Agents in the Agent Directory
5 min
The Agent Directory in Mark (Optimizely Agent Platform) offers ready-made agents that Optimizely publishes. Mark works automatically to help you improve and streamline your workflows. Agents enhance these core capabilities by handling specialized tasks like summarizing content, generating marketing emails, and analyzing data.
These agents are available in every Mark instance. Click an agent's name to see what it does, when to use it, and how to configure it. You cannot update the ID of agents in the Directory. A curated subset of these agents also displays in the Agent Library for Mark users to browse and launch.
See Optimizely Academy's videos on Meet the Agents to learn more about the agents.
Note
Mark Administrators, Agent Builders, and users with the Add, edit, and install specialized agents attribute for a custom role can add agents to their organization's Mark instance. See Add users and set permissions.
Brainstorm and plan
Campaign Brief Generation agent – @campaign_brief_generation
- Description – Generates a standardized campaign brief from the inputs you provide.
- Challenge – Manual brief creation slows campaign planning and produces inconsistent briefs.
- Value – Faster planning, consistent briefs, and less manual rework.
Conductor Competitive AI Share of Voice agent – @competitive_ai_share_of_voice
- Description – Compares your brand against tracked competitors across ChatGPT, Gemini, and Perplexity. Share of voice measures how often AI engines mention your brand compared to competitors.
- Challenge – Competitive AI search performance is invisible. Marketing and Search Engine Optimization (SEO) teams cannot tell whether they are gaining or losing ground against competitors.
- Value – Competitive AI share of voice in one run, without pulling data from multiple sources.
Content Ideation agent – @content_ideation
- Description – Generates 10 content and campaign ideas for a topic, audience, or quarter. The agent combines live trend research and competitor intelligence.
- Challenge – Generating content ideas that align with business goals, audience interests, and keyword opportunities is slow. Manual brainstorming cannot sustain a steady pipeline of differentiated ideas.
- Value – A fuller content pipeline, more consistent publishing, and ideas grounded in audience relevance and search opportunity.
Competitive Insights agent – @competitive_insights
- Description – Researches a single competitor. The agent generates a competitive intelligence report covering the past 30 days.
- Challenge – Conducting thorough competitive analysis for specific marketing use cases is a complex and time-consuming task.
- Value – Informed strategy, targeted campaigns.
Competitive Webpage Analysis agent – @competitive_webpage_analysis
- Description – Compares competitor webpages against your own. The agent captures screenshots of each page and recommends specific changes to improve your page.
- Challenge – You must understand what competitors do, identify effective market strategies, and find ways to stay ahead.
- Value – A clear view of what works in your market and specific changes to outperform competitors.
Creative Brief Generation agent – @creative_brief_generation
- Description – Turns a campaign description, asset type, and key message into a complete, structured creative brief. The brief covers strategy, audience, messaging, and visual requirements. Hand it off to a creative team or agency.
- Challenge – Without a clear, structured roadmap, the creative process leads to misaligned expectations, revisions, and delays. Gathering goals, audience details, and technical requirements into a brief is slow and delays the handoff to creative teams.
- Value – Faster idea-to-execution with fewer revision cycles, so campaigns launch sooner.
Email Ideation agent – @email_ideation
- Description – Brainstorms five to seven newsletter themes and content angles tailored to a business niche and current goals.
- Challenge – Content marketers spend too much time staring at blank briefs before generating newsletter ideas.
- Value – Structured, goal-aligned newsletter themes move content marketers from ideation to execution faster.
Product Promotion agent – @product_promotion
- Description – Builds and configures product promotions from a natural-language prompt. The agent assigns products and variants and applies the promotion types you describe.
- Challenge – Commerce teams face manual configuration, slow campaign launches, and a lengthy promotional lifecycle.
- Value – Launches targeted campaigns faster, reduces manual configuration, and accelerates the entire promotional lifecycle from idea to execution.
Smart Campaign Design agent – @smart_campaign_design
- Description – Reads a campaign brief and generates an Optimizely Campaign flow architecture.
- Challenge – Campaign managers must manually translate campaign briefs into multi-segment email flows with proper node logic, timing, and testing.
- Value – Campaign managers accelerate campaign deployment and prevent configuration errors in Optimizely Campaign.
Webinar Outline agent – @webinar_outline
- Description – Turns a webinar topic and optional notes into a structured outline. The outline includes timed sections, speaker talking points, engagement moments, and pre-webinar and post-webinar checklists.
