Friend requests are down by 10%. Evaluate why.
- Fergus Xavier
Structure
I’m going to make sure that I understand the journey of adding friends, ask for clarification questions, and explore the potential factors for the drop; I will ask for additional data and then provide one or a few hypotheses.
The Product
Facebook’s mission is the make the world closer and make tools for building communities.
A friend request is an attempt to contact a person you know or would like to know in FB’s social network.
I would say that there are 3 categories of friend requests,
(1) Suggestions – Facebook’s friend request suggestions mechanism.
(2) Direct – You see someone, in a group, in a post, in a comment, and you ask for a friend request.
(3) Search Bar – You know someone’s name and search for it.
Clarification Questions (answers)
(1) Are we talking about the number of requests or number of friendships establishedaccepted? (Requests. Relatively the number of approvals also decreased)
(2) Did the drop occur suddenly, a day or a few days, or over a period? (A drop in the average number of friend requests per user in the last quarter)
(3) Is it a problem? Did we experience such drops in the past? What is the variance of changes? (We didn’t experience such things in the past, 10% is high)
(4) Are we experiencing a significant drop or increase in other features’ activities, generally in WAU or new registers? (No)
Factors (answers)
General Factors
(1) Is it worldwide or only a specific region? (worldwide)
(2) Is it for the app or the web? (all platforms)
(3) Can we segment it by devices or operating systems? (No)
(4) Can we segment it with some other demographic dimension? (No)
(5) Is there a point in time that we could say that change started? (Yes, Weeks 14-16) – This is an important answer since it allows us to focus on a smaller period.
External Factors
(1) Did one of our competitors launch a feature or changed a policy? (Yes, but nothing seems to be significant)
(2) Were there regulation changes? (Not something significant)
(3) Was there some significant event (holiday, sports events, elections,..)? (Pandemic)
(4) PR – Was there something in social media or news? (Hard to tell)
Internal Factors
(1) Is there a difference in drop between user journeys?
(1.1) Suggestions – Facebook’s friend suggestions panels widgets (No change in conversions for relatively new users nor users with a lot of friends)
(1.2) Direct – A user sees someone and tries to connect (No change)
(1.3) Search Bar – A user is searching for someone by typing her name (A significant drop – Bingo)
Hypothesis 1: since it is a high drop, I would assume that more than one factor caused it. Such a thing can occur if a new change or a feature isn’t causing a significant change, but a combination of multiple changes can cause a snowball effect.
(2) Where in the search process we experienced a drop relative to previous periods?
(2.1) # of users click on the search (wo a change)
(2.2) Average searches per user (Decreased)
(2.3) Average # of characters typed (Decreased)
(2.4) Average # of suggestions presented during typing (wo a change)
(2.5) % Conversion of clicks suggestions (Decreased)
(2.6) % of users click to start search – get to the results page (Increased)
(2.7) Average # of results (wo a change)
(2.8) % Conversion of click on results (Decreased)
Hypothesis 2: Since there was no decrease in the number of clicks on the search, I assume that nothing changed in the discoverability of the Search bar.
Hypothesis 3: Something has changed in the search experience; we might have started presenting suggestions earlier or changing the suggestions algorithm. Since there are fewer characters, the quality of suggestions decreases, and the number of clicks on those suggestions decreases. In addition, maybe because the suggestions are not good enough, it causes users (pain and) to click faster on the search button (get to results page quicker to explore it deeper there). Since we are receiving fewer characters, the quality of the results decreases, causing a decline in conversion rates on the results page.
(3) Did we launched a feature or running an AB test on the search journey? (Yes):
(3.1) AB Test start presenting suggestions after typing 1 charter, 2 characters, 3 characters
(3.2) Feature launch – Added a button at the bottom of the suggestions of “Search” (After AB testing a few color options)
(3.3) New Suggestion Algorithm roll out – it was tested on 5% of the users and showed improvement and now was rolled out to 50% of users.
(4) Change in Performance? – time to load suggestions (wo a change) | time to load search results (wo a change)
Summary
We made some changes in the search user experience, causing a drop in the number of new friend requests.
Although there is a drop, it doesn’t mean that it is a bad thing. For example, a decrease in friend requests can cause an increase in requests approvals, the quality of the relationships, and the content on the feed (time spent on the site, engagement, reactions, and more).
Since there are many moving particles, I suggest improving the collaboration between the different teams working on that area and making sure that we agree on the trade-offs before deciding to revert something.

Meta