Joshua Eichler-Summers
Blog of Josh Summers

Venture capitalist & founder. Lots to learn, but happy to help.
Investment Team at DN Capital
Founder of Taaalk

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The Metric That Matters

21 Apr 2015

This post is about picking the right metric for your company to focus on, what it means for other tempting metrics, the financial opportunities that nearly always arise out of doing all you can to optimise it and how understanding the core metric of a situation lets you find potential gaps in the market.

What is the metric that’s important to your company?

It’s not daily, weekly or monthly active users - I can tell you that. Those are a function of the metric we’re looking for. And don’t look too far for it, except for your direct competitors no other company will share it.

A good place to start looking is in your user journey. If you run through it from top to bottom, at some point you’ll come across a spot where the true value of your product is at its pinnacle. That point, or as close as you can get to it, will be metric that you need to focus on.

Example 1. Tinder
Example Key:
Point in user flow
Associated metric
In ecosystem or out of ecosystem

Open the Tinder app
Monthly / Weekly / Daily active users
In app

Swipe through people
Number of Swipes / Users
In app

Get matched with people
Number of Matches / Swipes
In app

Initiate a conversation
Number of Conversation Initiations / Matches
In app

Receive reply from match (or have a real conversation)
Number of Replies (or real conversations) / Conversation Initiations
In app

Exchange telephone number
Number of Telephone Number Exchanges / Conversations
In app

Go on a date
Number of Dates / Conversations (or / Number Exchanges)
(In &) off app

Go on a second date
Number of Second dates / First Dates
Off app

Find a partner!
(Pinnacle of App’s Value)

Although I understand that there are a few different use cases for Tinder (you might not want a second date out of it!) ultimately if Tinder helped you quickly find someone you wanted to spend a good chunk of your life with it would have immense value.

If we work backwards from the pinnacle point of value we can quickly see that the closest easily recordable metric is Number of Replies / Conversation Initiations and with a little work it might be possible to measure Number of Telephone Number Exchanges / Conversations which is a more telling metric in terms of match success.

This is the one that matters if you’re looking to provide deep value as a dating application. Everything above that might make your users feel good for a while, but isn’t helping them meet their deepest internal motivations.

The effect on other tempting metrics

The more you optimise for the metric that’s closest to the pinnacle of your applications value, the ‘worse' the metrics above it will become. This is the right aim though; the faster someone can achieve the maximum value that’s possible with your application, the better time they are going to have using it.

Going back to our Tinder example, you can see that the efficiency of obtaining value from the app improves as the you take the strongest signal of value (Telephone Number Exchange) and work it back up the user experience funnel.

If Tinder was able to predict who I would like with enough accuracy that I’d be a close to perfect fit with the first 10 people I swiped the app would be phenomenal. It would revolutionise the way the way that people met (period), but it would reduce the chance the Tinder team would get to say fun things like “Tinder is currently processing an average of 750 million swipes and 10 million matches per day. We’re approaching a billion total matches.” or “The average user spends an average of 60 minutes per day on the app. Fifty-seven percent of our active users are using the app every single day, an average of seven times a day.”

This can be tough! Big numbers sound great and tend to convince investors.

Note: I believe in the same way investors moved away from total number of visits or total number of signups as a metric to value things by (1999), they will move away from MAUs and focus increasingly on measuring company dependant metrics.

Strong management beats temptation

A great example of a company that knows its core metric and has had the courage to ignore the short term upside on other highly tempting metrics (and positive press coverage) is Facebook.

Because of the vast number of ways it’s used, it’s hard to pin down the metric defines the pinnacle of Facebook’s value. I believe that Facebook’s product is predominantly about the network of real friends that extends beyond your circle of immediate friends (your phone contacts). You can do a lot with these relationships - message people, check out what they’ve been up to, invite them to events, etc… - but it all comes back to the ability to easily find and ‘friend' real people on the platform.

