Data Providers Need To Be Replaced By Data Partners If Brands Want To Succeed
There is an imbalance of priorities in our industry that is causing short-term and long-term damage. Data providers have to scale in order to survive, and that means producing thousands of data segments that can be sold over and over again to multiple buyers. A small amount of effort for a potentially large, repeatable return.
In the hands of the brands and agencies these segments often don’t perform through a combination of them being too generic, and that the more buyers there are, the more competition there is to target them leading to a higher media cost.
As a result, brands and agencies tell me they are burnt out from testing new data sources, and many have made conscious decisions to reduce spend on 3rd party segments for this very reason.
Yet what brands want isn’t complicated — they are looking for a positive ROI from their investment. They know who their ideal customer is, they know what characteristics they have, and so why with all the technology the industry has today can’t they be found.
They can. But a critical rule of data science is the more defined an audience is, the smaller the resulting audience will be, and lots of work for non-scaleable audiences doesn’t fit the business model of the tech company trying to scale.
The solution is to form a data partnership where the brand makes a commitment to the data company, and in return, the data company produces custom micro-segments that answer the carefully defined audience criteria. If this is built into the brand’s marketing processes, multiple micro-segments will add up to larger audience counts that are worth the brand’s time to target against.
The financial models are likely to evolve. Today most data is still bought on a CPM basis, but perhaps a SaaS model or an hourly rate might work better. Ultimately, as long as the tech company can show a profit from the venture, brands should be able to find someone willing to work in this way.
As a side note, I am writing from first-hand experience. We have found at audience.ai that custom data solutions lead to far higher results for our Clients. With one retail partner we build dozens of segments that fit some fascinating needs, and in aggregate, we can really move the needle on top line revenue.
Some brands may feel their audience definitions are very narrow and as such really don’t fit this model of multiple micro-segments. I thought the same. When we actually dug in though we started to evolve definitions that no one thought of without machine learning capabilities. Good example: one of their micro-segments turned out to be ‘people who actively post about Rihanna’, someone that was not on the brand’s radar, yet is a strong indicator of who is going to buy their type of yoga pants.
So if you’re facing the data provider downer, try giving a data partnership a try.
