Why Buzzwords Suck
In my previous column, "Don’t Hire Data Posers", I wrote that one of the first signs of a poser is excessive use of buzzwords. This month, let’s talk about why such buzzwords are bad for the data and analytics business — besides the obvious annoyance of overuse.
I don’t deny that there are some benefits of buzzwords. Sometimes buzzwords summarize a long list of complex concepts in one easy-to-understand phrase. Big data, CRM (in the past), customer 360, personalization, customer experience, real-time modeling or in-database scoring are some examples.
For instance, the term big data acts as an umbrella for many different ideas that not-so-technical people may not be familiar with. But by saying that magic term, we can cut to the chase much faster. Marketers and decision-makers often interpret the term as “all data and analytics activities that enable data-based decision-making processes,” regardless of the actual data sets and processes in question. So data players like me no longer have to take 15 minutes to explain what we do for a living, and data geeks have more succint voices in executive meetings nowadays.
Similarly, creation of a single customer view or a 360-degree customer view may include many intricate steps, but who has time to list them all in a planning meeting? Just drop the term customer 360, and people will get the general idea.
But there are definite downsides to these over-simplifications. So, let’s list the harmful effects of abusing buzzwords:
- Over-simplification in itself is bad already, as it undervalues the efforts. Just because it takes less than a second to say it, doesn't mean the actual steps are just as quick and easy. Executors still have to sift through painstaking details to get anything done. I’ve seen marketers who actually thought that properly executing personalization would be simple and easy, when the reality of it is that even the very definition of the word deserves a lengthy consideration. Is it about content, delivery, data or analytics? The answer is all of the above, and one must plan for every aspect separately. Calling personalization simple is like saying, “Why don’t we make more movies like ‘Star Wars’ and make tons of money?” Well, can you make that lightsaber look real in someone’s hand?
- Buzzwords often move the discussion away from the real issues. People who rely on buzzwords tend to be posers, and they don’t generally have the ability to see the real causes of problems or key success factors. I’ve seen IT folks who committed to system re-platforming (yet another buzzword in some circles, like system migration was years ago) to achieve better customer experience and more accurate targeting. That could have been a good first step if their data were a complete mess; but in my opinion, there were other pressing issues and cheaper solutions for them. I wondered where they got the idea of re-platforming in the first place — some conference somewhere?
- Many buzzwords were created by software and solution providers in a quest to capture the essence of the product in the simplest way possible. The trouble is that blindly buying into such technology-oriented terms moves decision-makers away from business, marketing and target audiences (who, by the way, are people — not merely subjects with whom to experiment). Marketing, as we all know, is not just sums of technical solutions. Even with the rise of machines that are capable of self-learning (machine-learning being yet another buzzword du jour), customer experience management, as one example, should still be a combination of mathematics and human elements. Marketing challenges are not merely mathematical problems with concise, numerical solutions.
- Related to the previous points, many buzzwords are simplified marketing tags, as in: “If you buy our product, all your dreams will come true.” We all make slight exaggerations, but that's bad news when it leads to false promises. There is no magic bullet that takes care of all issues in one shot. So, don’t hedge a bet on some latest buzzword-ridden product.
- False promises often lead to a false sense of security: “How can we have any analytics problems? We’ve bought state-of-the-art analytics software!” Well, state-of-the-art is another buzzword, isn’t it? I’ve seen cases where companies spent seven figures on CRM platforms, thinking that their revenue will match their unreasonable expectations based on false promises. But data and analytics are games of continuous small improvements, and favorable results do not suddenly appear just because you spent a lot of money on the problem.
- All of these issues lead to under-budgeting and over-spending, and blown budgets prompt the blame game. Who bought into the buzzword in the first place? Well, no one is stepping up, so let’s make that buzzword the scapegoat! A true Dilbert moment. I’ve seen companies where executives treated analytics as a bad word. I wonder who started that chain reaction? Could it have been a poser?
I’ve also seen cases where some shiny new buzzword became an absolutely dirty word within an organization in a matter of two years. The funny part is that the core concept may still be valid! Why? Because this data-based marketing is made of many components — much like the movie business. It is really the combination of ideas, data, analytics, contents, delivery and timely execution that gets the results, not just components with flashy brand names or subtexts.
It's bad when such catchy names go viral and start gaining some sort of magical power. People with different levels of technical understanding will rely on magic power for shortcuts, and that often creates a chain reaction of meltdowns, blown budgets, missed deadlines and disappointing revenue growth.
A short answer to all of this? Let me finish with a cliché: If it sounds too good to be true, well, it probably is. Unless you have a degree in wizardry at Hogwarts.
In other words, if you are a Muggle, don’t buy into the magical power of any word.
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is principal and chief product officer at BuyerGenomics. Previously, Yu was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, he was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.