Market researchers and marketers have always maintained that understanding customer attitudes, behaviors, and unmet needs are critical for business success.
In the past, this was simpler. There were fewer ways organizations engaged with customers and fewer ways customers engaged with organizations. Now, the number of channels and the amount of content consumption is varied and larger than ever. Understanding the customer is more complex, more dynamic, and increasingly more important.
However, thanks to technology, we are now able to understand customers more accurately and more authentically. There are platforms that allow us to aggregate insights from multiple sites, text mining and natural language processing tools that improve efficiencies, and with machine learning and AI, we will soon be able to use actual behaviors to accurately predict future engagements.
To demonstrate these exciting advances – this blog will take a high-level look at obtaining and acting on customer insights – all through the lens of where we’ve been, where we are, and where we are going.
Where we’ve been
It is hard to think of a time when there was limited internet access, virtually no social media, and no smartphones. But in the 1990s, this was the case, and market research and marketing outreach required very manual processes.
In quantitative market research, we sent surveys via the mail or used random digit dialing to call people on their landlines. And while we were able to obtain a representative sample of the population, question types were limited due to the static format. Every answer from every question had to be manually recorded and tabulated.
In qualitative market research, we flew across the country to conduct focus groups in large-scale facilitates or we drove hundreds of miles to conduct in-home one-on-one interviews to immerse ourselves in our customers’ environments. We recorded interviews on tape recorders and then manually transcribed interviews typing at a computer. We printed out and highlighted transcriptions to help analyze findings.
In marketing, direct mail, catalogs, print ads, and TV/newspaper ads were king. We “tracked” impressions based on publishers’ readership and circulation numbers and tracked response rates by returned post cards and orders.
The process to capture and analyze customer insights took months, the number of channels and potential touchpoints with customers were relatively small, and the ability to impact business outcomes took time.
Where we are
With the explosion of smartphones and social media, the advancements in technology, and the accelerated adoption of technology because of the COVID pandemic – the opportunity to understand customers is more dynamic, more automated, and provides more relevant insights.
In quantitative market research, we create dynamic online surveys that have multiple pathways based on respondents’ specific responses. Survey respondents can virtually draw on advertising creative with a click of button to show what they like or what is confusing. Open-ended responses can be completed with videos instead of written responses. Wearables provide vast metrics about consumer behavior. The personalization and depth of insights gleaned are enormous.
In qualitative market research, one-on-one interviews via online platforms are saving significant costs. We use these platforms to gain insights into our customers’ thoughts and needs, as well as the effectiveness and usability of online tools such as websites. Recorded sessions can be transcribed and analyzed via online tools in a fraction of the time. Video diaries via smartphones allow us to observe actual behaviors in grocery stores, at home, and across the world easier than ever before.
In marketing, there are no longer 5-10 marketing channels, there are literally hundreds of possible touchpoints. Multiple opportunities to reach and impact our customers through social media channels, websites, SEO, SEM, videos, e-mail, texts, etc.
In addition, there are social media tools that not only allow us to aggregate insights from multiple social sites, but we can analyze that data by specific audiences, by their sentiments, and by their behaviors. There is location intelligence, which visually depicts where our customers are shopping (and where they are not shopping) within broad geographic regions. There are text mining and natural language processing tools that help us create headlines, translate detailed transcripts into key themes, and more.
With all these advances, we have shrunk the insights gathering time. We are gaining targeted insights that businesses can use to reduce risk in decision making and improve outcomes better than ever before. By making more timely decisions, we can impact behaviors before those behaviors shift. However, very soon we will be able to take these insights to the next level.
Where we are going
With ongoing technology advances, we will soon have the ability to more accurately predict how customers will engage with organizations.
Quantitative market research, qualitative market research, and marketing channel insights will no longer be siloed. We will have a consolidated data set of survey data, interview data, social media conversations, purchase behaviors, wearables metrics, geolocation insights, and any other data points we can imagine.
But not only will we have massive and consolidated data sets, but machine learning and artificial intelligence (AI) will soon allow us to use actual behaviors to anticipate future actions. We will be able to predict whether a customer will purchase our products, use our services, and what the details of those specific interactions will look like.
These advances will shrink timelines from weeks to days. We will be able to impact business outcomes more authentically by understanding actual behaviors across channels, what those behaviors resulted in during the past, and how those behaviors will play out in the future.
Implications
There have been, and will continue to be, massive shifts in how we work. Shifts from manual to automated process, from slower to faster analysis time periods, from siloed to consolidated data, and from a focus on attitudes to behaviors. These shifts allow us to better understand customers, better meet their needs, and improve business operations and outcomes.
Yet despite these shifts, there has been and will continue to be, an underlying need. The need for the client and researcher to work together to define the business objectives. The need for researchers to use data to provide actionable insights based on clients’ business objectives.
