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Market intelligence software collects, analyzes, and shares information about markets, competitors, and customers from internal and external sources. Most enterprise teams already hold plenty of that information, yet a business question can still end with an email to the insights team and a wait for the answer.
Choosing a platform is harder now that general AI assistants can summarize almost any document, which blurs the line between a general tool and a market intelligence platform. This guide defines the category, separates the types of solutions, and gives you eight criteria and a five-step evaluation method that work whichever software you use today. It also states what market intelligence software does not solve.
Short answer: Market intelligence software collects, analyzes, and shares information about markets, competitors, and customers from internal and external sources. A market intelligence platform should add governed access, provide answers that cite their sources, proactively monitor data and trigger actions. Key capabilities to evaluate are compare source coverage, traceability, governance, fit with your AI tools, proactive analysis and monitoring, ease of adoption, and proof of value.
What is market intelligence software?
Market intelligence software comprise a category of tools that gather information from internal and external sources, analyze it, and then deliver insights that prompt action to the people who make strategy, product and go to market (GTM) decisions. It covers competitors, customers, categories, and trends, rather than only the operating data a company produces itself.
Gartner defines the category as Competitive and Marketing intelligence solutions that ‘enable organizations to systematically tather, analyze and act on actionable insights about industries, companies, products, competitors and topics from diverse internal and external sources.’
Three neighboring terms cause most of the confusion. Business intelligence mainly reports on internal data such as sales and finance. Pure competitive intelligence concentrates on rivals in isolation, and this explanation of how market intelligence differs from competitive intelligence shows where the two overlap. Market research produces studies on a defined question, and market insights are the conclusions teams draw from that research and other evidence, as described in what market insights are and how teams use them. Market intelligence software sits across all three: it connects the studies, subscriptions, and news feeds an organization already has, so people can ask questions across them.
Which type of market intelligence solution fits your need?
Five types of solutions answer market questions today: general AI assistants, knowledge repositories, custom builds on a general language model, monitoring tools, and specialized market intelligence platforms. They differ in sources, citations, and control, so the right choice depends on the questions you must answer and the evidence those answers require.
| Type of solution | Suited for | Where it typically falls short |
|---|---|---|
| General AI assistant, for example Microsoft Copilot or ChatGPT | Drafting, summarizing, and answering broad questions in tools people already use | Answers depend on what the assistant can reach, so check whether citations, source dates, and access to licensed research are included |
| Knowledge repository or research library | Storing and finding the reports your organization owns | Search may be keyword based, may cover only uploaded content, and may not watch for external change |
| Custom build on a general language model | Teams with engineering capacity and a narrow, well-defined use case | Connectors, evaluation, security reviews, and updates become your ongoing work |
| Monitoring or alerting tool | Tracking news, websites, and competitor activity | Delivers alerts, but may not connect them to internal research or explain what they mean |
| Specialized market intelligence platform | Analysis and questions that bring torgether internal research, licensed sources, and external news together, with citations and permissions | Needs setup, source licenses, and adoption effort, and its coverage depends on what you connect |
The types are not exclusive. Many organizations keep a general assistant for everyday tasks and add a specialized platform for market questions.
How do market intelligence platforms differ from generic AI tools?
The differences come down to three things: sources, traceability, and governance. A generic AI assistant answers from what it was trained on or can reach. A market intelligence platform should answer from sources an organization has curated and licensed, show where each answer came from, and apply the organization’s access rules.
Sources
Market questions rarely depend on public web text alone. They depend on the organization’s own studies, syndicated data subscriptions, and recent news. A platform is useful to the extent that it can read those sources in their original formats and keep them current.
Traceability and Weighted Evidence
A market decision needs to know which source an answer came from, how recent it is, and whether sources disagree. Citations that point to a passage let a reader check a claim against its source instead of trusting fluent text.
Governance
Research licenses and sensitive internal findings come with access rules. Look for a platform that carries existing permissions through, and ask in writing whether your content is used to train any model. Hormel Foods, for example, required that AI recommendations be grounded in its trusted, proprietary data rather than generic language model content, according to the Hormel Foods case study.
