When having conversations about data, all too often, a deafening echo can be heard reverberating – Track Everything.
Marketers realize all too well that, in the quest to understand their customers better, intelligent insights from relevant and accurate data are the ultimate game changer. If delivering exciting customer experiences is the new battleground for brands, a cohesive, technology-enabled data strategy is the ultimate weapon.
But does having a world-class data strategy mean that modern-day organizations really need to track everything? The answer, of course, is no. It’s time organizations prioritize smart data over big data.
“A good data strategy exists at the synergy of technology and strategy.”
Puneet Chadha, Chief Marketing Officer, Redington Limited
Conversations around leveraging data appropriately usually have a few overarching themes – either the organization doesn’t know what it wants to learn from its data, or there is too much data spread across disparate systems.
The result, according to research by Accenture, is a world in which only a quarter of organizations say they can translate customer data into actions. In the former case, the correct strategy is to take a step back and identify a handful of relevant questions that need answering. But sometimes, organizations make the mistake of thinking it’s a problem of lack of data and widen their funnels further to accumulate even more data.
This usually aggravates the problem, resulting in data silos across sales, marketing, and operations, and an extremely low signal-to-noise ratio. There are also potential cost implications to storing, maintaining, and processing copious amounts of data, especially if it turns out to be unnecessary, unhelpful, or just redundant.
Now let’s look at the second problem – that of data fragmentation. Most marketers rely on a CRM platform as the core source of truth for all customer information, knowing all too well that a significant portion of customer data doesn’t even live there. From email management platforms and ERPs to third-party data sources and external tools, marketers today have to deal with a glut of disparate data sources.
This is far from the ideal and can lead to situations where certain customers are receiving too many marketing messages, or worse, none at all.
To clear the data picture for marketers, identifying gaps in both technology and strategy is crucial.
The good news is that wherever you are on the data continuum, there are effective strategies that you can incorporate into your data strategy and avoid these pitfalls.
The world’s leading companies – those on the far right of the data continuum, are able to feed real-time insights directly into their product and service development cycle. They understand their customers’ needs and wants deeply. There are several real-life case studies – from social media giants using real-time user data to detect fake news to Netflix’s recommendation engine and McDonald’s using weather data to recommend hot tea or cold coffee to its customers.
Of course, this level of customer-focused behavior cannot be achieved without the help of technology. As such, organizations much strive to build future-ready systems that are intelligent, structured, and systematic, and that can enable them to interface with customers at a more personal and holistic level.
The vast majority of marketers would also find value in having direct control or ownership of their data, so they are not beholden to third-party data sources for their customer targeting strategies or budgeting decisions, especially when they’re unable to verify the quality of these external datasets.
Therefore, to get the most out of their data, organizations must first put real effort into learning more about the latest analytics processes and products. They must also define their core KPIs, and prioritize these when making decisions about what to track. These KPIs must be iterated regularly.
Bottom line – A good data strategy exists at the synergy of technology and strategy. If you want to create data magic across all customer touchpoints, focus on collecting the right data, sharing it appropriately, and acting on the insights, instead of just gathering more data.
