Growth Hackers Only Have One Metric of Power
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Date One Magic Trick to Keep Growing
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A growth hacker secret guide to solving why a/b tests go awry. One of the most simple way to solve growth problems is to make sure all tests, campaigns, whatever, are designed to optimize only one metric.
Transcript of Growth Hackers Only Have One Metric of Power
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One Magic Trick to Keep Growing
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Our friendly witch, Jordana, has been having a problem with her brand hacking
She’s Been Running A/B Tests
✤ A button
✤ Some copy
✤ Asking people to like her site
After an A/B Test, the button went up
✤ And then it went down again
The same thing happened with the Copy
Adding likes also saw a huge spike and dip
Why were they all losing their gains?
She’s missing her metric of powerOne metric to rule them all, one metric to bind them!
What is the Secret Magic of the Metric of Power?
✤ Math, particular an area called mathematical optimization. It is - given F(x) what x would make F(x) return the largest number?
✤ F(x) - Her End Goal of her site. x- The answers to her tests.
✤ Different tests Jordana performed will cause a different answer to F(x)
✤ If she figures out what x to tweak to make her master metric grow, then she figures out how to make her site grow.
Before her metric of powerShe would only check the matching metric and choose based on its result. Apparently her other testable metrics mattered in the long run!
Button Test
Clicks Pageviews Likes
Version A 10 ? ?
Version B 15 ? ?
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“But,” She sighed, “I have multiple goals!”
Well, (we reply), which ones matter the most for making your startup stick around?
“I think I can identify what makes my startup stay around.”
My goal is equal to the following:1 like is equal to 2 button clicks, and seeing a page equals 1/2 a like. That’s our new metric of power.
She ran the cumulative results from her previous tests “Oh no!” she realized. “By ignoring all the other metrics in a test, I ended up making my site go down against the master metric”
Button Test
Clicks Pageviews Likes
Before 10 10 10
After 9 9 9
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“But I still don’t know how to run my tests around my One Metric”
Scale them to the master metric. For example - if your master metric is pageviews:1 Opened email is the same thing as half a pageview. 1 clicked on email: a pageview.
Note that the master metric can be anything. You should choose something relevant to your business model though.
How did your A/B test for your emails perform in terms of pageviews?Answer: (opens/2 ) + (clicks)= total pageviews generated by that test.
Button Clicks Likes PageviewsMetric of
power
A 10 10 10 35
B 16 8 8 36
The first test:Did her metric of power work?
✤ She tested a new button - and her metric of power worked!
✤ `
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She started to run tests againEach interpreted against the one metric.
Over time, she found her metric workedHooray!
Suddenly, other benefits kept coming.
✤ She found it easier to choose what to build each sprint, since she could choose what would have the most measurable impact through her testing process.
✤ She figured out what kinds of products and APIs in her startup actually mattered to long term growth.
✤ She was easily able to start and stop ad campaigns, since she knew which ones were most impactful.
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Secret Bonus Hack
To make the premise of one metric more concrete: Assign goals in Google Analytics dollar values. Run your tests on the basis of what makes you the most money. Even if you are pre-revenue, it will make running tests feel more concrete since you are tying it to cash.
![Riga Growth Hackers meet-up [January 2016]](https://static.fdocuments.net/doc/165x107/58889fca1a28ab264b8b5aa9/riga-growth-hackers-meet-up-january-2016.jpg)
