Making Sense of Consumer Research Data with Smart Analytics
20 Dec, 2022
20 Dec, 2022
Consumer research brings in sets of consumer feedback or data. However, data in the format it comes in is quite linear. To comprehensively understand a consumer and cater to their needs and wants, marketers must delve into smart analytics. Data is useless until relations have been drawn among them. Only then does data become insights with which marketers can draw up campaigns.
What’s the Current State of Consumer Feedback Data?
Often consumer feedback can seem like the acoustic feedback that makes our ears ring. Let’s have a look at the struggles marketers often face when dealing with consumer research data.
More often than not, marketers when collecting feedback miss out on establishing data models. The lack of data models has data stored everywhere and anywhere, with no rhyme or reason. This makes it arduous when trying to paint a comprehensive picture of a consumer.
Lack of Context
The ‘why’ of the consumer’s response must be recorded, to better customize and cater to their expectations. Researchers usually go for feedback alone and are confused when their analysis turns out inaccurate. Lack of context follows a domino effect with marketers struggling to craft consumer-facing campaigns with non-contextual consumer insights.
Data analytics algorithms must be established after understanding the context of data collected. When context itself is absent, algorithms have no qualitative backing and reflect numerical insights alone. Owing to this, analysis of consumer feedback is misguided, effectively misleading marketers when crafting campaigns.
Lack of Actionability
Decision-makers are in no mood to sit through feedback after feedback, which is where reports come in. However, researchers only represent what the consumer said and why they said it(hopefully). The next course of action is often, ignored. Without detailing a call to action within the report, it is quite possible for marketers to take away the wrong idea from the report/dashboard.
Intro to Smart Analytics
Integrating smart analytics within consumer research makes it easier for brands to produce consumer insights. Integrated research platforms are built-in with algorithms that generate insights and represent them within dashboards. Smart analytics is the answer to all the drawbacks mentioned above.
Pre-requisite: Contextual Data
When working with integrated research platforms, researchers must ensure that the data they’re working with is contextual. It’s not enough that marketers know if consumers pick Product A over Product B. They must also be made aware of why the preference shifted in favour of Product A.
Research platforms are doing the heavy work by running consumer feedback through smart analytics. The presence of context within consumer feedback allows for increased accuracy in consumer insights. Brands now have visibility into consumer preferences and the reasons for them.
Integrated Research Platforms Delivering Smart Analytics
Smart analytics can be harnessed through integrated research platforms that reduce time and drive up productivity. Thereby, smart analytics is an efficient tool to have in the marketer’s toolkit. Let us have a look at how smart analytics helps marketers produce better consumer-facing campaigns.
Connect The Dots
Integrated research platforms are how brands embed smart analytics into their consumer research. Additionally, researchers can conduct both quantitative and qualitative studies through integrated research platform. Now that consumer feedback comes with context, smart analytics has to only connect the dots between them. Context is key in understanding the consumer, as well as deciding the next course of action.
The democratization of technology has increased the number of touchpoints from which consumer feedback and data can be collected. Context and smart analytics can help brands delve deep into consumer data – to look for patterns and conventions. Artificial intelligence comes in to provide an added layer of behavioral data, aiding marketers to connect with their consumers intent. This way, the course of action that follows consumer research will be rewarding to the brand.
React to Market Shifts
Traditional consumer research churns out consumer insights in 10-12 weeks. By the time consumer insights have reached the marketing team, the market trends would have shifted and evolved.
When working with integrated research platforms, consumer insights are churned out in a matter of 1-2 weeks. This makes it easier for marketers to react to shifts in the market and cater to consumer preferences in the nick of time.
With great power comes great responsibility. Marketers empowered with the power of smart analytics, gain faster access to consumer insights. This in turn is reflected in faster decisions and market releases.
With traditional consumer research, marketers have to wait for around 2-3 months to get consumer insights. Planning out campaigns comes afterward, dragging out the go to market (GTM) timelines. With smart analytics, consumer insights are delivered in a matter of 1-2 weeks.
Less Error Rate
When manually dealing with data, the number of intersections where error can creep in is high. Data models driven without context would end up connecting the wrong dots among consumer feedback. Algorithms to derive insights from the data could be faulty. Reports lack actionability, so on and so forth.
Employ smart analytics to marginally reduce error rate. The integrated research platforms automate the research process, reducing human intervention. This way consumer insights are more accurate and consumer-facing campaigns fare better in the market.
Data-driven Decisions with Smart Analytics
Smart analytics help researchers comb through consumer feedback and understand them inside out. Analyzing consumer feedback is only as good as the insights derived from it. The consumer insights derived via smart analytics will enable data-driven decisions.
These decisions are what make or break a brand. When employing smart analytics, researchers must bear in mind to couple quantitative studies with a qualitative flavor, to ensure contextual consumer feedback. Thanks to the evolution of technology, integrated research platforms these days come equipped to conduct such combined studies.