- Challenge – Building a webinar agenda from scratch requires balancing timing, audience engagement, and post-event follow-up across multiple documents.
- Value – Marketing teams launch webinars faster with a consistent structure adapted to lead generation, education, onboarding, or community goals.
Create
Blog Post Generation agent – @blog_generation
- Description – Writes a complete blog post for a target audience. The agent researches the subject and delivers an editable draft in a canvas. The draft includes SEO metadata.
- Challenge – Writing high-quality blog posts that fit a subject and resonate with a target audience is time-consuming. This slows publishing velocity.
- Value – Faster blog production at consistent quality, so teams publish more often without adding writing capacity.
Case Study Generation agent – @case_study_generation
- Description – Generates a publication-ready B2B SaaS case study from a company name and background material.
- Challenge – Writing a case study demands hours of research, interviewing, and formatting before a draft is ready for review.
- Value – The agent reduces case study production time from days to minutes, accelerating sales enablement and content marketing pipelines.
Content Analysis agent (CMS SaaS) – @content_type_analysis
- Description – Analyzes Optimizely Content Management System (SaaS) content of a specified content type. The agent identifies structural patterns and produces a reusable skill.
- Challenge – Maintaining consistent content structure across CMS (SaaS) content types requires manual review of existing content patterns.
- Value – Standardized content creation based on proven patterns, reducing guesswork and improving consistency.
Content Analysis agent (CMS 13) – @content_type_analysis
- Description – Analyzes existing content of a specified Optimizely Content Management System (CMS) 13 (PaaS) content type. The agent produces a markdown skill for creating content of that type.
- Challenge – Content creators lack a documented standard for how each CMS (PaaS) content type structures properties, components, and display settings.
- Value – Teams create consistent, on-pattern CMS (PaaS) content and reduce rework caused by inconsistent content structures.
Content Model Creation agent (CMS SaaS) – @content_model_creation
- Description – Builds a content model for Content Management System (SaaS) from a URL or an image. The agent references your existing content types to avoid duplicates.
- Challenge – Analyzing and creating content models that use product features is complex and time-consuming.
- Value – Faster development when creating new content types or adding features to existing ones.
Content Model Creation agent (CMS 13) – @content_model_creation-paas
- Description – Builds a content model for Content Management System (CMS 13) from a URL or an image. The agent references your existing content types to avoid duplicates.
- Challenge – Analyzing and creating content models that use product features is complex and time-consuming.
- Value – Faster development when creating new content types or adding features to existing ones.
Content Refresh Analysis agent – @content_refresh_analysis
- Description – Audits your website in Content Management System (SaaS). The agent finds outdated content, reviews it against compliance guidelines, and reports what needs attention. This improves SEO and site credibility.
- Challenge – Identifying which content on your website is outdated, underperforming, or no longer relevant is difficult. This leads to a stale user experience, lower search visibility, and inefficient content management.
- Value – A fresh, high-performing website with less effort, better SEO, stronger engagement, and content that stays current.
Email Content Translation agent – @email_content_translation
- Description – Translates a full email in Optimizely Campaign (body, subject line, preview text, and image alt-text) into a target language. The agent displays the original and translation side-by-side in a canvas.
- Challenge – Manually translating email content while keeping accuracy, cultural relevance, and brand voice across languages is slow and error-prone.
- Value – Faster, consistent email translation that preserves accuracy, cultural relevance, and brand voice.
Email creation agent – @email_creation
- Description – Creates marketing emails from a brief overview, target audience, and call-to-action.
- Challenge – Crafting marketing emails that consistently capture attention, drive engagement, and convert readers requires significant time, creativity, and expertise.
- Value – Engaging content, higher conversions, measurable impact.
Email Optimization agent – @email_optimization
- Description – Analyzes newsletter content in Optimizely Campaign and delivers structured feedback with recommendations for improvement.
- Challenge – Identifying specific areas for improvement, ensuring brand consistency, and generating data-driven A/B testing ideas is difficult. This leads to suboptimal campaign performance.
- Value – Actionable, expert-level analysis in minutes, so campaigns improve without manual auditing.
Email Subject and Preview Text Generation agent – @email_subject_preview_text_generation
- Description – Generates paired subject lines and preview texts for specific psychological triggers.
- Challenge – Email marketers write subject lines and preview text from scratch without a structured framework for testing.
