Neil Michel, Chief Strategy Officer at Wire Stone, argues that too many marketers are spending time trying to make sense of Big Data, but still aren’t using their existing marketing data and marketing technology as effectively as they should be
For all the talk about Big Data and the struggles brands face trying to put it to good use nowadays, I do not believe most marketers currently face a Big Data problem. What I do think is that there’s a prevalent misunderstanding of the difference between what is truly Big Data and what is just a lot of marketing data that isn’t being properly analyzed. It’s the latter that’s the real issue in our industry.
To define the terms here, Big Data should be thought of as a huge volume, variety, or velocity of data that typically arrives unstructured – or entirely new data types that our traditional databases are not prepared to handle. Examples of real Big Data include everything from brand mentions in social conversations to data streams from sensors in a company’s supply chain. To what degree are marketers really missing insights by failing to harness these huge new data sources? Not much, considering the opportunity that is readily available in marketing data that is not truly “big” in nature.
While Big Data is the new shiny object, there’s still tons of untapped marketing data readily available as low-hanging fruit for most brands. The good news is that any challenges you face in using existing marketing data are absolutely solvable with a strong technical ally and data analyst. Because most of what marketers consider Big Data is already structured in usable formats, mining new insights from traditional marketing data is simply a function of talent, using existing technology, and having the will to keep asking questions. Before going big with investments around Big Data, focus on the less romantic but more prudent choice of going small. Or, if you like the idea of going big, launch a “big analysis” project, not a Big Data project.
What’s important for marketers is to make smart business decisions with data, and to use data to deliver customer experiences that matter. Marketers are largely ignoring or underutilizing the data that they already have. On the B2C side, getting data analysis right means higher sales and loyalty earned by knowing when, where, and how to give the right customer the perfect offer – on the right channel and at the right time.
On the B2B side, savvy data analysis lowers your cost per lead, shortens your time to sale, and ultimately decreases the costs of servicing accounts. Imagine a manufacturer able to correctly predict demand and set inventory accordingly by properly analyzing quarterly (and even real-time) marketing data. Compare the advantages that manufacturer enjoys versus one simply guessing at their needs based on last year’s orders, because they don’t have the time, talent, or energy to develop a predictive model. This kind of predictive analytics is how companies like Amazon can fulfill same-day delivery: they can ship inventory ahead of time based on analytics that predicts what products will need to be in each region of the country prior to the orders for those products being made. It’s a Prime example (Amazon joke) of how investing in data can lead directly to amazing customer experiences.
In developing data analysis capabilities, marketers certainly need help. Our companies need to be committed to data analytics, providing the technical integration and data science specialists required to produce insights. Many modern marketing tools do a great job of producing single-channel reports but understanding the contributions – and opportunities – across channels requires integrating data. Business intelligence platforms can play the role of data-unifier for marketers, wrapping up customer knowledge into a single view. In a marketing landscape where customers are engaged via a slew of fragmented platforms – web CMS systems, marketing automation solutions, sales / CRM, social listening and management, customer service channels and others – the ability to see the whole customer is essential. While specialized tools for each channel can sometimes enable real-time engagement, a unifying business intelligence tool can provide much deeper and more impactful customer insights.
So remember: it’s not the size of your data that matters – it’s the motion of your analysis. Don’t chase Big Data until you’ve captured the opportunities right in front of you. In the end, it’s insightful data analysis that shows marketers the way and is transforming the quality of customer experiences for the better.
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