Choosing your Schools Engagement Metrics
Original article by relationshipone.com – https://www.relationshipone.com/blog/calculating-the-top-10-marketing-metrics-your-c-suite-actually-cares-about/
“Marketing Measurement is the 1 percent of effort that is the 99 percent of value for justifying spending in the future.”
– Mark Jeffery, Kellogg School of Management
For the average modern marketer, there are a million things you could be spending your time on. One day, it’s developing a nurturing campaign and the next it’s updating the website with the latest product changes. With all the demands on our time, we need to make sure we’re focusing our efforts on the things that really matter to business growth. At the end of the day, your boss’s boss doesn’t care that you wrote a killer subject line that bumped open rates by 20%. He/she wants to know how well the business is doing, and it’s your job to provide this information.
There are countless articles written about which metrics you should be looking at in order to make business decisions, but they never seem to tell you how to actually calculate these must-have metrics.
If you’re going to give the executive team data they want, you have to know how to calculate what they need. It’s all about getting your mind around the data – concrete, objective metrics that show the impact to the bottom line. Once you grasp what the metrics are telling you, the story behind the data begins to emerge.
1. Marketing-Sourced Revenue
The exact definition of “marketing-sourced” will vary by company and industry, but this high-level metric is critical to understanding whether and by how much marketing efforts are resulting in paying customers. To determine this figure, your company needs to agree on an internal revenue attribution model. First-touch and last-touch are common ones, along with other customized models such as date-weighted or revenue-weighted attribution. Marketing-sourced revenue is the sum total of all opportunities that are touched by marketing assets under your attribution model. Once you have this figure, an even better metric is to calculate the percentage of total revenue touched by marketing:
Marketing-Sourced Revenue x 100
Total revenue
2. Return on Investment (ROI)
As a corollary to Marketing-Sourced Revenue, companies are (and should be!) asking if investments in marketing yield revenue. ROI can be measured at a topline level or at a granular level (e.g. by campaign), and everything in between. The formula we see most often is:
((Revenue) -1) x 100
((Initial Investment) )
3. Conversion Rates by Stage
Conversion rates are critical to understanding how many leads are generated, how many convert to sales-qualified leads, and then to opportunities, and how many of those opportunities convert to wins. The common way to calculate these rates is to simply divide the number of opportunities that have reached the further stage by the number of the initial stage, as in:
Number of opportunities x 100
Number of leads
4. Conversion Rates by Lead Source
One particularly useful way to view conversion rates is by lead source. This allows marketers to better focus their efforts where returns are greatest. This is the same calculation as above, but by lead source, which allows for comparison across lead sources.
5. Conversion Velocity
A corollary to Conversion Rates by Lead Source is Conversion Velocity, which is a measurement of how quickly leads are converted to opportunities and how quickly opportunities are closed. Velocity is measured as the duration of a lead/opportunity/etc. within a pre-defined time period. For example, to measure lead to opportunity conversion velocity, you would measure the difference between the opportunity create date and the lead create date. This is equivalent to the amount of time the lead spent in the lead stage before it was converted.
6. Opportunity Pipeline
Every company’s goal is to have a healthy pipeline of opportunities. Understanding the Opportunity Pipeline will aid marketing in determining how many leads need to be generated to support sales in reaching their goals. In our experience, the best way to measure the Opportunity Pipeline is to view the different stages of leads by the expected close date. This can be viewed by the total number of opportunities but more typically by expected revenues.
7. Lead Quality
Marketing’s purpose has become much more sophisticated than simply collecting leads. It’s vital to understand and measure the quality of the leads generated. Tracking the percentage of Marketing Qualified Leads (MQLs) provides marketers with a metric to communicate how they are enabling sales and company growth. Each firm will define MQLs differently. Here’s the lead quality formula:
MQLs x 100
Total Leads
8. Lead Scoring Distribution
Lead score distribution is an equally important metric to understand marketing effectiveness. To determine effectiveness of your scoring model, add conversion rates by lead score to ensure that high quality leads are, in fact, closing at higher rates. To calculate the distribution, simply measure the number of leads at each stage.
9. Cost per Lead (CPL)
Similar to measuring campaign ROI, marketers need to understand the overall cost to generate one lead, and how this metric changes over time and/or across lead sources. Typically, CPL is measured at the campaign level (which allows for comparison across campaigns), but can be calculated at any level. Here’s how you would determine it at the campaign level:
Campaign Cost (£)
Number of Leads Generated
10. Won Amounts per Lead/Opp/WonOpp
Now that we understand how much it costs to generate each lead, measuring won amounts per lead (or opportunity, etc.) “closes the loop” by measuring what the expected return on a lead is. Hopefully this figure is higher than the CPL, otherwise each lead is costing you more to generate than its expected revenues. Use this formula:
Won Amount (£)
Total Leads Generated
An important thing to consider regarding marketing analytics is to consistently set goals for each metric. Doing so enables users to show trends for those metrics over time and helps identify areas of operations that need improvement.