Most things you are measuring in marketing can be thought of as a Amount or Flow that should be coupled with a Quality measure.
Most companies seem to have the same problem... an endless sea of reports and nearly as many Dashboards and Key Performance Indicators (KPI). These are all symptoms of a lack of understanding, focus, or agreement on an analytics framework. Let step back to get some perspective and get back to basics.
Basics
When thinking about reporting and monitoring indicators, there are 2 types of reports:
Forward Looking (Leading Indicators) - these are used to measure performance of the current cycle (i.e. quarter) using measures that are proxies for your goal to see if we are on track on need a course correction.
Backward Looking (Lagging Indicators) - these are used to look back at the past cycle to verify performance and measuring the goal directly to see if we hit our target.
Example
Let's say our marketing team's target is to generate $100M in new deals (new pipeline) this quarter. Examining historical data, we see that that means we need about 1000 Marketing Qualified Leads (MQLs) [It's preferred to have a pipeline figure related to number of Buying Group, but most companies are still using a lead-based funnel and reporting]. The Forward Looking reports are used during the quarter to see if we are on track will use MQLs as the Leading Indicator. We will track # of MQL thus far, pacing of the MQLs, etc. The MQLs isn't our end goal... but next best thing we can affect and measure... that should eventually translate to new $ in Pipeline. It's not a perfect conversion, if the MQLs convert at a high rate (than historical) this quarter then we will exceed the target, but they convert at a lower rate then we will miss our target. That's why we need to check at the end of the quarter to see where we land. To do that, we directly measure our goal $ of the new deals created that quarter to see if we met the target of $100M. We may look at breakdown of new pipeline by product or region or business tier (SMB / Enterprise).
Types of Measures
Most things you are measuring about your business and funnel can be thought of an amount (views, reach, etc) or flow of something (i.e. responses/day, leads/week, deals/quarter, etc). When building Forward looking reports, I find it helps to think of the measures as an Amount / Flow, which should be paired with a Quality measure. The Amount / Flow are items that we within your direct control. Quality should be something that is just outside your process and serves to validate the Quality of the output from your team. Backward Looking reports are simpler and typically an Amount (goal) and Quality measure here is often a distribution of sorts.
Example
Building on the previous example, our Leading Indicator is the MQL. Our Quality gauge should be something just outside our team's control and validate the quality of our MQLs. We could use Sales Accepted Leads as the measure of quality if this is the stage leads advance to after Sales take a look at the MQLs and decides it's good enough and can book a meeting (the definition of good enough is something negotiated ahead of time between marketing and sales). For reviewing the quarter we looked at the $ of new pipeline generated. Then to examine the quality, we look at the distribution across business tiers to see if it aligns with expectations for a healthy distribution. The distribution should be predetermined before the quarter starts.
Key Performance Indicators
I remember a time when marketers had a monkey see monkey do attitude to analytics. This will work fine at the tactical level where the definition of the measure are well-defined and industry standard and thus have little variation.
But when it comes to KPIs for the business and team there isn't a one-size-fits-all. These encapsulate measures with non-standard definitions, quality or consistency of the data, as well as unique focuses/initiatives at the company/team. It's ok to start with KPIs that are used at a similar organization with similar goals/initiatives. Think about it critically and adjust as needed.
Having too many KPIs is like have no KPIs. There are metrics we monitor because they have important insight, but that alone does not make them a KPI. You should have less than 10 KPIs. I would argue 3-5 at each level (team vs company) you are trying to observe. The more KPIs you have the less focus you have to make course changes to correct any movement patterns in the KPI without affecting the others.
Tips and tricks
Always strive to look for insights not reports. The difference is a nuance. Insights imply trying to find something to action on... whereas report are just a status update and action is optional.
Make searching for insights someone's job... if it's everyone's job... it's no one's job. Most businesses run pretty lean and there isn't a lot of spare time to indulge in no core duties. You have to get your day job done well.
Empower everyone to be able to look at the data, so they can self-serve finding answers to questions they have. But have a set of dashboards / reports that are considered approved view of the "truth". We all know data isn't pristine and there are conflicting fields and values... especially for data collected across systems. This is why it's important to have a set of approved reports with know source fields that represents the "truth".
Tie these dashboards into business processes like Quarter Business Reviews (QBRs) or Monthly cross-team funnel review etc. We need all teams using the same data sets... not cherry-picking data sources that support their narrative. Use the dashboard design process to standardize data across teams.
Establish a dashboard development lifecycle. Gather user requirements. Test user experience early and often. Find ways to make it easier to get to the end result they need for their business process. Don't try to do everything in one dashboard (pick a couple of related scenarios by job function). Trying to make it usable for every scenario will make it unusable for any scenario. When it comes time for roll-out, include time for users training, adoption effort and feedback collection for future feature evolution.
Don't overdo the data you include in a dashboard. Providing too many KPIs and other metrics complicates the analysis process and often leads to dashboard fatigue for users.
Pay attention to layout, colours, labels and other design elements - this separates the functional from the indispensable. Consider how different charts and other visualization techniques will affect the experiences of dashboard users.
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