Customer Intelligence Lab

We research how companies can use customer data and artificial intelligence to improve outcomes for themselves, their customers, and society at large.

Leadership

Ayelet Israeli

Ayelet Israeli

Marvin Bower Associate Professor

Harvard Business School

Ayelet's research focuses on the value of data and AI for business decision-making, with an emphasis on how firms can leverage their own data, customer data, and market data to improve outcomes. She translates cutting-edge research into actionable business strategies.

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Eva Ascarza

Eva Ascarza

Professor of Business Administration

Harvard Business School

Eva's research focuses on customer retention, personalization, and the role of AI in marketing. She is particularly interested in algorithmic bias and how companies can use data to better understand and serve their customers.

Personal Website ā†’

Our Mission

The Customer Intelligence Lab advances the scientific understanding of customer data and artificial intelligence in business. Through rigorous empirical research and methodological innovation, we develop frameworks for causal inference, experimentation, and machine learning that enable firms to optimize customer interactions while addressing critical questions of fairness, privacy, and social welfare. Our work is conducted in collaboration with organizations across sectors including technology, retail, and telecommunications.

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Value of Data and AI

Quantifying ROI of data and AI investments and GenAI applications in marketing decision-making

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Impact of Marketing Actions

Measuring ROI and causal effects at scale using advanced experimentation and causal inference methods

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Personalization and Experimentation

A/B testing, ML-driven targeting, and personalization strategies for customer engagement

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Customer Management

Customer journey optimization, CLV modeling, and retention strategies across touchpoints

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Responsible AI

Fairness, privacy protection, and trust in customer-facing AI systems

Research

We work at the intersection of marketing, data science, and artificial intelligence. Click on each topic below to view our publications.

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Value of Data and AI

What is the ROI of investing in data analytics and AI? How can companies leverage AI to make better marketing decisions? What types of data and analytical approaches create the most business value?

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Learning from Many Experiments: A Hierarchical Bayesian Framework

Ebbes, P., Ascarza, E., & Netzer, O.

2026

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Using LLMs for Market Research

Brand, J., Israeli, A., & Ngwe, D.

2025

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Incrementality Prediction: Synergizing Past Experiments

Huang, T., Ascarza, E., & Israeli, A.

2025

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Pricing with Bandits in the Long-tail

Israeli, A., & Anderson, E.

2025

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Learning When to Quit in Sales Conversations

Manzoor, E., Ascarza, E., & Netzer, O.

2025

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Canary Categories

Anderson, E., Chen, C., Israeli, A., & Simester, D.

2024

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The Customer Journey as a Source of Information

Padilla, N., Ascarza, E., & Netzer, N.

2024

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The Value of Descriptive Analytics

Berman, R., & Israeli, A.

2022

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How Market Power Affects Dynamic Pricing

Israeli, A., Scott Morton, F., Silva-Risso, J., & Zettelmeyer, F.

2022

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Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

Padilla, N., & Ascarza, E.

2021

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Impact of Marketing Actions

What marketing interventions work best? How can companies measure and predict the incremental impact of their marketing campaigns? How do we optimize marketing spend across different channels and customer segments?

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Doing More With Less: Strategic Marketing Interventions

Huang, T., & Ascarza, E.

2024

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Incrementality Prediction: Synergizing Past Experiments

Huang, T., Ascarza, E., & Israeli, A.

2025

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Improving Targeting with Privacy-Protected Data

Huang, T., & Ascarza, E.

2025

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Personalization and Experimentation

How can firms design effective experiments to test personalization strategies? What targeting policies maximize customer value? How do we learn from past experiments to improve future targeting decisions?

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Learning from Many Experiments: A Hierarchical Bayesian Framework

Ebbes, P., Ascarza, E., & Netzer, O.

2026

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Dynamic Personalization with Multiple Customer Signals

Ma, L., Huang, T., Ascarza, E., & Israeli, A.

2025

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Incrementality Prediction: Synergizing Past Experiments

Huang, T., Ascarza, E., & Israeli, A.

2025

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Protected Heterogeneity: A Variance-Based Framework

Ahmadi, N., Ascarza, E., & Israeli, A.

2025

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Policy-Aware Experimentation

Chen, Y., Ascarza, E., & Netzer, O.

