“Agile advertising” at Cannes Lions, Rich and the four feedback loops
So we got invited to speak about our experiences from the last year at the world’s largest and most prestigious advertising festival, Cannes Lions. Last year we were actually credited with Lion in the “Cyber” category for a campaign powered by our very own Meme Machine, and this year we had a bunch of award winning agencies using Burt’s tools.
However, our appearance this year had nothing to do with awards. The reason for Cannes Lions inviting a year old startup from Gothenburg, Sweden, was that Burt is one the few companies focusing on data-driven ad tech with decent traction among “creative” agencies. So we were asked to share our experiences from working with some of the world’s top agencies to change how they make and measure large scale, digital advertising.
A full description of the speech is available here and you can download the subtitled PDF here. Or you just browse right away:
As you can see in the deck, the talk was not about technology at all, but rather the process and workflow that technology can enable if used properly. And it was not about the future, but rather how drastic improvements in advertising effectiveness can be achieved using technologies that has been around for several years. For startup geeks, think of it as an attempt to apply the “lean startup” philosophy to digital advertising.
In fact, in honor of Eric Ries and Steve Blank I actually thought about naming the speech “lean advertising”, or even “the lean agency”, but felt didn’t convey the sense of speed and dynamic capabilities required when working on campaigns.
The thesis (currently a work in progress) is that the existing workflow is actually quite ok – no need to “reinvent the agency” – so long as you start integrating “the four feedback loops” of Agile advertising. The need for efficient feedback loops was actually the main reason for us building Rich in the first place. When we started out we had Copybox and Meme Machine, two products centered around the idea of real-time, dynamic advertising content, or “personalized ads”.
At the time, it was fairly obvious that personalized ads presented a huge opportunity in terms of maximizing the impact derived from each exposed ad. However, since most marketers weren’t using metrics to learn about consumer behavior in connection to dynamic ads, nobody was getting any better at leveraging the tools.
Sure, there has been alot of lip service paid to metrics in online advertising. Metrics was considered “solved”, as far as technology companies were concerned. But if you worked in the front-lines at an agency, you knew that campaigns metrics wasn’t being distributed, and when they were nobody understood what they meant and how to take action. Not to mention the fact that advertisers still considered the lack of transparency in online advertising a major headache. So much for “problem solved”
So we realized that in order to secure the long term sustainability of what we’re trying to accomplish, we needed to build the first analytics product that would also make sense to front-line people, rather than analysts.
Any person involved in a campaign should be able to grasp what’s going on when they see a report and use analytics to improve. Seems like a reasonable constraint, right?
In december we started seeding out an early beta of Rich to of our friends, and from may we’ve onboarded more and more users. We’re now into the hundreds of accounts created, having tracked billions of exposures. It’s been great to see that an easy-to-use metrics tool can be such a powerful driver in changing behavior.
We’re also happy to see that those predicting that “creative types” wouldn’t be interested in data, technology and metrics were plain wrong. Creatives really love metrics – not to mention the competitive dimension they bring Not that anyone should be surprised. Metrics is a great game mechanism, that makes people obsess about everything from Baseball to Farmville. The next couple of months will be really exciting or us, as we get more and more feedback on Rich. We like to look at it as that Rich is in the second our four feedback loops, working hard to level up to feedback loop number three
