Attending one of the many AI in Marketing conference in Zurich in March was not only inspiring for all the new things that are out there in Digital Marketing at the moment. Also, it showed the opportunities and challenges of today’s Digital Marketing.
If you look at all the data and new solutions and listen to entertaining (and emotional) speeches given for example by Marco Hochstrasser from Nexoya, a start up that uses AI to enhance digital marketing for corporations it all sounds so easy: data is the new bacon. We just need to buy and eat it.
The good news is: every Marketer out there knows that AI in Digital Marketing can be a huge enabler to make our businesses grow. I should give us more opportunities to understand our customers better and target more campaigns and content to the right people at the right time using the rich channel offering just the right product to the right price. Only: is it really that easy?
AI is the chassis, the driving has to be done by the Marketer
AI can definitely help to use and improve the data we get delivered every day in a better way. Campaigns optimize themselves without us spending hours on analyzing reporting and manually re-adjusting campaigns. AI helps us to shape products, services and messages. AI can significantly help us lower cost in service and turn a merely satisfactory service experience into a unique service experience e.g. by using Chatbots and complex machine learning for better data being delivered.
When developing AI technology for Digital Marketing there is no way to do so without talking to prospective clients
Still, we are talking to people out there. People are no machines, and as such we probably prefer a real person over a robot. That needs to be understood when developing data driven technology and solutions: without talking to real people and without understanding their real problems we can come up with the greatest and most advanced AI and big data technology solutions. If it doesn’t solve a customers’ real, daily problem it will probably be useless and ends up on the big pile of dead products of solutions trying to find a problem. Teams working on big data and machine learning have to understand what their clients problems really are. Their work might not (only) concentrate on how to deliver even better, purer data to improve the algorithms, but to put it in the bigger context of customer perspective. That’s the ‚emotional’ side to data, and what really matters
Successfully using AI in Marketing means pushing for organizational change
Even more important: technology is an enabler. But only if it comes with organizational change and an overall change in thinking. That means you have to get people within your organization onboarded. They need to see the benefits for their daily work and might have to adjust work routines accordingly. It will most likely also imply changes in sales performance metrics. If corporate companies understand the overall change that comes with AI it can be the bacon they should go out for and buy.