Is Data Becoming More Important than Budget for Marketing Departments?

For decades, Chief Marketing Officers have measured their self-worth and stature by the size of their budgets and the number of people who work for them. In 20th century marketing, a bigger budget meant you could buy more advertising; you could buy a bigger trade show booth; and you could buy more leads. But times are changing. In the 21st Century, technology and data science are leveling the playing field. You don’t necessarily need a big budget to win. Over 80% of marketing spend is wasted on trial-and-error – attempting to engage target buyers with the wrong message through the wrong channel in the wrong format at the wrong time. If you can make smarter decisions using data, you can yield the same results as competitors who spend 3-5 times more than you on marketing. I would much rather have one terabyte of data than another one million dollars in marketing budget.

I know what some of you are thinking. This kind of talk is blasphemy! We are marketers and spending lots of money is in our DNA. Sure, as much as the next guy, I enjoy spending a $100K on some over-the-top antic to generate publicity or attention. But there is also a certain swagger you can develop when you can achieve results on a much smaller budget than your competitor.

Make no mistake big-budget-holders will continue to be coveted by the Madison Avenue agencies selling advertising, branding and creative services. But the data-holders will be the longer-term winners in corporate board rooms with venture capitalist, private equity shops and Chief Financial Officers. Anyone who can reduce a marketing budget from five percent of new sales to two percent of new sales, while achieving the same results will be a hero. And this new breed of CMO will be the ones highly coveted by executive search firms for the next pre-IPO $1 Billion startup.

What types of data am I talking about? It could be demographic, firmographic or behavioral in nature. Any data point that will give you an edge in attempting to reach a buyer is data worth capturing.

Imagine if you knew that Jennifer Buyer, CIO at TBTF Bank responds to interesting direct mail, but never answers the phone or checks voicemail. She hates unsolicited messages on LinkedIn, but is a sucker for personalized emails that show thought and effort by the sender. She is most likely to respond to an email late at night or over the weekend than during the busy workday. She won’t come near a product page on the website or a product brochure. Instead, she prefers to read blogs and case studies. In Google searches, she tends to pick YouTube videos and SlideShare presentations over text documents. She craves benchmark data, but distrusts any research without a reputable brand name behind it.

Armed with this information your Lead Development Representative should have a pretty good idea how to engage Jennifer in a way that gets a response on the first or second try.

For one-to-many marketing programs (webinars, social media, eBooks, trade shows) it is unlikely that your target audience will converge around a single message, format, channel or time. Your target audience likely will be scattered across each of the different options. However, you can analyze patterns and probabilities to make more data-driven decisions about where to invest budget dollars.

Imagine if you knew that your audience is six times more likely to attend a webinar with a Gartner analyst than a Forrester analyst. Your audience is three times more likely to see an advertisement in the Wall Street Journal than the New York Times. Your audience is ten times more likely to watch a YouTube video than a Slideshare presentation. Your audience is fourteen times as likely to search on Google than Bing. Your audience is more likely to watch an ad during the SuperBowl than during a Presidential Debate. Your audience prefers Star Trek to Star Wars and Batman to Superman.

Armed with this information your Demand Generation team could have a pretty good idea how where and how to spend their money. In fact, they should be able to cutback on spending considerably by investing primarily on the channels and formats that have the highest probability of generating the most leads.

There is one small problem with this theory. It’s still really, really hard to get all of the data you desire with today’s marketing technology. You will never 100% of the behavioral and demographic data you are seeking. At best, you might get one-third or one-quarter over a multi-year period. Given that, would I still take the terabyte of data over the million dollars in budget? Absolutely! It would arm me with a considerable competitive advantage that would yield far higher results from my marketing programs than more budget.

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