New Product Development — Generating Insights

Insights provide a penetrating understanding of consumers, their needs and their motivations. They are the substance and the inspiration for breeding ideas and developing concepts. And they are often gleaned from the observations sourced during consumer immersion.

Observation

An observation is a factual, objective record of something read, seen or heard. It is the data that will lead us to identifying the consumer needs. It should be devoid of interpretation or judgement. Observations should not be confined within the category, they should relate to people’s day to day lives. Take for example:

  • He had a can of Jasmine green tea on his table and took the whole morning to consume it.
  • He took off his tie and rolled up his sleeves after the client meeting.
  • He walked down the stairs instead of waiting for the elevator.
  • He said he likes to eat only at restaurants where the service is prompt.
  • He often changed lanes while driving.
  • He said powerful, fuel-guzzling cars serve no practical purpose on our busy city roads. People buy them as status symbols to “flaunt” how successful they are.
  • He claims that the hybrid car he drives is good for the environment.
  • He said he does not buy personal care products. He uses whatever body wash his wife buys.
  • He does not use aftershave lotions. He says using scented products makes him feel “artificial”.

Observations are captured by associates during consumer immersion, preferably on Post-it notes so they may be grouped and mixed with other observations in the next stage.

Participants share their most interesting observations with the rest of the team. While we tend to focus more on the obvious, insights usually emerge from unexpected sources. Those observations that come as a surprise might be the ones you need to pay attention to.

Clustering Observations

Observations that share common ground are grouped to form clusters. For example the following observations could be grouped together under a cluster named “impatience”.

  • He walked down the stairs instead of waiting for the elevator.
  • He said he likes to eat only at restaurants where the service is prompt.
  • He often changed lanes while driving.

Similarly the observations below may be grouped under “my car says what I stand for”:

  • He said powerful, fuel-guzzling cars serve no practical purpose on our busy city roads. People buy them as status symbols to “flaunt” how successful they are.
  • He claims that the hybrid car he drives is good for the environment.

Generating Insights from Observation Clusters

Observation clusters are analysed to determine underlying consumer needs. A technique called laddering can facilitate this process. The team relentlessly keeps asking themselves “why” — why do people say what they say or behave the way they do? Laddering will evoke responses that relate to functional drivers to begin with, but as we persist with questioning, emotional drivers begin to emerge. The process helps to peel off the outer objective layers and delve deeper into the subjective truth — the emotional needs that are driving behaviours.

An insight may vary in form; it may reflect generalised human aspect, or it may pertain to a specific situation. Ultimately it uncovers a need that is applicable to a significant proportion of target consumers. It explains their behaviour, and is easy for them to comprehend and relate to.

For instance for the cluster “my car says what I stand for” we may come up with the following needs: individuality and belonging. By relating needs back to brand or category, we create a marketing insight. In this case it reveals what manufacturers already know: “the car is an expression of the owner’s individuality”.

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