Imagine that there are two gold miners: Swifty and Grace. Both are skilled mining managers and have dual degrees in engineering and mineralogy. Both are working mines that have been in operation for years.
Over time, Swifty experiences a decline in his monthly yield of gold ore. Figuring that the actions he has taken for years have always worked, Swifty has his crews blast away ever more aggressively, with more equipment deployed over longer hours.
Grace also experiences a similar decline in yield, but she takes a different tack. Instead of just doing more of the same, she assesses the situation. Grace conducts time studies among her work crews. She compares core samples from the areas being mined currently with samples taken in prior years and from outlying land parcels owned by her company. And she consults geological maps to see where gold ore yields are best.
In short, Swifty does more of the same to respond to the What, expecting a different result. However, Grace tries to understand Why her gold yields are down before deciding on a course of action.
Today’s Communication Professionals are Increasingly Like Swifty
Unfortunately, with the availability of “big data,” today’s PR and communication professionals act increasingly like Swifty. They focus solely on the What without first making the effort to understand the Why behind it. As a result, they generate a lot of failed programs.
Even when sales are declining, today’s PR and communication professionals beat up their data sources to discern past customer purchase patterns, falsely believing that doing the same things will lead to success. While we concede that this behavior is helpful to a degree, over-reliance on “excavating the past” has an insidiously damaging effect: It prompts organizations to continue to mine “tapped out” markets using the same old ideas and tactics. Accordingly, “excavating the past” discourages marketers from finding new market segments, identifying more successful selling approaches, using more effective information channels, and generating more innovative communication strategies.
So, ironically, an over-reliance on the shiny new thing we call “big data” too often prevents PR and communication pros from exploring or embracing newer, better approaches. It causes an unhealthy dependence on the What without first understanding the Why.
Where’s the Evidence for Big Data?
It’s true that the arguments above do fly in the face of convention. But ask yourself a simple question: Have you ever seen big data work? Has big data alone ever given you an “aha” moment that provided you with insights for selling a bunch more of…anything?
We asked some leading business professors – people who validate selling and communication strategies for a living – whether they’ve ever seen a positive sales result from big data alone. Guess what their answer was? A resounding “no.” Despite the hype, they couldn’t point to a single study or validated case of how big data, by itself, has improved an organization’s sales results.
So we posed the same question to a category marketing director for a respected global packaged-goods giant. He’s not a believer, either, despite working with data miners for years. Sure, he did say that his company’s data gurus once came to him after analyzing troves of coupon redemption and retail shopping basket data, suggesting that his pet product brands were most often cross-sold with a particular category of alcoholic beverage. Unfortunately, neither he nor his brand teams could figure out a way to capitalize on this pearl of wisdom. After all, he pointed out, it’s pretty difficult to cross-promote categories like dog food and beer.
Does this mean that mining big data never works? Not at all. But it does mean that blindly following past data to wherever it takes you is likely to lead to frustration and failure. There has to be a better way.
Back to the Future
For a clue to resolving the big data dilemma, it’s useful to reexamine the past.
There was a time – not very long ago – when PR and communication pros would examine and discuss whatever sales or market data they could readily glean from any product or service situation. This identified the What. They’d then develop a few hypotheses about Why things were happening and brainstorm the creative opportunities each Why implied for the widgets they were selling. Most importantly, they’d commission research to fill in critical knowledge gaps or test potential communication concepts that might make sense to pursue.
This old approach was clean, it was organized, and it made sense. And, importantly, it married information about What was happening with Why it was happening, resulting in a broad range of plausible marketing and communication ideas to consider and validate. In short, the old approach unleashed pragmatic creativity – not blind slavery to a database.
Under the old rules, for example, finding out that dog food and craft beer were heavily cross-sold couldn’t possibly supply enough information by itself to launch a new campaign, so PR and communication pros would first develop alternative hypotheses as to why this was the case, such as:
- Dogs love to swill beer.
- Dog owners are lonely and, therefore, like to drink.
- Dog owners tend to live in markets with heavy beer consumption.
- Dog owners become thirsty after taking their pets for a walk.
