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Future of work

Four steps to big wins with ‘little data’


Bryan Pearson

CEO of LoyaltyOne & bestselling author of The Loyalty Leap: Turning Customer Information Into Customer Intimacy

Many organisations have been caught up in thinking that Big Data – with high velocity, volume or variability – is a requirement when in truth they are already sitting on a wealth of potential in the data they have.

Organisations should shift their focus to finding new ways to use what they have, such as applying a customer perspective to the information, they can generate fresh insights and management options.

This was pointedly argued in an article about the virtues of little data, written by David Meer for Strategy + Business. Meer offered three steps that companies should follow to extract meaning from their little data. I would add one more step, and suggest that big companies, as well as small, would benefit from them all.

1) Be more fact-based

Organizations should think about what information is available to gain reliable insights into the business. Extending customer insights by using the data from a merchant-branded loyalty program that is tied to a credit card, for example, not only gathers information from activities with its brand but also activities with its competitors.

2) Learn by doing

“Since little data applications are not commercially available via third parties, companies have to use trial and error,” Meer wrote. Look for quick wins that come with data trialing, and how to leverage the returns in intelligence and business in the future. Importantly, such small successes will inspire incremental management support.

3) Be creative

Don’t underestimate the feedback that comes from employees. In-store observations, online surveys and call-center conversations all can reveal much about customers. Affordable technology, such as cloud backup services, can ensure customer information is securely stored and available for staff. Lastly, my own added step:

4) Think like your customer 

Marketers spend a lot of time gathering data on who buys a product, when and under what circumstances, but how often do they think like that end consumer – the Millennial starting a new job or a recent mother? To successfully analyze the data, organizations should get to the underlying motivations and aspirations of their customers. After all, the context of the information as the basis for “little data” experiments is as important as the data they are using.

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