Four Ways to Move from Passive to Active with Big Data Analytics

8/19/2015
For anyone with a product to sell or a service to promote, the Internet has a way of creating conflicting emotions.
 
On the one hand, it gives executives and entrepreneurs a sense of immense possibility, as social networking and cross-channel connectedness promise to open far-away markets and build customer engagement. But just as often, the web creates feelings of despair, as business owners realize how hard it is to actually get anyone to notice or pay attention.
 
To counteract the frustration of tracking sales through many online and offline channels, businesses find hope in analytics. Rather than just "putting things out there," business owners can see who's looking and what they're looking at. Plenty of services offer a wide array of metrics to give stakeholders detailed visibility into how customers are interacting with their products. In turn, that real-time awareness creates a sense of control. It's a wild world, but analytics make it manageable.
 
As more and more data streams open up and companies explore new types of metrics, the volume of information obtained through analytics is multiplying exponentially. Globally, the total amount of business data doubles every 1.2 years.
 
All that growth is exciting—and it has certainly led to a lot of hype around Big Data—but strangely, seeing all that information can actually have the opposite effect than intended. The quantity and availability of data is so impressive, it obscures the point of gathering it in the first place.
 
The fact is that data analytics can hold more appeal than value. The metrics look good, but all too often, that's as far as they go: surface information that never gets translated into meaningful improvements. In other words, they show, but they don't tell.
 
Business owners need more than superficial awareness of what's happening with their products and services. They need to move from knowledge to action. Analytics isn't the solution—it's a tool for finding solutions.
 
When we want to increase our understanding of an issue, we often talk about "shining a light" on it. Before analytics, the retail world was a very dark place. Now, better sources of data are making it a lot brighter. But like any bright light, if you stare at the source rather than where it's pointing, it can make you go blind.
 
So here are four simple principles for obtaining better value from your data analytics:
 

1) Don't just stare at the numbers as they go by. Interrogate them. Think of an area of your business that you would like to improve, determine what you need to know to help you accomplish your goal, and then formulate the right question to elicit that information. Now take your question to the data and look for the answer.

 

2) Experiment and try new things. Use the data as a jumping off point for experimentation with marketing and promotions, product assortment, and customer engagement. Identify a baseline, make a change, and then measure the business impact. Repeat.

 

3) Look for new types of data. Once you make the switch from passively observing your data to actively engaging with it, don't be content with the data you already collect. It's very likely that you can find new data streams within your current business, and publicly available sources of data can also add surprising value.

 

4) Keep your analytics in one place. Obtaining value from data is impossible if you can't see the correlations. Use a dashboard that lets you easily make comparisons to measure the impact of the changes that you make. Give everyone on your team access to this data hub.

Data analytics should lead to action. If data collection doesn't cause you to make real changes to how your business operates, then there's no point in doing it at all. Stop staring into the Big Data headlights, and instead look at where that information is leading you. New analytics platforms have the power to take your business farther and faster than ever before, but only if you take control and steer the way.
 
 


Eric Green is CEO of Askuity, a cross-retailer big data analytics platform that connects retailers and product manufacturers with insight and information, enabling better collaboration, planning and retail execution. Eric co-founded Askuity after living in the retail/CPG industry for many years and seeing an opportunity to improve it with Big Data analytics and cloud technology.

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