Well established players in quantitative market research are entering some troubled times. Their business model is being shaken by a paradigm shift operated by Big Data companies. Read further to discover two amazing examples of how big data and data mining might shake the gaming, real-estate and media industries.
Market share research is a million-dollar business
Many market research firms have specialized in market share analysis. Using panels and armies of people to collect data in the field, results are extrapolated and market share inferred per geographical areas. Retailers and producers had no choice but to pay such market research firms to calculate KPI’s that were crucial to conducting a business. Thanks to Big Data and data mining, this may well be the end of panels to calculate market share. Here’s how it works.
Why ask a third party to calculate market share when you can do it by yourself ?
Consider the following situation. You’re a producer of water bottles that you sell through 30 retailers in Europe. All products are scanned when cashing out and data stored to –at least- produce your invoice.
If you can convince the majority of retailers to share their data on sales of water bottles, and “dump” them into a data warehouse, a big data specialist may well help find out your relative market share. The data needs to be reconciled first but once it’s homogeneous you basically have a representative sample of water bottles sales for any given area. Who then needs to collect data manually on the field ? Nobody.
Imagine two further examples based on the same principle : one in real-estate, the other one in the media industry.
How to analyze actual price trends in real-estate
As of today, notaries have a monopoly on the sales of properties and are the only ones to have all the data on properties sold in one given countries. They are the only ones to know the actual prices paid for all properties and, as such, there are the only ones who can analyze trends. These trends are extremely valuable for individual who are about to buy. No one wants to pay too much for a once-in-a-lifetime purchase. Yet, there is a way to leverage Big Data and to bypass this monopoly. Have you ever realized that real estate agents also know the final prices paid and that these prices are most likely encoded in their accounting software or similar ? Have you ever imagined what could happen if all real estate agents would mutualize the data in a data warehouse ? Suddenly, the monopoly of notaries would come to an end and the data could be monetized.
How to analyze audiences in the broadcasting industry
As you know market shares and audiences are the number 1 KPI in the broadcasting industry. For the moment, the analysis is outsourced to third parties who build samples (once again) of people who accept to have a black box installed on their TV. This black box records what the person watches and an extrapolation is done to calculate the audience for each program and for each channel. This method suffers however from several drawbacks. The biggest one is that the analysis is based on a sample. Nobody will ever guarantee that this sample is representative of the whole population. Moreover, usages have changed and TV watching is now done on a several screens. There is a huge bias in monitoring only what people watch on the good old TV set. What is the solution ? The solution comes from telecom operators which sell you access to TV channels. Everyone has nowadays a box to decode the signal sent to the TV. The operator identifies you via the box and can monitor very precisely what you are watching. The next step is to aggregate the data from all telecom operators (fortunately 3 or 4 of them usually share 80% of the market) and let data mining do the rest.
These 2 examples (real-estate and media industries) show that pooling resources and data can help gain efficiencies and capture value that previously went to third parties.