Finding a no-BS brand voice

How do we stay consistent when there is no consistency?

When I first started at Work With Data, two of the many things I picked up were content and external comms. With those, came a challenge — making sure that the way we talked on different platforms was consistent or, at the very least, cohesive.

‘Brand Identity’ and ‘Tone of Voice’ have been all the rage for a while now and I felt like we needed ✨something✨ to make sure we sounded different. That we were different.

The company’s mission is unique. We want to democratise data and make it accessible to everyone by building an infrastructure based on open data where everyone can access, analyse and use data from many different reliable sources such as the UN or the World Bank, all in one place. The positioning itself is not enough, however. We also have to sound unique. We have to be unique in the wider social media space.

Think radical honesty, an almost annoying level of transparency, and a careful balance of jargonless casualness and authoritative guidance. Those were my starting points to what I thought would be a fairly straightforward task, but which turned out to be quite complex.

As you’ll come to understand reading this piece, a company can pull together a simple Google Doc outlining a tone of voice and prescripting how everyone should sound when speaking as the company, but that on it’s own is not enough and can actually do more harm than good for the brand.

Consistency is good. Stringent adherence is not.

Why do we actually need a tone of voice though?

Won’t it just happen organically? Surely, as we post more, we’ll start sounding uniquely us?

When reading company content — be it a Linkedin post, the copy on the website, or a blog post — people will feel something about that company.

At its core then, a tone of voice is a tool used to guide people towards a feeling that the company wants to inspire. It’s a really useful tool, I’ll tell you that.

For us specifically, we are a part of a busy and noisy landscape, filled with a lack of transparency, big and hard-to-understand terms, and over-promises. What this means is that for our voice to be heard in the noise, we must be radically different.

At the same time, the breadth of data we have available and the range of issues it relates to is so vast that maintaining a consistent tone of voice is quite tricky. How can we still sound the same when we talk about the most popular artist in Tate on one day, and the mortality rate in the UK on another? We need to account for this huge range of topics while still trying to stay quintessentially us.

All this to say: we need to identify and deeply understand our general tone of voice so that we can then apply and adapt it to the many contexts we operate in.

Coming up with 2 guiding principles

Because of this unique issue and the fact that we cannot really create a specific language and tone, what we came up with instead are two main principles: being honest and being human.

Honesty

Being honest means not hiding the issues inherent in the data space and shining a spotlight on all the difficulties we come across (or even are a part of). It means avoiding language that’s part of the problem — vague statements or empty promises.

We believe in radical transparency when it comes to data. We are honest about what we do with it. We say how things should be done, even if it’s not something we’re doing yet.

Humanness

Being human means writing like humans, for humans. It sounds silly, but is actually quite important. Aware of the fact that we are, of course, speaking as a company, we still want to make sure that the tone and languagee we use are our own. We are a group of people, each one with our unique way of speaking. That’s beautiful.

We connect with people in the community, because we ourselves are a part of it. We are excited to contribute and the way we speak conveys that.

So how do we talk about different data?

And now we’re arriving at my main issue. I’ve recently been thinking about our tone of voice and how it seems to change depending on what data we’re sharing with people. It’s easy to say that our tone relies on being casual, honest, and human, but we’re still facing the issue of having too many different things to talk about.

Our mission, once again, is to democratise access to data and make reliable information available to everyone. It’s a pretty big mission with a lot of seriousness involved. On top of that, a large portion of the data we have and share is pretty serious, not to mention heavy subject-wise. When we give our take on a statistic related to something horrific, we adopt a voice that matches the gravity of the data we use to explain the world.

At the same time, our team is, how can we put it, very far from serious. We find data just as confusing as everyone else and love figuring it out. Every day we’re learning and laughing about it. We’re also excited about open data as a concept. Some of the data we have is hilarious. When it’s not funny, it’s at least positive. This is why we love celebrating random international days on LinkedIn that relate to the data we have. It makes us happy. Our voice in those posts matches the data.

So can there be one tone of voice in a situation where the range of subjects is so vast that it’s difficult not to adapt to them? Are two gudining principles enough to stay consistent?

Yes. I think so.

I like to think of our voice as a chameleon and rather than trying to create one way of talking, we follow 5 rules and leave the rest to context:

1️⃣ The open data ecosystem is still quite young. We know it has a bright future and, actually, it is the future. We should be excited about it.

2️⃣ Data is a meaty subject that conventionally requires skills. Just the word itself sparks fear in non-technical folks. Sometimes what is needed to demystify it is a bit of silliness. When the situation calls for it, be silly.

3️⃣ Skills or no skills, people are not stupid. We can be funny, but never condescending or ‘dumbing down’ the language.

4️⃣ Sometimes the numbers reflect things that are not good or happy. When that’s the case, we should let the data speak for itself. Present the facts and step aside.

5️⃣ Data is just one of the ways to see the world, which means there is always context and room for interpretation. Read that room before you speak.

In conclusion…

Something I’ve found out as I continued creating content is that this is genuinely all there is. We do our best to always be honest and human, and we follow these 5 simple rules to match the context of what we’re talking about.

This approach is our tone of voice. That’s it.

It’s not a set of words or the way we structure sentences. It’s the way we think about data and how we believe it should be shared.

If Work With Data was a person, it would be a kind one— not necessarily nice, but always kind. We would be opinionated, but not in an insufferable way. We would always be honest and never believe that hiding the truth would somehow spare people’s feelings. We would generally keep things simple and short, and never waffle without substance. We would be pretty funny too.

Damnn… I kind of want to be friends with this person I created.

Come and say hi!

Come and say hi to me on Linkedin. 👋

For those of you who are either casual data enthusiasts, want to read news from all sides of the political spectrum, or just need reliable data for work or study, you’ll probably find what you need on Work With Data.

On a mission to democratise data and make access to it easier than ever before, WWD combines data from open data sources (from the UN to the World Bank to the British Library) with AI algorithms to fill in the missing pieces and build an accurate picture of the world… in data.

And if you’re an art and culture lover, join me on my Substack where I talk more about paintings, pastries & existential dread.