This is not a choice between a general assistant and a platform. The Model Context Protocol (MCP) lets compatible AI assistants call an outside system when they need information, so a general assistant can handle the task while a market intelligence platform supplies cited evidence. Our guide to specialized AI for market intelligence and insights covers the capability test in more depth.
Eight criteria for evaluating a market intelligence platform
Evaluate a platform on eight criteria: source coverage, cited answers, governance and permissions, fit with existing AI tools, proactive monitoring, usability and adoption, time to value and proof, and build versus buy effort. For each criterion, ask the question below, compare the answer with what good looks like, and watch for the red flag.
| Criterion | Question to ask | What good looks like | Red flag |
|---|---|---|---|
| 1. Source coverage | Which internal and external sources can the platform read, in which formats, and who maintains the connections? | Your research archive, licensed syndicated data, and external news in one place, with coverage limits stated | Coverage claims without a named source list, or connections you must build and maintain yourself |
| 2. Cited and traceable answers | Can I move from any statement to the exact source, and does the answer show recency and conflicting findings? | Every answer cites its sources, shows dates, and flags where sources disagree | Fluent answers with no citation, or citations that point to a general index instead of a passage |
| 3. Governance and permissions | How are access rights handled, and is our proprietary research used to train any model? | Existing permissions carry through, central control sits with insights and IT, and the vendor answers the training question in writing | Vague answers about training data, or a separate permission set to maintain |
| 4. Fit with existing AI tools | Can Microsoft Copilot, ChatGPT, Claude, or our own agents call the platform, and do permissions and citations carry through? | Connection through open standards such as MCP, with citations intact in the other tool | Every question requires users to leave the AI tools they already use |
| 5. Proactive analysis and monitoring | Does the platform watch for market change on its own, or only answer when asked? | Topic and industry monitoring that summarizes what changed, configurable by team | Keyword alerts with no interpretation, or dashboards someone must check manually |
| 6. Usability and adoption | Can a business user get a reliable answer without an insights specialist, and what onboarding is provided? | Plain-language questions, role-specific onboarding, and usage data you can track | Training needed before first value, or usage limited to a few power users |
| 7. Time to value and proof | What evidence shows value in a comparable organization, and how soon can we start using it? | Named references in your industry, independent studies with a disclosed method, and a trial or scoped pilot | Round-number claims without a source, or no reference you can speak with |
| 8. Build versus buy effort | What would it take to build and maintain this ourselves, including connectors, evaluation, and governance? | A realistic estimate of connector upkeep, security reviews, and updates | Comparing a vendor price with an unbuilt prototype |
Weight the criteria by what your decisions require. A team that works mostly in Microsoft Copilot will weight criterion four higher, and a team in a regulated industry will weight criterion three higher. Source coverage deserves the first conversation, because every later criterion depends on it. This overview of how different data sources drive market knowledge explains primary, secondary, third-party, and open sources and how to judge their reliability.
How do you run the evaluation?
Run the evaluation in five steps: write down your real questions, test every vendor on the same questions, involve security, legal, and procurement early, build the business case, and plan adoption before you sign. Two customer examples below show how enterprises handled these steps.
Step one: write down your real questions
Collect five real questions from your stakeholders, including at least one where internal research and external sources may disagree. Use the same questions with every vendor.
Step two: test on your own content
Ask each vendor to answer your questions over a sample of your own research, not a demonstration data set. For each answer, check whether it cites a specific passage, shows a date, and flags conflicting evidence.
Step three: involve security, legal, and procurement early
Mars launched DeepSights by Market Logic Software, a market and competitive intelligence platform, only after an eight-month approval process. According to the Mars case study, the process included a security and architecture review, a project charter, alignment with IT, legal, and procurement, and a review by the Mars Responsible AI Council. Mars also wanted confirmation that the underlying model would not be trained on any data from its knowledge base.
Step four: build the business case
Novartis developed a business case and value proposition before approaching its procurement team, outlining how DeepSights by Market Logic Software would reduce primary market research spend. Novartis reports a $30 million annual research spend reduction by eliminating duplicate research investments, and two hours saved by the insights team in answering major research queries. These are customer-reported results and will not transfer unchanged to every organization.
Step five: plan adoption before you sign
Adoption is where many programs stall, so agree who owns onboarding, which teams start first, and how usage will be measured. Mars reports that its insights engagement score increased by 60% within its market intelligence platform since the release of DeepSights by Market Logic Software..
