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ISG Research is happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Product Intelligence: ISG Research Buyers Guide is the distillation of a year of market and product research by ISG Research.
In today’s digital landscape, gaining insights into digital product representations through technology can be complex. The vast amounts of consumer interaction data generated can 
reveal performance metrics and growth opportunities. Digital reviews and advanced analytics quickly identify trends and address challenges, with product definitions serving as references for optimizing consumer guidance. A data-driven approach supports informed decisions and drives sustained digital growth.
ISG Research defines product intelligence as the digital practices and processes that optimize interactions between consumers and enterprise systems used for information and commerce. It provides tools for managing digital interactions through analytics and automation, utilizing AI and other techniques.
The evolution of product intelligence stems from over two decades of advancements in content and web analytics. These analytics have progressively supported the experimentation and testing of web content, transforming the digital representation of features and services to achieve optimal results. Initially, in the mid-1990s, websites relied on basic tracking methods using server logs to monitor user interactions, providing fundamental metrics like page views and unique visitors. These early tools offered minimal insights into user behavior. However, as the internet expanded, the demand for more sophisticated analytics grew, paving the way for solutions that incorporated product-focused metrics.
The launch of Google Analytics in the early 2000s marked a transformative shift, democratizing access to analytics tools. Although these tools provided significant improvements, they did not fully meet the needs for more advanced analysis. With the infusion of product intelligence, marketers gained the ability to analyze not just traffic sources and user demographics, but also digital product performance and user engagement on a deeper level within the context of user journeys. This integration of digital intelligence into web analytics frameworks has significantly evolved the field, allowing for more comprehensive and actionable insights.
The continued evolution of web analytics has been further enhanced by the emergence of AI and machine learning technologies, imbuing analytics processes with digital intelligence. These advancements enable predictive analytics, allowing businesses to foresee user behavior and optimize product offerings based on real-time data. Today, web analytics encompasses various techniques, including conversion rate optimization, A/B testing and multi-channel attribution. This comprehensive approach enables enterprises to make informed decisions regarding digital product and marketing strategies, enhancing user experiences and navigating the complexities of the online marketplace. Ultimately, this evolution has solidified web analytics as an essential tool for effective digital marketing and product management.
To enhance digital operations and drive growth in today’s data-driven environment, enterprises must strategically implement product intelligence. This involves adopting advanced platforms for real-time insights into consumer behavior and product performance. Product intelligence enables organizations to move beyond traditional analytics, providing a comprehensive understanding of user interactions and preferences for informed decision-making.
By 2028, one-third of enterprises will have invested in a common technological approach for product information management that is committed to product experiences and not just digital assets. Incorporating AI and machine learning into digital intelligence frameworks is crucial. 
These technologies enable predictive analytics, helping businesses anticipate customer needs and behaviors, which leads to personalized experiences and optimized product offerings. Techniques such as journey mapping, sentiment analysis and performance metrics enhance market understanding and improve strategies. Integrating digital intelligence increases enterprise agility, improves customer engagement and helps navigate the complexities of the digital landscape, securing a sustainable competitive advantage.
To thrive in this data-driven landscape, enterprises should invest in platforms that provide real-time insights and use methods like experimentation and testing for optimal performance. Moving beyond traditional metrics allows for a holistic view of user interactions, informing strategic decisions. By prioritizing AI and machine learning technologies, predictive analytics can better anticipate customer needs, enabling personalized experiences and optimized offerings. This comprehensive approach refines overall strategies, ultimately improving agility and enhancing consumer engagement.
Technology is essential for enterprises to effectively implement product intelligence in today’s digital, data-driven environment. With vast amounts of data generated across various channels, advanced platforms are necessary for real-time processing and analysis to ensure critical insights are not missed. AI and machine learning technologies enhance predictive analytics, enabling businesses to anticipate customer needs, create personalized experiences and optimize product offerings. Adopting technology is fundamental for extracting value from digital intelligence, improving customer engagement and maintaining a competitive edge in a complex digital landscape.
Optimizing product descriptions with SEO techniques and competitive pricing strategies will strengthen market positions. Utilizing AI and machine learning for predictive analytics will uncover new opportunities and mitigate risks. Structured product scorecards and digital dashboards will effectively measure performance, while insights from digital shelf analytics and sentiment analysis will enhance understanding of customer feedback. Integrating automated notification systems for real-time monitoring of compliance and product activity provides valuable insights for agile decision-making.
To harness product intelligence effectively, enterprises should take several strategic steps. First, they need to invest in advanced platforms that offer real-time insights into consumer behavior and digital interactions. Employing AI and machine learning technologies will enhance predictive analytics capabilities, allowing businesses to better anticipate consumer needs. Implementing journey mapping techniques will help gain a comprehensive understanding of user interactions and preferences. Focusing on personalization will enable organizations to create tailored experiences based on insights gathered from data analysis. It is also essential to enhance product data governance to ensure clean, accurate and compliant data practices, maximizing the value of product intelligence. Finally, providing technology that meets the diverse needs of product and technology professionals is crucial for guiding operations and informed decision-making. By following these steps, enterprises can improve digital engagement, adapt to market changes and achieve a sustainable competitive advantage.
The ISG Buyers Guide™ for Product Intelligence evaluates software providers and products in key areas that require support for digital representation of what we call product intelligence, and underlying support in content and data management, support for integration into digital systems, and the support for analyst, product managers, operations and administrative roles. Examination of digital innovation and investment were examined.
This research evaluates the following software providers that offer products that address key elements of product intelligence as we define it: Adobe, Amplitude, Contentsquare, Fullstory, Gainsight, Glassbox, MixPanel, Pendo, QuantumMetric and Sensor Tower.
This research-based index evaluates the full business and information technology value of product intelligence software offerings. We encourage you to learn more about our Buyers Guide and its effectiveness as a provider selection and RFI/RFP tool.
We urge organizations to do a thorough job of evaluating product intelligence offerings in this Buyers Guide as both the results of our in-depth analysis of these software providers and as an evaluation methodology. The Buyers Guide can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP and the definition of an RFI.
The Buyers Guide for Product Intelligence in 2025 finds Pendo first on the list, followed by Amplitude and Quantum Metric.
Software providers that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader.
The Leaders in Product Experience are:
- Pendo.
- Amplitude.
- Quantum Metric.
The Leaders in Customer Experience are:
- Amplitude.
- Adobe.
- Contentsquare.
- Pendo.
The Leaders across any of the seven categories are:
- Amplitude, which has achieved this rating in six of the seven categories.
- Pendo in five categories.
- Adobe and Quantum Metric in three categories.
- Gainsight, Glassbox, Contentsquare and Mixpanel in one category.
The overall performance chart provides a visual representation of how providers rate across product and customer experience. Software providers with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, providers that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as providers of “merit.” Software providers that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating.
Note that close provider scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every enterprise or process. Although there is a high degree of commonality in how organizations handle product intelligence, there are many idiosyncrasies and differences that can make one provider’s offering a better fit than another.
ISG Research has made every effort to encompass in this Buyers Guide the overall product and customer experience from our product intelligence blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which software provider and products best fit an enterprise’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects.
You can find more details on our community as well as on our expertise in the research for this Buyers Guide.
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