When Powerball hits a jackpot of 100’s of millions of dollars lines form, chatter about how you would spend your winnings begins and people buy tickets but what else drives sales for the Lottery? What is the optimal media spend level and what is the most effective vehicle to advertise? This week is the NASPL (North American Association of State and Provincial Lotteries) annual conference in Portland, OR. MMA’s Doug Brooks, EVP Strategic Account Relationships, has been asked to speak about how state lotteries are taking advantage of predictive analytics to optimize their marketing spend, how this practice is evolving and what is on the horizon.
Laura Sofro, Research & Analytics Manager of the Oregon State Lottery knows first-hand the power and value this type of analysis can deliver.
“Marketing Mix Modeling has been very valuable in helping the Oregon Lottery to understand the relative impact of macro-economics versus our operational and marketing efforts on our sales. We’ve effectively used the modeling results to help optimize the timing, tactics and budgets tied to each of our products.”
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MMA is proud to partner with Google in helping brands understand the impact of their marketing.
“The ability to collect and analyze digital data at extremely granular levels enables both marketers and their advertising partners to more successfully measure, predict and action the most effective and profitable means of optimizing each digital channel to achieve their business objectives. We are excited that Google has taken such a proactive approach in working with MMA and analytic companies within the marketplace in providing such a high level of objectivity and transparency.”
— Patrick Cummings, CEO of Marketing Management Analytics
Too often smart people get caught up in the details of the past and forget how quickly the future is moving…
I read another article about marketing mix modeling today and the commentary from the usual market research wonks. I laughed. I scowled. I shook my head. I wouldn’t have laughed but for the 356% growth MMA has experienced from this type of analysis in the past 6 years and more importantly, the over $10 billion in incremental revenue our clients have attributed to the work we’ve done with them during the same period. Their numbers. Not ours. Their references. Not ours. When I thought about that I smiled.
Yet the drumbeat from the market research wonks goes on. And on. And on. The wonks hold conferences and pontificate. Oh how they pontificate. They ramble on about ‘the death of marketing mix’. They pound the doomsday drums around data and methodologies. They try to build bigger, louder drums. “Marketing mix is too slow.” “Marketing mix is too pricy.” “Marketing mix is too hard to ever get right because the data is so bad.”
This type of analytics, when done right, produces measureable value – Big Time
Recently, Sequent Partners authored a white paper that laid out the current state of attribution and ROI measurement. Conducted for CIMM and the 4A’s, the paper highlighted the tremendous promise and opportunities associated with this detailed and more granular ROI methodology.
The results of our study suggest that right now, attribution analytics and applications are evolving. Historically, attribution was centered exclusively on digital pathways and consumer journeys. The analysis was isolated not only from the rest of the media mix, but also from other sales, products, long-term brand equity building efforts, prices, promotions, and operational and relevant external variables. Furthermore, attribution models were hampered technically by apriori algorithms such as “first click” or “last click,” which assigned outcomes to a fixed digital touchpoint, regardless of other influences. Misattribution and inefficient spending allocations often resulted.
Helping CEOs, CFOs and CMOs Sleep Better at Night
Through our recent work in assessing the ROI measurement landscape, Sequent Partners has seen a tidal shift in sentiment toward marketing mix modeling. Long a stalwart of corporate finance and marketing, some people still view mix models as too slow, too macro and too backwards-looking. The speed and agility of digital attribution modeling flickers ahead, like the glittering lights of Las Vegas against the starkness of the desert night, and marketers are urgently thinking about ROI measurement and driving business investments with ROI insights—at the tempo and granularity of today’s decision-making.
But there’s something else happening. Something more important. Digital attribution, no matter how sophisticated, is still solely about a marketer’s digital investment. It rarely takes into account the impact of traditional marketing and other important factors. Historically, marketing mix models—again, no matter how sophisticated—have been about the marketing and media mix, which can represent as little as 10% of corporate budgets, depending upon the industry. It’s evident to us that in many industries, successful marketing, both traditional and digital, is highly dependent on not only working together, but also working with sales, operations and other important internal investment areas. We’ve come to realize that too much of the dialogue in analytics is focused on the digital and offline marketing silos.
Measuring Digital Attribution Outside of a Silo and Within the Context of the Customer’s World
By Nigel Foote
Marketers have sought to understand the impact of all the elements of marketing on revenue and profit — in other words, to properly attribute the contribution of incremental revenue that each tactic delivers. For years, commercial effectiveness analytics and marketing mix modeling fulfilled this function, but as marketing tactics have gone digital the need to understand how they impact customers as well as properly attribute their effects has become increasingly important.
Today there are many “bright and shiny new objects” in the digital attribution space that offer solutions to understanding the impact to digital. Unfortunately, many if not most fail to look at digital through a customer’s lens. This creates a real danger of looking at effectiveness in a digital “silo” removed from the context in which customers really make purchase decisions.