Data That Matters – Interbrand
Data is everywhere. Big data, ambient data, real-time, benchmarking – there’s so much that there’s no one metric or one way of using it that works for every company or every industry. The data leaders are the ones who take risks, who look at all the information available and decide what matters right now. We’re spotlighting these innovators in this “Data that Matters” blog series. We’re talking to people in various roles across multiple industries to see how they collect, make sense of, and act on their data. Read the full series.
Next up is Nora Geiss, director of verbal identity and digital for global brand agency Interbrand. In advising brands like AT&T, Feeding America, and Johnson & Johnson, Nora suggests the biggest success when working with and understanding data comes from remembering that data is people.
I think people can get so caught up in the fact that data contains numbers that they forget that those numbers are really about people – and that’s where the story, the context gets lost.
Brands are collecting so many numbers from so many sources – their in-house web teams, their CRM agencies, their ad agencies; these guys are telling them the specifics about how certain campaigns are performing. Which is absolutely useful to tackling discrete goals. But looking only at this granular level doesn’t really tell you about whether or not people in general get your brand. Do you stand for something? And ultimately, do people actually care about what you stand for?
And you, as a brand owner, have the option to not care about all that. I mean, you can look at just the short-term numbers to see if you’re making money off an ad.
But if you want to be around for a while, to have real longevity and relevance through economic shifts and changing markets, then you need to care about the bigger picture. If you want to bring people back to purchase your products and services over and over again, to pay a premium for your product, to be an advocate for your brand to others — you have to care about the people and the story behind the data.
It’s not just about the moment “before purchase” — it can be more important, I think, to look at what happens after purchase.
What did your buyer say? Did they write a review? Did they post a picture of their purchase somewhere to share with friends? That’s where you figure out if you delivered something that’s actually valuable, something that your buyer is going to recommend to their friends, and their friends’ friends or even their not-friends through things like Amazon’s “people like me” type features.
The “people telling people” part of the loop drives more purchase and has more impact on brand value than anything else these days. So if you’re 100% focused on how people experience what you offer, and how they can share that experience, then your reason for being as a brand – to deliver a product that people recommend, ultimately driving purchase and loyalty – is more easily fulfilled.
Right now I notice a lot of brands looking at measurements out of context. Brands are only seeing “someone talked about me” or “4503 people are talking about me right now” and just focus on blindly increasing that number.
It’s just traffic and number of likes or followers or whatever right now.
Brands are just on the what, not the why – when the why is what gets into what people are thinking, doing, experiencing, saying.
You see a lot more when you get into the reasons why: you see that “someone talked about me because they saw this, they experienced this, they touched this” or “they talked about me to this person in this place.”
Context is key. You can’t succeed if you don’t know the context.
If, for example, my goal as a CMO is to drive premium pricing, and most people are talking about my brand in the context of coupons or discounts, then I’m failing – and I definitely don’t want the number of those mentions to increase. So purely looking at numbers don’t help me much in a case like this.
I think the brand world hasn’t moved past the numbers yet because, in large part, exposure to data happens every once in awhile and in an already numbers-heavy environment – as part of a quarterly report or an annual review of performance against financial goals.
When you’re seeing the numbers day-to-day, the constant fluctuation makes you more apt to wonder what’s happening behind those fluctuations.
Brand owners need to live in an environment of habitual measurement.
An environment that makes it possible to take action that matters.
You see successful brands taking that approach, like P&G and Dell and Starbucks. You see how they listen to what’s happening in the market, how they incorporate what they learn in their go-to-market strategy, how the audience is reacting to their reactions – the feedback loop. And I think you’re starting to see the change take root internally – it’s not just the marketing department participating, but the product teams, and the agency partners, which leads to much more agile internal process for everyone and everything.
Feeding America actually did an amazing job of listening and delivering when they went through their rebrand. Every single person in that organization understands who they serve and what that audience needs most, so they know how to reach them, what to learn from the actions they take, and how to change the way they deliver accordingly.
These guys doubled their revenue in one year after their brand relaunch. It’s amazing what can happen when you’re really paying attention to the right data – the data that tells a story about the people you serve.
This is such a crucial shift. If your brand is only talking not doing — using data and or feedback just in marketing and not using it to actually improve your products, quite frankly you’re screwed.
Because your brand is not just what you say, it’s what you do.
And if you set an expectation and fail to deliver – believe me, people notice.
We’ll be covering a new company each week – big & small, media & not, data junkies & analytics allergic – so let us know if there’s someone you want to see featured. Hit me up at email@example.com.