Econsultancy columnist Rebecca Sentance has published a case study on how British travel brand Secret Escapes reduced its cost per lead by 38% using machine learning.

Sentance says, “Because Secret Escapes is a members-only travel club that has built its brand and reputation around exclusivity, its growth and income rely on new users signing up for membership via the Secret Escapes website.

Despite running a number of marketing initiatives to encourage sign-ups, however, Secret Escapes was struggling to hit its target CPL (Cost Per Lead) goal with its existing bidding solution.

“We decided to put our existing bidding solution to the test, and see if we could identify a more efficient bidding setup,” said Miteva.

Using campaign drafts and experiments in Google Ads, which let marketers propose and test changes to their Search and Display Network campaigns, Secret Escapes was able to conduct tests across multiple territories simultaneously and compare outcomes”.

Secret Escapes: How machine learning reduced cost per lead by 38% [case study]

Econsultancy

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