What goals would you set for a Facebook Dating feature?

What is Facebook Dating?

 Facebook dating is build for people who are looking for a romantic connection. It is open to anyone who is a member of Facebook community.

The users can create a profile and set their preferences of who they want to date (based on demo, location, Gender, Interests, etc). Once the profile is created, they can go to FB dating homepage to look for the potential matches. If a user likes prospect, they will go to their detail page and give them a like. Once, the user get a match, they can start chatting and set up a date.

Facebook Dating Mission: Help people to create romantic connection and build a family.

Assumptions:

1. This will for people who are above the age of 21
2. The feature will be available on all platforms
3. Currently, the feature is available in the US.
4. A new product launch for FB app, which will be available within FB (i.e. not a stand alone app)

Who are the current competitors?

1. Craigslist
2. Serious Apps (eharmony, match.com)
3. Swipe apps (Tinder, Hinge)
4. Friends and Family Network.

Why did Facebook Entered the Market?

1. Facebook is uniquely positioned to utilize it’s community of 1B MAUto find romantic connection.
2. Facebook already has enough data in their social graph such that FB dating can provide better matches.
3. The Market size of Single people is huge, so building a product focused on this target segment can help increase the engagement on the platform and bring revenue (Ads revenue)
4. Could be a strategy to enter the wedding market and building products for end to end customer journey of finding love to getting married to share their stories on FB

What are the unique value the product can bring to the dating world?

Dating is a social activity and FB is uniquely positioned to help people find dates through their social network.

1. Better matches -- using the social graph of each user (their preferences, interests etc.)
2. Can better control fake profiles than other apps since most of the users are already have a history on FB platform.
3. Utilize Community help to find dates:  As a dater, I would feel more comfortable to go on a date with a potential match if the match is connected with someone in my network(1st, 2nd, 3rd degree etc.)

Market Size:

1. This is a population problem, so lets assume total US pop is 320 million.
2. Average life span is 80 years, so we have 40 million people in each age group. Calculation 320 Million/ 80 = 40 million in each age group of 10 years. (0-10 age - 40 million, 10-20 age group: 40 million etc.)
3. Lets assume this app is for anyone above the age of 21, and lets consider the age group 60 -70 years and 70-80 years outside the scope since this population will likely not look for a romantic connection on FB.  Therefore the total people who are eligible age group to use FB dating, which is around 160 million.
4. How many people are eligible to date. For simplicity, lets assume people who are not married or in a relationship are looking for a date. We can look at the recent divorced data and single's index report to estimate the number, but from lets assume there are at least 30% of single people. Calculation: 30% of 160 million = 48 million.
5. Of 48 million, how many are WAU on FB? Most of people will at least login to FB a week so I'd assume 90% of 48 million are WAU = 43.2 million.
6. Lets take 10% out for fake/duplicate WAU profiles, so our target segment is approximately 40 Million.

How do we define success?

Lets assume the timeline for goal setting is a year. Since this is a new product I'd say even if we get 10% of the market share in year 1, that would be an ambitious goal.

Again our goal is to help community find romantic connection. Therefore, the primary success metric would be the customer happiness with the app, which can me measured as NPS score, rating, or by users inviting their connection to use the App.

Secondary Metrics:

1. Awareness: 100% of the 40 Million (dating eligible WAU customers) are aware of the FB Dating feature
2. Profile Completion: This includes inputting preferences and uploading 4 pictures. At least 50% of 40 million customers = 20 million customers  have a completed profile.
   1. We can use the same structure that FB uses to help customers fill their profiles when they sign up for FB platform.
   2. For benchmarking, we can look at the publicly available data to see how many people usually complete their dating profiles on the other apps and why are the reasons they don't?
3. Active customers: at least 90% of the customers who finished their profile become active i.e. 18 million customers login to the FB dating app at least 2-3 times a week.
4. Maintain M:F ratio of WAU customers of Dating app  - 50:50 : 9 million each.
5. Show at least 50-100 new potential real matches(no fake profiles) to the Active members per week Again, we can look at the dating data from Hinge or Tinder and see how many new profile does the user see each week.
6. Engagement:
   1. Average number of profiles checked by user per week.
   2. Average number of matches per user per week
   3. Total number of matches per week on the platform
   4. Average number of chats that has phone number exchanged.
7. Churn and Retention:
   1. To be successful, we want user to find connection and delete the App.
      1. Track the average number of weeks user was active before churning.
      2. If the user churned, ask them did you find a connection? Y/N
8. # of users who found love and back promoter of the app that helped bring more users to the dating App.

