To make the most out of data brands need to use it to derive new insights

Guy kedar
Guy kedar
Feb 12 · 4 min read

In my previous post on the topic I reflected on the potential of turning data into commercial value and the importance of having a data strategy which is customer focused.

Data, however, is just the raw material in this process of value creation. In order to make value out of data, it has to be turned into information which in turn can be translated into knowledge and eventually insights (to learn more on these four stages of evolution it is worth reading about the DIKW pyramid).

To understand the importance of translating data into insights one should remember that ‘data’ is simply a collection of signals, and that information, while adding a narrative to data by putting it into context, still describes the ‘What’ (and sometimes the ‘How’) but seldom the ‘Why’ and therefore requires further investigation. Take for example Theodor’s Levitt’s famous quote: ‘People don’t want ¼ inch drills, they want ¼ inch holes’. A collection of ¼ inch holes is data which, on its own, tells us nothing more than that there are X holes at the diameter of ¼ inch. Put in the context of a wall, perhaps even in a living room, and that these holes were man-made, provides us with the understanding that humans create such holes in their own homes. This, however, is still information which bears limited commercial implication. Add to this the understanding that people drill ¼ inch holes in order to hang pictures and you enrich your ability to act upon this data, perhaps by deducting that there is a market for ¼ inch semi professional drills OR that there is room to innovate in the way people can hang pictures. I’d argue though, that this analysis (at least as widely quoted), still falls one step short as it doesn’t seek to uncover the motivation of people to hang pictures in their living rooms. An understanding that people hang pictures in order to preserve and present their memories could lead to innovation on the topic of memory capture and display whereas an understanding that people hang pictures in order to show off their good taste in front of guests could lead to entire new areas of innovation.

Let’s take another example: Many people use refreshing mouthwash. This fact on its own is data. Put in context, such as — Many 20–40 year old people who live in urban surroundings use mouthwash — this data (now ‘information’) can be utilised commercially (by enabling to forecast demand and sales volumes, for example). Further adding the understanding that these people use mouthwash because they want to feel good about themselves can help refine marketing efforts or drive development of additional products that make people feel good about themselves. But understanding that people do so because they need to feel good about themselves on specific occasions, such as dates or business meetings (would people really bother using mouthwash if they were on a desert island?) provide a powerful insight that can open the door to multiple related innovations (such as that enable/support social interactions).

Turning data into information, knowledge and ultimately insights is a key factor in the ability to use data as a commercial lever. Brands should therefore go beyond their observations and derive customer insights that can serve as springboards for innovation. They should strive to understand the Why behind the What and the How.

Working with a Telco provider on a recent project we leveraged data to gain both insights as well as incite more questions which otherwise wouldn’t have been asked. As a company which sells mobile and broadband, this brand has high visibility of the number of smart devices used by people. It knows the number of smart devices that are connected to a household’s router and it knows the type of smart devices used, based on the apps which each specific household’s residents download and use. As such, it can know various things: It can know which areas in the country are more populated with smart devices than other areas and it can know which smart devices are frequently bought with each other. This alone has commercial value to brands which manufacture and market smart devices. They can evaluate, for example, the sales potential in various areas and they can offer bundled products based on purchase habits. What this information does not explain is the Why. Why are some areas more populated with smart devices than others and Why certain people who purchase one specific product frequently purchase another one. Answering those questions requires further investigation and has far greater commercial potential: Understanding why specific areas have more smart products than others may suggest that better infrastructure, such as broadband or smart switches, is missing in undersold areas. Understanding why people purchase specific products in conjunction with others can lead to developing features that connect between these products, and understanding whether the reason for stagnating sales is market saturation or lack of residents’ time to visit the physical point of sale can impact marketing efforts, allocation of shelf space and development of ecommerce platforms.

More and more companies seek to make better use of their available data and turn it into commercial value. Answering the following questions can be a good first step in doing so.

1 — What data do you have?

2 — In what context did you collect this data?

3 — What do you believe this data tells you about your customers, employees, operations etc?

4 — Why do you think this data shows what it shows?

5 — Who do you think can make use of this data, if contextualised and properly story-told?

    Guy kedar

    Written by

    Guy kedar

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