Everyone’s an Analyst
Analytics is impacting the bottom line for brands and agencies alike
To understand just how important data and analytics are becoming to today’s consumer goods companies, one has to look no further than Nike.
Not long ago, Nike was buying up smaller athletic footwear and apparel makers while aggressively expanding its retail footprint. Today, the company’s growth strategy is tethered to data and technology providers like Celect, Zodiak and Invertex – all of which were acquired by Nike over the past 18 months in order to bolster the company’s internal digital expertise and create a deeper understanding of consumer behavior through the use of data analytics.
Nike is hardly alone in coveting analytics expertise. Today’s marketers spend an average of 5%-7% of their overall budgets on data analytics, and that number is expected to jump to 11.3% in the next three years, according to The CMO Survey. In the consumer packaged goods space, companies are shoring up their analytics capabilities in order to adapt more quickly to shifts in purchase behavior and ever-changing consumer demand. And increasingly, they have something to show for it on the bottom line.
During its second quarter earnings call in July, PepsiCo chairman and chief executive officer Ramon Laguarta attributed the company’s solid 4.5% organic growth rate to its investments in data and analytics (which also got “credit” for driving a substantial hike in the marketing and advertising budget for the quarter, by the way). “We’ve invested in advanced data and analytics to enhance our consumer and shopper insights and sharpen the precision of our execution,” Laguarta stated. “We’ve invested in increased go-to-market capacity and capability, including routes, other front-line selling resources, and e-commerce.”
To industry observers, such moves make a lot of sense – and not just for PepsiCo. “Data and analytics are the best opportunity for CPG companies to differentiate themselves during a period of massive digital disruption,” says Vittorio Cretella, principal at VCAdvisory and former chief information officer at Mars Incorporated. “That is the foundation for CPGs to become more agile, and then figure out how to do that at scale.”
New Engagement Tools
The increased emphasis on data and analytics has given rise to powerful new marketing tools like retailer ad platforms. In the last two years, major chains including Walmart, Target and Kroger have strengthened their digital media networks (which typically comprise the retailer’s own banners and participating external websites) to compete more forcefully with Amazon for the attention of shoppers.
These platforms are driving new levels of shopper understanding and fostering increased data sharing and participation between brands and retailers, says Laura Moser, director of business leadership at HMT Associates. “We are starting to see a range of regional retailers become more sophisticated in how they partner with brands on program development and additional targeted social, local and mobile tactics.”
Manufacturers are now devoting larger portions of their marketing budgets to platforms like Walmart Exchange, a programmatic infrastructure that uses the retailer’s in-store purchase data to target ads for participating manufacturers. As Moser notes, “Advertisers are using Walmart’s online and in-store data to help refine specific audience groups and to really get to key shopper target segments. Across the board [at major retailers], there is now an ability to more tightly define a range of social, local and mobile activations in reaching the right shoppers.”
At a time when merchandising and promotion strategies are becoming increasingly data-driven, new tools can help update traditional category management practices to account for more frequent changes in pricing and promotions, according to Rahul Tyagi, a data analytics expert who previously held executive roles at Colgate-Palmolive and Publix.
“We have to look at assortments today on a more granular level,” says Tyagi. “Merchandise planning used to be done manually at the corporate level with a very limited number of plans generated. Now we have to deliver assortments and planograms at a cluster level. We’re going from 8-10 planograms per retailer-category up to as many as 500 for a large retailer. This has driven a need for automation and there are tools in the market that provide rules-based co-optimization of assortment and space, thereby delivering customer-centric merchandise plans without additional manual overhead.”
The Changing Agency Model
Meanwhile, the marketing agency model continues to evolve, mainly because the industry has acknowledged the need for greater in-house data and analytics capabilities. As analytics expertise has become more critical to marketing success (and as more marketing functions have become automated), agencies have been moving into the space by launching analytics practices, some of which feature proprietary systems and software.
Momentum Worldwide, for example, partnered with IBM Watson Advertising to develop an artificial intelligence platform that the agency has been using to conduct more rigorous audience segmentation/targeting and personalization techniques.
“Everyone is feeling pressure to deliver on personalization, and that requires big data and machine learning,” says Shaun Brown, senior vice president-shopper marketing growth and innovation at Momentum in Atlanta. “With the ability to plug data into our dynamic creative platforms, and by using programmatic tools, we can target far more shoppers with personalized messages in the right context. That means we can increase the size of the prize and drive more revenue growth for our clients.”
Agencies are also branching out into analytics in response to a more competitive environment: Leading global consultancies including Accenture and Deloitte continue to expand their portfolios of creative services. “I do think it’s changed how we think of who we are and what we deliver as an agency,” says Tinesha Craig, SVP-strategic analytics at FCB/RED in Chicago. “Most of our clients work with Adobe and other large consultancies. The challenge for them is how to make sense of all that information as an integrated and cohesive story.”
Pradeep Kumar, executive vice president-director of analytics at FCB/RED, says, “Most of our client engagement is not about selling the tools, but how to use technology in such a way that it provides insights that we can funnel into our creative platforms and generate consumer feedback, so that we can learn something from every execution.”
As they take on a bigger role in analytics, agencies are now able to provide more strategic input early in the process of campaign development. Some even point to a readiness to collaborate on the creative brief. “The brief is not just a piece of paper anymore. It’s an ongoing experimentation process,” says Kumar. “Data experts are being brought in with account planners and creative teams to have influence on that process.”
Craig, however, cautions against taking on too much experimentation. “The question your clients will have is: How much of my budget will you allocate to what is tried and true, versus how can much can you use as a sandbox for playing and creative experimentation? We need to make sure we’re not taking on too much risk and fail to drive the revenues that our clients need.”
What the Future Holds
So what’s next for analytics and marketing? While many focus on artificial intelligence and “internet of things” applications, analytics expert Tyagi points to the growing field of neuropsychology. “The next evolution of digital marketing will come when we merge data analytics with behavioral science,” he says.
In Tyagi’s view, the pendulum has swung too far from the old mass marketing model to precision targeting. And he believes that behavioral science will eventually be used “like a consumer panel” to weed out ineffective messaging and better define segments and audience targets. “This will allow marketers to strike a more appropriate balance between just throwing everything at a wall and getting too granular with digital advertising, which can turn off consumers,” he says.
Will Leach, a behavioral science expert and founder of Dallas-based Trigger Point Design, says that behavioral science has yet to merge with big data in most marketing departments. “I think marketers and market researchers have set up an unnecessary dichotomy between investing in data science or investing in behavioral economics,” he says. “The majority of this investment was placed into the hands of management consulting companies with big promises around big data. Unfortunately, there have been very mixed results. There is an underlying belief in many companies that this data investment has not had a very good ROI. Some keep reinvesting. Others have moved on.”
Still, the two disciplines have the potential to take digital marketing to the next level. With its focus on the non-rational elements of decision-making, behavioral science concepts like “framing” and “priming” could be used to create more resonant messages that trigger a brand’s desired response. “Big data gives you who to target, when to send messaging and what to say in your message,” says Leach. “Behavioral design teaches you how to say it. Together they are much stronger than their parts.”
To be sure, today’s marketers are seeking any competitive edge they can get. And if there’s a scientific approach that, when combined with big data, lets a brand’s strategy become stronger than the sum of its parts … well, at least some marketers are bound to take the leap.
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