2025

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Improving Targeting with Privacy-Protected Data

Huang, T., & Ascarza, E.

2025

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Personalization and targeting: how to experiment, learn & optimize

Lemmens, A. et al.

2025

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Personalized Game Design for Improved User Engagement

Ascarza, E., Netzer, O., & Runge, J.

2025

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Doing More With Less: Strategic Marketing Interventions

Huang, T., & Ascarza, E.

2024

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Customer Management

How do companies retain valuable customers? What drives customer engagement and lifetime value? When should firms intervene in the customer journey, and what actions are most effective?

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Learning When to Quit in Sales Conversations

Manzoor, E., Ascarza, E., & Netzer, O.

2025

View Paper ā†’

Learning from Many Experiments: A Hierarchical Bayesian Framework

Ebbes, P., Ascarza, E., & Netzer, O.

2026

View Paper ā†’

Dynamic Personalization with Multiple Customer Signals

Ma, L., Huang, T., Ascarza, E., & Israeli, A.

2025

View Paper ā†’

Improving Targeting with Privacy-Protected Data

Huang, T. & Ascarza, E.

2025

View Paper ā†’

Policy-Aware Experimentation

Chen, Y., Ascarza, E., & Netzer, O.

2025

View Paper ā†’

Incrementality Prediction: Synergizing Past Experiments

Huang, T., Ascarza, E., & Israeli, A.

2025

View Paper ā†’

Personalized Game Design for Improved User Engagement

Ascarza, E., Netzer, O., & Runge, J.

2025

View Paper ā†’

The Customer Journey as a Source of Information

Padilla, N., Ascarza, E., & Netzer, N.

2024

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Doing More With Less: Strategic Marketing Interventions

Huang, T., & Ascarza, E.

2024

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Detecting Routines in Customer Behavior

Dew, R., Ascarza, E., Netzer, O., & Sicherman, N.

2023

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Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach

Padilla, N., & Ascarza, E.

2021

View Paper ā†’
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Responsible AI

How do we ensure AI systems are fair and unbiased? What privacy protections should companies implement? How can firms use customer data ethically while still delivering personalized experiences?

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Improving Targeting with Privacy-Protected Data

Huang, T., & Ascarza, E.

2025

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Protected Heterogeneity: A Variance-Based Framework

Ahmadi, N., Ascarza, E., & Israeli, A.

2025

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In Privacy We Trust: The Effect of Privacy Regulations

Demirci, O., Israeli, A., & Ascarza, E.

2025

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Eliminating Unintended Bias in Personalized Policies Using Bias Eliminating Adapted Trees (BEAT)

Ascarza, E., & Israeli, A.

2022

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In the Media

Our research featured in leading business publications

Harvard Business Review

Most AI Initiatives Fail. This 5-Part Framework Can Help

Using Gen AI for Early-Stage Market Research

Should Your Company Sell on Amazon? Reach Comes at a Price

Why You Aren't Getting More from Your Marketing AI

When A/B Testing Doesn't Tell You the Whole Story

Pricing Policies that Protect Your Brand

HBS Working Knowledge

Navigating Consumer Data Privacy in an AI World

Can AI Predict Whether Shoppers Would Pick Crest or Colgate?

Is AI Coming for Your Job?

When Bias Creeps Into AI, Managers Can Stop It

Identify Great Customers from Their First Purchase

Beyond Pajamas: Sizing Up the Pandemic Shopper

Other Outlets

Guinea pigbots

Science

Marketing With Generative AI

Me, Myself, and AI Podcast | MIT Sloan Management Review

Our Team

Co-Directors

Ayelet Israeli

Marvin Bower Associate Professor

Harvard Business School

HBS Profile ā†’

Eva Ascarza

Professor of Business Administration

Harvard Business School

HBS Profile ā†’

Lab Members

Isamar Troncoso

Assistant Professor

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Madhav Kumar

Assistant Professor

Website ā†’

Poet Larsen

Postdoctoral Fellow

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Liangzhong Ma

PhD Student

Profile ā†’

Zhongming Jiang

PhD Student

Profile ā†’

Noah Ahmadi

PhD Student, MIT Sloan

Profile ā†’

Victoria Zhang

Predoctoral Fellow

LinkedIn ā†’

Xiaowei Guo

Predoctoral Fellow

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