We are fortunate enough to be part of a new era in the digital marketing world. The amount of data at our fingertips is astronomical, and the value generated from applying that knowledge has the power to make or break an organization. Data has enabled insight into ROI-based decision making in a way where action and outcome can be measured to the dollar.

The Challenge of Non-Revenue Generating Conversions

Assigning value to explicit revenue events is simple, such as ecommerce where more transactions equal more revenue, but it becomes more difficult for industries without 1 to 1 measurement.

It is growing common practice to extrapolate the anticipated revenue of a micro-conversion that will likely lead to a revenue event. A example of this is with B2B lead-gen websites. The lead itself isn’t a revenue event, however over time the average value (revenue generated from lead) can be calculated. This can be dialed in further with lead-scoring to attribute value based upon likelihood to convert.

However, in many cases it is difficult to make a connection between a micro-conversion and the revenue outcome of the event. This is particularly highlighted with online conversions that intentionally conclude an online experience, but that we intuitively know has increased likelihood of a purchase – such as directing users to a brick-and-mortar location.

This type of user journey presents challenges for tracking the benefit of online interactions, as once a user identifies a brick-and-mortar to visit and exits a site, they can no longer be tracked (unless a universal ID is attributed that connects online users to offline customers – such as a user account). The disconnected user experiences can be tricky to attribute a value to,  but isn’t impossible.

A Real Life Example

A fast-food industry client recently came to us with this very problem. They had a web experience, with an array conversion points (content engagement, newsletter sign-up, coupon download, location finder, etc.) and yet were struggling to attribute a value to the various conversions to help make informed efforts to optimize the user experience. 

For the sake of privacy for our client, let’s dissect a similar experience on CarlsJr.com to attribute values to non-revenue generated conversion points. The primary functions of the site are to allow users to discover offers, explore the menu and find locations. None of these users paths include conversion points that directly generate revenue.

Content consumption (more engagement, page views, etc.) is a sign of user intent to convert – purchase, sign up, etc. Looking at the primary navigational paths mentioned above, engagement with any of these areas should increase a potential fast-food consumer’s propensity to make their way to their nearest Carl’s Jr. restaurant.

Unpacking the User Journey

Let’s assume a user arrives, visits a number of pages engaging with content and is compelled to find a restaurant to fulfill a newfound burger craving. They then navigate to the locations page. The user searches and identifies his/her nearest store … and then concludes his/her session.

No cash has been exchanged between this user and Carls Jr. – but did the location finder use have a conversion value? You bet!

 

By calculating the current amount of value that the on-site conversions (like location finder feature) is generating, it is then possible to focus resources on conversions that will provide the greatest financial impact.

Working with the Data Available

How then is a conversion value attributed for Carl’s Jr. location finder engagement? The calculation varies based upon data available. A common misconception is that only if a large, detailed data-set is available will this process work. Although this can help with the confidence of a calculated sum, simply having a base value gives something to optimize from.

Let’s take a deeper look at starting to break down our calculation case for Carl’s Jr.

  1. Let’s start with Average Meal Cost – This metric should be fairly easy for Carl’s Jr. to provide: a simple average revenue per mean. (Alternatively, average revenue per visit layered with industry margins (even with some fuzzy math from something like this) get us in the ballpark for calculating value.) For the case of Carl’s Jr., let’s assume this figure is $7.00. 
  2. ​Then add what I am calling the “Location-Finder-Use-to-Purchase-Rate​” – The idea here being attributing the likelihood of a user utilizing the location finder tool online and their propensity to buy as a result. In other words, “we believe 1 in 4 users who engage with the location finder will go make a purchase.” This could be a tricky one to nail down, but a series of user tests, or even an office survey would give us what we need to intuit a starting point. For the case of Carl’s Jr., let’s assume this figure is .25%.

Calculating Conversion Value

With Average Meal Cost & Location-Finder-Use-to-Purchase-Rate​, along with our Current Location Finder Engagement Rate and Web Visitors Per Month (pulled from web analytics platform) the VALUE of a location finder engagement is simple calculation away. 

Visitors
x (
Location Finder Engagment Rate
x
Average Meal Margin
x
Location-Finder-Use-to-Purchase-Rate
) =
VALUE
V
x (
LF
x
AM
x
PR
) =
VALUE
V = Visitors
LF = Location Finder Engagment Rate
AM = Average Meal Margin
PR = Location-Finder-Use-to-Purchase-Rate
900kWeb Visitors Per Month
22%Current Location Finder Engagement Rate
$7.00Average Meal Cost
25%Location-Finder-Use-to-Purchase-Rate
900k
x (
0.22
x
$7.00
x
0.25
) =
$346,500

And there we have it. For this case, we have assigned a value generation of $346,500 per month to the location finder conversion point on site. We can also dial this back to a per-conversion value of $.38 per conversion.

Clearly, there are many ways to look at improving this calculated number over time, and it is highly recommended to do so. This is about setting out to assign a starting point. Optimization of the data input to get there is a continual process.

Once values are attributed to conversions, it is important to add those metrics to your analytics platform and performance reporting. (For us, that most commonly occurs in Google Analytics. Watch for an upcoming post on adding value tracking to goals in GA.) The benefit of defining values for conversions is it provides multiple success metrics that can be tracked for over the course of marketing and optimization efforts to better understand behavior and impact in a measurable, meaningful way – and a documented value for celebrating optimization success.

Optimizing for Increased Conversions

Simply assigning a value to conversions as part of your approach to analytics and reporting will yield insights for better decision making and understanding of your customers.

But where the value really shines, is within the optimization process. With values assigned to all conversion points, web and marketing needs can be weighed fairly with a better understanding of the overall financial impact of conversions in relation to each other. From there, the highest ROI opportunities can be addressed first, and the impact can be measured.

Continuing with our example above, let’s assume Carl’s Jr. identifies a low effort, high yield update they can make to their location finder conversion funnel (this could be through additional content, navigational paths, incentives, etc. – we recommend testing all these things!).

For this example, the visitor to location finder use goes from 22% to 25%. All of a sudden we have a notable uptick in revenue:

900k
x (
0.25
x
$7.00
x
0.25
) =
$393,750

Assuming it is a sustainable optimization, the investment has yielded an impressive $567,000 per year!

It’s Difficult, But Worth the Effort

Each digital ecosystem requires its own set of data measurement practices and conversion value assignments. Whether there is black-and-white revenue generation that can be attributed, or if a little extra math is needed, the reward is worth the effort. 

We’ve worked closely with clients across many different industries and helped attribute conversion value – from eComm social share, to friend referrals, to student applications, to location finder searches. Just give it a shot – it’s worth the pay off.

Want to pick our brains around defining conversion values? Drop us a line, we’d love to chat!

– Written by Jedidiah Fugle.

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