The quick 101 of metrics to help with OKR Planning

Your business is surrounded by data and Metrics. For example, they surrounds your product in the form of account, user, billing, and usage data.

Metrics are in your marketing tools in software categories like Analytics, Paid Ads, CRM, and Marketing Automation, and your teams like Customer Success, Sales and Finance, spend lots of time trying to measure and improve them.

This is where KPIs come in. KPIs are Key Performance Indicators. They are the Metrics that correlate with business performance and lead to actions being taken to improve them.

Understanding which Metrics are your KPIs at a Company and Team Level and the relationships a KPI has with other KPIs allows for better planning and alignment of KPIs, OKR and Execution.

Qualitative vs Quantitative Data

When you collect conversations, debates, anecdotes, and feelings from your small sample to create hypotheses around the customer, the market, the product requirement, pricing and more. This is Qualitative Data.

If you take your Qualitative learnings and try and make them statically significant by increasing the sample size of the data, you move from Qualitative to Quantitative Data. The bigger the sample, the more statistically reliable and trustworthy the data.

Metrics & KPIs

Metrics are a numerical and quantifiable way of assessing the performance of a company, team, marketing channel, process, or individual.

If you want to grow faster than your competition, one way you can gain an advantage is be better at metrics than they are. Why? Because doing this drives the behaviours and actions that increase performance. Using your finite resources in the most aligned, and impactful way possible.

If you want to Grow Fast, you’ve got you measure what matters.

Metrics are not there to make you feel good or look better than you are. The metrics that measure and define success should be a source of truth and honesty, and more importantly correlate with business performance change. When you have a Metric that correlates with business performance it can be considered a KPI.

So to help you think about Metrics and KPIs in a more rounded and precise way, here’s some background knowledge to help you become better at thinking about when and how to use Metrics and KPIs, and be more challenging when you see bad Metrics being used.

Reporting vs Experimental Metrics

When reporting to your investors, your teams and your managers, your reports tend to have continuity which means the same Reporting Metrics are tracked Quarter on Quarter.

Experimental Metrics are Metrics that come from having a hypothesis and testing it. You know which metric you thought would change after you did an activity, you have a starting number, you can track progress through-time, and at the end of the experiment, you have an end number – the result. You can then choose to re-fine and re-do the experiment, or stop.

Reporting Metrics could be added to Dashboards in ZOKRI. Experiments might be better suited to Initiatives in ZOKRI.

Leading vs Lagging Metrics

Leading Metrics are Predictive Metrics. For example, SQLs in the sales funnel should be a good predictor of future sales. Leading Metrics are often trended through-time and reported on for that reason.

If one metric doesn’t impact the other in a consistent and predictable way, it’s not Leading.

So when changes in metrics like Session do not consistently predict a rise in Leads, you would conclude that Session is not a Leading Metric.

A Lagging Metric is a metric that characterises your historical performance, and is therefore a metric you can’t do anything about, accept look back and try and find the inputs that influenced it with a view to managing and improving them going forward.

Churn is a lagging metric that could be influenced through the improvement of on-boarding, UX, features, pricing and more. Which is why having OKRs and Initiatives that you know can correlate to metrics like Churn is useful. Together they allow you to identify the issues and take action.

Bookings are another example where only when you close the quarter do you know how you’ve done. However, Leads, MQLs, SQLs, Ramped Reps, and Sales Cycles are Leading Metrics that help you predict future Bookings ahead of time.

OKRs would ideally contain a good blend of Leading and Lagging Indicators.

Correlated vs Causal Metrics

A reduction is SEO traffic, might correlate with a drop in Leads, but if you updated the website, editing page copy and category architecture, and at the same time Google updated its ranking algorithm, you have a number of events that correlate, but knowing which one caused the drop in leads is hard to say.

Or if a reduction in SQLs was noted at the same time you changed the qualification process, a new SDR was hired, and marketing changed the way they score MQLs, you’ve got correlation, but the causation is not clear.

Knowing what you’re doing that can impact metrics then tracking and measuring that activity is an important part of creating your growth machine, and something you do in ZOKRI. You want correlation and if possible causation to be clear so you can act.

Vanity Metrics vs Influential Metrics

Philip Sheldrake defines influence as “a change in opinion or behaviour”. And some metrics can do just that. These tend to be connected to business performance and great leading and lagging indicators.

There’s another group of metrics that are often called Vanity Metrics that are poor and predicting future business performance, and correlate unreliably with other more influential Metrics which would be considered KPIs.

Examples of less influential / Vanity Metrics include:

• Sign-ups
• Sessions
• Followers
• Time-on-site
• Number of Pages Views
• Downloads

If you want to include Metrics like these you should include a Balancing Metric that shows that they correlate with KPIs like MQLs, SQLs, Bookings etc.

For example, if you had an Objective to 'Scale MQL to support Sales Growth', you may have a Key Result to 'Generate 1200 MQL for Sales this Quarter' this could be reached and Sales not have a healthy pipeline because the quality of the MQLs was low. So balance it with a MQL : SQL conversion rate metric, and add a Key Result like Have 60% of MQL convert to SQLs this Quarter. One keeps the other honest, and the Objective can only succeed if they both succeed.

KPIs vs Insights

If a KPI is a known and well understood number that allows you to track business performance. Insights are different as they go deeper and show you something that you didn’t know that you’re likely to act upon, and often impact your metrics.

Donald Rumsfeld said in a Pentagon news briefing:

There are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.

To find the Unknown Unknowns you need to be looking for patterns. Some patterns you’ll find have the potential to be acted upon.

Unknown Knowns are typically qualitative data that needs quantifying in someway and made statistically significant.

Known Unknowns happen when you have the question but not the answer.

And Known Knowns are literally that, and are often the KPIs we report on quarter after quarter.

Needless to say, looking and finding insights can significantly increase the performance of your company.

KPIs, Hierarchy & OKRs

KPIs and OKRs work well together as OKRs allow for KPIs to be grouped under and Objective and for there to be Hierarchy i.e. Parent / Child Relationships.

To carry on the MQL Objective example from above, how you propose to achieve this Objective will require other KPIs and Objectives to be defined as Children. These may include KPIs like Content Downloads, Paid Search Driven Sign-ups etc.

This is why KPIs and OKRs work really well together.

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