In this age of Big Data, there is more information than ever before about your customers and prospects. Consider the data your organization can harvest from every interaction a customer has with your business, including transaction details, loyalty card information, user device records, and customer surveys.
There’s also a tremendous amount of external demographic, firmographic, and segmentation data available from commercial sources such as Experian and Dun & Bradstreet. And now, there’s the ever growing array of social media content that your customers generate on sites such as Twitter, Facebook, Foursquare, and Yelp.
Unfortunately, when many companies look at all of their data in the context of their understanding of the customer, they find that even with all of the massive storage technology they have and all the processes they’ve put in place, their picture of their customers and prospects is not getting any clearer than it has been in the past.
That’s a big problem when you consider that customer insight and customer understanding should drive pretty much all of the major strategic customer decisions a company has to make. It’s not that these organizations don’t understand the potential value they have with data about their customers and prospects, the problem they have is how to utilize it effectively.
A few months ago we got together with a research and consulting partner of ours, AbsolutData, to execute a survey of industry thought leaders about how their organizations use customer data and analytics, with a specific focus on their goals, usage patterns, and relative maturity (both at a user and organizational level). We received responses from individuals who work in many different industries and departments, with equal representation by B2B and B2C companies of various sizes.
In subsequent blogs over the coming weeks, I will go into detail about the tangible benefits these organizations are receiving. But perhaps more important, I will also summarize the specific challenges they’re facing in their attempt to use data to predict customer behavior, and ultimately drive critical improvements in sales, retention, efficiency, and customer loyalty.
Customer Analytics Blog Series: Perspectives from Industry Leaders
| Part 1 – Customer Analytics Blog Series: Introduction |
| Part 2 – Customer Data and Insight Can Take Many Forms |
| Part 3 – Analytics Provides Input to Strategic Operations |
| Part 4 – Getting and Working with Data is a Problem for Many |
| Part 5 – Line-of-Business Users Want Access to Easier Tools |
| Part 6 – Big Data Should Make ROI Easier to Measure |
| Part 7 – Where are Companies Investing in Analytics? |
| Part 8 – Conclusion and Recommendations |
Bob Laurent
Director of Industry Marketing
