Market Research Redefined: How AI is Revolutionizing the Industry

How the Real-Time Data Mandate Came About

Leaders in market research understood the first problem: executives were forced to make decisions on small or slow data. The idea was to create a “Pulse of the world,” where real-time information about public opinion, the economy and consumer behavior would be available around the globe.

The pursuit of this goal became the focus of:

• High-Frequency Data Gathering: Building the capability to do informed, high-quality survey interviews everyday in many markets (e.g., more than 30.000 interviews across 43 countries per day tracking over 5.000 brands).

• Quality, not Quantity: Fiercely focused on bettering the data supply chain, reducing friction between the researcher and respondent, and delivering the best level of quality especially for critical decisions.

• Predictive power: Testing data quality by benchmarking against real world behaviour (for example, the extent to which a model can predict quarterly earnings for listed companies). It raises the profile of insight, it creates currency with CFOs, business leaders and so on.

Three Inflection Points: From Data to AI

We can observe the development of modern insights into markets in three broad phases:

• Inflection 1: High-Quality Data Collection
  Proficiency in obtaining a high-quality interview for the least amount possible.

• Inflection 2: Longitudinal Data Asset
  Using the collection capability to aggregate proprietary, longitudinal (time-series) data. This has turned into a Software-as-a-Service (SaaS) platform — a “Bloomberg terminal of public opinion market research data” — that allows users to analyze and connect economic and geopolitical data with audience demographics.

• Inflection 3: The AI Revolution
  Realizing that a platform approach, while powerful, is not currently viable without specialized user knowledge. AI equalizes access to the enormous an array of data.
  By deploying AI applications, such as a Retrieval-Augmented Generation (RAG) model, users can ask natural language business questions and preserve answers based solely on their proprietary structured data. This way, the "hallucinations" from which a person might suffer are ruled out – and good insights can be gained by non-experts.

What AI Means for the Insights Industry

The increasing rate of change and the need for speed-to-market is driving massive changes across the sector:

• Cost and Efficiency
  Research would be faster, more massive and cheaper. The cost of computation for simple operations is asymptoting toward zero, and we have to treat vanilla data processing as a commodity.

• Transition from Project Management to Consulting
  AI takes over the project management, leaving human insights leaders to do what they are actually good at – asking original, creative and critical “why” questions and acting as business consultants.

• The Power of Proprietary Data
  In the AI era, more value will accrue to proprietary, structured, high-frequency longitudinal data. General large language models (LLMs), that are to be trained on text, video, audio data suffer when learning numerical, structured data sets.

• Synthetic Data
  The value of synthetic data isn't about making old or small bad data look better ("garbage in, garbage out"), but solving problems not tractable before, such as cross-walking custom study data with syndicated sets (or integrating to other data flows -- credit card transactions).

• Agentic Future
  The third step is creating the function-specific AI agents. Rather than a generic chat interface, companies will have custom-built agents (an “Earnings Call Agent” or a “Real-Time Brand Reputation Agent”) that proactively parse data feeds and notify leaders about meaningful changes in consumer behavior or the market.

• LLM Agnostic Architecture
  Business need to be LLM agnostic (existing with different models e.g.: Gemini, ChatGPT etc.) in their architecture so that system should be resilient, flexible and best model can be targeted for a use case as technology evolves very fast.

The New Business Model: Subscription and Flexibility

The traditional onetime commissioned project model is being replaced by an annual license/subscription based model. This enables the continuous on-demand access to data and creates a virtuous circle of data collection, in which clients should be able to ask themselves an unlimited number of questions (as business needs change).

This change serves as a ultimatum to business leaders; either they can be at the tipping edge of progress by riding the wave of this intensive continuous learning mentality, or be crushed by an existential shift that is driven both purely through efficiency and innovation. The value of insights does not decrease — it increases — but the way in which they arrive through the delivery channel (research) will never be quite the same again.

EthosMR: On The Forefront Of AI-Based Insights

At EthosMR, we realize the future described is not happening tomorrow, but rather today. We are on the forefront of this evolution, building the custom application layer capable to power supreme business value. We are more than a data retrieval service, designing increasingly sophisticated AI solutions that simply meet the challenge of scale, speed and critically – depth of insight. We bring our experienced deep dive into market research methodologies, especially as it relates to the nuanced & diverse audience sets our AI agents interact with, to ensure science remains serious and applicable in order to produce culturally relevant results. It’s this mix of methodological rigor and tech savviness that enables our clients to turn their insights function from a cost center into a strategic growth driver.

The Power of Conversational AI: Voice Agents for More In-Depth Qualitative Research

A central part of our next step solution is leveraging AI Voice Agents. Whereas with conventional surveys you are restricted to asking detailed, structured, multiple-choice questions one by one in slow sequence - our Voice Agents enable the user to a free-flowing human-like conversation that mirrors real world research. To this end, this method liberates richer and finer grained qualitative data at a scale previously not possible. Our Voice Agents can modify their guide on the fly, sense emotional sentiment and then ask deep, fact-checked follow-up questions — all while ensuring compliance and keeping test takers happy. The result is exponentially higher completion rates and an unprecedented level of verbatims detail – bio luminally insightful – enabling the human insights team to shift instantly to ‘why’ behind consumer behavior.

For companies who want to do high-quality long form expert interviews, huge qualitative exploration or real time ethnography, our AI Voice Agents are the game-changing tool you’ve been looking for. They’re an example of the way in which AI can go beyond mere efficiency in order to unlock a completely new category of research capability.

Find out more about how EthosMR can quickly utilize custom AI Voice Agents to streamline your research studies and uncover meaningful, transformative insights as they happen - Get in touch today for a complete demo and ROI discussion.

Partner with Ethos Market Research

At Ethos Market Research, we specialize in multicultural market research that captures the unique voices of Canada’s diverse population. From multilingual surveys and ethnographic studies to advanced AI-powered insights, we offer customized solutions to help your brand connect authentically with multicultural audiences.

Let’s Connect:

Phone: 1-800-525-4134
Email: bids at ethosmr dot com
Address: 20 Bay Street, 11th Floor, Toronto, Canada, M5J 2N8

Contact Ethos Market Research today to learn how we can help you tap into the rich diversity of Canadian consumers and gain a competitive edge.