|Image courtesy of IBM Big Data|
Today’s post was originally published on April 2, 2013, on IBM’s The Big Data Hub.
While basketball fans are deep into their Sweet 16/March Madness brackets at the moment, I was asked last week to provide my picks/brackets for IBM Big Data’s The Smart Sixteen Big Data Challenge. I’m not a basketball fan and have never paid much attention to March Madness, but this intrigued me.
The image to the left shows the brackets; I selected Predicting Customer Behavior as my Top Priority, and my team has made it to the Elite 8. [Update: I am now in the Final Four!] This is where the fun begins! At the end of last week, a little challenge arose on Twitter with some of my fellow #CXO tribe mates, so I’m writing today about why, for the Marketing region, Predict Customer Behavior will womp on Improve Campaign Effectiveness to take the final win and the championship trophy.
First, a little background on the two teams :
Predict Customer Behavior: The strength of this team comes from its ability to work with a single view of the customer by leveraging data from across the enterprise (including external sources) for deeper customer insight.
Improve Campaign Effectiveness: Changing your shot mid-air takes skill. This entire team is able to determine in real-time the right message to engage customers and prospects with timely, personalized marketing.
While I see the value in being able to tweak your shots and your strategies as the game evolves, I think that if you spend your time practicing, watching films, and really understanding everything there is to know about the other team and about what your audience enjoys seeing, you’ll start the game ahead of the curve.
What does it mean? It means your game plan to create a personalized experience looks like this:
1. Define who your customers are
2. Understand the problems they are trying to solve/needs to be filled
3. Identify the customer journey (use a journey map)
4. Bring together all disparate data sources
5. Create a single view of the customer
6. Analyze that data to tease out insights and deeper understanding
7. Share those insights with the people who need to use it
Customers are tired of mangled multichannel experiences and the “Why don’t you know me?” syndrome that causes them to have to repeat and re-enter account numbers, contact information, and other details with every interaction. At the same time, they delight in things like Amazon’s “Customers Who Bought This Item Also Bought” feature or in businesses that make recommendations based on past purchases or conversations. While I agree that it can sometimes be creepy (like the story about Target and the pregnant girl), I believe there is more good than harm that comes out of predictive analytics.
[BTW, in some ways, I feel like predicting customer behavior is a precursor to improving campaign effectiveness; therefore, predicting customer behavior must win this championship!]
While predicting customer behavior is the framework or the foundation of the game, improving campaign effectiveness is like telling the audience why you’re losing and what you’re going to be doing about it.
I think this is a classic “chicken and egg” story: should Marketing prioritize messaging or should the organization as a whole focus on getting the customer experience right with every single interaction. I favor the latter because, when done right, the proper (personalized) messaging will also come out of that. Doing things right is also more cost-effective than tweaking your messaging on the fly.
I like to tell my kids, “Your actions speak louder than your words.” Making customers feel like you know them is more important than the messaging, which ultimately happens organically when you get the experience right.
I have always thought the actions of men the best interpreters of their thoughts. -John Locke