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Marketing Attribution & Stakeholder Enablement

E-commerce & Marketing

SQLSnowflakeSisense

Overview

Marketing and client-facing teams relied heavily on last-click attribution, which limited their ability to explain performance, justify spend, or confidently recommend optimizations to customers. They needed clearer insight into the full customer journey and a way to communicate that insight effectively to non-technical audiences.

My Role

I (Senior Business Intelligence Analyst) serving as the analytics lead in client-facing and cross-functional discussions. Regularly presented insights on calls, supported account managers in upsell conversations, delivered analytics demos for sales teams, and mentored junior analysts on stakeholder communication.

Data & Tooling

Used SQL to analyze portal performance and customer journey data in Snowflake, with insights delivered through Sisense dashboards and targeted ad-hoc analyses designed for client and executive audiences.

Approach

Partnered with marketing leadership and account managers to define attribution logic that aligned with real-world budget and optimization decisions

Led client calls to walk through attribution insights, explain trade-offs, and answer questions in clear, business-focused language

Supported AM teams by using analytics outputs in upsell and renewal conversations to demonstrate ROI

Delivered live demos of Sisense dashboards for sales teams, showing how attribution insights could be used in customer discussions

Mentored junior analysts on presenting insights, handling stakeholder questions, and framing analytics for executive and client audiences

Outcome

Enabled data-backed budget discussions across multiple marketing channels and supported client-facing analytics demos used in upsell and renewal conversations

Improved both client and stakeholder confidence in performance reporting and enabled more informed budget discussions. Attribution insights became a regular input into client reviews, internal planning sessions, and sales conversations.

Visuals

Dashboard Screenshot

Data Model Diagram

What I'd Do Differently

This work reinforced that analytics impact depends as much on communication and trust as on technical accuracy. In future iterations, I would invest even earlier in shared language and examples to ensure attribution concepts are easily understood by all stakeholders.