are creating content after the launch of this feature - segement by type of content, user type, demography, geography, channel
 
Engagement
  • # of posts per user per session, D, W - segment by user type, type of content 
  • % of non-like reactions per post/ user - segment by type of content, type of reaction
  • % posts with non-like reactions - segment by type of reaction
  • # of posts with a non-like reaction + share/comment / user - will also measure aggregate 
  • Frequency of posts / user (Low, Med, High) - I will look to move users from Low Activity Level (Less than 2 posts per week) to Medium Activity Level (3-5 posts per Week) and from Medium Activity Level to High Activity  Level (More than 5 posts per week)
  • Time spent per user / interacting with the post per session, D, W - segment by type of engagement (view, comments, edit etc)
 
Retention
Same logic as prior - will measure leading and lagging indicators but not prioritize as yet
  • % users that revert to post again per Session, D, W
  • Frequency of posting / user 
 
Monetization
Same logic as prior - I will measure behavior change for ad content but not prioritize it as a success metric as yet
 
Counter Metrics:
  • % Churn (% of users that disengage rapidly in terms on posting content after the launch of this feature) - segment by user type
 
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  1. CLARIFY: 
    1. Is this feature being rolled out to all markets? Yes.
    2. In regards to non-reactions, do you mean users who have viewed the post but never reacted? Yes. 
    3. Are there specific types of users that this feature is rolled out to or is it to all users? All users. 
  2. GOAL: Facebook is all about building connections. Adding different types of reactions adds a personal aspect to posts and allows themselves to express themselves better - i.e. enhances your connections.
  3. USER: There are different types of users we can think about. Specifically I'd like to focus on individuals (v. businesses) reacting to posts. For this exercise, I'd like to focus on the Low Engagement User.
    1. Low Engagement: Rarely engages with posts. May respond to 1-2 posts / day. 
    2. Medium Engagement: Sometimes engages with posts. May respond to ~5 / day. 
    3. High Engagement: Always engages with posts. Responds to 10+ posts / day.
  4. LOW ENGAGEMENT USER REASONS FOR ENGAGEMENT: I'd like to understand why this type of user chooses to react v. not react. 
    1. React: In regards to when a Low Engagement user reacts, they likely have a personal reason for doing so.
      1. Personal Call Out: Another user has tagged them in a post or directly called them out. 
      2. Meaningful Connection to Event: User feels greatly moved to respond to something for personal reasons - ex. personal cause, speaking out against something, etc.
      3. Personal Connect to Event: User feels greatly moved to respond to an event that has affected a friend - ex. a death of a relative. 
    2. Non-React: In regards to a non-react response for success, I'd like to focus on "Didn't Want To" and "Alternative Engagement", as in both instances the user has read the post to know enough about it; thus, we can measure success indirectly.  
      1. No Time: User is too busy to respond. 
      2. Didn't Read / Skimmed Post: User never read the post / skimmed by it.
      3. Didn't Want To: User didn't feel enough personal motivation to respond with a reaction though they read the post.
      4. Alternate Engagement: User may have engaged in a different way - ex. written a comment or shared the post.
      5. Accidental Un-Reaction: User reacted accidentally / un-responded or accidentally undid a response. 
  5. MEASURE SUCCESS OF NON-REACT: There are a number of alternative ways to measure non-response. These metrics all indicate that the user has engaged in the post somehow, which overall is the indicator of success for non-reactions. If I had to prioritize my most important metrics, I'd choose the high rank metrics; however, there is something to be said about a user that pauses / reads a post too. CTA response will not apply to all posts. 
    1. MetricDescriptionRank
      TimeUser has paused on post for at least 6 seconds (estimated time to read)Medium: User has likely read post if they pause on it (though it's possible they were distracted from Facebook too).  
      Alternative ActionUser engages in post in some other manner (comments, shares, etc.)High: User is clearly engaged with post / content.
      CTA ResponseIf post is a call to action (ex. survey, fundraiser,), user clicks on survey or fundraiser. Could also measure if they complete survey or donate.High: User is clearly engaged with post / content.
      EngagementUser clicks on profile of post or views more comments on post (i.e. engages in some other manner).High: User is clearly engaged with post / content.
      Indirect ContentUser continues to view similar content. For example, if the post is a video from a TV show, user continues to scroll through feed looking for videos of show / pausing on them.Medium: User is engaged in type of content though it's less clear to what extent the user feels moved by the post (v. donating to a fundraiser). 
  6. MEASURE SUCCESS OF REACTIONS: The direct measures of success of reactions would differ from the above metrics. For the metrics of success for reactions, I'd prioritize direct measures of success, which is not as possible with non-reactions. Overall, based on personal observations, I would guess that most posts are likely going to see non-reactions v. reactions. We can also indirectly measure the success of reactions to see if posts with more reactions get higher engagement (reactive and non-reactive). The indirect measures of success do overlap with the measures of success for non-reactions.
    1. Direct Measures of Success: Primary focus to measure success of reactions. 
      1. # of users to react after v. before roll out: Assume that there would be more users reacting after roll out.
      2. # of total reactions after v. before roll out: Assume there would be more reactions overall after roll out.
      3. Average reactions / post after v. before roll out: Assume there would be higher average reactions / post after roll out. 
    2. Indirect Measures of Success:  I'd also secondarily think about indirect measures of success.  
      1. Alternative Reactions: Assume a post with more reactions / emotions will also have more alternative reactions (comments, shares, etc.) 
      2. CTA Response: Assume a post with more reactions / emotions will have higher CTA responses. 
      3. Engagement: Assume a post with more reactions / emotions will have higher engagement re. clicking on user profile or viewing more comments, etc. 
  7. SUMMARY: Measuring of the success of non-reactions would differ from measuring the success of reactions for their direct success metrics. For success of non-reactions, we need to measure if a user engaged in a post indirectly, whereas I'd focus on direct measures of success for reactions though there is overlap in how we measure indirect success of reactions.
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Repeating the question:Imagine you are the PM in charge of Reactions on Facebook - the new way to interact with posts by using “love”, “haha”, “wow”, “sad”, and “angry” reactions. What would success look like in terms of number of non-like reactions per post at launch and how do you come up with this? Would this number differ by reaction? Why or why not?​

