HomeData EngineeringData NewsChoosing Thick Data Over Big Data

Choosing Thick Data Over Big Data

You would possibly be aware this story from 2012 that underlines the power of massive data: Based on the shopping for behavior of a teenager, U.S. department store Target concluded that she was pregnant and sent her an advert for baby-related products. Her dad and mom angrily known as the supervisor of the department concerned. A few days later, however, the parents’ apology came to the manager. It grew to become out that Target’s facts device knew their daughter higher than they did themselves.

And indeed, huge records has established its fee for many matters associated to sales and marketing, including for the personalization of promotions, guidelines and personalization of products. Big information creates remarkable opportunities to rapidly deduce “what” is taking place from very giant numbers of flat records and to make statements and/or predictions based on that. Due to an growing trust in technology, statistics and desktop learning, it appears alluring to additionally use massive information for innovation.

But it is when it often goes wrong. While large records can inform a lot about “what” is happening, it has massive shortcomings in telling you “why” things are happening. And that latter query is exactly the one fundamental for innovation.

An instance is the originally failed product Febreze from P&G. First delivered to check markets in the early 1990s, P&G used TV advertisements to instruct buyers what smells the product ought to put off and what it should be used on, such as fabrics, fixtures and different household items. The organization notion it had a prevailing product, but as months went by, sales dropped. Its leaders couldn’t apprehend why until they talked to customers, who confirmed them that it was challenging to market a product that neutralizes odors to buyers who do not trust odors exist in their homes. This shifted Febreze’s advertising and the work its innovation team was doing. Now Febreze is recognised for its fresh scents that act nearly as a “reward” after cleaning.

This product innovation and launch is simply one of many examples where a distinct type of data is needed, providing perception into deep-seated human aspirations and needs.

Invest in thick data to understand the “why” rather than the “what.” 

We name the beforementioned facts “thick data.” It issues small however very well-picked samples, information series in the consumer context and a focus on deeper insights. With thick data, it’s about people, feelings, situations, conduct and the prosperous records that results from research on these aspects. Instead of relying on statistics evaluation in giant numbers, insight is gathered by means of observing humans and doing in-depth interviews in which now not the “what” but the “why” query is central — and in which the surprise is central with the aid of asking in addition questions.

In my very own practice, I use an sizable set of methods that contain thick data, every with its professionals and cons and context in which they are fine suited. Let me share some examples:

Job-to-be-done research exposes why a person buys a sure product so that you reap insight into what improvement capacity for the user. Doing this type of research, a fast-food organization may determined out that it should not enhance or add style selections for its milkshakes however innovate on long-lasting taste, compatibility with cup holders and a straw that lasts.

Unmet need-finding exposes which troubles and priorities clients have in addition to the ones solved by means of your product or service.
Thick records provides route for opportunities to expand or create completely new services. This is why Netflix makes content material now rather of only being a streaming provider.

Customer journey/experience mapping exposes what feelings customers have when consuming your services. This thick data offers course in opportunities for better patron experiences. At a large airport in the Netherlands, my company determined that the ride used to be affected by means of a hostile protection experience that we had been in a position to revert into a hospitable experience.

Pretotyping exposes whether or not (and which) clients apprehend your product idea and how they identify the value by displaying a fake version of it in stores or digitally.

Thick records offers companies the capability to deduce “why” things manifest from small numbers of prosperous data. Finding relevant pointers for innovation often requires this kind of research and mindset.

Do companies have to forget about big data in order to innovate?

Not at all. The strength lies in understanding when to observe each disciplines and how they can beef up each other. For example, one can use thick facts to grant beginning factors for new purchaser troubles or needs, which can then be validated and deepened via the assist of big information available in systems. Or vice versa: Through consistent NPS measurements, one can see trends in customer experience or positive moments when consumer journey drops and then discover out thru interviews what triggered them, making designing applicable interventions easier.

 

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