How to outperform a Big Data competitor with Tiny & Small Data?

“We’re lost. Competition has more intelligence through their Big Data solution.”

Size doesn’t matter – on data

If you recently ran up to a marketing manager slash director slash VP Marketing, you’ll probably have heard the above sentence. And it seems to make sense at first sight. After all, there are plenty of articles stating that marketers should do Big Data or otherwise their organization will become obsolete because Big Data-driven Competitors will make them irrelevant. So if you want to sustain your marketing credibility, you better start your Big Data Project.

“You’ll win. Outperform them by using smart Small and intelligent Tiny Data.”

I disagree. Strongly. Most companies shouldn’t do Big Data. First of all because most are unable to collect them. Second, most are unable to crunch them into meaningful insights. To get to these insights, look at Small Data and Tiny Data. Small & Tiny Data are key to outperform your Big Data-driven competitor. Here’s why.

Why Tiny & Small Data are more important than Big Data.

As life partly moved to the internet and the internet became mobile (phones, cars, houses,…) , traces of our life are recorded and consequently quantified. This is what makes Big Data well … Big. It’s a collection of large and complex data sets. Insights and understanding of these data bears a lot of potential in them. But on the other hand, Big Data starts from a shaky premise: “we don’t need to think if we analyze sufficient data the numbers crunched say it all”.

In case I remember my stats courses well, this is just plain Bullshit. First of all there’s the difference between a correlation and a causality. It’s not because things are correlated that we understand the causality of the phenomenon. Furthermore, adding more data points to a collection does not automatically takes away all data issues. Just think of a “biased sample” in this respect. What if all “Big Data” you gather are from those people who are totally off-focus? Or do you really believe you can gather “all data” to counter all statistical reasons against Big Data. I guess you’ll never have “all population data”.

“Big Data for the What. Tiny Data for the Why.”

Big data show you the what. Tiny Data prove the why of that what. Marketers need to understand the why and work towards that insight. In today’s world, most marketers need to rely on Tiny Data to get those crucial insights on the why.

What is Tiny Data?

Tiny Data is a collection of qualitative / interpretative information. The data sample is rarely big. You take a few well-selected data points (sample) and get in deep touch with these data points. Observe these data points in real-life (participatory observation), talk with them individually about the subject (interviews) or run collective discussions (focus groups) to retrieve the information you’re looking for.

The information generated through these research techniques are not quantified. Variables are described in a human language. Not through statistical numbers based on – wrong – assumption. This in turn results in a better understanding. In true insights. Insights that are actionable. Insights that help you understand your customer. Insights that help you talk the customer’s language, etc. Don’t you want that in times where “engagement” seems a crucial marketing KPI?

“Big Data is here already. Big insights too but through Tiny Data”

Data without knowledge and information is useless. Current Big Data initiatives (like e.g. predictive buying) mostly lack true insights. As shown above, this will always be its problem. As this is a problem linked to the very nature of statistical modeling.

But what does one need to do now when he’s convinced he needs to be a data-driven business? Well, get insights through Tiny data. Second focus on getting your small data right!

“The Small Data challenge is already big enough.”

Regardless of the Big Data buzz, I notice a lot of companies not even properly handling their Small Data. That’s a shame because handling your small data well drastically improves your customer relations, lead generation, lead nurturing, etc. How do you automate your digital marketing communication without any solid Small Data behind it?

What is Small Data?

Small Data are the “regular” data information about a customer. These aren’t big – not large and not complex – but are crucial to get the conversation going. Think of elements like first name, last name, address, e-mail, birthday, sex, language, locale, channel preference, purchase stage, current products / services, …

And yes keeping those small data up-to-date is more important than gathering more and more data without any purpose. Or did you never get that “personalized e-mail” addressing you with the wrong name yet? “That couple who used to order a case of wine every fortnight for dinner parties is now buying diapers and baby food. Like your products, customer data has a sell-by date.”

“Size doesn’t matter?”

When it comes to data, size doesn’t matter. The goal of data is to get those that solve our problem or provide answers to the questions we have. For most problems and questions, small and tiny data do the trick. That’s how you outperform a big data competitor.