While kicking off a project last October, a client showed us slide after slide of reports, architectures, and data flows. Overwhelmed by information, the client looked at us and asked, "what do I do with all this data?" A plea for help I have heard on almost every engagement since. Due to this trend, I am starting a blog series answering the question from a multitude of perspectives. Each blog will dig deeper into a particular dimension including organizational communication, analytics processes, reliance on technology, and creating actionable data dashboards.
Clients usually start conversations thinking they need to re-evaluate their technology in order to more efficiently automate their insights-to-action process. However, after digging under the surface, this is rarely the crux of the problem. Technology is usually just the easiest target. In addition, vendors usually over-promise on what they can deliver.
Due to the marketer's pursuit of a "magic bullet" to automate data into insights and insights into action, leaders enter into contracts with solution providers boasting "omnichannel" capabilities that "connect data across channels to personalize communications." Unfortunately, technology companies rarely focus on or understand the process and organizational changes that need to happen in order to successfully leverage these capabilities.
In an engagement with a B2B client implementing an attribution solution, the main roadblock to success was communication and coordination of information from agencies, different marketing groups, and inputting it into the system. The technology works if the information is there, but getting it there is more than half the battle and something out of the solution partner's hands. This situation brought frustration for all parties and delayed change to customer engagements.
What to do about this? Stop thinking technology can be the solution to the data conundrum. Instead, understand the complexities of this transition through:
ï‚§ Mapping the customer life cycle: Gather representatives from all steps of the data-to-insights-to-action process. This might include marketing, information technology, analytics, and sales. Create a high-level customer life cycle (5-8 phases) and then map out the touch points, insights, metrics, and sources that support customer interactions at that phase.
ï‚§ Assessing the current state: Evaluate how your strategy, organization, processes, and technology are currently working to help your company towards their desired future state. Where are there gaps? What obstacles are preventing progress? Where should you allocate more resources?
ï‚§ Evaluating the vendor landscape: What technologies currently make up your stack? Are there too many to efficiently get the data to the right people at the right time? More often than not, the technology that you need is there, it is about building an organization and process around it to maximize effectiveness (more on that in a later post).
ï‚§ Creating a roadmap: After evaluating the different aspects impacting your business' ability to create action from your data, create a roadmap outlining the steps needed to reach your future state. This roadmap should also assign internal responsibility to ensure ownership of execution.
Take a deep breath and a step back from the question, "what do I do with my data?", and instead ask "what do I want from my data?" This adjustment will help prioritize what within the ecosystem needs attention and, possibly, a new partner to execute.
+ + + + + +
About the Author: Kara Hoisington is an Associate Customer Experience Consultant at Forrester Research