Marketing funnel metrics are always at the forefront of a B2B marketer’s mind. We’re constantly looking at conversion rates, cost data, social shares, open rates, and click-throughs -- just to name a few. While different teams focus on different metrics (because we’re all running different marketing strategies), how do all of these metrics compare to each other?
Take a look at this matrix of 31 marketing funnel metrics to see which ones your team uses, as well as which ones would be worth adding to your reports. The matrix also shows which buyer journey stages the metrics measure, the type of data the metric produces, and the martech solution(s) responsible for generating the metric.
(click to enlarge)
Metrics at the top of the funnel measure prospect behavior, such as impressions, bounce rates, average time on site, and volumes of various types of web traffic.
These are helpful when optimizing web pages for TOFU conversion rates, and they provide a general understanding of the health and effectiveness of a website. However, when it comes to impacting the bottom line, they don’t provide many down-funnel insights.
Marketing funnel metrics around the middle of the funnel include open rates, click-through-rates, lead volumes, lead scores, and lead conversion rates by channel or landing page. These metrics help show you where your prospects are most often turning into more qualified leads.
However, these metrics can quickly outlive their usefulness when marketers begin asking questions like, “How much revenue did this channel generate?” and “How much revenue is marketing contributing to the business’ bottom line?” Those questions can only be answered by even lower-funnel metrics...
Funnel metrics near the end of the buying journey can yield a plethora of data-driven insights. These metrics measure conversions, costs, win rate, and overall results based on opportunity conversions and closed-won customers.
BOFU metrics can also compare lower-funnel results with higher-funnel activities in order to inform on which TOFU and MOFU strategies ultimately generated opportunities, customers, and revenue. These metrics are the clincher that give the marketing team all the information they need to optimize their marketing spend and generate more revenue on every strategy iteration.
Volume-based metrics (like website traffic, lead volume, opp count, etc.) are metrics that show magnitude, but they lack perspective. While they provide a cumulative total across an array of sources, they don’t provide much insight for decision-making purposes.
Cost-based metrics show return on marketing spend. “Cost-per” metrics are the most common examples (cost-per-lead, cost-per-MQL, cost-per-opportunity, etc). These help to gauge spend on a channel-by-channel basis.
Percentage-based metrics are your “rates” (e.g. bounce rate, open rate, click-through rate, conversion rate, win rate, etc). These compare two different metrics against each other, which means they have unlimited potential to provide helpful insights, depending on the type of comparisons they make. Lower funnel percentage-based metrics (e.g. opportunity conversion rate and win rate) are far more insightful than the typical TOFU rate metrics (bounce rate, click-through rate, etc).
Algorithmic metrics compare more variables than percentage-based metrics, and they usually result in a “score” of some kind. The two algorithmic metrics shown in the matrix are “lead score” and “predictive engagement score” -- both of which take a myriad of factors into account when generating their overall result. These metrics are built to do more than just inform, they’re configured to prompt a specific action.
This type of metric also belongs to the family of “adaptive analytics,” which is defined as “marketing data and insights that leverage real-time capabilities and algorithms to provide the most accurate information in the moment.”
Revenue-focused metrics are metrics that directly impact revenue generation. Almost exclusively BOFU metrics, they can be directly linked to the bottom line. These have also come to be known as “revenue analytics” and can be used to show real-time ROI of a marketing spend.
These are metrics that can imply specific, measureable, strategy changes. Most cost-based metrics are also decision-making metrics, because they show the direct impact of a marketing spend. Volume-based metrics provide less contextual information, so they’re generally not classified as decision-making metrics.
Down-funnel metrics tend to be decision-making metrics because they show tangible impact on activities leading to revenue generation, whereas higher-funnel metrics give less actionable implications.
Metrics Derived by Web Analytics
Web analytics platforms give mostly top-of-funnel stage insights, including web traffic figures and basic user behavior metrics. While web analytics platforms can show overall growth over time, or general upticks (or red flags) in user behaviors, they shouldn’t be used to make sweeping strategy decisions.
Metrics Derived by Social Media Networks
Social media networks provide a few key metrics that show social engagement reach (followers, shares, etc).
Metrics Derived by Marketing Automation
Marketing automation is a highly insightful tool that can generate a number of key metrics, mostly in the middle-funnel stage. Not all marketing automation platforms generate the same metrics -- some generate more, some generate less.
Overall, marketing automation is used to gather lead-stage insights, but lower-level measurement transitions to the CRM-level with a marketing attribution solution.
Metrics Derived by Marketing Attribution
An advanced, marketing attribution solution has incredible power to generate insightful lower-funnel metrics. Because the attribution solution connects directly to the CRM, it’s able to pull granular, touchpoint-level data across all marketing funnel stages and compare that data directly to revenue. For example, marketers can see MQLs, opps, pipeline, and/or revenue by keywords, ads, landing pages, campaigns, channels, and events -- down to the touchpoint level.
These granular, revenue-based metrics provide the most powerful insights available to marketers. Directly able to impact decisions based on revenue, marketers can optimize their TOFU and MOFU strategies based on BOFU results from the past -- and they can use those insights to make accurate forecasts for the future.
For more information about advanced, B2B marketing attribution, take a look at this ebook to see how it works.