What marketers need isn’t big data, it is smart data
Over the past couple of years, we have been bombarded with reports from big data firms on various subjects. It is deployed to track the solar system, universe, population changes, climate changes and so on. Given the buzz, it was only a matter of time before big data would make it’s play into marketing as well.
Facebook & Google are perhaps the pioneers in this space for marketing as they have used big data quite effectively. The search auto fill or the usage of google maps is powered at the back end by big data analytics. Facebook’s ability to know that you have received your salary and would have a higher propensity to spend in the next 1 week is powered by the very same big data. This goes on to other platforms like a DMP as well as DSP/SSP where they are able to match what the brand is selling with consumers who are in need for that product.
Before we proceed further, let us try to see how big data looks like for marketers and by marketers I refer to the Brand Marketing Team and the Agency partners. Big data involves a lot of data points that come together, is analysed to formulate certain trends & patterns. This involves a lot of modelling and predictions basis data. As a marketer, what is needed is insights on which certain actions can be taken. We don’t have time to analyse data and then create models around it. Due to this primary reason, big data looks like a complete set of gibberish for marketers. But it certainly makes a good slide in the review presentation.
For a brand like Facebook or Google, whose primary revenue is from advertisement, it makes sense to invest, analyse and make themselves superior with big data. For a brand like a Modelez or BMW which gets is revenue from selling a product to the customer, the priority was and should always be understanding the consumer better. Big data may not help you in that aspect, it would be researches, interviews, shadow shopping which gives you insights about your consumers.
When it comes to media placement, primary platforms are Google & Facebook, which is already on BD. The next port of call would be programmatic platforms, which again is on BD. Then comes the ad tech platforms, which have also embraced BD. When upto 80% of the media is already bought with the aid of BD, brands really do not have to invest in it from there side. What they need to invest then is getting insights from all these platforms, which is now highly fragmented.
Every platform is using separate measurement metrices in digital; at any given point there are multiple associates doing multiple things, some are increasing the brand buzz on social, someone is optimising the spends on SEM, someone is trying to fix the broken links for SEO, others are improving the user experience on website by reducing the time to convert, all the while the media team is busy spending money on another zillion platforms. What the brand needs at this stage is not the analysis of big data, but a simple platform that says “Am I doing good, bad or ugly, supported with some good old benchmarks”. For this to happen, the fragmentation needs to be addressed before moving into any sort of insights & actions.
There are multiple tools that are available which is replicating each of the individual data of POE. There is Tapclicks, adalyz, klipfolio, etc which are great at visualising your data. However, at the end of the day, they are still fragmented under the dashboard. What is needed is to correlate between data points. IRA, the tool that we have been working on is a start towards this. IRA works with the current platforms and tools what may or may not be using big data and convert that into smaller bits of smart data to help taking decision. By adding a layer of historical data, benchmarking is a possibility and these two together answers the proverbial questions for marketers “So I have spent so much money in digital, is it good, bad or ugly?”.