Guardrail Metrics:

1. Uptick in the fake profiles.
2. Customer tickets about potential harassments.
3. Negative impact to the overall engagement to the FB platform.
4. Negative impact to the WAU of Facebook App.

Before I proceed to discuss the metrics for Dating feature, I would like to first clarify if my understanding of the feature is correct. Facebook Dating feature helps users ages 18 and up find a meaningful relationship.

How does the feature work?

Facebook Dating feature is available on the Facebook app. To use it you need to set up a separate profile. The service will present you with potential matches based on your location, indicated preferences, and other factors.  Once the match is suggested and you acknowledge you can start exchanging messages

Let’s talk about how Dating aligns with Facebooks overall mission

Facebooks mission is to give people the power to build community and bring the world closer together. Dating feature helps to connect people who are looking for meaningful long-lasting connections thereby bringing them closer

Goal of Dating Goal of this feature is to help find meaningful relationship. Facebook has around 2B active users. Many of these users have used this platform passively to find their match. 

Product Lifecycle: Facebook Dating has been around for around 4 years. Due to this I would not like to focus on awareness but adoption and engagement

Let us now talk about the users of the groups

 Users of Feature

1.   People looks for serious long-term relationship

2.   People looking to meet new people

Let us talk about the user journey and then I will focus on metrics around specific steps that are important to track for engagement and adoption

 User Journey

1.   Candidate opts into the feature

2.   Candidate creates a profile

3.   Candidate is presented with potential matches

4.   Candidate accepts or declines

5.   If both candidate accepts then they can exchanges messages

METRICS

ACQUISITION

1.  Avg no of new users / month and evaluate this trend over time (MoM)

2.  % of profiles completed

ACTIVATION

1.  Number of unique users who either accepted or declined the suggestion once and see how this metric is performing over time(month over month)

ENGAGEMENT: 

Recommendation engine

• Acceptance rate >80%. Track this month over month
• Decline rate<20%. Track this month over month.
• Acceptance is when both accept and declined is when one declines the recommendation

Depth of interaction

• % of users who exchange more than 5 messages when a connection is matched

Time spent 

• Time spent on dating on average / member. Would like to measure this over time and correlate this with Accept rate. If accept rate is high and time spent is more then maybe they do find some use.If decline rate is more and time spent is less then they are not finding value on the website

RETENTION

1.  Avg no of users who come back to the feature after 30 days of creating a profile
2. Avg no of users who come back even after declining the match
3. Avg no of users who delete profile every month

 Counter metrics

1. Number of profiles reported every month
2. Number of people who never responded
3. Cannabilazation across different facebook services due to time spent on this website

Now I would like to evaluate these metrics against the goal of increasing engagement and adoption

METRIC SELECTION: Based on prioritization, I'd focus on the 4 metrics below with a high weighting .These 4 metrics fall within the engagement bucket, which is a direct measure of how valuable the feature is. Measuring these trends overtime demonstrates how valuable is feature  

1.  Acceptance and decline rate

2.  Message depth - % of peopke with 5 or more message exchange when a match is made

3.  MAU - Retention

4.  Avg time spent on website correlated with accept rate

5.   

Facebook’s mission is to bring the world closer together.

Dating helps with that mission by creating a space within Facebook that makes it easier to meet and start new conversations with people who share your interests. This can potentially lead to long term, meaningful relationships.

The users are people who have a FB account and they are looking to meet other people that they can date or become friends with. These are users of all ages across the markets FB dating was launched in. The value they drive is based on finding people they can click with it. 

For Facebook the value comes from people spending more time on the platform.

In a very competitive market, this product stands out as it decreases the risk of dealing with fake profiles (due FB’s ongoing integrity efforts), and potentially allows to bring in other components of a participant’s life like IG stories or events that both who matched have in common (thus showing a more nuanced view of a potential match). An easy North Star metric would be Monthly Active Users but I believe we should actually focus on providing users with a high quality experience. 

I would like to take a few minutes to establish the North Star Metric, and then maybe we can brainstorm some metrics that come out of that, along with some counter or downstreams  metrics that we need to keep in mind as we are developing the product.

