Looking at the cost per lead across your paid media campaigns, especially paid search and social media can be deceptive. Too often we have seen that the campaigns with a low cost per lead hardly convert into enrolments. Optimising on a cost per lead often leads to false positives.
From an attribution modelling perspective, lead forms represent conversions that are deferred in time. The value of the conversion becomes known not when a potential customer clicks on a lead form submission button but later on when he/she becomes an opportunity and then enrols as a student at the school.
Many schools ask themselves on how to reduce the overall cost per enrolment.
Overall marketing spend
___________________
Number of enrollments
=
Cost per enrollment
Instead, you should ask yourself the question: “Which campaign brings me the lowest cost per enrollment?”
How to measure the cost per enrolment on a campaign level?
To get from cost per lead to cost per enrollment, the journeys which are stored in your web analytics platform and your CRM system (e.g. Salesforce) need to be matched together. Matching this information makes it possible for you to understand the complete journey before a lead becomes an opportunity or enrols as a student at the school.
Now each customer journey is captured and matched together across all touchpoints you can use this data to understand what channels played a role in the upper funnel (awareness), the middle funnel (consideration) and the lower funnel (purchase intent).
Some common patterns are that display and paid social activities do perform well in the upper funnel, email marketing performs well in the middle funnel and organic and branded search campaigns perform really well as closers.
How do we now optimize the marketing strategy to lower the enrollment costs as a second step?
Here we see the best results by applying an algorithmic model which gives each touchpoint credits based on probability. More about this can be read here.
We now divide the spend by the number of enrollments we are able to understand the true cost per conversion on a channel level.
This data will also be available on a campaign and even down to a keyword level and can now be used for optimizations.
You can read further information on the topic in the case study here.
