1,589 pieces of content. 9 buyer personas. 25 product intelligence rubrics. 158 themes that connect what a buyer cares about to what they should read next.
AI agents can reason, synthesise and act — but when they go looking for content to inform a research journey, they hit a wall. Thousands of assets with no structured signal about who they're for, what stage they serve, or which priorities they address. Content Compass is the bridge.
No persona signal. No stage awareness. No play alignment. Generic results for a specific need.
Recommendations customised to your priorities — not a list of results, but a structured research journey built around three dimensions of what matters to you.
Themes are the secret sauce — the connective tissue between what a buyer says and what content will actually matter to them.
158 themes mapped across 9 personas and 25 product intelligence rubrics. Each theme is a bridge — connecting what a buyer cares about to the plays that address it and the content that proves it. The rubric isn't keywords. It's structured intelligence.
Every piece of content is evaluated against the rubrics and assigned scores for persona fit, journey stage, and product alignment. Those scores power every recommendation.
Every journey follows a progressive arc — from awareness to proof to evaluation. The system detects where a buyer is and adjusts accordingly. While today we offer a focused set of journeys, customers and their agents can tailor the arc to their own priorities, timelines, and ways of working.
BUILT FOR 9 PERSONAS
The Content Compass 1.0 solution is the product of nine months of research, experiments and pilots. What you're seeing today — this agentic experience — was built from scratch in four days with Claude. Two very different timelines. One intelligence layer.
Adobe has thousands of GTM practitioners making content strategy decisions every day — and so are their agents. GTM Strategy partnered with Experience Intelligence to build a universal intelligence layer for both: humans and agents making better, faster, more consistent decisions at scale.
We built this for internal agents. Now we’re asking: can it serve external agents too? We don’t have the answer — and we want to hear yours.
Intelligent recommendations are only partly about scoring. The rest is judgment — choices about what matters, what to fix, and what comes next. Here are the ones that shaped Content Compass.
1,589 pieces of content. 9 buyer personas. 25 product intelligence rubrics. 158 themes that connect what a buyer cares about to what they should read next.
AI agents can reason, synthesise and act — but when they go looking for content to inform a research journey, they hit a wall. Thousands of assets with no structured signal about who they're for, what stage they serve, or which priorities they address. Content Compass is the bridge.
No persona signal. No stage awareness. No play alignment. Generic results for a specific need.
Recommendations customised to your priorities — not a list of results, but a structured research journey built around three dimensions of what matters to you.
Themes are the secret sauce — the connective tissue between what a buyer says and what content will actually matter to them.
158 themes mapped across 9 personas and 25 product intelligence rubrics. Each theme is a bridge — connecting what a buyer cares about to the plays that address it and the content that proves it. The rubric isn't keywords. It's structured intelligence.
Every piece of content is evaluated against the rubrics and assigned scores for persona fit, journey stage, and product alignment. Those scores power every recommendation.
Every journey follows a progressive arc — from awareness to proof to evaluation. The system detects where a buyer is and adjusts accordingly. While today we offer a focused set of journeys, customers and their agents can tailor the arc to their own priorities, timelines, and ways of working.
BUILT FOR 9 PERSONAS
The Content Compass 1.0 solution is the product of nine months of research, experiments and pilots. What you're seeing today — this agentic experience — was built from scratch in four days with Claude. Two very different timelines. One intelligence layer.
Adobe has thousands of GTM practitioners making content strategy decisions every day — and so are their agents. GTM Strategy partnered with Experience Intelligence to build a universal intelligence layer for both: humans and agents making better, faster, more consistent decisions at scale.
We built this for internal agents. Now we’re asking: can it serve external agents too? We don’t have the answer — and we want to hear yours.
Intelligent recommendations are only partly about scoring. The rest is judgment — choices about what matters, what to fix, and what comes next. Here are the ones that shaped Content Compass.
