brandcentric blog

On May 21 at 11 AM Pacific, John Carlson from Cannondale Associates and I will appear together on a webinar on trade promotion effectiveness.   You can click here to register for this event.  John’s insights are based on a set of one-on-one interviews that Cannondale conducted with category management and merchandising executives from large grocery retailers.  These interviews focused on which manufacturers set the bar for trade promotion management, and what specifically the manufacturers were doing to distinguish themselves.

Cannondale was kind enough to invite me to provide DemandTec’s perspective on what this means for the CPG manufacturer community.  I’ll plan to tee up some pretty tactical recommendations to help put into action Cannondale’s observations.  As I started to sketch out my talking points, I ran a quick analysis to track share price performance of the short list of recognized manufacturers.  Interestingly enough, every member of the group outpaced the S&P 500 in a trailing 2 year comparison.  It would  be unfair to attribute this performance to just effective trade promotion practices, but clearly there is a common thread with how this group of leaders manages their respective businesses.

The webinar will be hosted and facilitated by our friends at Consumer Goods Technology (click here to register).  Hope to see you there!

Now more than ever marketers are evaluating budget allocation: where to invest, why to invest, and what to expect out of the investment.  Traditionally marketing mix allocation was a mashup of last year’s plan and a few top-down financial objectives.  There was little in the way of science, program simulation and predictive planning found in the allocation decision process.

A cottage industry of agencies emerged.  Firms like MMA, Hudson River Group and Analytic Partners introduced modeling science to mix planning.  Other strategy consulting shops like Bain and McKinsey developed  marketing mix analysis frameworks.  In both cases, the deliverable was either a 2 inch thick binder of recommendations and/or a “what if” tool built into Microsoft Excel.  Nothing scaled beyond the initial deliverable.

There is a new breed of marketing mix modeling technology that is starting to shift how CMOs are managing their marketing investments.  While the underlying science is consistent with what the cottage industry players provide, the step change is in the delivery.  This new breed is delivered via Software-as-a-Service, providing always-on access, frequent model updates and broader visibility throughout the enterprise.  Companies like M-Factor and Breitley are leading the charge with promising customer traction.

The big unknown here is whether marketing leadership is ready rethink how they approach mix allocation.  By and large, mix modeling is still an annual (and perhaps bi-annual…maybe quarterly) process that then drives a lot of downstream decisions.  Mix allocation is not really thought of as a fluid process to accommodate the week-to-week noise that filters in from the market.  But the upside is potentially so big if the industry does embrace this new way of thinking.  And some big CPG manufacturers have put a stake in the ground and are starting to shift behavior to be more in line with a fluid, “always on” approach to mix management.

The tools are upon us and the economic case is starting to gel for a different approach to marketing mix allocation.  It should be exciting to see this new and emerging space take shape.

My first guest blog entry comes to us from Mark Ahrens, VP of Product Management at The Nielsen Company.  Mark is a career marketer with a strong CPG industry orientation.  He shares a very interesting perspective on the tools CPG brand managers ultimately want (and need) to mine data and develop informed business decisions.  Thanks for the entry, Mark!

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Given Amazon’s recent stellar financial performance, few people remember the collective mocking of CEO Jeff Bezos when he proclaimed, during the Internet boom of the 90s, that “Wall Street (read: profits) is largely one huge distraction.”  At the time, many thought him to be another naïve webbie who couldn’t, as they say, monetize his business model if it bit him on the you-know-what.

Well, the real genius of Bezos was not that he was able to amass a wonderfully efficient network of distribution centers.  His genius wasn’t in the clever deployment of a data mining algorithm-collaborative filtering–into the buying process nor was it in being an early pioneer of shopping cart technology and e-commerce breakthroughs (e.g. One-click Shopping).  His real genius was that he assembled all of this technology as a means to an end.  Bezos’ end game, so prescient when viewed over a decade later, was to enable a consumer to purchase almost anything they could think of, have it delivered to their house overnight, and do so at a low price point – become the Wal*Mart of ecommerce.

Now, let’s take Google.  Millions of people have specified Google as their default when they launch their web browser.  Is it because they really like its creative interface?  Hardly.  Is it because Google has one of the world’s most powerful and sophisticated search engines?  Sort of… The real reason people set their web browser to Google is because they know that if they need to find something on the web, launching Google will help them find it very quickly, reliably, and easily.  Google accomplishes this simple-sounding task so well that to “Google-it” has become part of our vernacular.

The two examples above share a common thread.  Both Amazon and Google solve a first-order need state for users in a way that is faster, simpler, and better than was previously possible. At this point, you might be asking “What do Amazon and Google have to do with the CPG industry?”  They serve as reminders that technology, by itself, doesn’t solve the day-to-day tasks of CPG knowledge workers. 

