Analytics and Data Science have the potential to significantly transform the way companies do business, but many brands haven’t yet achieved its full potential.
Analytics and Data Science may have climbed to the top of the C-level agenda, but many executives, marketers, and media buyers have only scratched the surface of the field’s potential. According to a highly-referenced Gartner study, 60% of big data pilot projects are eventually abandoned beyond the pilot phase. Below, I’ll run through three of the biggest barriers that I see in the health and wellness marketing world when it comes to successful partnership with analytics teams, and the steps marketing teams can take to overcome those barriers.
Barrier #1: Information Siloes
Brand teams often work closely with data analytics teams to assist in designing, implementing, and continually improving marketing campaigns. And while it’s fantastic that they’ve chosen to make an investment in data-driven marketing, it’s important to optimize that investment by eliminating internal process-related barriers (particularly in large organizations). Corporate bureaucracy can lead to significant analytics investment inefficiencies when, for example, data engineers are trying to piece together information in relation to one specific team or department, when the needed information is actually siloed in another division of the company.
Solution: Designating Communication Access Points
At the outset of any data analytics project, the brand’s CMO should ask the data team for a topic scope. With that in mind, the company can build a project plan and involve the appropriate stakeholders from key divisions to facilitate access to critical information before the data team begins its work. Formally establish these stakeholders as access points in order to ensure that all information requests are facilitated by them. This not only increases the efficiency of information gathering, but builds accountability for the project’s success across the organization.
Barrier #2: Overlooking Key Stakeholders
That said, even with the help of appointed in-house communications managers, healthcare marketing campaigns remain, by nature, cross-organizational efforts. In order to convey medically sound, scientifically rigorous information to consumers, it’s important for key stakeholders — typically executives — from each corner of the business to weigh in on messaging strategy, KPIs, desired outcomes, and overall expectations. Input from relevant in-house experts is essential not only in order to keep a project on-track, but to align external messaging and avoid a public relations snafu.
Solution: Involve Stakeholders Across the Board — Even Those You Might Not Expect
While internal marketing teams and analytics staff should absolutely provide agency guidance, they should not be the exclusive drivers of the collaboration process or final determinants a project’s overall success. In order to achieve best possible outcomes, it’s important to establish which executives will be involved in each project and how communications will be managed between teams. Bringing a cross-functional team to the table during measurement planning will ultimately enrich results.
Barrier #3: Lost In Translation
For those who haven’t spent their careers learning the nuances of analytics and data science, it can be challenging to dive headfirst into collaboration with teams that often speak what can sound like a totally different language. But miscommunication can give way to avoidable mistakes, and the last thing anyone wants is for something as seemingly innocuous as a mislabeled column heading to result in inaccuracies that could jeopardize or protract a project.
Solution: There’s No Such Thing As a Stupid Question — Ask!
If your marketing team has limited experience with analytics and data science, or has encountered roadblocks to understanding in the past, tell your data partners at the outset of the project. Rather than being a cause for concern, this will give your analytics team the opportunity to provide everyone involved with the tools needed to conduct thorough and efficient analyses. Ultimately, the extra resources spent on a one-to-two-hour training up front could save literally hundreds of hours that might be necessitated by a simple mistake. There’s no such thing as a stupid question — when in doubt, be sure to ask!