Using the Evaluating Dashboard

Measure Your Impact

Please note: While this video refers to Response Management, its content applies specifically to Funnel Metrics.

Have you ever met a marketing skeptic? Marketing skeptics aren't convinced that marketing actually works. "Where are the numbers?" they ask. "Where's the proof? Why are we spending money on this?" Good news! The next time your local skeptic calls marketing "the t-shirt department" may be the last, because you're now in possession of the cure for marketing skepticism: Funnel Metrics' Evaluating dashboard.

Those numbers and that proof the skeptics have been asking about? They're right here. The metrics on your Evaluating dashboard show exactly how your marketing program is performing — particularly in terms of its contributions to revenue. Using this dashboard, you can offer data-supported answers to questions like: Are industry conferences worth your company's while? How are conferences performing as compared to webinars? Are partner marketing activities yielding a lot of opportunities, but not a lot of revenue? It's all about tangible value, so here are the key metrics included in the Evaluating category:

• Opportunity to Won Conversion Rate by Campaign
• Opportunity to Won Velocity Rate by Campaign
• Average Deal Size by Campaign
• Top Campaigns by Attribution – Most Revenue (Won)
• Top Campaigns by Attribution – Most Revenue (Lost)
• Top Campaigns by Attribution – Most Won Opportunities (Count)
• Attribution by Campaign Type
• Average Number of Touches for Won and Lost Opportunities
• Disposition Reasons – MQL Disposition Reasons by Campaign Type
• Disposition Reasons – SAL Disposition Reasons by Campaign Type
• SQLs by Lost Reason
• Pipeline by Lost Reason
• Touch Timing by Type – Won
• Touch Timing by Type – Lost

At Full Circle, we've seen time and time again that when marketers explore this data consistently, they uncover valuable insights that have gone unnoticed. Those insights drive even more successful marketing, which drives even better business — and now, you can prove it.

Let's get started.

Example Use Case: Evaluating Campaigns by Conversions, Velocity, and Deal Sizes

The scatterplots at the top of the Evaluating dashboard provide three critical metrics to help evaluate campaign performance: campaign conversion rates, velocity rates, and deal sizes. Think of these as three different lenses you can look through to see new things about your campaigns.

Opportunity to Won Conversion Rate by Campaign

Your Opportunity to Won Conversion Rate scatterplot analyzes the number of opportunities each campaign was responsible for (opportunity volume) and the average conversion rate (from opportunity to closed-won). In a perfect world, all of your data points would cluster in the top right, with every campaign yielding a lot of opportunities with high conversion rates. Reality, however, has other ideas. The data here clusters loosely in the bottom left, with most campaigns yielding fewer than 100 opportunities and conversion rates below 50%.

Note: This dashboard component allows for mouse-overs! Just hover your cursor over a data point to reveal underlying campaign data, like this:

Mouseovers show unique metrics for each campaign. Here, you can see that this particular webinar yielded a conversion rate of about 18%, and influenced 33 opportunities. Information like this can help you recognize if certain campaigns are yielding lots of opportunities that don't convert. Those campaigns will cluster in the upper left corner, and if you were to have a lot of them, they could be creating unnecessary and futile work for Sales and wasting resources across departments.

Digging further into this data can surface patterns or micro-patterns to explore. Maybe certain segments, industries, or types of company are consistently yielding undesirable results. Alternatively, maybe your data points cluster toward the bottom right: Very few opportunities, but extremely high conversion rates. This might not scale well, but if it's working, is it a sacrifice your organization is willing to make?

For this example scenario, you can draw an imaginary trend line through the data points. It looks like there's a negative relationship between opportunity volume and conversion rate. Basically, the more opportunities a campaign influences, the lower its conversion rate. The inverse is also true: The higher the conversion rate, the fewer the opportunities.

You can also explore this dashboard component by right-clicking on it to open the underlying report and explore its data. Here's what you'll see:

This report is similar to the above scatterplots, but instead of data on individual campaigns, it shows all of the data by campaign type. Opportunity volume and conversion rate are still the primary metrics dimensions. Interestingly, that negative relationship that came to light in the dashboard component holds true here, as well. Might there be really important insights in your own data where you can, for example, confirm that certain campaign types tend to yield really high conversion rates but lower volumes of opportunities —and vice versa?

Opportunity to Won Velocity Rate by Campaign

This component analyzes the volume of opportunities each campaign influenced and how quickly those opportunities closed. In that perfect world we were talking about earlier, all the data points would cluster in the upper right, with lots of opportunities moving very fast through the sales process. Yet again, reality has dashed our hopes: They're all in the lower left.

Most of these campaigns influenced fewer than 10 opportunities, with nearly all of them taking 200 days or fewer to become closed/won deals. The implications of this insight extend beyond just measuring campaign performance — it's valuable information to have for demand planning exercises, too.

