As a marketer my daily life is reflected in data, be it response time, conversion rates, engagement rates, demographics, customer behaviour, trends, ROI, analytics, correlations, statistics...and the list goes on.
Despite the popular believe that marketers do nothing but smart graphs and a ad once in a while with a nice picture it is far mor mathmatical than you would think.
Although I'am not a numbers guy - e.g. hated math in school - I suprisingly do embrace numbers and its magic in my profession. Why is that?
"Look at data the artist's way and create something new"
The thing about data is that it gives you something to work with. It is impressive how you can create knowledge and new insights from huge sets of data that lies within our companies - not in the creepy way of course!
Finding new connections and analyse different sets of data can give you invaluable insights.
Let me give you an example: Payback
Payback is part of the American Express Group and a very popular service in Europe, especially Germany (for more information see their website http://www.payback.net/en/about-payback/facts-figures)
What they do is simple, you register as a consumer, you get a plastic card (one more for your already stuffed purse - am I right?) and are able to collect points each time you buy something at a partner shop, be it offline or online. If you gathered enough points your are able to redeem your points for something like a usefull item, coupons etc. etc.
Great, right? Well yes, from a personal perspective this is great, conveniant and I get more value for my money in the long run.
Now let's take on the view of a marketer at Payback
Their site tell us that there are currently 27 million consumers in Germany who use Payback. So roughly one third of the population (heuristics rule).
What do I know about these people?
Probably (I haven't worked with them, so I have to guess) the following:
- Name, address, email, telephone - the basics really as with every registration.
But is that all? Considering they have to track your purchases with the provided card and customer account to give you points in return - they track all the items you buy as well. No big deal right? Well, considering how firmly some people don't want to be on Social Media, I suspect that some of them use Payback, and thus contradict themselves. Although I don't share selfies with the world, I share my behaviour as a consumer with a marketer.
So despite the mentioned things above - I would probably know if you are living alone, in a relationship or a student apartment. I would (roughly) know how much you earn depending on the items you puchase and how frequently. I would know if you are vegetarian, vegan or have other eating habbits. I would know where you buy, when you buy - so the job might also be transparent to me. Do you have a family with a child, do you own pets - that would be cristal clear as well.
I could continue to image what your behaviour as a consumer would tell me as a marketer. Since there is also the possibility of conditioning and checking out the habbits of what attractive deals are to you etc. pp.
Well, this data is the real win in the end - for the marketer at least. This knowledge is than sold to the partner companies so they can learn more on how to adapt products, how to advertise them and if they are reaching their target group.
So data is a business in the end - as you might know from the example of Google.
In the end it is a good deal for everyone and it makes research much more real and easier. In the end you will also benefit as a customer when the market respond to your needs. So don't get me wrong - Payback is a good thing! I hope it didn't come of as bad in my earlier description. It just served as an example - as well as Amazon or Google could have been, but sometimes it's more intersting to learn something from other companies as well.
Let me know what you think about data yourself and if your professional life is dictated by it. Do you use data also in your personal life for decisions? Are you a Payback memeber?
Share your thoughts in the comment section below.
Thanks for reading!