In March, I attended The Insight Show in London. This event has grown and grown in recent years, thanks to its partnership with Marketing Week, the U.K.-based website covering all aspects of the industry. From walking around the show and talking to partners, one expression seemed to keep coming up in conversations: “artificial intelligence.”

It’s a little funny that AI—a term I used to associate with science fiction—is increasingly being used within the marketing research sector. This got me thinking about its impacts, not only now but also into the future.

So what is “artificial intelligence,” anyway?

To truly understand AI’s effect on marketing research, I think it’s essential to be clear exactly what we’re talking about when we say “artificial intelligence.” In all honesty, I think many organizations in many sectors boast about deploying AI to sound cool and forward-thinking, but the vast majority don’t use actually use AI at all.

Artificial intelligence is learning undertaken by machines to understand trends and key insights, which can then be adapted for a range of scenarios. To be clear, this is not the same thing as “automation.” That term is widely used throughout the sector to describe the speeding up of many processes—from recruiting a sample to data collection to analysis. However, automation can’t learn, and it needs human intervention to change.

Learning is what separates AI from automation.

So how has marketing research adopted AI?

When it comes to marketing research, AI can come in many forms, but two of the ones in which I’m most interested are social media listening and community engagement.

Social media listening

The ability to listen to people’s thoughts on social media is now widely accessible through organizations such as BrandWatch and Crimson Hexagon. Sometimes referred to as Big Qual, this technique involves using artificial intelligence and applying analytical techniques to big data, which can then be distilled into actionable results and insights to impact the bottom line.

Using AI, social listening devices can now offer insight on sentiments being shared across multiple languages. According to Hootsuite, 326 million people actively use Twitter every month. Think about the incredible combined number of comments these individuals are posting! Applying AI on this sort of large scale reduces the time it takes to analyze responses from days to seconds. (This is particularly the case when thinking about open-ended responses.)

Community engagement

Behavioural predictions help identify those individuals within a community who are at risk of disengagement. Traditionally, this would take days for a researcher to understand, but the AI greatly speeds up the process. This allows moderators to more efficiently use their resources to decide how to manage a situation, rather than spending time trying to find those at-risk individuals in the first place.

Using behavioural predictions, AI can understand and analyze the number of times someone has logged in to their community panel, the specific pages they visited, and the time they have spent on the website. This helps build a picture of an engaged individual in comparison to a disengaged person. With more data and predictive capabilities, researchers equipped with AI will be able to offer support or support to someone before that person becomes disengaged. The result is reduced dropout rates.


What does the future hold for artificial intelligence?

Artificial intelligence isn’t perfect yet, but progress is continually being made. Although it is very hard to predict where AI could be taken in the marketing research sector, certain areas have been developing at a rapid pace. One example can be found with chatbots, which are computer programs designed to simulate conversation with human users.

At the moment, most chatbots are driven by pre-programmed questions, presented via a user interface on an organization’s website. Increasingly, though, advanced chatbots are becoming able to interpret answers from respondents in a way that allows followup questions to be tailored to that user’s individual needs. This is where a chatbot and the online conversation format evolves to the next stage—virtual moderators for websites.


How will the marketing research sector be affected?

I’ve heard concerns that automation and AI could have a substantial impact on jobs in the marketing research sector, but I honestly don’t see this to be the case. As I mentioned, artificial intelligence is helping researchers by taking away mundane tasks that otherwise take days. As a result, the human researchers can better analyze the data to make real outcomes with their work.

With the continued evolution of AI, I see the role of marketing researchers changing. There will be more emphasis on their ability to do a deep dive into the data in order to truly understand what an individual or respondent is saying and how the results can have an impact on a business. For marketing research and insight professionals to make the most of a technology this powerful (and still not fully understood), all avenues and applications must be fully explored.