Harvard’s Gary King once said that “Big Data is not about the data”. It sounds like an oxymoron but it’s true. Big Data is not about the data – it’s about the analysis.
For anyone involved in the world of marketing, the opportunities are huge. Big Data in marketing is a multi-channel option for any business, as it can inform pricing strategies, sales activities, customer response, and your entire marketing strategy.
The range of data available means that companies have been utilising it in extraordinary manners. In the US, Big Data even showed Wal-Mart that sales of Pop-Tarts go up by a factor of 600% when a hurricane is announced.
On the tech side of things, General Electric has put data-gathering sensors into its industrial gas turbines. They generate more data in a day than the entirety of Twitter does in a week.
Big Data is seriously impressive, so today we’re taking a look at three companies that are using predictive data to improve the ROI of their digital marketing departments.
After all, it’s not about the data… it’s about how you use it.
Using analytics to a T
T-Mobile is a worldwide telecoms company active throughout Europe and the US. Analysing data has been part of the game plan at the company for the best part of the last decade.
T-Mobile uses social network analysis (SNA) to identify influencers within its customer base. These aren’t ‘influencers’ like celebrities on Instagram or Twitter. Instead, they are the people in a family, business or community who have the most influence.
T-Mobile classifies these communities, which average about 18 subscribers each, by looking at customers' call records, such as their voice calls and text messages. By using different data points, T-Mobile then identifies the person in the family who is most likely to influence the others.
In one SNA test, T-Mobile identified 15,000 influencers and sent them a personalised message offering €50 off a handset upgrade. When influencers took the offer, the take-up rate among non-influencers nearly doubled.
In fact, SNA modelling helps T-Mobile differentiate itself from its competitors. A marketing executive at the company said: “We were able to optimise marketing spend based on this in-house Big Data and that's a competitive advantage that some other industries don't have.”
An unexpected silver lining
Red Roof Inn is one of the largest hotel chains in the US. In the winter of 2014, the weather was incredibly bad. At one point, 2-3% of flights were being cancelled across the country.
Red Roof recognised that it had a potential audience of 90,000 stranded customers.
In addition to harsh weather conditions and flight cancellations, the location of several Red Roof Inn hotels near major airports put the company in an optimal position to craft enticing offers.
So using flight-tracking technology, the team at Red Roof developed a marketing campaign based on weather information, flight cancellations and customers’ locations. They also used an algorithm and geolocation information to consider the best time of day, location, and the sort of message (e.g. a mobile ad on a phone) that would work best.
The ads not only told stranded passengers how much a room would cost but the steps to get to the nearest Red Roof Inn.
Marina MacDonald, the CMO of Red Roof explained the strategy. “We knew where the customer would be; for example, at Chicago's O'Hare airport,” she said. “Then we delivered a personalised message reading something along the lines of 'Stranded at Chicago's O'Hare? Check out Red Roof Inn.'
“Because of this campaign our business was up [by] double digits system-wide,” MacDonald said. “It was a double-digit growth because it was unique.”
Double-digit growth is certainly nothing to sniff at!
Moving with the times
Moovly is a video-creation and infographic platform. It provides a SaaS system for creators to make videos and has four basic pricing options: free; basic (€9.50 per month); pro (€23 per month); and business (€47 per month). As a start-up, identifying customers is paramount.
But Moovly has used Big Data to do far more than identify potential customers. Instead, it uses Big Data to identify the people who are most likely to become paying customers – then targets a limited marketing budget to them.
Moovly wanted to find out what differentiated the paying customers from those who were likely to stay on the free model forever, and it found that only three metrics were needed to calculate whether a customer would subscribe or not. These metrics were the number of logins since opening the account, the number of projects created, and the number of logins before the second welcome email.
With those three pieces of information, Moovly could predict whether the customer would pay for its service with 97.2% accuracy. That means it could then target those exact customers with ads extolling the virtues of Moovly – with a phenomenal conversion rate on a comparatively small budget.
Indeed, so accurate was the data that the analysts only saw two outliers. These two people didn’t log in or do anything with the site in the first two days. They just subscribed.
Moovly did some investigating and it turned out that one outlier was the wife of the co-founder and the other was someone in the office next door.
Interested in using Big Data to grow your marketing ROI?
In the time it took you to read this blog, more data will have been created online than from the beginning of time until the year 2000.