The GRIT data collected toward the end of 2022 included 918 open-ended replies to the question “Related to insights, research, or analytics, which topics do you follow most closely and why?”. These replies were assessed via Ray Poynter using Word Cloud Plus to extract the key themes. After some cleaning, for example, translating the open-ended comments into English (US spelling) and replacing ‘ai’ with ‘artificial intelligence’, the accompanying initial cloud was generated.
The sizes of the words and phrases were generated automatically and relate to their frequency scoring. The locations and colors were added by a human.
Note the scoring system used by Word Cloud Plus favors terms with two words over single words as we believe this gives more insight. For example, we think it is better to have data quality, data analysis, data visualization etc. as separate phrases, rather than a large ‘data’ item.
The analysis of the word cloud suggested five key themes. These themes are Artificial Intelligence, Data Quality, Analysis and Analytics, Consumer Behavior, and Trends.
The first trend to mention is artificial intelligence (and remember this data was collected before the ChatGPT hype had taken off). As the three quotes below show, it is of interest in a number of ways.
- artificial intelligence being used for research analysis because this is helpful for a small team like mine where we have few resources and using an artificial intelligence-enabled tool for research would help extend my team
- AI and machine learning in analytics and insights platforms (for analyzing marketing research…seemed very far off but the technologies are getting better and more efficient cost-wise so it’s likely not that far off now
- adaptive artificial intelligence systems can offer companies the ability to make fast and flexible decisions by adapting more quickly to changes
Most of the good things about insights and research depend on having good data, and people are clearly worried about it.
- data quality data quality data quality!! how to improve data quality
- data quality – I spend most of the time cleaning data
- panel data quality and monitoring as we are kicking out respondents at a high rate
Analysis and Analytics
There is much interest in what we do to find the answers we need, be that text analytics, data vizualisation, or data science.
- digital analytics and advances in attribution technology and modeling because attributing results based on consumer actions is increasingly difficult in a multi-touch, omni-channel consumer experience
- reporting (easy to understand); this may include dashboards tools such as Google Data Studio, PowerBI
- technology trends in data engineering, data management, etc.
Note, during the cleaning stage we replaced the word analytics with analysis as we had lots of examples of pairs, such as ‘data analytics’ with ‘data analysis’ and ‘text analysis’ with ‘text analytics’.
Not surprisingly, people are interested in consumers, with some elements of this topic also overlapping the Trends category.
- behavioral science – how can we bring underlying consumer behavior motivations and drivers into the big data analysis
- customer experience management / nps system
- consumer trends particularly in relation to shopping behavior in inflationary times
Trends is a bit of a catchall, covering quite a wide range of interests. The trigger here is the word trends itself, i.e. focusing on change, whereas the other four themes are more focused on topics.
- client trends in terms of what they are looking for
- analysis of media consumption trends
- thought leadership and industry trends that inform our analysis and insights
- industry trends of both new tools and customer needs
Dogs that didn’t bark (much)
The 918 open-ended comments, comprised 11,947 words, or 2,838 unique words. In addition to creating themes from the words and phrases that occurred frequently, it is interesting to consider some of the terms that were used less frequently. Below I highlight three themes that have been hot topics in recent years.
- Storytelling appeared 19 times in the comments, which is why it is not featured in the word cloud. By comparison, Innovation was mentioned 41 times.
- Neuro appeared in two forms, neuroscience and neuromarketing. Neuroscience was mentioned seven times, and neuromarketing three times.
- Blockchain appeared just twice in the comments, and no words starting with ‘crypto’ appeared at all.