Marketers love it when important influencers share their stories, videos, and even ads. As a journalist, I could spend all day simply sorting through emails, DMs, and social media comments asking me to cover or share something.
The problem is that 99 times out of 100 those requests focus on the needs of the person sending it, and they completely ignore my needs as a journalist, while also ignoring my audience’s preferences.
Lesson for IT: Figure out who the key IT influencers are in your organization and develop a plan for winning them over. Every organization has a few tech-savvy, non-IT people, who are often the first people their colleagues turn to with their tech problems.
How do you find these people? If, for instance, you’re busy implementing new BYOD policies, how do you target key influencers so the policy becomes widely understood and followed – naturally, with the employees reinforcing it themselves?
Sentiment analysis isn’t just for finding fans on Twitter. Rather, it can be used internally to help you target influencers who will help amplify important IT messages.
Before marketing switched to data-driven approaches, it was often distrusted by many business leaders. Too much of what marketing did was fuzzy and impossible to measure.
How times have changed.
Yet, there are still plenty of challenges to contend with before organizations become truly data-driven. One of the biggest challenges is figuring out how to break down data siloes, so you can actually analyze all of the data – both structured and unstructured – that your organization has collected over time.
Easier said than done.
Marketers were early adopters of Big Data tools, and this is one reason that Gartner predicts that by 2017 CMOs will spend more on IT than CIOs. Marketing’s effective use of Big Data has caught the attention of the C-suite, and, as a result, the power of CMOs is on the rise.
Yet, no one really owns Big Data yet. Marketing and sales both have the momentum, but they don’t have the tech-savvy of IT. They don’t understand how various systems influence one another, for good and ill, nor do they understand how to build out the infrastructure to support widespread data analysis.
In fact, much of marketing’s Big Data lead is due to the fact that many data-driven marketing tools are consumed as cloud-based services.
Lesson for IT: IT has the chance to leverage Big Data to boost its own profile within organizations, much as marketing has. The fact that there is no coherence to the many Big Data efforts happening across organizations is actually an opportunity for IT.
If IT can proactively break down data siloes, can implement better data creation and retention policies, and can create and own the underlying infrastructure that will enable Big Data initiatives across the organization, IT will carve out a more strategic, proactive role for itself.
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