Ray Poynter describes how using the Harmoni product from Infotools enabled him to analyse a NewMR project at speed.
When people buy goods or services they do not typically rate them, so why does market research use rating scales? Ray explains why and how they are used.
Ray Poynter explores why data scientists often describe the results of market research surveys as ‘qual’ while market researchers describe them as ‘quant’.
A short description of Partial Correlation.
In this 2010 recording Ray Poynter provides an introduction to Factor Analysis.
Are you asking survey questions the way you were taught 20 years ago, or are you learning from recent ‘Research on Research’?
Posted by Ray Poynter, 27 August 2018 Too many digits can obscure the story being communicated by numbers. Let’s consider a simple example from a trip to your gym and its hi-tech weighing machine. Perhaps the machine says that your weight is 101.7865 kilograms and that it should be 82 kilograms. The story is that you are about 20 kilograms too heavy. To see the story you need to focus on comparing 102 kilograms with 82, not 101.7865 with 82. If your presentation or report displays too many digits you will obscure the story you are trying to communicate. The choice about the right number of digits to display is the choice about how many significant digits to display – the topic of this post. Digits Obscure – Example 1 Consider the table below, which is extracted from the ITU (International Telecommunication Union) and shows how many mobile phones there were in each of the countries displayed, from 2010 to 2017, per 100 people. If you click on the data tables they get bigger. The data shows four decimal places and is not very easy for most humans to quickly review. This data is not friendly for the analyst looking […]
From time to time, I am asked to write some notes (or teach a section) on hypothesis testing. Each time I do this, I am reminded how little the theory of hypothesis testing has to do with modern, commercial market research. Perhaps we should stop focusing on a theory that does not really apply, and talk about what we actually do? At its simplest, the hypothesis process is as follows: Decide we want to show X is correct Design a situation ‘Not X’ and collect data to investigate ‘Not X’ Show that ‘Not X’ is very unlikely Assume X is right. This is highly unnatural for most people. People want to focus on X, not show it as a by-product of something completely different. This method is loosely what is done in academia, but almost never in the commercial world. Consider an example from concept testing Assume we are testing three new concepts and the forecast market share values are 5%, 6%, and 12%. What do we really want to know? On most occasions, I think we would like to know whether we should choose the concept with the 12% score. For example, is it genuinely better than the 5% […]
Update, the survey is now closed and the analysis has begun. When we have finished the analysis, reporting and story creation we will update this page and tell you how to get a copy of the final report and provide a link to a short form of the report. You can still see the topline result from the data collection below. We (Ray Poynter and Sue York) are running a study that seeks to benchmark the current state of play in terms of what research terms are understood. Once the data is collected we will be analyzing the data and creating a report, looking at the key issues identified by the research, and making suggestions for career and professional development. Before looking at the data results so far, please take part in the survey by clicking here [survey now closed]. The survey comprises: 9 terms used in market research, asking participants which are they familiar with (as in could explain to somebody). A series of questions asking how often people do things like attend conferences, listen to webinars, take part in training, and read articles and books. There are just two demographics, age and country. A question about topics you would […]
Back in 2010 ,I caused a minor stir in the research world by predicting (at the MRS Conference in London) that surveys would have disappeared in 20 years (i.e. by 2030). This prediction was put into wider circulation when I clarified my prediction in a blog. The key point being that I was predicting the end of the commercial, long survey, and it being replaced with social media listening, online communities, new ways of researching, the use of open-ended questions, and the use of stored information to remove the need to keep asking questions. In 2014 I updated my prediction and showed some numbers from the ESOMAR Global Market Research Report. The table below shows the figures from ESOMAR for 2007, 2010 and 2013, and my projections for 2016 and 2019. Note the figures show the spend on research, not the volume. (Click on the tables to enlarge them.) So, how did my predictions stand up? The table below shows the ESOMAR figures for 2016, below my estimates. Note, I have added a new column which combines Other Quant (e.g. traffic and audience data) with Other (e.g. big analytics). In the future I will focus on Surveys, Qual, and a single […]