A Look at Facebook Dating through the Lens of FriendsPlus

In 2013, I led a team to create FriendsPlus, a mobile app that was acquired (and killed) right at launch.

It turns out Facebook’s new dating app, announced last week, is very similar. Let’s see how Facebook talks about it:

Facebook Dating product manager Charmaine Hung tells me that “I have 2,000 Facebook friends. I’m not best friends with all 2,000 people, and there’s a good chance that one of that could be a really good match with me. I trust them, I appreciate them and I know we’re compatible. The only thing missing is knowing if we’re both interested in being more than just friends without the fear of rejection if you were to do this in real life.”

Let me first share how I talk about FriendsPlus on my LinkedIn Profile, with my intro deck and a screenshot below.

Dating service acquired in 2013 by Vietnam’s largest dating community, Noi.vn.

► Recruited and managed 5 person cross-functional team to produce FriendsPlus, a social / local / mobile dating (SoLoMo) app for iOS and Android.

► Created service targeted towards professional-age females, emphasizing real relationships to make romantic connections in contrast to typical male-oriented “browsing”​ dating services. Product Manager.

► Led startup to acquisition of application and technology platform.

An overview of Friends+ as pitched to investors and later, acquisition partners. The application and technology platform were acquired pre-launch in Q4 2013 by Vietnam’s largest dating service, Noi.vn

I first started work on FriendsPlus in 2013 while I was COO at Cyworld, a social networking service. When I first arrived in Vietnam in 2006, it was still common for women to get married as early as age 18 and slightly older for those who went to university. My theory is that limited life options in education or careers streamline roads to marriage and children.

As women started to build great careers in the blooming (tiger) Vietnamese economy, there was less time to focus on relationships; some of Cyworld’s female employees became increasingly frustrated at growing older but not finding marriage partners.

Going deeper into the problem, traditional methods such as matchmaking could be a bit archaic or difficult if a woman was working away from her hometown. Dating apps like Tinder were primarily focused on (ahem) male psychology; women needed a digital tool to help them meet people in a way that still felt conservative and true to the values (less about hookups) with which they grew up.

After hearing about these problems for some time, I decided to take action. I formed a new company to help my female employees find love: FriendsPlus.

From my user research, I learned that Vietnamese women did not want to meet random people. At the same time, it was not yet culturally acceptable to make the first move (unless you were my future wife).

My problem was how can you bring two people together in a natural, almost magical way?

The solution we proposed was: serendipity.

At the time, Facebook was already the most popular (sigh…Cyworld) social networking service in Vietnam, and you could still pull in friends lists from the service. We let users connect their Facebook accounts to FriendsPlus and select up to the second degree of friends (friends of friends) of people they were interested in as “romantic crushes”; the idea was to include your friends and people that you might have known or seen occasionally but were still a bit shy around.

From here, the app was “set it and forget it.” As other people started to use the app and set their own crush preferences, our system would monitor when two crushes were in close proximity (ex. 1KM away on a weekend afternoon). If you were both around each other, the app would ping you and try to convert you two into meeting – this would also be the first time you knew about each other’s mutual interest. This was a magic moment that might not happen again for a very long time.

FriendsPlus was about removing frictions to create a real meet up and opportunity at love. One point that spurred furious internal argument was leading users to meet offline in the real world instead of to chat. My argument was that if you start chatting, it’s easy to postpone a meet, and basically never meet. Chatting was also what every other dating service did; I felt that the case for chat was the common mistake of seeing what everyone else was doing and assuming you needed to do the same. FriendsPlus needed to be clearly different in how it operated and generated successful outcomes for users.

If you have noticed, however, FriendsPlus had a problem, at least in comparison to social apps of the day: engagement. In 2013, success was about creating addiction, a problem we understand more clearly in light of Facebook, YouTube, and fakes news /  junk content / data privacy. FriendsPlus was a utility that only appeared in your life when something special was about to happen.

Thus, there wasn’t a clear business model (though we could have highlighted places to meet as ads, that ad volume would have been low) or virality. Before launching, we also added ways for people to meet people at random, my homage to ChatRoulette. You can see a preview of that below.

Friends+ Screenshot – Finding People Nearby

FriendsPlus Screenshot.jpg

Feature: Allowed you to propose a meetup right now based on the type of activity and person you would like to do and meet.

To be honest, the app was not going to be easy to launch and have traction grow on its own; this is why I ended up selling it to Noi.vn, Vietnam’s most popular dating service. Noi never launched the app either. I suspect it was hard to get internal support for something that did not work on traditional engagement metrics.

