“Every company has big data in its future, and every company will eventually be in the data business.”
– Thomas H. Davenport
I’d like to ask a few questions and perhaps suggest a new KPI. How long does it take your company to decide and act? How long do you actually have to decide and act in the face of competition? Are you relying on blind guesses instead of actionable data? Perhaps the “readiness” of your organization is directly related to the degree to which your data is business-ready.
What does “business-ready data” mean?
Think about your data warehouse like an antiques mall. Everything you need from armoires to wooden xylophones is in there. Somewhere. But can you find it? Can you find it quickly? There is a reason there isn’t a game show called Antiques Mall Sweep – trips to the antiques mall are never quick and productive. When not deliberately organized for business readiness, your data warehouses can wind up in the same state. This results in complicated workflows, slow decision making and an over-reliance on luck.
How do you know if your data warehouse is more like an antiques mall or a well-catalogued library? Consider the following: When you need to activate against your beautifully segmented audience, optimize your message or allocate your spend, how confident are you? How long does it take to find the data to support a decision? How many cooks are in that kitchen?
Business-ready data is data that is easy to understand, find and use. The often-overlooked pieces of this puzzle are all the resources, time, effort and strategy required to make your data ready for prime time. That’s right. Just like a marketing campaign, business-ready data requires a well-considered strategy built around your business goals.
Business-ready data is about consumers.
Let’s do an experiment. Right now, ask yourself this: “Is my data arranged for me or for my consumer? Am I looking at how much product I’ve sold or who is buying it and when?” We’ve all been guilty of a “me first” approach to database design, focusing on our own products and services rather than the consumer’s needs, but this approach only hinders your ability to extract the most value from your data.
Consumers don’t think about your franchises or product teams. They think about their problems and seek solutions to those problems.
Is your data ready the second you need it so that you can intercept your consumers at the point of decision, or are you leaving it up to chance?
It can be as simple as serving the right ad to a family of four as they look for dinner options at their new beach vacation spot. Or it can be as complex as orchestrating the best message to deliver to a physician’s office using owned and personal channels in a highly regulated space.
Here’s the key to creating business-ready data:
- Start with your consumers or demand-driving stakeholders in mind. What do you need to know about them? Where are they, how do they behave, what transactions do they generate, and what is the journey to maximize lifetime value to the brand?
- Next, ask yourself where your data needs to go to activate. What steps do downstream users have to perform once data is transferred to your CRM platform, programmatic media platform, ? Consider a straightforward and secure pull strategy to enable the downstream platforms.
- Build your data warehouse or mart to be as agnostic to your current MarTech ecosystem as possible. Activation platforms come and go. Data does not.
The goal is to minimize massaging, formatting and any level of touch. Because at the end of the day, business-ready data is as much about data out as it is about data in.
If you equip yourself to understand what your audience is responding to and make that information easily actionable, then you can quickly tailor your delivery and messaging strategy to better serve your audience and ultimately increase your ROI.
Don’t leave it to luck.
At Luckie, we help brands do things that real people care about. We are a creative, data-driven agency that builds brands and brand experiences to solve business problems and achieve results luck can’t explain.