Marketing sits between science and art.
The art comes in learning to understand what people want. Seeing them and the problems they have, then delivering a solution that addresses the problem. Often, they themselves don’t know what they want, at least consciously. It comes in packaging your solution so that you present it in a way that connects with them and motivates them to take action.
The science comes with testing one element of your campaign against another. Constant testing, trial and error, can cause a fundamental impact in your marketing response and success.
The art is in creating ten headlines, the science is testing which performs best.
Big data can’t do your job for you
Some people and organisations act as if big data can help us answer all marketing questions. It’s easier to make decisions based on big data rather than doing the emotional work, the art, and learn to see how your client sees things. But, all big data can tell you is how everyone clumped together acts or behaviours in a given environment.
When your PPC agency tells you their data proves that blue enquiry forms deliver a better conversion rate than red, stop and think about this. Do they work with businesses like your own? Is this data representative of the people you want to reach? Is this causation or correlation?
It’s unlikely that the data is an exact sample of your customer base and the relative relationship they have with your business at the moment of entering your website. So, listen to the advice from the PPC agency, but you should question it. Knowing what you know about your target clients, is it worth my time to change or test the form colour right now? Or, is my time better spent on some other task?
The messenger is biased
When a big organisation like Google or Amazon release results from their tests, take two things into account before implementing their findings into your marketing campaign.
Firstly, they’re measuring online behaviour by everyone. You’re not trying to sell to everyone, so immediately the data isn’t representative of your users.
Secondly, these businesses have an agenda and reason for publishing their findings. Both sell advertising, and in Google’s case their whole business model is built on the back of their advertising. Ultimately, if they have data that encourages an increase in usage of their ad platform, directly or indirectly, they’ll publish it. They want to help you build vanity metrics, because vanity metrics get you spending more on their platform.
If the data is relevant to your audience, it’s worth analysis. If it’s representative of the masses, it’s of little use to you unless you sell to everyone. If you work for P&G, you sell to everyone. For most of us, that’s not the case.