Small data. The way for a more precise data-driven strategy

Small data

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We always listen to people that discuss Big data. But have you ever considered going small and to know more about small data?

Yes, they are a real thing, and probably one of the most useful sources you could add to your marketing strategy toolkit.

We will tell you what they are, why are useful for marketing strategies and why they make a beautiful couple with Artificial Intelligence!

Is it big data’s little brother?

We are all familiars with Big Data. It is a buzzword that has become common in the last decade and sometimes still has a mysterious and super tech vibe.

Today, most of the marketing strategies are data-driven. It means that marketers and communication experts don’t follow their guts any more to launch a new product or service. Luckily, they started to learn how fundamental it was and still is, and decided to implement them in their big picture.

It is fundamental to create strategies for the future. Experts have to collect, pick and analyze it to obtain significant results, but they need to learn that it is not the same. 

Small data is one of the most important categories, and we are going to know them better.

What is the small data?

Big data is crucial on a data-driven strategy: they are a sort of giant agglomerate of indistinct pieces of information, from demographic to sales, from which marketers will extract the bits of information they need to project the next campaign. 

One of the main qualities of big data is its wideness, which is also one of its flaws. In such a vast amount of information, it may be hard to extract only the marketing department’s relevant ones.

Of course, if you need to know more about your customers, you can always rely on our GhostwriterAI Profiler.

Here the small data comes to the rescue.

Despite the name, it is no less important than its “big brother”, it only has a different function.

It is tinier and more precise. It doesn’t give you the big picture, but a more detailed one.

Martin Lindstrom is the most famous theorist of it. In an interview for the [email protected] show on Wharton Business Radio, he said that “Big Data is all about finding correlations, but Small Data is all about finding the causation, the reason why.”

Reading the bits of information that you collect from a new perspective may be the game-changer. It may lead you to think differently and have a different vision of your target audience, brand and even your product. Marketers collect small data from the daily experience of people. It makes it more personal, reliable and more useful for marketing and advertising campaigns. We are going to discuss this aspect in a few lines.

Which is the relation with big data?

Even if the two are different, it doesn’t imply they can’t work together for a more significant project. It is what they do to create better strategies for marketers.

If big data works on the quantitative side, small data is on the qualitative one. Which already tells us why the two are complementary, and combining the two, can lead to marvellous outputs. Quantitative analysis is responsible for the big picture. Simultaneously, with small data, we can dig deeper and understand them from a more personal and near to the customer point of view. Marketers collect it with more unique methods, like interviews, often individual ones.

Small data is “data that humans can observe and process personally. Information about any individual in a crowd is small data”. Together, the two can work to generate more accurate and complete bits of information. They usually follow one another. For instance, with surveys for the first step and interviews for the second.

Small data, AI and strategy

Now that we know the difference between small and big data and their importance, it is time to understand how to apply them to a successful marketing strategy.

Are you ready to learn how to power up your data-driven content plan?

Why and how to use small data in a strategy

We have often said how much data is crucial in 2021’s marketing strategies, but marketers also need to understand how to use them properly after collecting them.

Small data is so important because it helps to understand your target uniquely. It gives you a perspective that big data, because of its nature, can’t take. It is one of the most crucial sources for a small business because it brings marketers closer to customers. 

Why should you bother to collect small data? Let’s see a couple of ideas.

  • Small data is all around you. To collect it, you have to open your database, CRM or Facebook business page. People leave it behind themselves almost every time they connect to the Internet and the web. They are not an FBI secret.
  • You can use it immediately. Human beings can understand it easily. It means there is a shorter span between the moment you collect them and the moment you can use them.
  • The focus is on the target. There is no fuss with it; it corresponds one-to-one to the consumers’ mind. You will have a better view of what people think, which leads to more pointing strategies right afterwards.

Use artificial Intelligence for a fast, useful small data analysis

The more you can collect small data, the more you will know about your target market. This knowledge leads to precise, powerful results – personalization at its best.

The main advantage of it is that you don’t have to cancel the background noise – every single word is relevant for the strategies. 

The real issue stays in the advantage itself: the noise.

We said you don’t need to clean it, sure, but you need to recognize the value melted with all the rest.

Extract, categorize, dig out the value.

That is where Artificial Intelligence comes to be helpful.

Artificial intelligence algorithms will extract insights from small data that otherwise would be hard or impossible to find, for example, information about people’s habits, personality, even motivations. 

If you feed AI with small data, you will have less volume – which means more significant results in less time

Also, consider that companies, 9 out of 10, don’t have enough information. They have not collected it correctly. They did not have the privacy authorization rights, or even their business is so traditional that information about people is hidden under dusted folders and papers.

Most successful AI-marketing use cases come from it, and competitor analysis too.

How to apply small data to marketing strategies: some examples

Now we know how fundamental it is, that after all, it is not so “small” and that AI can enhance it in a previously unseen way.

All of this is amazing, but we can see it – you crave examples!

Here you can find two of them to understand the potential of it better.


The Lego case is one of the examples Lindstrom makes in the same interview we quoted before. The story starts in 2002, when the famous brand was almost going bankrupt.

In the first place, they decided to rely on big data only, and it is what almost destroyed the company. So, they switched to small ones, and it was the smartest choice they could make. It translated practically, like going home after home asking questions to young boys and girls. In this way, they realized how immense was the number of insights they could collect by talking to people and asking them questions – indeed, small data at its finest.

Luxury footwear

With this pairing, brands can obtain a personalization that is almost overwhelming. Do you know which field desperately needs it? Footwear.

Personalization is one of the principal keys to luxury footwear. The brands that create custom shoes need small data like air, because “Using small data, one can move from average-based analytics to immediate decision making, from multicast to individualization, from generalization to personalization.”


If you need personalization, you need small data. They are your best friend to understand your target better, customize your offer, and look closer at your market. If you pair it with the power and velocity of Artificial Intelligence, nothing can stop you!

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