Burning Questions
Hey there,
Welcome to a free post of the databeats community newsletter tailored to help growth practitioners drive data-powered growth.
In last week’s post, Contextless Data Collection, I discussed the perils and consequences of collecting data without context. Today, we’ll discuss all the good things that happen in the presence of proper context.
So, when context exists, people start asking questions.
And asking a lot of questions without expecting immediate answers to every question is the only way to get better at asking the right questions – it’s a muscle that one needs to build.?
When I was leading Growth at Integromat (now Make.com – Zapier’s toughest competitor), and we were setting up our data infrastructure, I had a ton of questions.
In fact, we were acquiring hundreds of new users every day – sometimes even crossing a thousand in a day – and if we wanted to, we could have collected massive amounts of data to track everything every user did on the website and inside the app. However, as a bootstrapped company, Integromat operated lean, and thankfully so – it pushed me to think things through and question popular narratives like why it’s a good idea to collect as much data as you can.
I had been a power user of Integromat even before I joined the team in early 2018. And I’d already helped a ton of people with their questions about the product through a couple of communities I was active in. As a result, I intricately understood the product and the various personas it catered to, and by the time we started implementing our data stack in late 2019, I had enough context to start asking questions – lots of questions.
However, as I started listing them down – questions I thought I badly wanted answers to – a pattern emerged and it became crystal clear that every question of mine fell into one of two categories:
The Type 2 questions are essentially what I refer to as burning questions.
Here are two distinct characteristics of a burning question:?
Let’s look at an example:
“We’re acquiring a ton of users every day but very few end up hitting the activation milestone; what’s preventing users from performing the actions leading to activation?”
It’s specific with context baked in.
The first part of the question, “We’re acquiring a ton of users every day but very few end up hitting the activation milestone” is the context to ask something specific like, “What’s preventing users from performing the actions leading to activation?”
On the contrary, a Type 1 question is super broad and lacks context. The answer tells what’s going on but it doesn’t help understand the cause and the fix.
Here are a few examples:
Answers to Type 1 questions like these provide a bird’s eye view of the health of the business – perfect for an executive dashboard powered by a BI tool.
But a bird’s eye view is not what you’re looking for as the person responsible for getting more users to use your product more often, is it? You’re not looking for numbers without any context for you to do something to increase or decrease those numbers.
You’re looking for specific, contextual information that you can act upon immediately and continuously.
For instance, you can identify the causes responsible for a low activation rate if you have context about the actions performed by users as they move through the onboarding process
But that’s not it, is it?
When you have context, you also have the exact data points you need to run campaigns and experiments to fix the problem.
As you start thinking through the solution, you are likely to have more questions and might need additional data points in the destinations where you intend to consume and act upon the data. At the very least, you’ll need to run through a series of steps to figure out whether the issue lies with how your product works, how and when a feature is presented, or something else altogether.
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You might end up talking to inactivated users only to figure out that they had very different expectations from the product, indicating a misalignment between Marketing and Growth. By relaying the data to your marketing team, you might further learn that one of the ad campaigns being run by an external agency is driving visitors to an outdated landing page that talks about features no longer available on the free plan.
It’s good to keep in mind that context leads to burning questions, which lead to better collaboration and ultimately, better quality data. Let’s explore how.
Not just about insights??
It’s important to highlight that the goal of a burning question is not only to derive an insight but also to figure out how to run an experiment, how to do so effectively, and how to measure the impact of an experiment.?And experiments lead to additional insights which lead to more context and thereby, more burning questions.?
Growth practitioners, in particular, need to come up with a lot of burning questions that can’t always be answered using a predefined metric – questions that facilitate better collaboration between teams.
A scenario
Growth, in collaboration with Product, has decided to enable new ways for users to invite members to their workspace. While Engineering builds the feature, Growth wants to ensure that the feature is instrumented before it hits the production environment.
Growth also wants granular data to be made available in their activation tools to experiment with the messaging of the invitation emails and to send out reminders. As they think through all the specifics, they come up with the following questions:
The growth team brings together folks from Product, Engineering, and Data so that everyone is on the same page sooner rather than later. Besides massive productivity gains and cross-team alignment, doing so enables fast, accurate answers to the burning questions that follow once the new invitation flow is live.
Closing thoughts
As growth professionals, asking a lot of questions is part of our job, and investing in the resources needed to answer our questions is the employer’s responsibility. Moreover, a number isn’t the answer to every question – we need our data and engineering counterparts to understand the problem we’re looking to solve and help us figure out the best way to solve that problem (using accurate data, of course).
Also, if internal teams are not equipped to answer our questions, there’s no shortage of external help. Organizations need to spend less on technology and more on equipping people like us to get expert, unbiased, actionable answers to our questions.?
Burning questions are highly contextual in nature so let me list down a couple more. You will notice that these are unlike the ones that can be answered by running a quick query or referencing an existing report:
These are some of the burning questions I had during my time at Integromat and we’ll be digging deep into these in future posts. ?
Today’s exercise
List a few questions you’re trying to answer right now and then evaluate if they meet the criteria of burning questions:
This isn’t a quick exercise but it’s certainly one that you must initiate at the earliest.
And if you already have, well, amazing – I’d love to hear what worked and what didn’t, and maybe even collaborate on a guide based on your insights!
Coming up next
The next 3-4 subscriber-only posts will go deep into the process of getting answers to burning questions. In particular, they will help you figure these out:
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6 个月Great article, Arpit ???? . Your definitions of type 1 and type 2 questions can be used to distinguish between traditional BI vs. a more contextual and relevant style of analytics. That said, type 2 questions need type 1. In other words, you first need to ask questions like "how many daily users are we acquiring?" and "how many users are hitting the activation milestone?" (type 1) in order to use that as context to help formulate a question like "what's preventing users from performing the actions leading to activation?" (type 2). The next challenge in analytics will not be simply about answering questions. It will be about asking the right questions: questions that are contextual, relevant, and can lead to action.