GaaS Case Studies—Massage Envy, Imagine Learning & Lyft
Prior career examples from Massage Envy, LearnZillion and Lyft, with the work, reported outcomes and measurement limits.
Three different growth problems
These are examples from Anthony Sledge’s prior career work. They show the work and reported outcomes in their own settings; they are not a promise of the same result for a new client.
Massage Envy: restore the business before scaling demand
The franchise had lost staff and customers. The recovery combined recruiting, local outreach, search ads and weekly reporting. Anthony’s career account reports growth from one to 25 employees and recovery of 80% of prior revenue in six months. The result reflects a business turnaround, not the isolated effect of one campaign.
Read the turnaround caseLearnZillion: connect acquisition to a self-serve offer
The work joined paid acquisition, lifecycle messaging and product access. The career record reports that the program generated 28% of new business at 2,040% ROAS and that a new product reached 5% of subsidiary revenue in its first year. These are historical program-reported figures, not an independent attribution audit or evidence that marketing caused the later acquisition.
Read the LearnZillion case and its limitationsLyft: measure a seasonal messaging test
A two-week holiday test sent post-ride messages to eligible riders who rarely or never tipped. The retained account reports about $80,000 in additional driver tips and 23,000 additional tipped rides. Tips are driver earnings, not Lyft revenue. A short seasonal result does not establish what would happen across a full year.
Read the experiment and its limitsChoose a relevant starting point
Compare the problem, intervention, measurement window and limitations with your own situation before choosing a service.
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