Let’s get a better understanding of how conventional market research still holds its own, as AI-based market research fails in an actually recorded market scenario.
Scenario: A region recorded an astronomical rise in sales of automotive batteries in the recent past. Based on this information, a car manufacturer would like to explore avenues of growth in the region and seeks market research data to help with decision making.
AI-based Research Findings: Sales of automotive batteries in a particular region reported an astronomical rise in the recent past. AI integrated market research, in its current nascent stage, which relies on large volumes of data to deduce patterns and arrive at conclusions, would attribute this to high sales of automobiles in the region. A steady increase in sales of automotive batteries may be indicative of the increasing volume of vehicles plying on the roads in the region.
Conclusion: This can be interpreted as an ideal scenario for a new car manufacturer to venture into the market, especially dealers of used cars, given the high demand for second-hand automotive batteries.
Conventional Market Research Findings: Conventional research, would factor in other aspects, which may not be evident at the surface level, such as prevalent economic, regulatory, social, and even climatic conditions. Secondary research revealed that electrification in the region was just over 50%, mainly limited to urban clusters. The region in question had a disproportionately low vehicle parc, something that would probably not be factored in during AI-based market research. Moreover, poor economic conditions and abysmal road infrastructure, coupled with harsh environmental conditions in the region would be deleterious for the automotive industry. Primary research revealed that sales of used car batteries were high, with the local population relying on these batteries–that they would periodically charge –to power their homes during daily power outages that last for as long as 8 hours.