5 reasons why data science needs market research in a post-COVID era
With the COVID pandemic, we’ve experienced unprecedented changes in consumer behavior, affecting all areas of business. As a Data Scientist, I’ve built my career training models based on past actions to predict what will happen in the future. With the media and consumer landscape changing beyond recognition in the last 12 months, historical data availability is sparse and rapidly evolving.
We can see these changes in everything from how people are consuming movies and TV shows on PVOD services to purchasing tequila and yoga pants. Yet, assuming every behavioral change can simply be chalked up to COVID is overly simplistic. We must understand why various aspects of the coronavirus pandemic have driven these changes.
At MarketCast, we work in the fields of market research and data science. They are two separate disciplines that can work beautifully together. Both answer questions about consumer behavior, pinpoint changes over time, and identify the actions that can be taken to better position and market products and services to meet consumer needs now and in the future. Far from being competitors, these two disciplines complement each other, and I would argue that either is incomplete without the other.
Primary research fills in big data gaps
The kind of available big datasets we gather and work with as data scientists can tell us a great deal about consumer actions and behavior – what people are buying, watching and listening to. Yet, there are often gaps in the data. While data science can measure consumer behavior as it happens, understanding why consumers think, feel and behave a certain way is beyond the means of the datasets we measure. This gap can be filled by market research.
Identifies key drivers of shifting COVID / Post-COVID behaviors
Combining quantitative and qualitative research with big data enables us to understand the drivers of consumer behavior. Then we can take actions that lead to better outcomes and measure the impact of our efforts. If our actions aren’t working, researchers can dig deeper, asking further questions, to try to understand why these actions aren’t working and what can be done differently to produce better results.
Data science enriches primary research
Just as market research can enrich data science the converse is also true. Marketing teams have used MarketCast’s research to identify audience segments and discover which marketing messages and creative is most likely to appeal to them. The logic is that the most appealing messages or concepts lead to a higher number of conversions. Historically, these segments were mostly demographic, such as age, location, gender, or ethnicity. With data science, we can augment the number and variety of possible useful segments, e.g., based on interest in genres or on types of behavior, e.g., fans or disinterested consumers.
Data science tells you what marketing is working (or isn’t)
Suppose we identify four essential audience segments and want to target two of them. When we analyze how the campaign has been going, we find that one of the audience segments responds much better than the other. We can tweak the campaign, focusing less on the segment that isn’t responding well and replacing it with one not initially included in the campaign. Small tweaks like this can turn around an ad campaign that overall wasn’t performing to expectations.
Primary research identifies why marketing is working (or isn’t)
With data science, we can quickly identify which elements of a marketing campaign are successful and we can hypothesize why this is so. But we cannot determine why one TV or digital ad is better at connecting with people and nudging them toward converting with data science alone. Enter market research. We can run a quantitative survey to compare people’s attitudes to each creative or marketing message or run an online focus group to hear from consumers in their own words.
As we begin to enter the post-COVID period with hope and optimism, I am convinced that researchers and data scientists working together, instead of apart, can create a potent combination.
Just as consumer behavior dramatically shifted as a result of pandemic lockdowns and social distancing, we as researchers and data scientists can expect similar behavioral shifts as people slowly begin to socialize again, travel and vacation, return to the office, and enjoy sports and entertainment together. If we can answer both the what and why of consumer behavior during this uncertain period, we can learn and adapt to whatever the new norm becomes.
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