Mary Alfheim, VP of Data & Analytics at Scribd, Inc.
- James Pepper
- Feb 19
- 5 min read
Updated: Mar 4
We sat down with Mary Alfheim, VP of Data & Analytics at Scribd, Inc., to discuss her career journey, the evolving role of data in business, and the intersection of analytics, leadership, and creativity.
DE: With over 15 years of experience in data and analytics, how has your perspective on the role of data in driving business success evolved over time?
MA: My perspective on data’s role in business success has evolved dramatically alongside technological advancements and shifting business priorities. Early in my career, data was primarily seen as a reporting mechanism—a way to track key metrics and generate dashboards for leadership. The focus was on historical reporting, which, while still valuable, often led to reactive insights. As an early data scientist, I spent much of my time here, interspersed with occasional predictive work, such as basic propensity models or media mix models that were updated sporadically.
As businesses began recognising the value of data, the conversation shifted from simple reporting to data-driven decision-making. Data became a strategic enabler. I witnessed the rise of self-service analytics, cloud-based platforms, and AI-driven insights. My role expanded from generating reports to fostering data-driven cultures, ensuring teams could trust, interpret, and act on insights in real time.
Today, I see data as more than an enabler—it is a core differentiator. Companies leveraging advanced analytics, machine learning, and real-time decision intelligence are outperforming those relying on intuition. The best businesses don’t just collect data; they use it to predict, personalise, and innovate.
Additionally, data ethics, governance, and AI responsibility have become critical discussions. As a leader, I prioritise data trustworthiness, security, and bias mitigation as much as I do insights and automation.
DE: As part of Scribd, Inc., what has been your most rewarding challenge in transforming complex data into actionable strategies?
MA: Scribd operates at the intersection of content, user behaviour, and engagement analytics. With millions of users consuming books, audiobooks, documents, and more, the challenge was to move beyond surface-level metrics and uncover deep behavioural insights that unlock new user experiences.
This challenge is incredibly fulfilling because it’s not just about optimising numbers—it’s about creating a more immersive, user-centric platform. Our users have distinct motivations: some are students creating study materials, others are professionals drafting presentations, and some simply seek entertainment in the latest bestseller. Understanding these motivations allows us to tailor experiences to their specific needs.
The ability to bridge data science with storytelling and content accessibility has had a tangible impact. Seeing how these insights translate into business success has been one of the most rewarding aspects of my career at Scribd. Ultimately, this experience reinforces my belief that data isn’t just about numbers—it’s about understanding human behaviour and creating meaningful, scalable experiences.
DE: What are the key traits a leader in data analytics needs to succeed in today’s competitive landscape?
MA: The role of a data leader has evolved beyond number crunching—today, it’s about orchestrating data-driven transformation across an organisation. Here are the key traits I consider essential:
Visionary Thinking & Strategic Alignment: A data leader must connect insights to business strategy. Instead of just answering “what happened,” they must anticipate what’s next and influence decisions accordingly. Key questions to ask include:
How does this insight drive revenue, retention, or efficiency?
How can data improve customer experience and personalisation?
Are we solving the right business problems with data?
Strong Storytelling & Communication Skills: Data alone doesn’t drive action—compelling narratives do. Translating complex analytics into clear, impactful stories influences stakeholders and fosters a data-driven culture.
Technical & Analytical Mastery: While leaders don’t need to code every model, they must stay fluent in modern data technologies, including:
AI & Machine Learning for predictive insights
Cloud & Big Data Platforms for scalable infrastructure
Data Governance & Privacy for trust and compliance
Data-Driven Culture & Influence: Success isn’t just about technology—it’s about empowering teams. Leaders must:
Foster a culture of experimentation and learning
Champion data literacy across all departments
Ensure teams trust and use data in decision-making
Adaptability & Continuous Learning: The data landscape evolves rapidly, from AI advancements to new regulations like GDPR. Leaders must remain curious and adaptable.
Ethical Responsibility & Data Governance: AI and automation bring ethical challenges. Leaders must prioritise:
Bias mitigation in AI models
Transparency in decision-making
Privacy and security to maintain user trust
The best leaders don’t just manage data—they drive transformation, innovation, and business impact. And we don’t have to do it alone! Data leaders should engage with peers, ask for guidance, and share insights to stay at the cutting edge.
DE: What’s your approach to using data to enhance customer engagement and retention at Scribd?
MA: We leverage data to create personalised, frictionless, and value-driven experiences across our brands. Our approach includes:
Behavioural Insights: Analysing past interactions, session lengths, and drop-off points helps us optimise user journeys. We track metrics like content discovery rates, session duration, and conversion rates to measure success.
Predictive Analytics for Retention: We use machine learning to identify at-risk users before they churn, activating insights through recommendations, notifications, and personalised outreach.
Content Strategy: We analyse completion rates, bookmarks, and reader sentiment to determine what content resonates most with users, providing valuable insights to content partners.
UX Enhancements: Continuous A/B testing ensures seamless reading experiences, improving navigation and audiobook interaction.
DE: How do you simplify and communicate complex data insights to non-technical stakeholders?
MA: My approach centres on storytelling, actionable recommendations, and collaboration:
Storytelling: Spreadsheets don’t inspire action—stories do. Instead of stating, “Users with app bugs churn at twice the rate,” I might tell a story: “Imagine a mystery novel lover who reads daily but experiences app issues. They disengage. We can prevent this by doing X, Y, and Z.”
Actionable Recommendations: Data without direction leads to paralysis. Every insight includes a proposed action step to initiate discussion.
Driving Collaboration: If teams don’t trust or understand data, they won’t use it. We promote self-service tools and co-create solutions with stakeholders to foster confidence in data-driven decision-making.
DE: Looking ahead, how do you see the role of data analytics evolving in industries focused on customer engagement and digital products?
MA: I see data analytics becoming even more central, driving real-time intelligence, hyper-personalisation, and AI-driven automation. Future success will depend on:
Real-time decision intelligence
Ethical AI and data governance
Customer-centric, data-driven product development
A balance between data-driven decision-making and creative intuition
That said, the industry will continue to evolve in unexpected ways. The key is to remain adaptable, open to new approaches, and committed to both innovation and ethical responsibility.
Final Thoughts…
DE: What advice would you give to professionals aspiring to a career in data and analytics?
MA: You’ve likely heard the advice to master the fundamentals, stay curious, and build your network. I’d emphasise one more thing: storytelling. Data is only valuable when it drives action. Work on communication, design compelling data visualisations, and tailor your messaging for different audiences. And most importantly—stay curious!
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