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How John Jacobs increased revenue by 3x by using first click attribution model



Increase in revenue


Drop in CAC on Facebook


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Meet the Brand

John Jacobs offers the trendiest eye wear for men and women, who believe in making smart choices in life. Their 180-degree product simulation feature enables you to buy eye wear online without any hassles.

The Challenge

With only one attribution model(Last-click) to measure full-funnel performance, they were facing challenges in scaling campaigns

Although Last-click attribution models were giving the right picture of Bottom and Mid-funnel campaigns, it wasn't giving the proper attribution to the Top of the funnel campaigns.

The brand was experiencing a high CAC on the Google Display network, impacting the overall efficiency of their digital marketing efforts.

The Solution with EasyInsights

Full-Funnel Blending at User-Level Data: To gain a comprehensive understanding of the customer journey, we performed full-funnel blending at the user-level data. This involved collecting and analyzing data at each stage of the marketing funnel, from awareness to conversion.

First-Click Attribution: To address the attribution challenge, we implemented the first-click attribution model. This model assigns conversion credit to the first touch point in the customer journey, providing insights into the top-of-the-funnel campaigns that drive initial awareness.


Google Display Campaign Optimization: We conducted a thorough analysis of the Google Display campaigns, identifying under performing segments and optimizing targeting parameters. By refining audience targeting and creative elements, we aimed to enhance campaign performance and reduce CAC.

Attribution Model Integration: The first-click attribution model was integrated into the analytics framework. This allowed us to allocate conversion credit to the first interaction a user had with the brand, providing a clearer picture of the impact of top-of-the-funnel campaigns.


CAC Reduction on Google Display: The optimization efforts on the Google Display network led to a significant reduction in Customer Acquisition Cost. This was achieved by targeting high-performing audience segments and refining ad creatives based on user engagement patterns.

Improved Visibility into Customer Journey: The implementation of the first-click attribution model provided valuable insights into the customer journey. By understanding the impact of top-of-the-funnel campaigns, John Jacobs could make informed decisions about resource allocation and campaign optimization.

With EasyInsights
Effortless Data Analysis: Seamlessly analyzed user-level data from various touchpoints in the marketing funnel with a user-friendly interface.
Holistic Customer Journey Understanding: Gained a comprehensive understanding of the customer journey, from awareness to conversion, through full-funnel blending at the user level.
Attribution Clarity: Implemented the first-click attribution model effortlessly, attributing conversion credit accurately to the initial touchpoints in the customer journey.
Optimized Resource Allocation: Made informed decisions on resource allocation, focusing on high-performing campaigns across all channels
Without EasyInsights
Tedious Data Analysis: Struggle with manual data analysis, spending significant time and effort to gather insights from disparate sources.
Limited Customer Journey Visibility: Lack a comprehensive view of the customer journey, making it difficult to identify key touchpoints and understand user behavior at each stage.
Attribution Ambiguity: Face challenges in implementing and understanding attribution models, leading to uncertainty about the true impact of various marketing campaigns.
Resource Allocation Guesswork: Rely on guesswork for resource allocation, potentially misallocate budget to campaigns that may not be contributing significantly to conversions.

Your Data, Your Way: Custom Models for Your Business

With EasyInsights, get on-request custom data models that suits your business. We can build any use case that can be powered by first party user data.