Mobile Potential Relies on Using Data


Following the rapid rise of Groupon it seems like everyone from Google to Amazon is now offering some version of deals. A few months ago I signed up for Visa Mobile Offers and had an interesting experience with their program.


Last weekend I visited The Gap and bought jeans and then I went to a specialty running store and bought shoes. While I was riding the train back to my apartment, I received an offer from Lands’ End, followed by an offer from


Based on the timing and nature of the offers it was clear that my purchases triggered the offers. As a marketer I thought it was powerful that they had the capability to make a message pop up on my phone in such a timely manner based on my purchase history at competitors; however, I had no interest in either of these offers.


What was I supposed to do? Return everything that I had just spent the morning purchasing, re-purchase the same items from the websites that were sending me the message, and then wait for the items that were literally already in my hands to be shipped to me (it was online only)? That seems like a lot of hassle to get some airline miles, which is what they offered.


I’m sure that some people went through that whole process, but it seemed backwards to me that they were reacting when they probably had the information to be predicting.


I went back and actually read the terms and conditions of Visa Mobile Offers to see what information I had agreed to let them use. It turns out the program gives them access to pretty much all of my credit card data:

• Where you use your enrolled Visa card to make a purchase, which may be at a physical store or online

• The type of merchant where you make a purchase with your enrolled Visa card

• Purchases at the Merchant and its affiliated brands

• Time of day of your transaction

• Transaction count

• Transaction amount

• Profile information

My Visa card is my primary credit card that I use to pay for pretty much everything. So they have an extremely rich data set that could be used to drive some interesting offers.


They could see that I often times buy coffee in the morning, but that I rarely go to Starbucks. They could send me offers for Starbucks 30 minutes before I usually get my morning coffee. That would be timely.


They could conclude that I likely don’t have a car from the fact that I never buy gas and I’ve taken a taxi multiple times. Perhaps Zipcar would be relevant to me.


They could see that I’ve made purchases at sporting goods stores and send me proactive offers speaking to my interest in sports… However, I didn’t get any of these hypothetical offers, which is pretty disappointing.


There’s a lot of talk around the potential of mobile marketing and big data, but that potential is oftentimes just hype because the wealth of information that is buried in the data is not leveraged to its potential.


Posted by Matt Siedlecki on 10/09