The promise of Big Data to the CMO

By Michael Gold, Farsite

Michael Gold

My 2 and a half year old daughter loves the Mickey Mouse Clubhouse. She watches episodes on TV and our iPad. She wears Minnie Mouse flip flops and giggles just about every time she sees anything with Mickey, Daisy, Goofy…you get the idea. And when she’s old enough to go to Disney World, Minnie might walk right up to her and say “Hi Jemma!” and give her a big hug.

Creating a personal interaction between a child and a beloved Disney character exemplifies the company’s recent initiative to deliver a personalized, hassle-free experience at their theme parks. ¹ With the wireless tracking wristband ‘MagicBand,’ families are able to reserve spots in lines for popular attractions, purchase items at the parks, and unlock their hotel rooms. The MagicBand is part of the MyMagic+ system, which enables Disney to collect data on visitors’ purchasing habits and real-time location, among other things. Disney will use this vast trove of information to deliver a personalized experience at the parks and tailor marketing messages and promotions.

This initiative typifies how a company can take advantage of the proliferation of digital technologies in a multi-channel environment to offer a better customer experience. But this is easier said than done. The growth of new channels can heighten the potential for a fragmented customer experience. It’s up to key individuals within the organization, often the CMO, to turn a disruptive change in consumer behavior into the source of a competitive advantage.

One important resource CMOs have in this challenging environment is data. As we all know, data about consumer behavior and market trends are available at unparalleled scale and granularity – to companies like Disney that can invest massively in collecting it (estimates of MyMagic+ are $800m), but also to companies large and small alike. This data can help target customers, uncover their preferences, and isolate their buying behaviors. Hundreds of software platforms have popped up that seek to leverage this data to help marketers optimize search, social marketing management, e-commerce platforms, retargeting, attribution modeling, and so on…(does a LUMAscape ² look like a rorschach test to anyone else?) The number of software solutions is dizzying – but it makes sense given the size of the market opportunity and the variety and complexity of questions marketers are confronted with on a daily basis.

Almost two years ago Gartner made a prediction that by 2017 the CMO will spend more on IT than the CIO. ³The pronouncement begs the question – what is the CMO going to spend all that money on? For a very large company like Disney – they are likely to build some massive, custom solution. What about for everybody else with less than stratospheric budgets? Point solutions are likely to be more cost effective, but alone may not be the best approach.

The promise of Big Data to the CMO is to provide both a comprehensive and nuanced view of the customer. This is the game changer – for a marketer to pinpoint what a customer wants, when they want it, and how they want to hear about it – and then to be able to do iterative experiments to continue to hone the approach and be responsive to changes in consumer habits. The applications of this capability are almost endless. For instance, with this insight a CMO will know what sales are incremental and which are cannibalizing other channels. What a CMO doesn’t want to do is offer a promotion on merchandise to customers in one channel (e.g. mobile) that they would be willing to purchase full price in another channel (e.g. in store).

Only a comprehensive view of the customer and the company’s pricing and merchandising data make these insights possible. The challenge with a lot marketing software is that they are point solutions and don’t incorporate often siloed data. These platforms are relatively new and are solving difficult problems for a marketer, and to turnkey that kind of solution is challenging. So it is understandable that the flurry of marketing platforms tend to be point solutions. The problem is when these marketing questions are addressed individually it prevents the comprehensive view of the customer that Big Data enables – and where the most valuable insights can be obtained.

So what’s the alternative? CMOs need to prioritize what questions they want to answer and then work closely with CIOs to iteratively build an IT infrastructure that captures the right data and makes it available for turnkey and ad hoc analysis. Doing this work in stages will help contain costs and ensure that the project is successful. This is no easy task and requires a combination of database platforms, BI tools, and advanced analytics capabilities. In addition, it necessitates a close working relationship between the CIO and CMO. With the emergence of the Chief Marketing Technologist, a position that Gartner estimates exists in 70% of today’s companies, we are beginning to see a move towards this kind of collaboration.⁴ There is a lot to figure out and there will be important tradeoffs between turnkey and custom solutions. In the end the promise of Big Data and the ROI justifies the effort. Disney has paved the way with MyMagic, and those companies that will continue to flourish are likely pursuing a similar strategy.

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¹ http://www.bigdata-startups.com/BigData-startup/walt-disneys-magical-approach-to-big-data/?imm_mid=0ab5eb&cmp=em-strata-newsletters-strata-webcast-20130626-direct
²http://www.lumapartners.com/resource-center/lumascapes-2/
³ http://my.gartner.com/portal/server.pt?open=512&objID=202&mode=2&PageID=5553&ref=webinar-rss&resId=1871515 ⁴http://chiefmartec.com/2013/03/gartner-confirms-rise-of-the-chief-marketing-technologist/

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