Why Human Insight Is Critical, and Data Alone Doesn’t Suffice
AI and automation are unparalleled in studying patterns, but human insight is necessary to add the right context.
It is the digital age, and data is the driver of all significant decisions. Organisations guide their strategies from data, which undoubtedly is the backbone for marketing operations. However, while data in all its beauty can offer scale, efficiency, and evidence, there is one aspect it fails to provide—context.
Today, all marketing functions are dependent on algorithms, which has enabled faster decisions. However, while algorithms can inform marketers of what a customer wants, it misses to identify the “why.” Data can read trends and patterns but human insight is needed to read between the lines and understand emotions behind certain behaviours and actions.
As reliance on digital channels spikes, there is lesser direct interaction with customers, leading to scarce human insights. This makes it difficult to understand the consumer psyche. Before digitalisation, the store manager would meet the customer frequently, getting a chance to peek into their behaviour as often as they made purchases.
Now, with online commerce being the sole driver of sales, customers do not interact with brands directly. All marketing decisions rely solely on algorithms and the data they provide. What’s the problem then? This data, while efficient and helpful, can lead to generic marketing that feels impersonal and fails to resonate with audiences.
Why Over-Reliance on Automation Is Dangerous
Let’s take a retail example to understand exactly how businesses could face losses upon depending heavily on automation. Algorithms are adept at reading trends and patterns, and analysing data like purchase histories to guide marketing decisions. They even successfully offer personalised recommendations that tailor to the customer. However, without incorporating human insights into it, this process becomes robotic and stagnant.
The algorithm ends up showing the same recommendations repeatedly without refreshing. Shoppers do not get to access refreshed ideas and end up having an unsatisfactory experience. This way, brands ultimately lose the opportunity to cross-sell and retain the customer for long periods.
Three Major Pitfalls of Pure Automation
Bias Creeps In
The data that algorithms feed and train on is collected over years and more often, is historically biassed. Biassed inputs fed to algorithms can lead to ads and suggestions that are discriminatory in nature and can offend customers.
Big companies like Facebook and Google, whose AI models are those trained with the most massive volumes of data ever, have been found to be discriminatory too. Facebook was sued by the US Department of Housing and Urban Development over the way it let advertisers purposely target their ads by race, gender, and religion. In more instance, jobs ads for janitors and taxi drivers were shown to a higher fraction of minorities, and homes for sale were shown to a higher fraction of white users.
In the case of Google, independent research at Carnegie Mellon University in Pittsburgh revealed that Google’s online advertising system displayed high-paying positions to males more often than to women.
Biassed inputs, hence lead straight to legal and ethical challenges.
Lack of Human Touch
Without human insights incorporated in the recommendation process, algorithms are trained to deliver results optimised for more clicks and conversions.
B2B Marketers say the most profitable uses of automation are lead generation (80%) and conversion (71%). However, this implies use of sensationalistic content meant entirely for generating clicks, leading to a loss of customer trust. Customers, dissatisfied by the experience, switch brands.
Personalised Vs. Personal
Data is the only way to deliver hyper-personalisation, but without context and an understanding for customer behaviour, this data can end up over personalising the content reaching the customers.
“Privacy has divided opinions in adland. On one side are platforms, advertisers, and adtech companies that understand and respect the need for consumer privacy, and have embraced the opportunity to make advertising better,” says Maor Sadra, Co-Founder and CEO of INCRMNTAL.
“On the other, are those clinging on to user-level tracking, refusing to cave to privacy legislation for fear it would impact the effectiveness of ads regardless of consumer sentiment,” Sadra adds.
In this era of data privacy, over personalisation drives customers away by making them feel stalked. Customers become uncomfortable in sharing further data with the brand and ultimately choose to stop engaging.
How to Make Human Insights a Part of Strategy
The first and foremost way to integrate human insights into decision making is to make it a central part of the organisational culture. The key here is to make direct interaction with customers a necessary part of operations. There are multiple ways to do this, including in-depth interviews and customer feedback loops.
Commenting on getting in the customer’s shoes, Alex Swain, Digital Design Director at Deutsche Bank, says, “I love the idea of a job swap, even for a few hours. When you spin the perspective on something, you learn more and your bias changes.”
Another approach to go about this is instilling customer research as the blanket of all customer processes. Marketers can read beyond data points by conducting detailed customer research and ethnographic studies. Insights into customer behaviour can be revealed by going deeper beyond surface-level data. The marketing team can also sit in workshops to challenge assumptions around customer behaviour, imagine customer scenarios sitting in their shoes, and derive unique perspectives that can guide marketing decisions.
Finally, when packaging the recommendation process, appoint a member responsible for integrating human insights into all decisions. This person ensures that the decisions aren’t entirety automated and reserves the right to overrule algorithms, wherever necessary.
Human insights must be brought into the company’s DNA in order to best utilise its power. This can be done by regularly organising customer interaction sessions for all teams whose work directly or indirectly impacts the customer.
All said, technology’s role is in no way any less significant than human oversight. Winning businesses will know how to strike a balance between the two. The future is driven by AI, but human guidance will only supervise it for the better. The two will function the best when they complement each other.