What market intelligence software does not solve
Market intelligence software does not replace human judgment, or fix a weak insights process. Its output is only as good as the sources and quality of research information connected to it. While a platform can identify market insights early, leaders in marketing, brand, product and strategy will still need to apply their professional expertise to translating those insights that deliver clear business impact. Know these limits before you buy.
- Source dependence. A platform cannot answer from research you have not connected or licensed. Gaps in coverage become gaps in answers.
-
Judgment. AI analysis, summaries and syndicated findings will still need a senior insights leader and business professional to review before making
forhigh-stakes decisions, especially where underlying sources conflict. - Adoption. Access is not use. Without onboarding and owners, usage can stay with a few specialists.
- Synthetic research. Leading brands including Hormel Foods and Philips treats synthetic personas as a complement to human consumer research, not a replacement. for real consumers.
- The role of general AI. A general assistant remains useful for drafting, summarizing, and everyday tasks. A specialized platform adds value where market decisions need cited, governed evidence.
For the approach to work, four things must be true: a named owner, current and licensed sources, permissions that match your organization, and success measures agreed before launch.
How does DeepSights approach these criteria?
DeepSights by Market Logic Software is built for insights teams and business users. Market Logic describes it as connecting internal research, syndicated sources, and public news, with answers tied to evidence. The notes below map it to the eight criteria.
- Sources and traceability (criteria one and two). Market Logic describes the platform as bringing internal research, syndicated providers, and public news together, with answers that link back to the underlying evidence. See the DeepSights platform overview.
- Governance and fit with AI tools (criteria three and four). DeepSights MCP by Market Logic Software connects the platform to MCP-compatible assistants such as Microsoft Copilot, ChatGPT, Claude, and Glean, and Market Logic states that every call is checked against the DeepSights permissions of the caller.
- Proactive analysis and monitoring (criterion five). DeepSights Radar uses AI agents to track topics and industries and highlight what changed.
- Adoption and proof (criteria six and seven). The Mars and Novartis results above are customer-reported. The Forrester Total Economic Impact study (July 2025) of DeepSights by Market Logic Software is based on five decision-makers at four customer organizations. Its reported figures are listed after these notes.
- Build versus buy (criterion eight). Ask Market Logic Software for implementation effort and timelines in writing, and compare them with your internal estimate.
Forrester Total Economic Impact figures for DeepSights by Market Logic Software, as reported in the study:
- 411% ROI over three years. Source: Forrester Total Economic Impact Study (2025)
- 97% reduction in time to answer insights requests. Forrester TEI, based on 10,800 requests per year
- 27% reduction in market research expenditure. Forrester TEI Study (2025)
Market Logic Software has been positioned as a Visionary in the 2026 Gartner Magic Quadrant for Competitive and Market Intelligence Platforms. In our view, Gartner’s analysis highlights a shift away from general-purpose AI tools toward purpose-built competitive and market intelligence platforms for high-stakes decisions. Read more on the Gartner Magic Quadrant position page.
Choose on evidence, then test on your own questions
Market intelligence software earns its place when it gives a business user an answer that cites its sources, respects access rules, and arrives in the tools the team already uses. Score your shortlist on the eight criteria, test every vendor on the same five questions, and involve security, legal, and procurement early. To see how DeepSights by Market Logic Software performs on your own questions, request a demo.
Frequently asked questions
What is market intelligence software, and which platforms support it?
What should you look for in market intelligence software?
Is there a difference between market intelligence software, platforms, and tools?
What makes a good market intelligence platform?
How is a market intelligence platform different from ChatGPT or Microsoft Copilot?
Can a market intelligence platform work inside Microsoft Copilot or ChatGPT?
How do you check that a platform's answers are trustworthy?
What is the difference between market intelligence software and competitive intelligence software?
How do you shortlist market intelligence platforms for an enterprise or an industry such as pharma?
Gartner, Magic Quadrant for Competitive & Market Intelligence Platforms, Rahim Kaba, Chris Meering, Ethan Budgar, Dan Tolan, 21 April 2026. Gartner and Magic Quadrant are trademarks of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose.