Going back to Facebook, its Dating team is going to face the same issues in defining success. After you set up crushes, what do you do?  FriendsPlus would wait for that magic moment, but if the user does not take action right away with Facebook Dating, she will not go back into the app. It’s also not like you add new friends (I guess this rate declines with age) constantly and consistently over time and can be reminded to set new crushes.

I imagine the real-world usage as follows: I set some crushes. Some time later, as not all users will use the app at the same time, a crush of mine may also use Dating and set me as a crush. Facebook whisks us into an awkward chat:

Facebook: “You guys seem to be crushes. Go chat!” (at a random time of day in which the pair may or may not be busy)

Me: “Hi”

You: “Hi” (anywhere from immediately to days later, have you seen how the modern generation replies to messages?)

Me and You: [Uhhh, what now?] (Hopefully, not a dick pic)

Potential awkward fail, at least based on how the app is described in the TechCrunch article.

The Facebooks and Googles of the world get easy media attention any time they release a new app. My impression is that most of these apps are tests from product teams that need to build out their resumes. These apps are not real businesses; they get 15 minutes (seriously, go search Techcrunch) of media attention and die out months later.

While this sounds like a humble brag, I claim this more about my failure in social products: I feel I hit my peak as a social innovator in 2012/2013, seeing pain points and constructing social utilities to solve them on a monthly basis. Because I was in Vietnam, these ideas died; I could not get investor support for anything without clear virality (“build it and they will come” and gamification are not strategies) and revenue models. (Cyworld and Mimo failed in significant part because unlike MySpace, Facebook, and Snapchat in the West, we had to grow users rapidly and make money.) Months or years later, I would see these same ideas I had get millions in funding in Silicon Valley, like Facebook Dating. They unsurprisingly all failed, though perhaps some like FriendsPlus in Vietnam eventually got acquired.

That is what I expect to happen here.

My Facebook at Work Launch Analysis – September 2015

As with my Minecraft post, I do have an ego-driven need to see my insights proven correct. (Don’t worry, I know I am often wrong) Below is a slide deck I put together in an interview with Facebook for Facebook at Work (now called Workplace) in September 2015.

After 1+ years and only thousands of paying users and questions about what how the site should be used, however, perhaps my Slide 5 was onto something.

Facebook claims it has already signed up “thousands” of paying subscribers to Workplace Premium, spokeswoman Vanessa Chan told CNBC. Facebook’s name recognition and user familiarity could be a major asset that should help it muscle into the marketplace. But the social media site needs to overcome the perception that the site is a productivity killer at work and convince employers that staffers will be using the tool for work, not social purposes.

Silicon Valley Business Journal – April 2017.

Secret Pro Tips for International MBA Students who Want to Work in the United States

As a former Northwestern Kellogg MMM (MBA + Masters in Design Innovation), I’ll tell you something that you want to know but that no one at Kellogg will ever tell you:

Secret Pro Tip:

If you’re an international student who REALLY wants to work (and  / stay) in the United States (USA) after graduation, invest in the MMM program.

Here’s why:

  • As an international MBA student in the US, you will be on a F-1 Student Visa for full-time students (if you are an exchange student, you will be on J-1). You are allowed to work up to 1 year in the USA on OPT period (Optional Practical Training), given that you find a job no later than 3 months after graduation.
  • In the unfortunate situation you have not found a job three months after graduation, you must leave the United States.
  • If you find a job with a company that is willing to sponsor your H1B Visa, you enter a one-time lottery for the H1B Visa. The probability of winning this year (2016) was just 40% for those holding a Master’s degree from the US. The odds were lower if you only held a Bachelor’s degree. Generally, this percentage becomes lower with each passing year due to increases in demand (from people like you who are reading this).
  • If you lose the lottery (odds are you will), you go back home.
  • Now, with MMM, the M.S. in Design Innovation is an engineering degree (that does NOT require an engineering background) from the McCormick School of Engineering at Northwestern. This engineering degree allows you to stay in the US an extra two years (3 total) and participate in the lottery a total of 3 times.

It can be said that the MS DI program is not really an engineering program, in the way that most people think about engineering (hardcore math & science). Nonetheless, it’s classified as an engineering program.

Beyond that are the more traditional reasons to be part of Kellogg: long-time elite business school brand, the amazing new all-glass lakefront building, rise in the rankings, leading percentages for diversity in gender and internationality, continued emphasis on tech, and my articles on the experience). Plus the MS in Design Innovation offers a great core of classes that will help you understand problems from bottom up (“what is the user/customer thinking?), rather than just top-down (“well, it’s clear from the financials, we have too many employees, let’s just fire them”).

