Asked for predictions and future trends, younger people and elders forecast a different future. The judgement is based on past experiences, where the elders had a longer time to watch. Now there is research which uses stock market predictions and inflation expectation to measure the difference in estimation between age group.
Ulrike Malmendier and Jessica Wachter show in their paper how long time experience correlates with investment decisions. People with long experience include old information in their judgments. Do they make better predictions? The study has no answer for that.
Past experiences stick. Did you ever notice the warm emotions showing up when memories to a nice situation long ago appear? Another nice thing of the past is that we know how all ended. And we can connect with others about the long gone events.
For the ones who follow politcs: party members choosing a candidate are mostly elder and more extreme than the ones who vote. So their candidate might have problems.
Artificial Intelligence has no memory
Humans differ from artificial intelligence in learning. AI connects the data and learns from what was in short sight. Humans take their whole life experience together and build their judgements on that.
Hiding the past helps sometimes
There is a connection between memories memories in market research and in own, personal ways to think and judge. Discovering the role of memories in own judgements and being able to switch it on and off helps to get a better picture of the world of younger people. It is about trying to look at the world while leaving out past memories.
Having a long memory may be helpful in forecasts and judgements. Mathematical evidence from the stock market does not give any proof for that.
Customer journey and past experiences in market research
Along a customer journey the traveller takes a lot of decisions. Will old memories take a big influence on that decision? Research shows it does. Big example are cars. Seniors buy different and bigger cars.
A buyers persona is a picture of our targeted group. It says persona for the reason we do not need to know everything about that person and there might be different persons in our target group. The second part is about qualitative market research. We use this kind of searching for behavioural characteristics for creating this buyers persona.
A wrong image of our target group costs us money and makes our brand less popular. Simple example is posting on Linkedin without reducing the number of followers. I looked at the list of people I unfollowed. The reason for doing that was that they posted repeatedly content I do not like or is just not true. Most of them are aging german business trainers spreading far-right political statements and sometimes even far-right lies. The other ones are sales newbies who spread too often their pitches aimed at a different buyer persona than me. Is a close group of followers who believe the same political statements as the poster the thing the poster wanted? If there is no reaction to your post does hammering out repeatedly the same sales pitches again and again to the wrong targets a good thing? Or should we appeal to a broader audience?
Why qualitative Market Research
This article is about bringing qualitive and quantitave research together with integrating numbers and representativity into qualitative research. Quantitative research is primarely counting and statistics.
The topic of qualitative market research is understanding. What does the world of my target group look like? What emotional and financial settings do they have? Quantitative research, on the other hand, determines how many people in the target group have which attitudes, how many they are and how their budget looks. A random sample is drawn so that not all members have to be questioned.
The claim of qualitative market research
Qualitative market researchers understand the customers. Its like some newspapers articles, where journalists describe some individuals where they think they are good for the numbers. Quantitave shows the numbers – for example 60% believe that the government does a good job in education. Discussions in focus groups, in-depth interviews, images, social media and much more can be used as data sources for qualitative research.
Also compare here (New Market Research Blog). The qualitative market researcher is an active part of the research process. He or she uses their subjectivity to better understand the phenomenon being studied. You want to understand why people believe in what and see the world a certain way. A qualitative researcher wants to understand the process of selecting a product, for example. A quantitative researcher wants numbers, averages, and more. Manufacturers and dealers can then base their decisions on this.
How qualitative researchers can do representative studies with small numbers
A qualitative researcher makes small samples. Understanding the process and the mindset of the subjects, this researcher assumes some validity. To ensure this this procedure can help:
The result of the small sample are suitable when no changes are to be expected from a larger sample. This can be checked by first evaluating 30 questionnaires. Hopefully there is no significant change with a further 10 questionnaires. If there is, another 10 questionnaires are added. If this does not maintain the hypothesis that the differences in responses are statistically insignificant, the study can be considered representative provided the responding participants represent the target group.
Some subjects suitable for qualitative studies:
Lists of ideas – if the ideas are repeated, the study can be ended. Studies that do not record the subjects’ ideas via structured questions but via free text information fall into this category.
All – or – none results. If every participant in a small study says the same thing—like, “I see a train station in this ad,” or “I prefer the new packaging”—the conclusions are likely to be valid, even with small samples.
Strong hypotheses for the study to support If we have a hunch and it is supported by the small sample, we can be sure that the hunch is correct. All we have to do is verify that the underlying hypothesis is not just speculation. This type of market research is popular with journalists who can get by with just a few interviews.
Understanding instead of measuring – for example customer journey. This analysis helps testing new products.
The problem of representativeness in qualitative research remains.
With small samples, the problem of representativeness remains. There is no statistical way to ensure the representativeness of a non-probable sample. The market researcher’s judgment must be added here: can the result be as the study suggests or are there other, contradictory results? Trusting only statistically proven results without knowing the underlying connections can be misleading.