This year, Black Friday may have felt more like Cyber Monday for a lot of people, as an estimated half of all holiday shoppers did their Black Friday shopping online as opposed to waiting in the long lines outside of big box retailers. But that doesn’t necessarily mean that half of all shoppers stayed home. 25% of all online browsing on Black Friday was done on smartphones—though consumers were twice as likely to make their final purchase from a tablet than a smartphone.
In my last blog, I talked about the need to integrate and understand data across channels. Black Friday is a perfect illustration of this. More than ever before, marketers need to look beyond people and products to see the complete customer journey. Are their customers searching for products on a smartphone before they get in the store? Are they comparing prices on their smartphones while they’re in the store? Are people travelling for the holidays more likely to shop on their tablets?
The more you look at the data from Black Friday, the more you will discover. In a sense, it’s not unlike when astronomers pointed the Hubble Space Telescope at a patch of black sky on a hunch some years ago, only to discover thousands of galaxies they didn’t know existed. In the same way, data scientists can learn a lot by studying phenomena such as Black Friday, provided they’re looking at it through a wide enough and powerful enough lens.
Like most science, data analytics starts with testing hypotheses. You look for where you think the discoveries can be made, and prepare to make discoveries you might not have expected. A good example of this is the work we did with Cabela’s. Together with Baylor University, Cabela’s wanted to test their theory that the first items placed in an online shopping cart have a high propensity for purchase. In finding their answer, Cabela’s made an even more important discovery: that some items were clearly connected with quicker online order completions and higher purchase totals.
This leads us to the second step of creating a data-driven marketing strategy: Analyzing and discovering the meaning and value of data. Once you see the big picture, you can begin to connect the dots. With Cabela’s, for example, they were able to discover a clear relationship between specific products and faster, higher online transactions. Going forward, they can now extend the value of that data by featuring those products more prominently on their web site, placing them on the cover of their direct mail catalogs and even including them in the subject headlines for email campaigns to drive more revenue.
Consider all of the data that you’ve collected in the last 72 hours: online data, point-of-sale data, customer call center data and more. There are worlds of opportunity to discover in that data, including product relationships that you didn’t know existed, customer behavior that differs radically from previous years, failed experiences that may cost you customers if unaddressed and new relationships that need to be nurtured. These are the real stars of Black Friday, and there’s no end to them; you just need the vision to look for them.