Based on what I think is this product’s point of differentiation (e.g. building more authentic connections), a good North Star metric would be matches that result in a meaningful connection.However, since that is likely to happen offline (with no way for FB to track what happened as soon as things were taken offline), I think a measurable metric would be  number of matches per user per month - as I think connection is what will eventually drive engagement up.

I’d like to break down that metric down as follows:

Metrics based on user journey:

Acquisition: num of people on FB who sign up for FB dating 

• Num of DAU/MAU

• Num of matches per user per month

• %of likes that result in a match

Activation: %of MAU who filled in any sections of their profile

• Average completion rate of profile 

Engagement:

• Num of meaningful conversations (at least 3 lines exchanged) per user per month

• Num of virtual dates (e.g. video/audio calls assuming that is possible)

• Time spent per user per month

Retention:

• This is a tricky metric in the context of dating as eventually a successful interaction might result in the deactivation of the profile

Monetisation: - there are opportunities for monetisation by showing people ads but since this is a new product I imagine that will become more important as the product reaches maturity.

I’d also like to go through some counter metric or downstream metrics that we would also need to measure in order to see how this app adds value to the platform overall

Counter metrics: 

-percentage of users who un-matched someone

- total number of un-matches per month

- conversations unreplied /per user (one user initiates convo after match but goes unreplied) as this might be a big pain point for many users

- num of fake profiles taken down

- % of users who reported a profile as fake/abuse

Downstream metrics

• We see time spent in Feed or Groups per user per month going down due to canibalization from FB Dating

• Number of User accounts blocked

• FB MAP goes down as a result of a bad experience with Dating

Product Rationale

Facebook dating allows users to meet other facebook users and form meaningful relationships. A user is matched with potential facebook user profiles based on her specified interests, geo location etc. A user is able to "accept" the match and if the match accepts the user as well, they are paired, and they can start dating. Additionally, a user is able to add "secret crushes" from her list of facebook friends and instagram followers. If she happens to be one of her secret crushes' crush, they are matched and they can start dating. Facebook dating also has safety features for users to share their location with their friend when they are going on a date. 

Since FB dating allows users to meet and form connections with new people, it ties right back into FB's mission of helping build a community and bringing the world closer together. 

User segments

FB dating caters to the below broad user segments:

1. Users that have never dated before and want to date

2. Users that have dating experience and want to date

3. Users that just want to check out the dating market and may not necessarily be serious about meeting

Goals/User actions: Now let's look at what the user journey looks like within facebook dating:

1. User accesses the feature

2. User creates her dating profile

3. User views suggested matches

4. User likes a match and is paired with one another

5. User goes on a date (may not be completely visible within the app)

6. User adds a FB or insta follower as a secret crush

7. User shares shares location with a friend before going on a date as a safety measure

Overall, I would track the users that were matched successfully over total number of users daily, weekly, monthly (let's call this match rate) and users that were matched that exchanged messages, while passively monitoring adoption rate of users

Goal: FB overall goal is to Give people the power to build community and bring the world closer together. Dating should align with that as well.

Product feature: People create profiles, write about themselves, and set preferences in what kind of people they are interested in, in order to find a partner

Metrics:

• Adoption
  • % of FB users using FB dating
  • # of daily/weekly new user profiles being created
• Engagement
  • % of FB time spent on FB dating OR avg session time/user
  • # of swipes/user
• Retention
  • % of DAU of the WAU
  • % of repeat users after getting a match
• Conversion
  • # of matches/user
    • Cohort by light, moderate, and highly active users
• Revenue
  • % of FB revenue generated from Dating from ads/premium accounts
• Counter metric:
  • FB DAU/WAU

Prioritize metrics to keep top 2 or 3

• Conversion and Retention - If they run well, there will be automatic more adoption and engagement, and thus revenue by network effect/word of mouth

Growth ideas (in case product growth analytics team works on this):

• Understand the pain point by understanding the user journey (to understand user drop rate by creating funnel metrics):
  • User lands on the dating app UI
  • Signs up
  • Creates his/her profile
  • Set preferences in what they are looking for
  • Start swiping
  • Gets a match/not in X timeframe (say a week)
  • Start a conversation
• Notify single people for more adoption
• Ads in newsfeed
• Free trial version
• Pre-filled what to write in bio, suggestions in setting preferences (If the drop off is high at creating profile or setting preferences)
  • AB test feature: with and without pre filled text to see increase in profile creations
  • Control and experiment: New users signing up for the first time
  • Metric: # of profile creations
  • Trigger: Lands on profile creation page
  • Power analysis: Significance level, min detectable lift needed, and volume coming in
    • Will determine the duration based on above
• Suggestions to start a convo (ice breakers/one liners etc)