- Beer drinkers and dog owners share the same demographics.
They’d then test their “dog/beer hypotheses” by commissioning a research study and develop initiatives or campaign ideas around those validated findings. Additionally, these PR and communication pros would almost certainly test their initiatives and campaign ideas to refine them and make sure they had the power to move the sales needle.
Under the old rules, PR and communication pros wouldn’t put their own creative egos ahead of the needs of the customer, nor would they risk monetary or reputational damage to the client to speed some half-baked campaign to market under the guise of “gotta do it fast.”
Now here’s the maddening thing: This more disciplined “excavate, hypothesize, test, and create” approach would work even better today. That’s because, used correctly, big data has the potential to identify so many more What circumstances than the syndicated market studies and sales data of old. Additionally, research techniques are immeasurably faster these days, so testing the Why hypotheses and validating ensuing creative concepts no longer leads to a long delay before PR pros can hit the start button.
This more disciplined approach is still used by the most sophisticated marketers and their agencies, but not often enough. Additionally, the approach is almost never used by smaller clients and agencies, who would almost certainly receive the greatest marginal benefit from it.
For this unhappy situation to change, PR pros need to be gently reminded that not all What opportunities are fruitful, and not all creative ideas are effective ideas. They also need to become more educated about the many new research methodologies and tools that are available to them.
Tools and Techniques for Better Results
Regrettably, many PR pros (and far too many of their marketing associates) seem to be familiar with only two research techniques: Pre/post campaign measures and gathering online metrics. The problem is, these techniques are far better at assessing the What than the Why of a marketing situation, and they do almost nothing to prompt or validate effective communication initiatives or campaign concept ideas.
For this reason, it might be useful to briefly describe just a handful of the newer research techniques that can help communications pros pursue a more disciplined “excavate, hypothesize, test, and create” development approach:
- Online focus groups – Fast and comparatively inexpensive, online groups use specialized software that enable moderated, real-time chat sessions to generate a rich understanding of the Why behind a situation. They can also be used to validate and refine communication ideas and initiatives. Project turnaround: About four weeks.
- Segmentation with Segment Target Modeling – A sophisticated, large-scale online survey and statistical modeling approach that identifies relevant market segments on the basis of needs or lifestyles, profiles each segment, quantifies the client’s potential in each segment and – perhaps most importantly – develops scoring models so real people in each segment can be located and targeted with segment-specific messaging. Project turnaround: About seven weeks.
- Channel Support Modeling – A survey-based modeling technique to determine which communication programs or initiatives would gain the most support from marketing channel members (e.g., distributors, retailers, trades people, etc.), who typically have the power to make or break most client marketing efforts. These studies usually provide a simulator that allows the client or its agency to test the likely effectiveness of a multitude of program scenarios. Project turnaround: About five weeks.
- Message combination modeling – Another survey-based modeling technique that models the best combination of messages needed to motivate target customers to consider a client’s product or service. Most messages are communicated in sets instead of individually, so this is an important and frequently used research technique. These studies almost always provide a simulator that allows the client or its agency to test the relative effectiveness of thousands of message combinations. Project turnaround: About five weeks.
- Graphical concept testing – Think of this one as A/B testing on steroids. Using this methodology, an agency or client can pretest hundreds or even thousands of electronically-generated versions of display ads, landing pages, search ads, billboards, or promotional graphics all at once to determine which are best at motivating desired behavior. Importantly, this approach tests actual graphic/copy design combinations – not just attributes or message lists. Project turnaround: About four weeks.
Don’t be like Swifty
Today’s lesson is easy: Don’t be impulsive like Swifty. Use big data to identify the What, but avoid launching an initiative or campaign until you understand the Why that drives it. Finally, don’t let your creative ego get in the way of success – use one or more of the techniques identified above to validate your assumptions and the likely market acceptance of your proposed solution.
Over the long haul, you’ll gain time, money, and quite a bit of professional respect.
Have you ever been in a situation where big data led your marketing strategy down the wrong path?
If you’d like to understand the Why to your What, contact us here.