Brandon   Purcell

Brandon Purcell

Principal Analyst Serving Customer Insights Professionals

Brandon serves Customer Insights Professionals, covering customer analytics and artificial intelligence. His work helps organizations derive meaningful insights from customer data to attract and retain customers, increase customer loyalty and profitability, and inform product development and service delivery. His research agenda includes customer analytics and artificial intelligence strategy, innovation and best practices, skill development, and vendor evaluation.

Previous Work Experience

Prior to joining Forrester, Brandon led the data science team at a boutique consulting firm, helping marketers derive actionable insights from their customer and marketing data. As a data scientist, Brandon employed advanced customer analytics techniques such as predictive modeling and text analytics to address his clients’ business challenges. His engagements included helping a large retail bank develop a voice-of-the-customer program and creating a patented predictive location algorithm using geospatial data from mobile devices. His extensive analyses of the Consumer Financial Protection Bureau’s Consumer Complaint Database have been featured in Bloomberg, Forbes, and The Financial Brand.

Brandon spent many years as a financial specialist on the floors of the American Stock Exchange and Chicago Board Options Exchange. He also spent two years as a Peace Corps volunteer teaching English in the Republic of Benin in West Africa.

Education

Brandon holds an MBA from the Haas School of Business at U.C. Berkeley and a B.A. in English and creative writing from Dartmouth College.

Brandon Purcell

Principal Analyst Serving Customer Insights Professionals

Brandon serves Customer Insights Professionals, covering customer analytics and artificial intelligence. His work helps organizations derive meaningful insights from customer data to attract and retain customers, increase customer loyalty and profitability, and inform product development and service delivery. His research agenda includes customer analytics and artificial intelligence strategy, innovation and best practices, skill development, and vendor evaluation.

Previous Work Experience

Prior to joining Forrester, Brandon led the data science team at a boutique consulting firm, helping marketers derive actionable insights from their customer and marketing data. As a data scientist, Brandon employed advanced customer analytics techniques such as predictive modeling and text analytics to address his clients’ business challenges. His engagements included helping a large retail bank develop a voice-of-the-customer program and creating a patented predictive location algorithm using geospatial data from mobile devices. His extensive analyses of the Consumer Financial Protection Bureau’s Consumer Complaint Database have been featured in Bloomberg, Forbes, and The Financial Brand.

Brandon spent many years as a financial specialist on the floors of the American Stock Exchange and Chicago Board Options Exchange. He also spent two years as a Peace Corps volunteer teaching English in the Republic of Benin in West Africa.

Education

Brandon holds an MBA from the Haas School of Business at U.C. Berkeley and a B.A. in English and creative writing from Dartmouth College.

Brandon Purcell's Research

Most RecentMost Popular
  • For CIO Professionals

    REPORT: Emerging Technology Spotlight: Computer Vision

    Computer Vision Gives Machines The Gift Of Sight

    December 10, 2018Brandon Purcell, Kjell Carlsson, Ph.D.

    Thanks to massive training data sets, deep neural networks, and graphics processing units (GPUs), computers can now accurately identify objects and features in images and video. CIOs and business technology leaders should read this report to understand how they can leverage computer vision for security, social media monitoring, marketing asset management, manufacturing, and myriad other use cases involving the classification of unstructured image data.

  • For Customer Insights Professionals

    REPORT: The State Of Customer Analytics 2018

    Benchmarks: The Customer Analytics Playbook

    December 4, 2018Brandon Purcell, Emily Miller

    To assess the state of analytics adoption, including goals, challenges, and analytics sophistication, Forrester and Burtch Works fielded an online survey to 144 North American analytics and measurement pros. In this report, we give customer insights (CI) pros key benchmarks to plan their customer analytics capability. Compared with our 2017 benchmarks, we see firms adopting more predictive analytics techniques for deeper customer understanding. We also uncovered three levels of analytics sophistication — leaders, followers, and laggards — and continue to see increasing analytics maturity.

  • For CIO Professionals

    REPORT: Predictions 2019: Artificial Intelligence

    No Pain, No Gain With Enterprise AI

    November 6, 2018 Michele Goetz, Brandon Purcell, Craig Le Clair, Diego Lo Giudice, Mike Gualtieri

    Your enterprise AI journey is going to be a rollercoaster. You want immediate rewards from AI but realize the risks. You will overcome your cautious cynicism by overplanning. You'll dive in anyway and dabble. You'll make rookie mistakes. You will think of quitting. But you'll strive on to reap tangible benefits and bragging rights. In the last couple of years, we've seen firms learn to fail fast with AI initiatives, but 2019 will bring a more refined approach to going after the AI opportunity. CIOs: Read the five predictions that will guide your data, talent, automation, governance, and machine learning (ML) decisions.

  • For Customer Insights Professionals

    REPORT: Evoke Trust With Explainable AI

    Balance Transparency With Accuracy To Increase Stakeholder Adoption And Mitigate Risk

    November 1, 2018Brandon Purcell, Rob Koplowitz, Christopher McClean

    The promise of AI is rapidly materializing; however, not all AI is created equal. Some machine learning algorithms are transparent, allowing brands to see how they make decisions, while others are opaque, obscuring the inner logic of models. Still others are transparent yet so convoluted that the results are not easily explainable. This report highlights the evolving area of explainable AI and how customer insights (CI) pros should consider the tradeoffs in risk, accuracy, and applicability when they determine the level of explainability in AI.

  • For Application Development & Delivery Professionals

    REPORT: What Software Developers Don't Know About Neural Networks Could Hurt Them

    How To Balance The Risks And Benefits Of This Powerful Technology

    November 1, 2018 Rob Koplowitz, Brandon Purcell, Christopher McClean

    The promise of AI is rapidly materializing. Capabilities once available only to data scientists are now easily accessible by app developers. The results are compelling, but they also come with risk. Developers must approach opaque AI models like neural networks that cannot reveal the logic behind a decision or insight with caution — and with support from risk and compliance pros. Application development and delivery (AD&D) pros should read this report to learn how to balance risk and reward with these powerful deep learning techniques.

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