Taking a Qualitative Approach to a Data-Driven Market

Undeniably, the power of data is unmatched. With an abundance of data collection opportunities available online, and with an increasing number of businesses taking them, the potential and value of such information is richer than ever before. And businesses are benefiting.

Particularly where data concerning customer behavior and market patterns. For instance, during the past Christmas period, data were clearly suggesting a preference for e-commerce, with marketplaces such as Amazon leading the way due to greater convenience and price advantages.

Businesses that recognized and understood the trend could better prepare for the digital shopping season, placing greater emphasis on their online marketing tactics to encourage purchases and allocating resources to ensure product availability and on-time delivery.

While on the other hand, businesses that ignored or simply didn’t utilize the information available to them were likely to be left with overstocked shops and out-of-season items that have to be heavily discounted, or worse, disposed of.

Similarly, search and sales data can be used to understand changing consumer needs and consequently what items businesses should be ordering, manufacturing, marketing, and selling for the best returns.

For instance, understandably in 2020, DIY was at its peak, with increases in searches for “DIY face masks,” “DIY decking,” and “DIY garden ideas.” For those who had recognized the trend early on, they had the chance to shift their offerings and marketing in accordance, in turn really reaping the rewards.

So, paying attention to data certainly does pay off. And thanks to smarter and more sophisticated ways of collecting data online, such as cookies and through AI and machine learning technologies, the value and use of such information is only likely to increase.

The future, therefore, looks bright. But even with all this potential at our fingertips, there are a number of issues businesses may face if their approach relies entirely on a data- and insight-driven approach. Just as disregarding data’s power and potential can be damaging, so too can using them as the sole basis upon which important decisions are based.

Human error

Although the value of data for understanding the market and consumer patterns is undeniable, its value is only as rich as the quality of data being input. So, if businesses are collecting and analyzing their data on their own activity, and then using them to draw meaningful insight, there should be a strong focus on the data-gathering phase, with attention given to what needs to be collected, why it should be collected, how it will be collected, and whether, in fact, this is an accurate representation of what the business is trying to monitor or measure.

Human error can become an issue when this is done by individuals or teams who do not completely understand the numbers and patterns they are seeing. There is also an obstacle presented when there are various channels and platforms that are generating leads or sales for the business. In this case, any omission can skew results and provide an inaccurate picture. So, when used in decision-making, there is the possibility of ineffective and unsuccessful changes.

But as data gathering becomes more and more autonomous, the possibility of human error is lessened. Although this may add fuel to the next issue.

Drawing a line

The benefits of data and insights are clear, particularly as the tasks of collection and analysis become less of a burden for businesses and their people, thanks to automation and AI advancements. But due to how effortless data collection and analysis is becoming, we can only expect more businesses to be doing it, meaning its ability to offer each individual company something unique is also being lessened.

So, businesses must look elsewhere for their edge. Interestingly, this is where a line should be drawn, and human judgement should be used to set businesses apart from their competition and differentiate them from what everyone else is doing.

It makes perfect sense when you think about it. Your business is unique for a number of reasons, but mainly because of its brand, values, reputation, and perceptions of the services offered. It’s usually these aspects that encourage consumers to choose your business rather than a competitor.

But often, these intangible aspects are much more difficult to measure and monitor through data collection and analysis, especially in the autonomous, number-driven format that many platforms utilize.

Here then, there is a great case for businesses to use their own judgements, expertise, and experiences to determine what works well and what doesn’t. For instance, you can begin to determine consumer perceptions toward a change in your product or services, which quantitative data may not be able to pick up until much later when sales figures begin to rise or fall. And while the data will eventually pick it up, they might not necessarily be able to help you decide on what an appropriate alternative solution may be, should the latter occur.

Humans, however, can listen to and understand qualitative feedback and consumer sentiments, which can often provide much more meaningful insights for businesses to base their decisions on.

So, when it comes to competitor analysis, using insights generated from figure-based data sets and performance metrics is key to ensuring you are doing the same as the competition.

But if you are looking to get ahead, you may want to consider taking a human approach, too.

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