This blog post was written by Jeremy Cho, BA, Economics, ‘21 University of California, Santa Barbara

Data is likely the driving force of most decision-making processes in your organization. Finding trends, areas for improvement, and solutions in your digital environments can only be done accurately and effectively through the examination of data. If you’ve been using KPIs to help your organization make more informed decisions, that’s great, but, you may have noticed that these metrics alone are not enough to capture the entire picture. How can we add more meaning to your key performance indicators (KPIs)?

The solution to this problem is to ask yourself, why are these KPIs and other gathered data points important? Are they meeting previously set goal targets? Do they show underperformance or overperformance in relation to your organization’s averages? Are they significant in regard to changes over time? These are all good questions to ask when you look at your data. You can provide further context by going an extra step to process your data, which will allow you and others within your organization to make informed decisions.

You may now be wondering, how do I go the extra mile with my data? To help answer this question, Digital Marketing Evangelist at Google Avinash Kaushik compiled a list of 7 different ways to add meaning to your KPIs in the context of your dashboards and reports. If you aren’t currently using these, you might be missing out on an opportunity to help yourself and others understand your key performance indicators.

1. Use Supporting Metrics: Pairing related metrics can provide more dimensions of understanding than a single static figure. Additionally, pairing metrics instead of just bombarding the audience with a long list can make the data easier to digest.
2. Averages: Averages can help your company understand how it is doing in comparison to its historical performance. 
3. Use Like-Type Time Periods: When presenting your data in relation to time, it is important to avoid mix-matching time periods. Comparing monthly statistics to yearly statistics can sometimes be very misleading and this applies in varying degrees to any combination of time periods. Therefore, when comparing time sensitive KPIs, make sure to use like-time periods—weeks to weeks, months to months, and so on and so forth.
4. Use Segments: Segmentation of your data can help contextualize static KPIs. A large, hard-to-digest figure can be broken down into smaller pieces to show additional trends and explain specifically where movements are coming from. For example, one static number for total visits can be more useful if the data is split up into segments to show exactly where users are being led to your website. As Kaushik suggests, going even further to add percentage changes over previous periods can help you learn even more about what was once a singular KPI.
5. Use Costs: Costs can be important for others to understand how KPIs relate to budgets. It is important to explain intricacies with data in relation to conversion rates, Cost Per Visits, and other KPIs to avoid misconceptions that higher cost is always bad.
6. Pre-set Targets: Pre-set targets or goals are a luxury of data-mature organizations that are, for obvious reasons, the most effective comparative metric you can use. These targets are considered a luxury because they should be carefully calculated and reflect the goals of your organization as a whole. 
7. Industry Benchmarks: Comparing metrics to other organizations in the same or similar lines of business can be helpful, but it is also important to recognize that industry goals may differ from your organization’s goals. 

Static KPIs, while important to refer to, may not be telling the whole story. You can examine your “Pageviews” statistic from last week, but what conclusions and more importantly, actionables, are you going to be able to make from that number alone? Next to nothing of substance. KPI’s need context and comparative benchmarks, similar to the ones above, in order to be truly helpful.