You’re measuring the wrong metrics 📊

Too many technology startups don’t have a clue when it comes to metrics.

They don’t know what to measure, how to measure it and, more fundamentally, why they’re measuring it.

This isn’t just reserved for the two-person early stage startup either, I’ve witnessed startups with millions of dollars of funding make the same mistakes. In fact — it’s more likely in the latter stage high growth startups.

The startups are collecting the wrong data and formulating strategy without understanding their funnels, audience, or product.

In this article I hope to point you in the right direction. My mission is to help you recalibrate, pause for a moment, save some cash and execute upon the right strategy with the right data.

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First, you’re focusing on marketing too late

Time and time again I see founders too focused on “building”.

After all, it is easier to report and update investors with “we’re building and improving, v2 is coming soon” rather than pay attention to the cold hard truth of metrics.

This is why you should always start with the customer and work backwards. Focus on the MVP, ensure your building something people actually want and need. There’s a reason Amazon starts with “Customer Obsession” in their Leadership Principles.

Don’t be the person who thinks by creating “the best in class” product the users will just somehow find you. I have lost count of the number of founders who tell me their primary acquisition strategy is word-of-mouth and virality. They just expect the flood gates to open once launched. They won’t.

Marketing, and within that — analytics, will let you understand if you are building something people want. How often do you speak with your customers? And not just a net promoter score from Delighted. When was the last time you actually spent more than 5 minutes speaking with one of your customers? What did you ask them or what would you ask them? How would you translate that into understanding if you are solving a real pain for them?

Every business has a funnel — you need to understand yours implicitly.

This includes understanding the psychology of your audience at every level of the funnel. What they are thinking, what are their needs, what pains they need relief from. The only way you can do this is from a mix of quantitative and qualitative data, with clear hypotheses.

You do this by starting with strong marketing expertise on your team. It’s not rocket science, one of the co-founders could make it their domain to start with — just read a tonne, watch a bunch of videos and speak with people who have been there before. It’s not rocket science.

Long story short, product is not > marketing. Both need some deep thought, both are reliant upon one another.

Second, your focusing on too many metrics.

Have you signed up to Geckoboard? Was it just so that you’d look impressive to investors if they ever doorstepped you? How often do you get meaningful insight from your dashboard? And I mean truly business critical decisions being made as a result of your dashboard. In the past when I made this mistake, the only thing these dashboards gave me was a general unconscious sense or feeling that something was improving or worsening. But not why.

The problem with Geckoboard is you feel you have to fill the whole screen. This means next you’ll be filling your dashboard with meaningless statistics just to make the screen look pretty. Furthermore, you have to fill the screen with their templates — unless you invest significant time in building your own. Hence, the value is straight out the window from the get-go. If you’re using some basic template (e.g. last 7 days revenue, compared with the 7 days prior) it will more than likely tell you nothing actionable and just waste mindshare.

Google Analytics, Mixpanel, Sumo, Moz, KissMetrics, Localytics, Adjust, Optimizely, the list could go on and on — all of these provide metrics tracking for websites. Which one do you think is most important?

At the start, none of them.

You should be able to tell if your startup is solving a real pain point without the need for the above, at least for the first couple of months. Focus on one key thing.

E.g. number of emails collected from landing page.

Too low? Why? Is the value proposition explained clearly enough?

Gathering some email addresses? Reach out to them ASAP, offer them some Amazon vouchers in return for their time to talk about the product.

The highest value “plugin” that I have used for some of my startups in the past (especially in their early days) has been FullStory. Why? Because you actually get to understand your audience. Where does their mouse go throughout the whole time they are on the website? Is everything where they expect it to be? Is there anything that is confusing a large majority of the audience?

Imagine if you’d installed Google Analytics; you’d be confused and waste time slicing and dicing your data in every direction.

For sure install the services mentioned above and have the data being collected, but don’t make them your go-to resources to start with. Don’t over engineer the problem.

Third, you’re focusing on the wrong metrics — typically vanity metrics.

Cost per install, cost per click, number of installs per day, number of unique visitors — they’re typically pretty useless indicators. They’re just numbers.

You really need to understand the drivers of these high level numbers.

  1. Cost per click decreased yesterday, why?
  2. We adjusted our bidding schedule, why?
  3. We had a hypothesis that our core audience were most active online between 6pm and 8pm; thus allocated spend there.

Hence, instead of the key metric being cost per click, the key metric was segmenting the converting traffic, understanding the commonalities between those who converted, and noticing that a higher percentage converted at a certain time of day.

You need to start with a hypothesis. Without a hypothesis, you’re just guessing and reporting on guesswork. If there isn’t a structured approach to success, you’re just hoping that your product will do all the hard work and you’ll end up burning through all your funding.

After you’ve come up with a couple of hypotheses, you then need to identify, collect and analyse the data. Again, this doesn’t need to be rocket science and can be a mixture of qualitative and quantitative.

Finally you need to understand how the above impacts your strategy and what the plan of action from there, to improve, is.

If you are struggling on how to frame your hypothesis, or what questions to ask — do the “5 whys” exercise. Asking why, and going deeper and deeper will eventually get you to key core metrics. Usually they will surprise you. It will surprise you how one small thing, you hadn’t thought about is having such a huge impact.

Hopefully this article helped point you in the right direction; over the next couple of weeks I will go into more detail for each type of startup and the key metrics they should be tracking as well as going through the typical funnel.

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