All that sounds sound great, but let’s be real. The reason you go to business school is to fulfill your professional goals. If your goal is to be in the United States long term, apply for Kellogg MMM.

The simple math: at today’s acceptance rates, you have a 60% chance of getting rejected and having to leave the country after one year. With MMM, you can stay at least three years and the chances you will end up having to leave the US without a Visa is only 21.6%.

Is this worth an extra quarter of tuition? Of course it is.

The Case for Yelp User Subscriptions [Product Monetization, Revenue Ideas]

Yelp

Yelp’s financials have been fairly strong lately, and with $550M projected revenue for this year and the aim of getting to $1B (82% jump) in 2017, the company will need to be open and aggressive about new revenue steams. Let’s explore how to generate an additional $100M (conservatively) in yearly subscription revenue that would directly monetize (and further diversify revenue streams) Yelp’s most loyal users, generate data that can improve the overall service, and avoid conflict with existing advertising partners. (note: my sister used to work at Yelp as an accountant, but provided no information or insight for this article.)

Yelp Power User Subscriptions

The basic premise is to provide additional functionality for a subset of Yelp’s users and charge them for it, but using the benefits from their usage to positively impact the service for all.

Personalized Recommendations – Replacing “Best Match”, Netflix Style

The problem with Yelp reviews, as with many review systems, is that actual results are skewed. On a 5 point scale, one might think that 2.5 / 5 would be an average venue. However, for Yelp, the average score is more like 3.8. And while Yelp may want people to be forced to dive deeper (Virtually identical ratings mean people have to dive into reviews to understand what’s different, said Vince Sollitto, who heads communications for the San Francisco-based company.) into reviews because these scores make it harder to differentiate among venues, this is not a very user-centric, empathy-driven approach. In fact, this is better for venues and Yelp – the more venues are better ranked, the more open venues will be to working with Yelp on advertising. The more venues are better ranked, the more people will visit them. This is a clear conflict of interest.

I would like to see smarter recommendations with the option of going deeper into reviews only when I want to. If you have ever used Netflix’s recommendations system, you understand how this could work. As a user creates more reviews, the system is able to predict which others users are similar to that user and provide predicted rankings for new venues. Admittedly, this only works if you and other reviewers have a common set of visited locations and would thus work best in places you live in. However, if you visit a new place, Yelp could use your demographic data to create a profile that may match other users in new locations – there are a number of different approaches to predicting responses without historical data, and this would be a very useful data experiment to create value across all users.

A simple story to explain the need for personalized recommendations comes from a friend. She is Vietnamese and went to Palo Alto in California for Vietnamese food. It was not only expensive ($50+ per person) but terrible. Yet, people in Palo Alto love it and review it accordingly. With a personalized recommendation, I would be steered away from this place despite its positive reviews and to a place that people with my tastes enjoy.

Personalized Recommendations – Incorporating External Data

In addition to predicting scores and using that to sort recommended places for each individual user, Yelp should incorporate external data. While user ratings are great, I also want to know what has been featured on TV (Bourdain) or has won awards from professional reviewers. In many ways, that data already exists on Yelp, created by users – for example, search for “Michelin” and you should find a good list of Michelin-places in that city. These metadata should be officially added into listings. Such locations would automatically receive a bonus in the personalized recommendation scoring or include special badges, and users who value (and visit) them would see more such venues in their recommendations.

Normalized Review Scores

Beyond ranking places for the individual user, scores should be normalized over the last one year of reviews using the full 1-5 spectrum. Ever see complaints about a restaurant that changed ownership recently? Or a place that lowered its quality standards after building a strong reputation? How good is this place right now? Current Yelp review scores don’t take currency into effect very well. I want to create clear separation in order to compare places more easily. How much better is this place than the other place?

While the math to normalize is pretty easy, the process (by area radius, venue category?) to do so is a little complicated and would need to be tested to finalize on format.

Getting More Data – Allowing Data Export and Pure Numerical Reviews

Although Yelp has the most user-review data of any source, it creates barriers preventing additional data that could be used for the product features mentioned above. For example, I am very uncomfortable with Yelp owning my data and making money off of it, thus I would rather write on this blog than for Yelp. I do not need Yelp to share money with me, but I would like to export my data (reviews, bookmarks, check-ins) for myself.

In addition, Yelp forces reviewers to write reviews. I prefer the IMDB method which allows both numerical-only ratings and detailed reviews for those who like to do so. To see the stark difference this can make in conversion and user data, my IMDB history has over 1,100 reviews (average of 70 per year) while my Yelp has 2 after eighteen months.

