Before we get into the “what and how” of KPI Dashboard Design, there are some overarching guiding principles to consider for identifying what metrics you need, how you want to view them, and more importantly, how to develop and support them:

  • Start with what you know. Don’t get visions of grandeur or mesmerized by “consultant speak” with the mythical 360-degree view of the customer if your organization is currently not equipped to support the vision (or some semblance thereof). Work with the data you have in your current environment as a baseline; plan accordingly, and enhance capabilities at your own speed – in other words, with what your budgets, resources and technology capabilities will allow. In many cases, you may already have all the data available and just need a modest investment to yield significant results. Quick wins could come in the form of a data strategy, an analytic sandbox environment, a predictive model, or a data visualization/reporting tool to derive and serve up your ideal metrics.
  • Reality Check – understand where you are and be honest with yourself. Start with a data and technology assessment to fully understand your data availability, enabling infrastructure, capabilities, processes, integration points, linkages, gaps and limitations that could impact KPI dashboard design, development and ongoing support.
  • Avoid the “old school, traditional discovery phase”. You don’t have to wait to conduct a “traditional discovery phase” before you move forward with designing your dashboards. Actually, we find it extremely effective to mock up your “end state KPI dashboard” at the onset of a project and leverage it as a collaborative tool to facilitate discussions, identify KPIs, validate requirements, determine gaps and develop an action plan. You might not be able to measure everything at the onset, but it gives you a set of goals to achieve.
  • Focused and targeted wins the race. Avoid analysis paralysis by identifying and prioritizing KPIs, views, dimensions and filtering attributes that only provide tangible, actionable and measurable value.
  • Sometimes a box of crayons is just what you need. Do not over-complicate or over-architect dashboard designs – simplicity is a good thing. Whatever your design, make sure it is sustainable, repeatable and scalable for the long haul.
  • Think hierarchy. Understand the organizing principles of your data at the plan, program, campaign and delivery levels as well as implications to workflow and processes. This is a key success factor for organizing your data into a systematic directory structure to aid in data collection and management, matching, aggregations, filtering and calculation efforts for analytic and reporting purposes.
  • With hierarchy, comes metadata. In conjunction with your data dictionary and organizing principles, leverage metadata functionality in your current systems (e.g., CMS, Marketing Automation, ESP) to enhance and expand your data set with campaign and delivery attributes to further support your analytic and reporting efforts.

  • It isn’t just about you. No longer can marketing, IT, product and other groups be at odds with project ownership and decision making. It is imperative to work collaboratively across different groups to support required cross-functional impact and integration efforts. All relevant stakeholders should be part of the planning process throughout the entire effort, rather than “intermediately engaged when convenient”, especially given the fact that you are probably reliant on other groups to support certain aspects of KPI Dashboard development.
  • You can’t always get what you want. The Rolling Stones knew it, now it’s your turn. You might not be able to get exactly what you want; sometimes you have the let the data dictate the prioritization of your customer intelligence efforts.
  • Manual Dashboards – good business sense. Develop dashboards manually first as a “proof of concept” to determine if the report design makes sense, if the data tells a compelling story once populated, if you have the data to support these metrics, and/or if the investment into an analytics, data visualization or reporting tool is necessary.
  • Plan for tomorrow. Just because your ideal metrics are not available, don’t put them on the shelf to collect dust. Keep future metrics on the radar as part of planning roadmap that prioritizes by level of effort and business value. In some cases, the infrastructure can easily support the data enhancement opportunities, it is just a matter of employing different data capture strategies such as preference management or progressive profiling to complete and/or expand the data set.

Key Takeaway: Ultimately, it is about understanding your ideal metrics relevant to your business goals and marketing objectives, determining what data is need to support those metrics and how you capture and manage that data across all customer interactions.

Did you miss the KPI Overview? If so, you can read it here.