Facebook has persistently pursued this metric despite short term negative reactions:

  • In August 2012 Facebook told investors that there were 87 million (8.5% of total) fake or duplicate accounts on the platform. This caused FB stock to slump below $20 for the first time.

  • In October 2014 Facebook introduced their real names only policy. This led to the shutdown of accounts that looked suspicious - which happened to include the real accounts of many Drag Queens and Native Americans. Despite thousands signing a petition against the scheme, Facebook stuck with it (while introducing policies to deal with these specific cases).

  • During this cull of users many brand pages saw their number of likes drop significantly (not the most enjoyable experience if you’d been paying for Facebook ads to increase that number).

Imagine what weaker management would have done. How easy it would have been to change an internal policy to say that Facebook now let you have as many accounts as you wanted so that it didn’t look bad to investors in 2012. Or to go back on its real name policy in 2014 to reduce the press and user backlash. But it didn’t do either of these things because they knew what metric that mattered and had the strength to focus on it.

It’s common to hear long term thinking be praised - I think knowing your metric and putting its optimisation above anything short term is a sensible guide.

Money from the metric

Optimising for this metric nearly always creates two opportunities for monetisation - a dirty one and a clean one.

Let’s look at Tinder again. Recently they’ve introduced a limit to the daily number of swipes. This has been designed to stop the tendency of some groups of users to swipe ‘like’ unconditionally. ‘Fake likes’ lead to lower quality matches, fewer established conversations between matches and a reduced user experience for all. This daily limit means that people treat their, now scarce, likes with more value and think before they swipe (improving match quality).

It also opens the door to make money. If you want to be a badly behaved user you can be - but it costs. For ~$10 a month you can get your unlimited likes back. This is the dirty method: you improve the user experience for all and then let people pay if they want to continue polluting the platform.

Facebook could have done the same with it’s user accounts. If you want to keep your fake profile you can - but it will be $5/month.

Taking Tinder to the other extreme reveals the clean monetisation route. If the matching ability was so powerful that anyone using the app can feel confident they’re going to find someone special in a short period of time the willingness to pay for the experience (either with money or via extensive ads) would go through the roof.

I think the choice to go dirty or not depends on the value that you see on the other side. Facebook probably believes that a platform where a billion+ people are having a great time has far greater value (from advertising) than a billion+ people having a good time plus 10 million people paying $5/month.

Tinder may believe that they’re never going to get telephone number exchanges / match up to a suitably high level that people will be willing to throw money at them to use the application, so going dirty is the logical choice.

Know the metric, find a gap

Understanding the metric that matters in a particular use case lets you spot gaps in the highly crowded tech ecosystem.

Going back to online dating again; it would have been very easy to see the rise of Tinder and assume that it was a shut market. But if the the question becomes ‘can we do something that improves the number of second dates / match?’ the opportunity looks quite different.

Hinge is a company that’s taken this position. Instead of swiping with anyone near by you only swipe with people that are part of your extended network (via trusty ol' Facebook). The idea being that someone you share a connection with will make a better fit for your life. And it’s working - Tinder is for hookups, Hinge is for relationships writes TechCrunch.

So have a think! How are you creating value for your users? What can you measure that comes closest to that? And what are you doing to optimise that number?

I work at DN Capital as part of the Investment Team and I want to know about your business. You don't have to be raising funds today, it's always good to say hello.

Please write to me with a one or two paragraph description of your business and where you are currently (10,000 registered users, 500 paying, etc...). Feel free to attach a deck if you'd like.

I'd love to help you out too, so if you have any questions you'd like to ask a VC please reach out and I'll do my best to get back to you. (There are no stupid questions!) Email me at josh(at)
I am also the founder of Taaalk. A platform for observable conversations about interesting things or between interesting people. Here's an example of one between my good friend Robert Heaton and myself on the topic of chess: link.

Please check it out, and if you feel you're an interesting soul, that you know one or would like to interview one yourself - reach out to hi(at) or hit us up at @gotaaalk on Twitter.
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