And More

It is unlikely I will ever be a Yelp Elite because I am not much a Yelp community driver. However, that does not make me a non-active user. I am joining a couple of official Yelp events below soon, but would like to see more, with exclusive slots set aside for paid Yelp users as an added benefit of subscription.

Yelp Events

Paid subscribers should have the right to opt-out of ads (but can be on by default) and receive exclusive promotions (offers) for subscribers from businesses. Similar to social media ads on Facebook and Twitter, users would be allowed to vote for or share promotions in order to show interest. As on Google Adwords, advertisers who are just paying to spam users would have to pay more as a penalty for being less relevant. This would create a win-win scenario for both users and businesses who truly care.

I would like to see the ability to review individual plates or meals, not just the venue. Not everything a place serves is equal in quality, and I would like reviews to be broken down into smaller components such as service quality. Some styles of restaurants are affected by lower grades of service, but often I do not care about that. I just want to know what is the best food for a best price, and there is no way to quickly determine this. Yelp should be making this possible!

Revenue Forecast

This service would be provided at $5 per month or just $30 per year for annual subscriptions. Imagine the $5 per month as a perfect solution for travelers visiting a new location (ex. 4 day trip in Chicago) and needing to know the best places specifically for them. It’s not too much different from buying a travel guide. Perhaps only yearly subscription users would have certain features such as the history export, but I think that numerical-only reviews should be opened to all. I use $30 per year as a personal preference that seems reasonable to me but also as a stark contrast to paying the per month fee ($60). Fees would be due at the beginning of any subscription period, providing Yelp instant cash flow, but could be refunded at a pro-rated level. Yelp Elites could be given free subscriptions.

Yelp currently has approximately 150 Million Users (including international markets). To reach $100M in yearly subscription revenue, just 2.22% of these users would need to subscribe – I believe (based my own experience in social networks) that this number could reach 5%. Please note that I have simplified the calculation, not accounting for regional user / wealth populations, single month purchases, future growth, mobile vs. desktop, and new ad product growth for subscribers, etc.

If you are thinking you would never pay for such features, that is ok! You are one of the 98% who would not need to. However, I am one of the 2% who would. 2 out of 100 people is fairly low on the requirement side.

Stakeholder Impact

Since Yelp is trying to reach $1B in revenue in two years, they clearly are concerned about their existing sales, which has been slowing in growth the last few years. Although paid subscribers could turn off ads, by keeping them on by default, Yelp would reduce impact on the ad impressions removed. Normalized Reviews could impact businesses, but this would only be available for subscription users and would be a complimentary score to the existing system – most people could still remain confused (yay!) by the overly positive Yelp review system. Yelp’s current display of Google Display Network ads would be minimally affected.

A great benefit of reducing the review barrier and allowing numerical reviews is providing more data that can be used to promote businesses, which in turn helps businesses. In particular, this would help smaller businesses with less than 100 reviews because they have the most to gain from more reviews. (If you are concerned about fake reviews with the numerical-only system, there are different ways to filter and normalize that data as well) Offering advertising access to paid subscribers also creates new revenue opportunities for Yelp and focused opportunities to improve the perception of the business. Paid subscribers are more likely to review and create content for a business and Yelp helping businesses get subscribers in the door first is a more cost-effective method to seed business perception.

Recap and Conclusion

Here is a recap of my proposal:

For All Users:

  1. Enable numerical-only reviews, with breakdowns for specific aspects, such as service quality and food quality (but not required)
  2. Enable dish-specific reviews, numerical and tagged text reviews
  3. Enable personalized recommendations, IMDB-style, based on past review history and incorporate external data such as Michelin and TV mentions – do not show predicted ratings

For Premium Users:

  1. Normalized reviews for easy comparison, including recency data
  2. Show predicted ratings for personalized recommendations
  3. Op-out for ads
  4. Exclusive targeting from advertisers for promotions, using Google Adwords and Facebook style feedback to penalize spam
  5. Subscriber-exclusive invite slots for official Yelp events
  6. User Data Export

Revenue:

  1. Conservative estimate of $100M in revenue (150M users * 2.22% * $30 /year / user)
  2. Not including monthly one-time payments for “tour guide” like service
  3. Long term potential of $225M (even with no further growth of userbase)

Yelp is in competition with Facebook, Foursquare, Google and others for local advertising dollars. Despite Yelp’s data trove, it can do more to get more data as well as create more value to its users through that data. Over the long term, this would create more loyalty lock-in to the service, even without forcibly locking users in (as it does now). 

I welcome all comments and thoughts below!