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

• # Likes / User / D,W,M
• # Likes Received / User / D,W,M
• # Messages Sent /User / D,W,M
• # Messages Received / User / D,W,M
• Aggregate Engagement Score: Total engagement (Likes, Messages, Reactions per user over a period of time)
• # of dates that result in Friend connections outside Dating feature
• # Matches made in a D,W, M
• % of initiations that result in a successful match in a D,W,M 
• % users that modify their profile  after account set up in a D,W,M
• #profile modifications per user per D,W,M
• Time Spent on dating feature / user / Session, D, W, M
• Avg amount of time a user has to wait before a match is made

• % Users that re-initiate search after a match is made
• Identify metrics that correlate best with long term engagement with the feature throughout the journey and measure those - e.g. 

• If Referrals is a feature in Dating, I will track that as word of mouth can be extremely powerful for a feature like this. 

Counter Metrics: 

I will have a control group for this feature to understand the impact it's having on overall engagement with FB

• Time Spent on FB / User / D, W, M
• DAU/WAU/MAU
• Aggregate engagement / user / D, W, M
• Amount of time spent / user outside Dating per D,W,M - Assuming the amount of time one has for social media is finite, if a user is spending a good amount of their time on a feature like dating, there is a chance they are not spending much time on it outside Dating. I would want to make sure users continue to remain interested in FB overall so they can continue to engage with their cmmunity after they find a match.
• %Churn (% users that disengage with FB after using Dating)

Taking another  stab at this question. Hopefully I'll fair better than my earlier question

Background

FB dating as the name suggests is an FB product, FB's mission is to connect the world/provide the tools to build community.

FB falls under the latter category.

What is FB dating?

Dating feature within FB where can sign up to find potential dates around you - you take a quiz and basis that + Im assuming FB's social graph  based enrichment it suggest a set of people to you who match your preferences and vice versa.

It's an opt-in feature and available in limited countries.

Users 

FB People users opting into dating.

Product goal

The nature of product seems to be targeting towards engagement/retention.

User journey 

User finds out about FB dating -> searches for it -> Signs up/takes the quiz/profile -> Starts swiping  -> Matches -> Conversation/engagement -> offline date/meet up -> relationship ends -> user comes back 

I'd like to map the above with the AAARC funnel 

I want to focus on Engagement and retention part of the funnel given the product goal - metrics that indicate engagegment 

1. DAU and Active DAU as a % of app open DAU (Open the product and took an action)- Weekly/daily/monthly. 
2. Swiping users 
3. Matches count/user and conversations(1 way and 2 way split) count/user count 
4. Timespent per user 
5. Users taking things offline ( proxy can be number or snapchat or IG handle exchange)

I want to pick a metric for goal and health 

- Product goal/mission focussed metric: Swiping users/ users having conversation count absolute and  % of app open 
this gives a peak into actual DAU for the product vs a vanity metric like feature open 

- Product health metrics: Time spent per user and daily/weekly retention, retention is reliable indicator of product health however its a lagging metric and hence balance with time spent per user.

Time spent captures the overhall health since - swiping or conversation both will lead to increased time spent. We can further  choose to track swipes/matches user count and total count daily to get a more granular understanding of product health. 

From an FB perspcetive the goal of FB dating is to increase net FB engagement so I would want to track timespent/retention for users using dating feature to make sure Im not cannabilising FB feed users/leading to a net negative. 

Feature Description : Since i dont know much about this app , assuming its for people to connect with like minded individuals tas well to pursue long term relationships.

Goals : Facebook's goal for this feature would be increasing the engagement as well as retention of  existing users. As this comes along with the exusting facebook account, we are not actually looking at increasing users count.

Customer Journey :

User logging in -> Create dating profile -> Selects the recommended matches provided by FB -> Start conversation if interested

Metrics to measure : (using the AARRR framework)

1. Acquisition and Activation 

• No of users exploring the dating app (separate section provided in FB home page)
• No of users creating dating profile ,monthly and quaterly basis
• No of users churning out during profile creation.

• Average No of interests made by user.
• Average no of conversations per user.
• Average session time for the user

• No of users who comes back to the app and the frequency of coming back within a week , month or 45 days
• No of users who didnt come back even once after profile creation .