Last week we were at Emerce eDay 2019 with the team from Stroom . A mixed group of speakers told their stories, but there were actually two things that recurred in many presentations. Namely data and the steps you need to take to innovate successfully.
To begin with innovation.
When we think of innovation, we quickly think of Uber and Netflix. The so-called gamechangers we all, unconsciously perhaps, want to be. The reality, however, is somewhat different. Because although innovation sounds very sexy, according to several speakers it is still simply a process in which craftsmanship plays a major role. For example, what the quadrant of innovation shows is that there is more potential in incremental development, getting better at what you do step by step, than aiming to be a gamechanger.
Incremental development is not big and immersive, it's taking your product further and further by seeing what can be done even better with new techniques. Or by taking an existing thing and adding something to it that no one has done yet.
Take Tesla.
Although we think it is completely new what they are doing, Tesla started with an existing car and they made it electric. That provided knowledge that they took a step further by developing their own (very expensive) car. The next step was to come up with a car that could be put into mass production. This was improved, production processes were tweaked (work in progress...) and another model was developed. And now the more affordable Tesla Model 3 is the best-selling car in the Netherlands.
Then dates.
When we look at data, thankfully it is no longer a trend. What is so interesting this year is that many different actual cases are now becoming available demonstrating the effectiveness of using data. Chris Wiggins of the New York Times showed how they can use data to provide better customer experiences that keep readers subscribed to the digital newspaper longer. Werner Vogels, CTO of Amazon, gave a presentation on what Amazon is doing with AI to improve business processes and ultimately make the customer journey as smooth as possible.
What both gentlemen emphasized is that at some point you have to hand a data model over to "builders. Data scientists who develop the model are, by nature, people who want to endlessly tweak a model to best mimic reality. Developing the gamechanger. But developing alone won't win you customers. So what's more important is putting the model into practice to see if it works. And on the basis of that data to improve the model. Actually, again, that's in line with the rules of successful innovation.
In media, we run into the same issues. Always we see the big cases coming by (Evert_45, KLM on social, etc.) with which advertisers want to show that they are communicating totally new and different. But the reality is that for most clients, we always take small steps with which we make campaigns better. Taking a few percent of the budget to test and improve. We know this works because we are getting better and better performance for clients (stronger increase brand KPIs, higher conversion rates, etc.). Nice to hear that this is apparently a successful way to innovate. We will continue with this.