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Data is man-made

This post will take you about 4 minutes to read.


Here’s a secret from the support team at Highrise. Customer support metrics make us feel icky.

Our team doesn’t know our satisfaction score. We’ve never asked any of the people that use Highrise to try those types of surveys.

We can’t give you an exact number for our average response time. It depends. Sometimes it’s 90 seconds, and other times it’s within 24 hours.

We can’t tell you our average handle time for an issue. Our team has a general idea, but no exact number.

These types of customer support metrics aren’t wrong. We’re sure they work for other support teams.

We’re just not sure they’re right for us.

Because there is one piece of knowledge we’ve come to realize: data is man-made.

What do you mean data is man-made?

Data or metrics or stats are all man-made. A human decides what to measure, how to measure it, how to present it, and how to share it with others.

But why does it matter to measure these things? And what’s the point?

A lot of times people avoid these questions when it comes to data. Companies copy what other teams measure, ignoring the fact if it’s important to measure the same things in the same way, or if it’s even important to measure it at all.

But isn’t all data objective?

Many people view numerical data as more trustworthy than qualitative data.

Clayton Christensen, Competing Against Luck

Numbers are black and white. Concrete. You can trust the numbers.

Right?

Nope. Almost all data is built on biases and judgement. Because humans are deciding what to measure, how to measure, and why to measure.

Numbers fit perfectly into a spreadsheet or a graph. A number gives a definitive answer to questions like how much or how many.

That doesn’t mean you should treat those numbers as insights and act immediately. Data shouldn’t be used to prove a point.

Data should be used to fuel your imagination.

Words > Numbers

Qualitative data isn’t easy. There aren’t any formulas or simple math. It doesn’t fit into a spreadsheet. It doesn’t answer questions. It’s not black and white.

It’s colorful. Messy. Qualitative data creates more questions. It’s not simple to present or share with others. It takes some time.

Our support team has found one thing to be true. Qualitative data is worth it. 100 percent worth it.

For example, our team recently updated the filters in Highrise. This update was to an earlier revision to filters we made during the year.

It wasn’t driven by one piece of data. One piece of quantitative data. It came from a new user:

Thanks for pointing out those filters. I didn’t even know they were there. Those icons weren’t obvious to me at first.

This hit all of us across the nose. The filters looked better, aesthetically it was a much more clean than the previous design. But how to use the filters wasn’t as obvious any longer.

Folks need to find a specific set of contacts in the city of: Chicago, that have the value: Interested in the custom field: Status, and that are tagged: Potential.

It wasn’t clear how to do that, so our team made a change.

new-old-filters.gif

Quantitative data didn’t tell us we needed to make this change. It was all qualitative.

Questions from customers and questions from our team. It was a conversation. There is not a numerical value you can put on that.


So what do we measure?

Instead of striving to lower our average response time or improve our customer satisfaction score, our support team is aiming for something a bit different. Something harder to measure. It’s not a number.

As Alison would say, we strive to put ourselves out of work.

Don’t confuse that with us not wanting to work at Highrise. We love it, and love working with our small team.

What we mean is we want to make it easier for people to use Highrise. We want to create a product that is so obvious and so easy to use that we seldom get questions on how to use it.

And when folks do have questions, we want to have resources available to them right away, so they can help themselves. So if someone has a question at 2 am in the morning, and we’re not around, they can find an answer without waiting for us.

Because we don’t believe managing a number is going to improve our support. We believe focusing on customers and what they are trying to do with Highrise is going to make a better product, and better support.

Please don’t take this as gospel. What works for our team, might not work for your team. And vice versa.

Chapter 9 of Clayton Christensen’s recent book, Competing Against Luck, was a big inspiration for this post. The entire book is great, and you should check it out.



Find me on Twitter @cjgallo or GitHub @gallochris or Instagram @heygallo.