Maximising durable Marketing performance
- sarahfoss8
- Apr 3
- 2 min read
Updated: Sep 3
CASE STUDY: Automotive
PRODUCTS: Dragonfly-Connect - our Data Clean Room Solution | BigQuery | Analytics Hub | Ads Data Hub | SA360 | DV360
The Challenge
A global automotive giant came to Dragonfly with the objective of boosting its online sales and increasing market share in an increasingly competitive and fragmented digital landscape.
To achieve this, they required a plan that could address a future where privacy changes threatened their ability to collect customer data, making it much harder to track and target potential buyers effectively, directly challenging their primary objectives.
The Goals
To achieve this, we implemented our data clean room solution, Dragonfly-Connect - a secure platform designed to overcome data fragmentation within the digital landscape. To meet their objectives, we created a strategic 2-step plan...
To enrich consumer insights for improved targeting and activation by establishing a secure data platform that enables both internal and external data collaboration.
To advance the client's first-party data capabilities by applying AI to enhance advanced targeting tactics such as personalisation & consumer-centric media bidding.
The Solution
By integrating Cloud and Ads capabilities with privacy-centric technologies, we increased visibility into customers and prospects’ behaviour. This revolutionised the understanding of how purchasers engage with digital content that exists beyond the client's websites, creating an holistic view of online behaviours across their digital ecosystem.
To achieve this, we leveraged Dragonfly-Connect, our customisable data clean room (DCR) solution to drive Marketing effectiveness through two business use cases:
1. Enhanced Value-Based Bidding (VBB):
• Analysed website actions linked to sales revenue
• Used insights to recalibrate media bidding algorithms
KPI: Incremental high-value website actions
2. Predictive Audience Value:
• Evaluated user behaviour for high-value actions
• Modelled predictive value and targeted leads based on profiles
KPI: Incremental lead volume from high propensity audiences
The infrastructure we built enabled user matching and modelling for privacy-compliant data flows.
This work reduced data silos, improved targeting and measurement capabilities, and provided deeper insights for a comprehensive understanding of the clients’ customers.
The Results
These enriched insights transformed personalisation capabilities, enhanced precision targeting, and increased qualified leads and online sales.
-7% | +71% | +7% | +23% |
Cost per Qualified Lead | Increase in Online Sales | Qualified Leads | Uplift in ROAS |
This case study was accredited by Google Cloud, certifying our Google Cloud Analytics Product and Technology Expertise.
