LinkedIn: amplifying customer case studies through programmatic ads
A combination of compelling creative and programmatic advertising
The challenge
LinkedIn approached us to promote a series of key customer case studies to targeted industry verticals, each with distinct HR challenges and audience profiles. The goal was to showcase LinkedIn’s value across multiple sectors, increasing awareness and engagement among senior HR decision-makers.
Working with a new contact at LinkedIn, we collaborated on a fresh approach - testing programmatic advertising as a new channel for amplification. This was a first for the team, moving beyond traditional direct publisher activity to a more scalable, data-led model that could deliver measurable, efficient results.
Engaging CHROs and HR leaders across diverse industries
Standing out from competitors and driving quality engagement
Capturing highly relevant traffic
Introducing a new advertising approach to a client new to programmatic
Our solution
We developed and executed a short-run programmatic campaign designed to amplify LinkedIn’s case studies across specific industry verticals. Each audience received tailored creative assets aligned to their unique HR priorities, ensuring relevance and resonance at every touchpoint.
As co-branding wasn’t previously explored within LinkedIn’s brand guidelines, we led the creative direction to establish a complementary look and feel, one that reflected LinkedIn’s identity while elevating partner visibility. This new design approach became the visual standard for future case study promotions.
Media planning and buying across programmatic channels
Delivery of multiple HTML and static artwork assets optimised for mobile and desktop
Creative direction, co-branding, and asset development
Strategic messaging tailored to each target vertical
The results
With an average CTR of 0.58%, the campaign proved highly effective in reaching and engaging senior HR audiences. The success of this pilot laid the foundation for future campaigns, each iteration refined with new learnings and optimisations to continually enhance performance.