A lot has been written in recent years on the topic of data-driven marketing. The idea seems to be fairly straightforward – the more consumer data you have, the easier it is to craft marketing campaigns that appeal to their needs and desires. This approach has been gaining more and more traction ever since the internet became the marketing channel of choice for businesses. After all, in the digital world everything is expressed in terms of data, so it makes sense to try and find patterns within it which would indicate what course of action a company ought to take to attract more consumers. In recent years, even artificial intelligence is being used for its data-crunching capabilities to find ways for achieving the best possible marketing outcomes.
Data-driven marketing rests on the assumption that consumer behavior can be quantified in an unambiguous way. However, upon closer inspection, the situation is not as unequivocal as it appears. For one, there are multiple ways to derive data from facts – a person walking down the street can be represented in terms of a physical object moving in a trajectory, or a sociological subject that frequents a particular walkway. To further complicate the matter, certain behavior that people express can correspond to widely different internal states. A person might be checking his social media profile as a result of an unhealthy obsession, or they might be doing it as part of their daily job. Observations such as these point to the conclusion that data might not be the be-all, end-all solution to marketing. Instead, what is needed is a more nuanced approach, one that combines insights gained from data, with those achieved through careful observation of the way people feel, act, and think in the real world.
Striking a balance between these two marketing perspectives is not an easy task, especially when you take into account the fact that marketing is biased by definition – proponents of the data-driven approach likely have stakes in the endeavor, which leads them to highlight its advantages at the expense of pointing out flaws, and the same goes for proponents of the other side. While we have no pretense of settling the issue, we would like to venture a few suggestions on how the two sides can work together to create marketing campaigns that utilize the advantages of both approaches.
How Much Data Is Enough?
Gathering more data on consumers seems to be inherently desirable. After all, the more information you have at your disposal, the better equipped you will be to offer on-point product and service suggestions. However, there is a problem with this line of thinking. Namely, while it is true that having more data on hand allows you to target consumers with pinpoint accuracy, this also means that consumers are likely to become cognizant of the fact that you have been gathering intel on them. And as a result, they feel start to feel that you are infringing on their privacy, which is a precious commodity in our digital age. Needless to say, once this realization sets in, consumers will quickly turn their backs on your brand, potentially causing a wide-reaching backlash if they take to the proverbial streets. In this sense, gathering data is not always in a company’s best interests.
The prerequisite for successful dialogue, marketing or otherwise, is to have both parties stand on equal ground, and this can be achieved by pursuing information symmetry. A more prudent tactic would therefore be to limit your data collection efforts to an extent, approach consumers as you would strangers on the street, and start relying on the quality of your sales pitch to get them on your side. The leading digital agencies concluded that they can reach better results if they approach consumers as human beings, instead of numbers to be analyzed.
How Useful Is Data?
Data analysis is often presented as the sole means of understanding what consumers want in the digital age. While this kind of reductive, one-sided claim can easily be dismantled on theoretical grounds, it still a fact that data-based insights do produce measurable results. However, what is questionable is the idea that this is the most efficient, cost-effective way to figure out what drives consumer desire. At a certain point, gathering additional data on consumers will start to bring diminishing returns, since the more you have of it, the longer it will take to analyze, and neither human analysts nor AI-powered analytical engines come cheap. This creates the illusion that only big companies such as Google or Amazon have the needed resources to determine consumer preferences.
To counteract this, one simply has to remember that marketing has been present in society in some form or another since biblical times, and for the majority its historical existence it didn’t rely on measurable data in order to be effective. What they did instead was talking to people, often face to face, in order to find out what they want. It is striking how this simple idea became so neglected with the recent rise of data-driven marketing. After all, if you could find out how to appeal to consumers by simply asking them what they want, the current data-mining industry would have little reason to exist. In fact, the internet is the ideal platform for initiation dialogue with large numbers of people, and yet there is an insistence on using roundabout ways of understanding what they want. Data gathering has its place in marketing, but it is at its most useful when it is used as a supplement to more human-centric approach.
Conclusion
Finding a marketing approach that leverages the benefits of modern data gathering and analysis techniques, while still maintaining a human face, is a careful balancing act. The first step towards finding a compromise that works is to approach data-driven marketing with a critical eye and see it for what it is – a useful strategy for, but one among many others available.
