The scoreboard, and what is not on it. The hard targets, how often each is actually
looked at, and the quiet signals that never reach a dashboard.
Marketing Budget Reallocation based on MMM
The percentage of the total marketing budget that is demonstrably reallocated to higher-performing channels or activities, directly influenced by your Marketing Mix Models.
Target · Influence a 10-15% shift in annual marketing budget towards more efficient channels. Your MMM reveals that organic social has a higher ROI than paid search for brand awareness. You then influence a £500K shift from paid search to organic social, demonstrating a 12% reallocation.
Incremental Lift from Targeted Campaigns
The measured increase in conversions or revenue from campaigns that use your predictive models for targeting (e.g., propensity to buy, churn risk), compared to a control group.
Target · Achieve a statistically significant 8%+ incremental lift in target campaign conversions. A campaign targeting 'high propensity to buy' leads (identified by your model) generates £200K in revenue, while a control group generates £180K, showing a 11.1% incremental lift.
Predictive Model Accuracy & Stability
The ongoing accuracy (e.g., AUC, R-squared) and stability (e.g., minimal model drift) of the core predictive models you own, such as CLV, churn, or lead scoring models.
Target · Maintain model accuracy within a 5% variance of initial baseline performance, with less than 10% drift annually. Your churn model consistently identifies 75% of actual churners within the top 20% of predicted risk, and this performance holds steady month-on-month, even as customer behaviour subtly changes.
Data Quality & Readiness for Modelling
The completeness, accuracy, and timeliness of the marketing data pipelines and datasets you rely on, as measured by error rates and stakeholder satisfaction.
Target · Reduce critical data errors (e.g., missing UTMs, incorrect event tracking) by 25% across key marketing platforms. After implementing new data validation checks and working with Marketing Ops, the percentage of campaigns with incomplete UTM tracking drops from 20% to 15%.
Strategic Influence & Thought Leadership
Your ability to shape the strategic direction of Marketing through data-driven insights and to be seen as the go-to expert for complex analytical challenges.
- You're proactively invited to Marketing leadership's quarterly planning sessions. Your recommendations are regularly adopted into strategic initiatives. You're asked to present at internal 'all-hands' meetings on the future of marketing measurement. Other teams (e.g., Product, Sales) seek your input on their data challenges.
Team Leadership & Mentorship
How effectively you lead and develop your team of analysts and data scientists, fostering a culture of technical excellence and continuous learning.
- Your direct reports consistently meet their project deadlines and grow in their technical capabilities. They express high satisfaction in 1:1s and performance reviews. You're regularly conducting code reviews, providing constructive feedback, and unblocking your team members. You've successfully onboarded and ramped up new team members within 3 months.
Cross-Functional Collaboration & Buy-in
Your skill in building strong relationships with other teams (e.g., Data Engineering, Marketing Operations, Product) to ensure your models are integrated, trusted, and actionable.
- You're seen as a trusted partner by Data Engineering for schema design. Marketing Operations actively seeks your input on new MarTech implementations. Product teams value your input on A/B test design. You can get different teams to agree on a 'single source of truth' for key metrics, even when they initially disagree.
Innovation & Future-Proofing
Your proactive efforts to explore new methodologies, tools, and approaches to keep our predictive capabilities ahead of the curve, especially in the face of privacy changes.
- You've successfully piloted a new attribution methodology (e.g., a privacy-preserving one). You've introduced a new ML technique that improved model performance. You're regularly sharing insights from industry conferences or research papers with the wider team, and these insights often lead to new projects.
