It is common thought today that if your company wants to create scalability, you have to automate using Big Data and Artificial Intelligence, and the more you automate, the better your bottom line.
For the same reason doctors will probably lose their jobs before nurses do, automation cannot hope to deliver the ‘human touch’ unless it learns to be human first. The more parts of marketing we allocate to machines, the more we see our audience as nothing more than numbers and graphs.
This is not to say automation is bad and Big Data is evil. Well, the latter is up for debate. But the idea isn’t to rely fully on them, rather using it to further personalize and humanize marketing.
Before we delve into the nitty-gritty discussion on Big Data, allow me to first define what it actually is.
What is Big Data
It is defined as informational assets of such high volume, velocity, and variety, that specific technology and analytical methods are required to make sense of it[1]. All the information compiled from user data, images, videos, texts, and audio, are gathered and processed into meaningful findings using Machine Learning and other Artificial Intelligence algorithms.
In short, we are compiling all the information from all corners of the world, online and offline, in order to figure out how each and every one of us tick. And with this information, we hope to be able to understand why we buy what we buy and why we behave how we behave.
Big Data and Marketing Today
But as much as we hope the data tracking our every move can answer fundamental questions as to why we behave the way we do, it just doesn’t. All it does it show statistics that marketers will then have to make sense of.
Sadly though, marketers have begun relying too much on the data collection system, that they neglect the tedious task of asking the right questions. Instead, they just take the findings at face value and act accordingly.
The approach marketing teams take is from the angle of meeting required KPIs with suggested budgets, rather than trying to reach out to the thoughts and emotions of buyers.
Here’s how it typically works now:
First, we run ads based on the settings we think will work, assume Age Group, Interests, Search Keywords, Reach, Impressions, Engagement, Leads, and Sales. The system will then suggest the amount of budget allocation if marketers hope to achieve their target sales KPI.
We track what users do on your website, where they go, how long they stay, what else did they look at. And then we tally the user information with other information, making generalizations and placing them into Set and Subsets.
Then we sell them based on what they may be interested in and cross-sell or upsell them. We remarket based on their intention and interest. If they have abandoned carts, we push them short-term promotions to entice a purchase.
Advertisement content and narratives are built around the limitations of the media by which they appear and the Call to Actions that they require.
In no part of the advertisement process above did marketers ever looked at their audiences as human beings with feeling and emotions.
Why We Shouldn’t Put All Our Eggs Into The Big Data Basket
Jumping on the Big Data bandwagon is cool. It’s very ‘Silicon Valley Startup’. It will help a company reduce headcount while increasing productivity, and therefore profits. There are, however, some really compelling arguments to dissuade you from putting all your eggs into the Big Data basket.
Unethical Level of Data Collection
In case you don’t already know, I will explain the level of tracking that is happening everywhere online right now.
Marketers use a host of platforms and applications that track users using embedded cookies. They will be able to see everywhere you go online, what you do, how long you stay there and what you buy. Some apps will also go to the extent of tracking your physical whereabouts using the GPS on your mobile device.
Although this level of data collection is still arguably legal, users are growing increasingly worried about its ethical implications. More and more concerned people are reducing their reliance on some tech giants like Facebook, Google, and Amazon, who are known for collecting massive amounts of user data.
Government Backlash
The level of unethical data collection has reached such an alarming level, that some countries are beginning to set up regulations to reduce or even stop it.
The rate of Facebook’s disregard for user privacy has caused a severe backlash from regulators all over Europe and the USA. In 2016, the European Union introduced the General Data Protection Regulation (GDPR) that aims to give EU citizens more control over their personal data[2]. In order to protect themselves, applications and services applied the same limitation worldwide.
Facebook has recently been asked by the Belgium court to delete all of its users’ data[3] and was ordered by the German Federal Cartel office to stop gathering data of users[4].
Although all these troubles have befallen the social media giant, authorities worldwide are taking this opportunity to step up their game against any and all forms of user data collection.
And Big Data Marketing which starts with an extensive collection of personal data will soon be severely hampered by these regulations. But if marketers cannot rely on automation, what can we do instead?
How Can Businesses Change?
First thing’s first. This article isn’t implying that Artificial Intelligence is evil and shouldn’t be used. We cannot avoid the coming of AI and automation, but we can change how we use it and how much we rely on it.
The problem lies in marketers treating the numbers as ultimate decision-making denominators. Instead, we should observe those findings and asking Whys, Hows and Whats.
By asking deeper questions, marketers are able to better understand the intentions behind consumer behavior, and therefore able to create valuable marketing content.
Advocating for Privacy
All the upcoming US and European government regulations post-Facebook are making it harder for marketers to collect user information as easily as before. Apple initially advocated for user privacy and subsequently crippled the ability for their voice assistant Siri to evolve and compete with Google’s and Amazon’s counterparts. Today they are basking in the fruits of their ethical decision.
If other companies can follow Apple’s lead and start advocating for the protection of user information, the positive brand awareness itself will increase confidence among the public.
Creating Valuable Content
Consumers today no longer buy into the hype created by advertisements. Instead they listen more to their peers, which is why Reviews are so important. If brands can focus on creating valuable content, the power of social media and virality will do the rest of the work for you.
Journalism sites like New York Times and The Economist are some that managed to apply a paywall onto their content in times when content is free and still be able to turn a profit.
Netflix, with their subscription model, is able to create content that can amass virality on social media. The recent Birdbox and Marie Kondo craze are testaments to that success.
Mozilla, maker of the web browser known for privacy and security, launched a serial podcast called IRL. This immensely popular audio content talks about online privacy and its perils, without mentioning much about the product itself.
If, for example, a local bank like Maybank were to publish podcasts or YouTube videos teaching people about smart money management, loan application and management, and how to pay off student loans. Their brand will emerge as a strong proponent to a worthy cause, all while spending less than they do on advertisements.
Conclusion
It is easy to get lost in the craze of Automation and Big Data, when it promises opportunities to maximise profits while minimising costs. But unlike systemic tasks like Accounting and IT, Marketing is a human-to-human operation. And no matter how smart or capable the computers become in the near future, they will not replace actual humans.
[1] “What Is Big Data? | SAS.” https://www.sas.com/en_ca/insights/big-data/what-is-big-data.html. Accessed 22 Feb. 2019.
[2] “What is GDPR? Everything you need to know about the new … – ZDNet.” 23 May. 2018, https://www.zdnet.com/article/gdpr-an-executive-guide-to-what-you-need-to-know/. Accessed 20 Feb. 2019.
[3] “Facebook ordered to stop collecting user data by Belgian court ….” 16 Feb. 2018, https://www.theguardian.com/technology/2018/feb/16/facebook-ordered-stop-collecting-user-data-fines-belgian-court. Accessed 20 Feb. 2019.
[4] “German watchdog will reportedly order Facebook to stop … – Cnet.” 14 Jan. 2019, https://www.cnet.com/news/german-watchdog-will-reportedly-order-facebook-to-stop-gathering-some-data/. Accessed 20 Feb. 2019.
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