How can you go beyond tracking clicks and impressions to see the bigger picture of advertising effectiveness?

A large, highly selective graduate program in New York was already tracking clicks and impressions on their advertising, however, this information could only go so far in indicating the overall success of the campaigns and whether they led to enrollment.

Data on the media activity was sitting in one system, and the data on conversion activity was sitting in a different system, and neither were communicating.

This meant a disconnected picture of how the money spent on advertising was impacting enrollment, leading to guesswork around where and how this budget was spent.

How we got involved:

INSIGHT

We collaborated with the marketing and admissions teams to address the limitations of only tracking clicks and impressions on advertising, as that doesn’t connect to eventual enrollment. 

Our experts highlighted that if we connected the data points sitting in silo (e.g. cost per click and cost per enrollment) this could reduce overall cost per acquisition and generate more precise marketing tactics.

ACTION

The first step was to create a bespoke integration between Akero and Slate to make sure that all stages of the process, from the very first ad click right through to eventual enrollment, were connected and all parts of the system were speaking to each other.

Next, we built a pipeline that precisely mirrored the student journey and combined this with Akero performance reporting to find out what was/wasn’t working to make recommendations on how things could improve.

OUTCOME

This connected journey meant that full visibility on recruitment processes was achieved for the first time, with a clear picture of which messages, platforms and many other things were impacting enrollment.

We were able to identify true cost per acquisition from the first advert click right through to eventual enrollment.

Our experts swiftly implemented real-time changes on marketing tactics to help lower this cost due to increased precision.

We were also able to use these insights and actions to generate long-term learnings, which would eliminate future guesswork and mean the team can do more of what works, and less of what doesn’t.