1,589 pieces of content. 9 buyer personas. 25 product intelligence rubrics. 158 themes that connect what a buyer cares about to what they should read next.
AI agents can reason, synthesise and act — but when they go looking for content to inform a research journey, they hit a wall. Thousands of assets with no structured signal about who they're for, what stage they serve, or which priorities they address. Content Compass is the bridge.
No persona signal. No stage awareness. No play alignment. Generic results for a specific need.
Recommendations customised to your priorities — not a list of results, but a structured research journey built around three dimensions of what matters to you.
Themes are the secret sauce — the connective tissue between what a buyer says and what content will actually matter to them.
158 themes mapped across 9 personas and 25 product intelligence rubrics. Each theme is a bridge — connecting what a buyer cares about to the plays that address it and the content that proves it. The rubric isn't keywords. It's structured intelligence.
Every piece of content is evaluated against the rubrics and assigned scores for persona fit, journey stage, and product alignment. Those scores power every recommendation.
Every journey follows a progressive arc — from awareness to proof to evaluation. The system detects where a buyer is and adjusts accordingly. While today we offer a focused set of journeys, customers and their agents can tailor the arc to their own priorities, timelines, and ways of working.
BUILT FOR 9 PERSONAS
The Content Compass 1.0 solution is the product of nine months of research, experiments and pilots. What you're seeing today — this agentic experience — was built from scratch in four days with Claude. Two very different timelines. One intelligence layer.
Adobe has thousands of GTM practitioners making content strategy decisions every day — and so are their agents. GTM Strategy partnered with Experience Intelligence to build a universal intelligence layer for both: humans and agents making better, faster, more consistent decisions at scale.
We built this for internal agents. Now we’re asking: can it serve external agents too? We don’t have the answer — and we want to hear yours.
Intelligent recommendations are only partly about scoring. The rest is judgment — choices about what matters, what to fix, and what comes next. Here are the ones that shaped Content Compass.
1,589 pieces of content. 9 buyer personas. 25 product intelligence rubrics. 158 themes that connect what a buyer cares about to what they should read next.
AI agents can reason, synthesise and act — but when they go looking for content to inform a research journey, they hit a wall. Thousands of assets with no structured signal about who they're for, what stage they serve, or which priorities they address. Content Compass is the bridge.
No persona signal. No stage awareness. No play alignment. Generic results for a specific need.
Recommendations customised to your priorities — not a list of results, but a structured research journey built around three dimensions of what matters to you.
Themes are the secret sauce — the connective tissue between what a buyer says and what content will actually matter to them.
158 themes mapped across 9 personas and 25 product intelligence rubrics. Each theme is a bridge — connecting what a buyer cares about to the plays that address it and the content that proves it. The rubric isn't keywords. It's structured intelligence.
Every piece of content is evaluated against the rubrics and assigned scores for persona fit, journey stage, and product alignment. Those scores power every recommendation.
Every journey follows a progressive arc — from awareness to proof to evaluation. The system detects where a buyer is and adjusts accordingly. While today we offer a focused set of journeys, customers and their agents can tailor the arc to their own priorities, timelines, and ways of working.
BUILT FOR 9 PERSONAS
The Content Compass 1.0 solution is the product of nine months of research, experiments and pilots. What you're seeing today — this agentic experience — was built from scratch in four days with Claude. Two very different timelines. One intelligence layer.
Adobe has thousands of GTM practitioners making content strategy decisions every day — and so are their agents. GTM Strategy partnered with Experience Intelligence to build a universal intelligence layer for both: humans and agents making better, faster, more consistent decisions at scale.
We built this for internal agents. Now we’re asking: can it serve external agents too? We don’t have the answer — and we want to hear yours.
Intelligent recommendations are only partly about scoring. The rest is judgment — choices about what matters, what to fix, and what comes next. Here are the ones that shaped Content Compass.
Content Compass is a proof of capability — a demonstration of the intelligence layer that could power any AI agent researching on behalf of a buyer. The rubric is the product.