I frequently hear my colleagues lamenting over the challenges of leveraging (or trying to leverage) multiple data sources every day -- Web analytics, marketing automation, CRM, social listening, keyword performance, income statements, budgets, persona profiles, and more. Marketers are blessed to have so much insight into their customers’ behavior and interests, and the volume of this valuable data is growing exponentially
What is clear is that CMOs are struggling to take advantage of this great blessing. Even if CMOs are aware of the opportunity in big data (capturing and using large data sets from both within and outside of an organization), the fear is that for every new application of big data, there will be higher costs associated with it -- including the need for new staff to manage the technologies associated with big data. All this investment comes along with only a faint hope that these efforts will generate any ROI.
Even retailers, who are not new to large data sets (although big data -- with its constant changes and many, many sources -- is a new beast) face significant challenges when it comes to leveraging big data, according to a survey of North American retail executives conducted by Edgell Knowledge Network.
Forty percent of respondents to this survey named handling the volume of incoming data as their primary challenge, while 34 percent said handling the sheer variety of data was their primary challenge, and 20 percent identified dealing with the frequency with which data was generated as a problem.
So CMOs struggle.
Marketers need to embrace the next paradigm in marketing. There is no manual way to collect, interpret, and act on the insights from big data. The insights are too frequent, too small, and too voluminous. Just as big data comes from the machines, so will the ability to leverage it. This isn’t about giving people tools that they can implement to help glean insights from big data -- that's too slow. In fact, it’s rear-view mirror navigating. The future will be won by those who can anticipate what their consumers will need.
Processing and acting on big data is a massive problem. Trying to adapt to big data using the current models and (most) technologies available to marketers, even “big data” analytics tools, is ludicrous. Historical analysis -- enhanced by big data -- is a great idea, but it won’t help you satisfy the needs of customers in real-time.
There is an emerging class of technology called big data applications. These applications collect, interpret, and act on big data in real-time. They use existing content and goals as parameters and run in parallel with your marketing efforts, and are enhanced by your expert curation. Done well, they are “set it and forget it” technologies that truly optimize for the best return on marketing investment.
Instead of talking with vendors who are promising a better way to analyze your data, marketers need to seek out partners who deliver big data solutions that take action and continuously adapt to the interactions consumers have with your content. How do you know it’s a big data application and not a more robust analytics solution (with more specialized staff)?
The marketing future is a world where instinct, experience, and even data inform marketers about the tone, images, and words to describe their offering that will resonate emotionally with customers who have different needs and interests. Matching the content with the customers -- all machine.
Instead of struggling, reinvent online marketing. Find the learning systems that put big data to work for your company alongside your content. The marketers who crack that code will most definitely outrun the competition.