Answer:

Let’s see if we can use some of the components of STAR methodology?

S = Situation

T= Task

A = Actions

R= Results

 

Start with a clarifying question?

 

Why did Facebook added expressions (additional four expression categories in addition to the Like)? Was Facebook:

 

1- Losing users/subscribers in one of the states or countries?

2- Trying to compete or distinguish from Snapchat (Chat) and Instagram (pictures)?

3- Increase engagement that will lead to retaining what they have (and stop losing)?

4- Increase average revenue per user?


 

So, we could hypothesize that Facebook is changing to expressions to:

1: Increase engagement of existing users

 

By keeping users more engaged, they could stop losing, and perhaps attract some moree from thee millennium category that are looking for more granular expressions.

 

Next, would be the Task- let’s first categorize users in certain buckets:

 

There are four types of users:

1- Who builds relationships? 35%

2- Self Promoters - 15%

3- Bearer of important news - 15%

4- Watchers - 35%

 

I am not guessing, the ratio, but #1 and #2 should be at least 70% each.

We need to reach this 70% market and keep them more engaged.

 

So, what metric, we need to track and for what duration?

Duration of at least two weeks, to make sure the users are fully aware of this new feature launch.

 

And what tests, we need to perform? They are called A/B tests to measure engagement.

 

1- How many times do the users come back and check Facebook in a day and in a week?

2- What happened to Like, did it increase or decrease? Is the sum of Like plus five other expressions ( a total of 6) is equal to when there was Like alone or did it increase? For example, without this feature, Likes were 100 Million, and with the launch of five expressions, we now have 6 choices, so the total should exceed 100 Million.

 

We can run a significance test and compare before and after values by computing P-Value. Say, we set a null hypothesis and then set a threshold of 0.05, below this value we assume that we can reject the null hypothesis and in fact engagement has increased.

 

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