No Assistant Brand Manager wakes up in the morning thinking their job is to run the latest report or produce mind-numbing rows and columns of numbers.  They don’t wake up thinking how great their BI reporting tool or data warehouse is. Rather, they wake up (or at times, are kept awake) wondering “Where’s the next big product idea?”, “How am I doing versus plan?”, or “How’s my shelf price gapping to Private Label?” 

CPG knowledge workers want, literally, to be able to “Google” for high-value, business insights. They don’t want to have to track down arcane DB names, memorize multiple passwords, or master complex navigational paradigms across multiple systems both within and beyond their corporate firewall. Rather, they want systems that “talk to one another”…not exact look and feel, but a shared context when moving from one system to another.  They want help in interpreting what caused what to happen and what should they do next. They want the proactive answers to questions they didn’t even enough know to ask.

Solving the needs states above for CPG knowledge workers will certainly involve a broad array of technologies.  For instance, intelligent, scaleable DB design, including both physical and federated integration, business-issue data marts, and a robust meta-data management system will certainly play a large part of any such solution. Other technologies such as data visualization, expert systems, embedded data mining, modeling and simulation, and social media-based collaboration will play an important role as well.

However, as we have learned from Amazon and Google, it will not be the brute-force assembly of technological piece parts that separates winners from losers in the CPG vendor marketplace.  The winners will have focused its technology laser-like against the highest value tasks of a CPG person’s day-to-day job.  The blueprint for winners will include a solution that tells someone What happened?, Why it happened?, and What they should do about it? With the same simple elegance as the search answers they currently receive from Google or the purchase experience of Amazon.

Upon reflection, Bezos’ vision is really only a present-day derivation of Ralph Waldo Emerson’s old adage-build a better mousetrap and the world will beat a path to your door. Those vendors who provide the better mousetraps to the CPG industry’s business problems and provide them in a way that is faster and simpler for users to consume and collaborate will capture the marketplace.

Like all good marketers ought to do, I wrote the obligatory contributed story on what this challenging economy means for CPG brand health.  Specifically, my call to action was to apply more rigor and science to the trade promotion planning process.  Doing so is both good brand hygiene and also a likely long-term competitive hedge against private label.  You can find the published story on the Journal of Trading Partner Practices website.

On a side note, as this story went to press commodity food ingredient costs started to tumble back to reality after unprecedented gains in the first half of 2008.  But the same rationale for a better planning process still applies, even in a highly volatile cost environment.  The price hikes that P&G, ConAgra and Kraft were all forced to make in the first half of the year have yielded price decrease decisions that require the same analytical rigor.

As a young buck associate brand manager at ConAgra Foods, I developed a deep appreciation for how big brands stay competitive at retail.  My assigned brand, Wesson Cooking Oil, enjoyed a strong affinity with loyal consumers, near ubiquitous distribution, and the halo effect from a long-time celebrity spokesperson, Florence Henderson (aka “Mrs. Brady”).  We had a sizable consumer marketing budget to build off an established base and compete for consumer mind share against Procter & Gamble’s Crisco brand.  This was the fun, “creative” part of brand management.

But what I quickly learned is that building great brands also requires sound business management and a command of the data.  Nowhere was this more important than on the cooking oil business, where a good chunk of retail sell-thru takes place between October and December — holiday cooking season.  Getting the trade marketing plan right meant securing all feature and display activity during the right weeks with the right retailers.  It meant making, or even exceeding, your number.  But getting the trade plan wrong meant a potentially devastating peak season was in store.

Fortunately for me ConAgra was (and still is) a pioneer in using predictive planning software to build better trade plans.  This made my job somewhat easier. We used two first-generation tools to predict promotion events and our overall trade plans, appropriately called PROMOMAX and TRADEMAX.  With a few key inputs such as trade allocation, product mix and merchandising assumptions, the software would spit out our expected volume and profit for a given scenario.  This was a Microsoft Excel model on steroids.  We didn’t blindly follow what the software told us to do, but we sure paid close attention to the simulated results.

So my early lesson as an ABM was that big brands need both art and science to thrive.  Strong, creative consumer marketing is critical, combined with a fundamental understanding and use of data and technology to drive the trade.  Left brain/right brain thinking at its best!

As a funny side note to this story, I had the chance to meet the entrepreneur behind PROMOMAX and TRADEMAX my first day on the job at DemandTec.  Jose Anstey, who founded Applied Information for Marketing (AIM), and I were at an industry conference in Tampa Bay.  It didn’t take us long to put two and two together.