From Blind Spend to Full-Funnel Visibility: Corning Life Sciences Unlocks Attribution with Bizible
Industry
Healthcare
Challenge
Corning Life Sciences faced significant limitations in understanding and optimizing its marketing investments due to disconnected data across its Marketo and Salesforce environments. Despite a robust MarTech stack, marketing leadership was unable to accurately attribute MQL generation, calculate the cost of opportunity creation, or optimize channel investments for maximum ROI. The absence of an integrated attribution infrastructure resulted in subjective, non-evidence-based decision-making and restricted marketing's ability to prove its impact on business outcomes.
Results
With a unified attribution infrastructure in place, Corning Life Sciences achieved seamless data integration across Marketo, Salesforce, and all paid ad platforms. The organization implemented a custom attribution model aligned to its funnel stages and campaign types, supported by a comprehensive reporting framework. Corning's marketing team is now equipped to interpret and act on attribution data, with live Salesforce dashboards and reports providing leadership with actionable insights to optimize channel performance, allocate spend confidently, and quantify marketing's impact on both pipeline and revenue.
Key Products
Marketo, Attribution & ROI Modeling, Salesforce Sales Cloud, Marketo Measure
Before this engagement, we were making channel investment decisions on instinct. TPG didn't just implement Bizible — they built us a custom attribution model around how our business actually works, and gave our team the reporting and the training to use it. For the first time, we can see exactly which channels drive pipeline and shift spend with confidence
Greg Hoff
Director of Marketing Communications @ Corning Life Sciences
About your Customer
Corning Life Sciences, a division of Corning Incorporated, is a global leader in specialty glass, ceramics, and optical physics. The company provides innovative life sciences solutions to support research, development, and manufacturing.The Challenge
Before engaging with The Pedowitz Group, Corning Life Sciences contended with fragmented marketing data spanning Marketo and Salesforce, hindering the ability to connect marketing activities to outcomes. Leadership lacked visibility into which channels drove qualified leads, the associated costs of opportunity creation, and how to optimize spend for measurable ROI. Without a scalable attribution infrastructure, critical investment decisions relied on subjective judgment rather than empirical evidence, limiting marketing's proven contribution to pipeline and revenue.
The Solution
Recognizing these constraints, Corning Life Sciences partnered with The Pedowitz Group to architect a robust attribution solution. The engagement was structured in two phases: first, TPG built the foundational technical infrastructure by integrating Bizible with Salesforce, Marketo, and paid ad platforms, ensuring accurate multi-touch data capture and spend mapping. Next, TPG collaborated with Corning to design a custom attribution model, establish stage-based weighting, and enable historical campaign data integration. The team was trained to interpret complex attribution data, and a suite of custom Salesforce reports and dashboards was deployed, delivering real-time, actionable insights to marketing leadership.
The Results
Following the phased deployment, Corning Life Sciences now benefits from comprehensive full-funnel attribution and transparent reporting. With Marketo, Salesforce, Bizible, and all paid ad platforms unified into a single attribution infrastructure, the team captures 100% of touchpoints across the buyer journey — giving marketing the evidence to identify high-performing channels, accurately measure MROI, and make data-backed budget allocations. Ten custom Salesforce reports and a dedicated Bizible dashboard provide leadership with on-demand visibility into marketing's influence on pipeline and revenue. In just five months, Corning transitioned from siloed data and subjective spend decisions to a scalable, evidence-driven attribution framework that continuously compounds in value.
