The former chief marketing officer at Procter and Gamble, James Stengel, said in 2012 responding to a question about how to achieve brand growth, “Get to know the consumer and then do something with it.” Marketing research has always had more success with the first part of this statement than the “doing something with it” part.
When marketing research conducts a survey among 1,000 people, you get to know 1,000 people. Important insights but limited to what you can ask in a survey, and then of limited use for media targeting purposes where media placement strategy always seems to deteriorate to the lowest common denominator of age and gender. In fact, to be a hard grader, if standard research doesn’t demonstrate a repeatable ability to improve advertising productivity or innovation success rates, there really isn’t much proof that the insights are worth the billions of dollars we pay for them.
Marketing research needs to start thinking at scale…and this will change how we research customers and profile brands…from a small number of segments intended to inspire brand ideas to a large number of targetable audiences intended to drive advertising ROI, from brand attribute profiles to response profiles, from survey tracker measures to integrated brand KPIs.
Big data promises to be the game changer. Now marketers can get to know tens of millions of consumers in actionable ways who interact with their brand by using big data and data science approaches…leveraging the transactional and digital data you naturally could capture, and the social, third party and sensing data you can easily bring in. Tens of millions? Yes…when you consider all those consumers who buy something from you, visit your website, interact with you in social media, or who have profiles in 3rd party databases that can be used for lookalike modeling…yes, we have found a way to scale research and analytics and do something with it.
And what WILL a marketer do with this knowledge?
- Strengthen brand-consumer relationships via hyper-relevant content and experiences
- improve short term advertising ROI
- …basically establish for once and for all the value that the marketing function brings to the enterprise!
So why are marketers behind where they need to be? Most marketers know they need to leverage their data assets but have not made much progress. Different data streams are usually siloed, poorly matched and often unstructured, so marketers analyze one data stream at a time and it feels impossible to really get a handle on synthesis. They fail to capitalize on opportunities to capture important data via tagging and usually do not database all naturally occurring experiment-style results about digital marketing effects. Most importantly, they have not worked effectively with IT to link business use cases and marketing activities to data streams.
Consumer knowledge based on using big data to scale insights into the tens of millions changes the ways that marketing works:
- Personalization of content
- Ad optimization (right message, right screen, right time via programmatic)
- Optimize programmatic ad bidding across brands in a portfolio
- Cross-selling products and service offers based on lookalike modeling and predictive analytics
- Retail optimization (right product in the right store)
- Powerful marketing research insights by tracking the brand across all signals of brand health
- Marketing ROI knowledge management
I am starting to see a number of players in the marketing research ecosystem now emphasize platforms that integrate data sources, so where this is headed is unmistakable. Rubinson Partners and IIS, a top 100 big data technology solution provider, have mapped about 25 data sources to business purpose and developed a process to move you from point A to point B. We encourage clients to consider these data as organized by levels of sophistication or readiness to fully compete based on data…based on understanding millions of consumers and then doing something with it via personalized and precision marketing approaches.
With these shifts in mind, my strong suggestion is that your organization should move quickly to do an assessment of your readiness to compete on data and a plan for how to take your enterprise to the next level.