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Little data trumps big data

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These days “big data” is all the rage, and with good reason, too. There is so much data being created, captured, sorted, sifted through, analyzed, reported, sold and shared that extraordinary business insights are inevitable. But not so fast! With all this trumpeting of the “new” new thing, let’s not forget about what’s really important: little data.

Little data. Big data is the data drawn from lots of individual consumer transactions (the data forming the digital wake now trailing behind each of us). This data is being used to determine how best to sell to individuals and groups, how best to reach buyers. That’s great, but you already have the data that can help you serve your clients right now. And that’s little data.

Over time, you’ve captured your clients’ communication preferences. You know whether they prefer phone calls to email or, in some cases, text messages. You know that your client likes a follow-up call when he places an order. You know that sometimes he needs to see your face and sometimes he just wants you to listen. You’ve already got information about your clients’ communication preferences in your sales automation software.

You’ve also captured information about your clients’ ordering patterns. You know the big shifts in their businesses, their peak seasons and their ordering patterns. You’ve got all this information at your fingertips.

Context and insight. If you’ve done a reasonably good job capturing information from all the interactions you’ve had with your clients, you’ve also got something big data doesn’t necessarily give you: context. For example, recently I bought my son the Japanese animated “Hellsing” videos on Now Amazon is recommending I buy all kinds of cartoons and other items I have no interest in.

You see, the data Amazon collected didn’t come with any context. Amazon doesn’t recognize that I am not my son and that the videos were just a reward for his good grades. Amazon doesn’t realize that it is now cluttering my customer experience with inappropriate recommendations. It’s not the perfect analogy, but Amazon’s algorithm says that if I bought “Hellsing,” then I must be interested in stuff that other “Hellsing” buyers bought.

You, on the other hand, know why your clients ordered what they ordered, when they’ll need to order it again and how they might do better by doing something different in the future. You are constantly collecting and capturing data about your clients. But to make this little data work for you, you have to use it to generate insights, ideas and value for your clients.

Sometimes little data is bigger than big data.

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Anthony Iannarino is the managing director of B2B Sales Coach & Consultancy, a boutique sales coaching and consulting company, and an adjunct faculty member at Capital University’s School of Management and Leadership. For more information, go