When you right-click into the underlying report on this component, try scrolling all the way to the bottom of the report and selecting "Campaign: Type" from Campaign Fields category in the drill-down dropdown box. Here's what that gets you:

Again, this report shows all data by campaign type, rather than just individual campaigns. Opportunity volume and velocity rates are still the primary metrics dimensions. The following table of data appears directly below the report visualization:

With this information, you can now determine how campaign types influence the volume and velocity of opportunities. This enables you to, for example, compare webinars against events in terms of the volume of opportunities they generate for your company.

Average Deal Size by Campaign

If someone's asking you to show them the money when it comes to marketing measurement, this is the component to pull up. It plots the volume of opportunities influenced by each campaign and the average deal size for each campaign. Ideally, you're hoping to see data points clustered in the upper right, with high opportunity volumes and large deal sizes. But it's no fun to live in an ideal world, so let's try this on for size:

From the rough bell shape of this data, you could surmise that there appears to be a sweet spot in the middle, with relatively higher numbers of opportunities and relatively larger deal sizes. That sweet spot is useful to know. The campaigns in it (remember, you can hover over the data points to identify them) are likely to be the ones you'll want to replicate and optimize.

In looking at this component and its underlying report, it's important to pay thoughtful attention to the volume of opportunities associated with each campaign. If only one or two opportunities are associated with certain campaigns, it may be unwise to ascribe too much significance to their deal sizes. The idea of "critical mass" comes into play here — basically, how many opportunities it takes to make a campaign meaningful enough to extrapolate from — but your organization will need to determine for itself what exactly constitutes that critical mass.

Note: Always proceed with caution when using averages for calculations, as outlier data points could skew results. Sometimes median is the better calculation to use.

For example, let's say you closed 10 deals last year and all but one (1) of the deals had a typical $10,000 deal size. That one unusual deal brought in $1,000,000. Calculating from the average of all 10 deals, your average deal size would be $109,000. That's $99,000 more than your typical deal. Calculating from the median instead, your median deal size would be $10,000. Median is typically the more effective calculation to use when dealing with data that have the potential of being highly variable. Even when you don't use median, be sure to consider — and perhaps even make a special note of — the role of outlier data points in providing context for your calculations and reported data.

As you've seen, the first three scatterplots on your Evaluating dashboard can help uncover powerful insights. By keeping regular tabs on these components, you can always tell how your campaigns are:

• influencing opportunity volume;
• influencing conversion rates;
• and influencing deal sizes.

Combined insight from these components can guide your decision-making. For example, now that you can identify which campaigns have very high deal sizes and velocity rates, but low conversion rates, you can create a task force to explore opportunities for increasing those campaigns' conversion rates. In the case of campaigns with high conversion rates and large deal sizes, but very low velocity, you're now aware that it may be useful to plan the timing of those campaigns so the company doesn't depend on them at the most critical points during the year.

Additional Evaluating Dashboard Components

Top Campaigns by Attribution - Most Revenue (Won)

This component lists your campaigns in descending order of influenced won revenue, as determined by Influence Model 1 settings.
Time Parameter: All time

Top Campaigns by Attribution - Most Revenue (Lost)

Here, you can see your campaigns in descending order of influenced lost revenue, as determined by Influence Model 1 settings.
Time Parameter: All time

Top Campaigns by Attribution - Most Won Opportunities (Count)

This list lays out your campaigns in descending order of opportunities with won revenue.
Time Parameter: All time

Attribution by Campaign Type

And now for something completely different! Here's a pie chart showing the distribution of revenue by organizational department (based on campaign sources). In other words, this is where you check to find the amount of revenue for which each organizational department is responsible.
Time Parameter: All time

Average Number of Touches for Won and Lost Opportunities

This comparative bar chart gives you the average quantity of influential touches for both won and lost opportunities by fiscal quarter, as determined by the settings in Influence Model 1. Over time, you'll see patterns emerge here. In this example, there's a general trend of increased touches for both won and lost opportunities over the past eight fiscal quarters. 
Time Parameter: All time by quarter

Disposition Reasons - MQL Disposition Reasons by Campaign Type

Wondering why certain types of campaigns get dispositioned at the MQL stage? Find your answers here.
Time Parameter: Fiscal Year to Date

Disposition Reasons - SAL Disposition Reasons by Campaign Type

Here, you can see why those same types of campaign get dispositioned later on, at the SAL stage. 
Time Parameter: Fiscal Year to Date

SQLs by Lost Reason

This pie chart shows you what proportion of your SQLs are lost due to each opportunity lost reason. 
Time Parameter: Fiscal Year to Date

Pipeline by Lost Reason

Check here to see the volume and frequency distribution of Pipeline lost reasons.
Time Parameter: Fiscal Year to Date

Touch Timing - Touch Timing by Type (Won)

This very colorful component component lets you track the pattern of touches by campaign type in 30-day cohorts prior to a won opportunity. For example, for the 151-180 time cohort, you can easily compare how many touches each campaign type received relative to other types in the same period. This can help answer questions about which types of campaigns people interacted with at a specific time, and how that time period compared with others in terms of interaction types.
Time Parameter: All time

Touch Timing – Touch Timing by Type (Lost)

The final Evaluating chart shows the pattern of touches by campaign type in 30-day cohorts prior to a lost opportunity. 
Time Parameter: All time