Observations from IIeX North America 2019 in Austin
Insight Innovation Exchange is a tech-focused research conference that wrapped-up at the end of April. This was my second time attending (first time in Austin), and I thought I’d share a few takeaways and observations, which I believe are relevant for Dig Insights, as well as the marketing research industry overall.
The death of the research panel
For the past several years, Dig Insights has been appending consumer behavioural data shared by clients to strengthen our analysis of survey responses. In the process, we rely less on stated answers to market research surveys, and increasingly on behavioural data. This is becoming more common, and I believe most clients and research agencies understand the value of properly combining attitudinal data with real behaviours, as opposed to relying on a consumer’s ability to recall what they did.
The next step in this evolution appears to be relying even less on opinions; so much so that we may not need to screen based on the consumer’s intentions at all.
Eliminating need for pre-screening
A growing amount of data collected across browsing history, as well as device and app interaction, is available and beginning to be useful for respondent recruitment. For example, why ask someone if they are interested in applying for a new credit card when their web history accurately tells us if they’ve recently looked into credit cards?
A research panel member knows, when a screening question like this comes up, that they’ll receive the survey if they say they are likely or interested. Although we do accept a certain amount of overstatement in survey research, more scrutiny is now possible.
The opportunity to use publicly available social media, web browsing history, in addition to improvements of this data to profile consumers, presents an opportunity to significantly increase the reliability of our research recruitment. Access to individual consumers who live outside of research panels is also improving. Many non-research focused apps with large user bases are a source to find these consumers.
If the accuracy of targeting for research studies, and access to reach individuals is dramatically improving outside of the research panel, then the need for a pre-screened consumer waiting to complete our market research survey will become less relevant.
Conversation-style data collection
There is now a long list of companies taking traditional survey logic and layering conversational-style approaches to create more interactive survey experiences. I tend to agree that these methodologies offer advantages over a traditional survey, and lead to greater participant engagement.
Conversational insight methodologies (such as Chatbots) make so much sense from a marketing research standpoint. There was no shortage of these technologies at IIeX, and several of them are leveraging AI in the ways that they interact and respond to an individual’s answers.
Like most companies using chatbots, we have not ‘cracked it’. The interface is intuitive and familiar, but the dialogue still feels a long way from ‘human’. I expect these methodologies will be more prevalent in the coming years as the underlying technology powering these interactions improves.
Customer service chatbots present a massive opportunity to offload human costs for large service organizations. So, there is the interest and financial incentive to make these interactions better. Market research methodologies can simply piggy-back off this learning.
I believe conversational-style approaches offer two meaningful improvements that suggest to me they are here to stay:
- Opportunity to engage hard-to-reach demographic groups via social media and messaging platforms. Everyone who uses a phone sends messages; not everyone fills out surveys.
- In-the-moment feedback. The immediacy of a text message and response can lead to faster and more timely interactions.
Have we finally moved past Millennials?
No, but have we?!?!?!
You know Millennials, those illusive magical unicorns that every research brief spell out the need to subsegment results by?
Well, if IIeX is any indication (if it isn’t, then your LinkedIn feed should be), we have now moved on to Gen Z, which is defined as individuals born between the mid 1990s to early 2000s.
They are a larger age cohort than both Boomers and Millennials. There were half a dozen sessions at IIeX that focused on how to engage Gen Z in survey research. Many of these were obvious ways such as mobile-first design and shorter surveys. Have you heard these before?
Different in ways people expect
Understanding large generational shifts is important, and I’m all for using a few shortcuts that help us align on what is meaningfully different about segments of consumers.
What I’ve seen for the past 10 years of researching Millennials is that they are different from the total population, but most often in ways that people expect. This isn’t to say we should lump all people of a generation together, but more often than not, the individual responses from an age cohort make sense.
I’ve been in countless research reviews where we examine the results among Millennials and the takeaway is “as you would expect, Millennials think…”. Get ready for the same thing with Gen Z.
