Telling Better Stories with Data: The "So What" Approach

by Sarah Bedrick November 3rd, 2022

When I started reporting on metrics on HubSpot Academy, asking myself this two-word question, "so what?" became my cheat code for success. 

It cut through my mental clutter and helped me to see which data was worth sharing in its current state, and where I could focus my attention to start digging even further. 

By continually asking this question, the metrics we were able to uncover became increasily more impactful.

Here's an example of how one data point evolved: 

  • V1: HubSpot Academy generated 10,000 new leads this month.* So what? Well..
  • V2: That is 10% of the company's new net leads this month.* So what? Well...
  • V3: Academy leads are 5x more likely to close than those who download an ebook.* So what? Well...
  • V4: Academy leads also have a higher average contract value than any other lead source.

(*exact numbers not included)

The first metric above combined with the "So what?" approach allowed me to take a crawl, walk, run approach to metrics, which eventually led me to valuable metrics on impact.

Asking myself this question is one of my favorite lessons I learned in telling meaningful stories with data.

The "so what?" approach

If you're able to overlook it's inherently condescending or hostile tone, it turns out it's actually a very helpful question to ask yourself when trying to improve the stories you tell with data.

When you can answer the question, you provide context, which helps you to tell the story of why this data point is worth tracking and why it matters.

And if you can't answer it, it makes it clear that more digging to uncover the value might need to be done.

"So what?" in practice

To further explain the concept, here's an example:

It's best to start with some metrics you already report on internally. Pick a few you regularly share at monthly meetings or quarterly reports.

Here are a few we've heard of people tracking before:

  • Number of new learners in LMS
  • Current active learners
  • Total hours of learning
  • Total enrollments
  • Number of course page visits

To put the approach into practice, you'd ask yourself that question at the end of these data statements. It would look like this:

  • We had 1,100 new learners in our LMS. So what?
  • We have 950 active learners. So what?
  • There are 2,100 hours of learning time. So what?

Notice how it's challenging to answer the question.

Why asking "So what?" is powerful

It forces your thinking.

By asking, "So what?" you're forcing yourself to identify, explain, or find a reason for why you and others should care about this data.

It contextualizes the data.

By including your answer to "So what?" when sharing data, you educate others why you're reporting on this metric, find it valuable, and why they should care too.

As mentioned above, it is the story about why this data point matters.

You preempt what others are thinking.

Most people are already inundated with their own projects, meetings, and data -- and unless you can connect the dots for them, people are usually left asking this question anyhow.

Just as a good sales rep answers an objection before it arises, being able to provide context into why a data point matter addresses people's questions before they have it.

Strive always to have the answer to this question when reporting on metrics, especially ones you share with others.

Interesting data < important data

By asking "so what?" you're sharing data that's worth people's attention and focus.

Callum Ballard makes this point in this piece on the "so what?" approach:

"Having spent five years in Management Consultancy, conflating things that are ‘interesting’ with things that are ‘important’ is a mistake that I’ve seen all too often."

You gain insights into what data to look for next

If you're overwhelmed with data in general, starting with a few key metrics you have access to right now, and use the question to guide you in a helpful direction on where to probe next.

What to do if you cannot answer "So what?"

If you cannot answer it right now, it likely means that you need to do one of these two things:

  1. Start digging to uncover why this matter matters. It's natural for many initial data points not to be able to answer this question, but the trick is to use it to help you identify where you can start digging for meaning. For example, if you're reporting on new learners, see if you can find a thread about why this number matters. It is a great metric to report on if you can identify what each new learner does for the business. Maybe your learners go on to increase their usage of the product? Or people who start off learning give a better score on an NPS. Or do these people submit fewer tickets to support? Following the thread of what happens next with these new learners can give you valuable insights that will make your data point highly valuable.
  2. Or find a new metric to report on. Move on to another, more promising number. Then invest your time and energy in getting a helpful answer to "so what?".

But before you give up on that number, see if the trick below works for you.

A tip to answering "So what?" 

If you can't tie your metric to a meaningful impact on your business, a tip would be to reference industry benchmark data.

You might use "So what" to formulate and then share an answer like this:

"We had 950 new learners in our LMS. So what? Why does that matter? Because this shows that 40% of our new customers are going through training -- which far surpasses the industry-reported average that only 29% of customers are engaged in training.
And why that matters (here's another "so what?" again!) is that the industry also reports that companies with formalized education programs see a 7.4% increase in retention. And while it will take a while to determine the retention of these new customers, our 40% account penetration is an excellent leading indicator of what is possible to come."

While the customer education industry has more benchmark numbers available today than before, this tip may only be feasible for some of your current data. But it's worth giving it a try.

What do you think? How might asking yourself, "So what?" change what you report on and how?

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