Blog: Tectonic Shifts in Market Research for 2020

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The marketplace is being leveled, at least in the early stages, by Artificial Intelligence (AI) and machine learning

The Economist famously characterized data as the new oil of the emerging digital economy[1], yet that concept needs to be expanded. Raw data is useless until there is a story behind it — linking qualitative data from surveys to real-time behavioral data. If data is the crude oil equivalent, then databases, blockchains, and data warehouses are the drilling rigs, and deep learning is the refinery that turns that oil into other useful products. Deep learning is at the heart of the emerging AI boom[2], and market research as an industry is not immune.

As we have recently seen, SAP purchased customer insights and market research provider Qualtrics for $8 billion (20 times Qualtrics’ revenue — an expensive price to bring research in-house) to grow their cloud software as they compete with Salesforce.

Yet SAP and other leading market research providers (Toluna, Kantar, and Ipsos) are reading the tea leaves. It’s not just about creating and triggering surveys — SAP can and likely will blend their software operational data with customer and employee data into one hell of a predictive narrative that could rival that of Amazon.

Because we spend a fair amount of our lives in mobile and online, market research (MR) providers who blend AI into their insights and research panels will soon be indistinguishable from some Ad agencies, social media networks, fin-tech and big tech — think FAANG (Facebook, Apple, Amazon, Netflix, and Google). These firms will already know more about customer behavior and insights well before the MR industry even starts to create job descriptions for AI-related roles. Inevitably, it will come down to data rich and data poor companies. Those who have visibility will thrive and others who do not will simply copy trends or do their best to steal talent away.

“50 percent of search will be voice-based by 2020, and commerce is obviously going the same way.”
 -comScore 2018

In a world where we delegate to Amazon’s Alexa, Google’s Home, Apple’s Siri, and Microsoft’s Cortana commands on our behalf by way of voice, it’s only a matter of time before one of those platforms asks us if we would be willing to participate in a voice survey of a product we recently bought, or frequently use or talk about based upon the deep knowledge of those systems. In actuality, these firms are already mining this data, and will be able to provide deeper context than bolt-on API’s. Whoever owns the channel will own the research and behavioral insights. Then it’s logical to assume that within the next evolution of MR, existing players will be a software and AI company in the future that taps into the massive data players (Amazon, Apple, Facebook, Google, Microsoft, Baidu, and Alibaba) while also packaging broader social insights.

It would be silly to not imagine the leading voice providers (Home, Alexa, Siri, and Cortana) to use their treasure trove of voice data to further create a moat of customer data that is both personable and predictive to create a long-term competitive advantage. However, if any one of them decided to productize, their insights could prove fatal for MR providers.

“AI is like a constantly learning child, yearning to excel every day, and data is like food to it. The bigger the variety of data the better the results. So, it’s a giant self-learning tool. As a result the competitive advantage is gathering and mining the data for insights, which companies like PepsiCo and Unilever are doing well with it, but will strain budgets in the future.”[3] BV Pradeep, Unilever’s VP Consumer & Marketing Insight

Consumer product goods (CPG) companies feel traditional players in the MR space take too long to deliver insights, and budgets continue to contract or get slashed altogether.[4]

Imagine the following scenario: a small business owner uses a debit card for a business trip to London, the bank and debit card knows what airline he or she flew, as well as the hotel and restaurants visited on the debit card. However, if he or she uses Apple Pay or WeChat, the bank and debit card know nothing about that trip. [5] In fact, they are blind to the behavior all together. Yet Apple and WeChat will be able to model the behavior and predict much more accurately and quickly than a bank or debit card company can.

The future of the MR industry is being led by both incumbents (traditional MR firms), new startups like Tethr will eventually be able to blend both MR through speech analytics and broader social insights into their client offerings, and clients themselves, attempting to build within in hopes of meeting the expected demand of a 24-hour turnaround time. The shift is moving from being able to describe and explain customer’s insights from yesterday and today to being able to predict customer insights for tomorrow.

I see the tectonic shifts happening in three core areas: quality, speed (automation), and scale, which then branches out on predictive, guidance, and consultative. Oh, and expect for the client to ask, “While you’re at it can you create a customized strategy and experience that reflects our brand?”

One thing is certain, the quick evolution of the changing MR landscape means the broader definition of MR as an industry doesn’t quite cover all the skills and services it once did, which is why we will see a lot of overlap from other industries. This partly explains the recent popularity of firms self-identifying as “Strategic Insights Consultancies” compared to positioning as a Full Service Research Provider.[6]

In short, the key takeaway for MR providers is to invest heavily in behavioral models rather than segmentation and targeting. MR as an industry will turn into data science rather than insights and research, so firms should plan accordingly. User data is the new currency.

[1] The Economist — The World’s Most Valuable Resource Is No Longer Oil, But Data. May 6, 2017

[2] Bret King — Bank 4.0

[3] ESOMAR Global Market Research 2018 Industry Report

[4] Research-Live: Budgets Continue Downward Trend

[5] Bret King — Bank 4.0

[6] GRIT 2018 MR Industry Report

Source: Artificial Intelligence on Medium

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