- Value – Ready-to-test email copy moves marketers from a blank page to an A/B test faster.
FAQ Creation agent – @faq_creation
- Description – Analyzes content at a provided URL and generates contextually relevant frequently asked questions (FAQs) optimized for AI-powered search.
- Challenge – Creating and maintaining a comprehensive, up-to-date FAQ section is difficult. Identifying common user questions, drafting clear answers, and keeping them current with product or service changes takes time and resources.
- Value – Less time on FAQ creation, stronger self-service coverage, and better visibility in AI-powered search.
Image Metadata Ideation agent – @image_metadata_ideation
- Description – Analyzes provided email content from Optimizely Campaign to suggest accessible alt-text and titles for the images included. The agent helps ensure your content is user-friendly and compliant.
- Challenge – Email images often lack compliant, context-aware alt-text and titles, which reduces accessibility and deliverability.
- Value – Streamline accessibility compliance for email campaigns without manual image-by-image auditing.
LinkedIn InMail Ad Brief agent – @linkedin_ad_brief_generation
- Description – Generates structured LinkedIn Sponsored Content ad briefs with copy variants validated against LinkedIn character limits.
- Challenge – Writing LinkedIn ad copy that meets character limits and aligns with funnel stages requires manual validation and revision.
- Value – The agent produces LinkedIn ads faster with compliance checks, reducing revision cycles and improving campaign launch speed.
LinkedIn InMail Copy Generation agent – @linkedin_inmail_generation
- Description – Crafts headlines, body text, and calls-to-action aligned with LinkedIn's professional audience and ad specifications for B2B outreach.
- Challenge – Manually crafting engaging and compliant LinkedIn InMail copy for B2B outreach is time-consuming and difficult. It requires copywriting expertise, an understanding of LinkedIn's professional audience, and adherence to ad specifications. These skills support effective B2B communication.
- Value – The agent streamlines content creation and saves time and resources. It helps ensure InMail messages are engaging, compliant, and effective for B2B outreach.
List Creation agent – @list_creation
- Description – Guides you through creating a global list or wishlist in Optimizely Configured Commerce.
- Challenge – Administrators must manually look up products, define rules, and scope customers across multiple admin pages to configure global wishlists.
- Value – Administrators configure targeted product lists through conversational prompts with validation at each step.
Page Builder agent (CMS SaaS) – @page_builder
- Description – Analyzes a document, image, or URL. The agent creates an Optimizely Content Management System (SaaS) content item of a specified content type.
- Challenge – Editors spend significant time manually creating CMS (SaaS) content from designs, documents, or external sources.
- Value – Page Builder accelerates content production by eliminating manual content entry and formatting steps.
Page Builder (CMS 13) – @page_builder
- Description – Analyzes a document, image, or URL. The agent creates a content item of a specified content type in Optimizely Content Management System (CMS) 13 (PaaS).
- Challenge – Editors spend hours rebuilding designs, documents, and existing web pages as structured CMS content.
- Value – Teams move from ideation to publish-ready CMS content faster and structure content according to Optimizely CMS best practices.
Press Release agent – @press_release
- Description – Creates professional press releases structured for media pickup, from a brief overview of the announcement.
- Challenge – Writing compelling and newsworthy press releases that capture media attention is a specialized and time-consuming task.
- Value – Time saved, consistent messaging, media attention.
Promotion Creation agent – @promotion_creation
- Description – Guides merchandisers through creating promotions in Optimizely Configured Commerce.
- Challenge – Building a promotion in Configured Commerce spans four admin tabs. You configure details, rule conditions, reward results, and website scope.
- Value – Merchandisers configure promotions through conversation instead of manual admin configuration, with validation at each step.
Restriction Group Creation agent – @restriction_group_creation
- Description – Creates product restriction groups in Optimizely Configured Commerce through a step-by-step wizard.
- Challenge – Configuring a restriction group requires multiple admin API calls. It also requires exact Open Data Protocol (OData) filters and manual universally unique identifier (UUID) lookups.
- Value – Commerce teams define customer and product restrictions accurately without hand-building API requests.
Social Media Image Generation agent – @social_media_image_generation
- Description – Generates platform-ready social media images from a text prompt or reference image. Each image uses the exact dimensions for its supported format.
- Challenge – Creating correctly sized social media images for multiple platforms requires manual resizing and format-specific knowledge.
- Value – Eliminates resizing guesswork and accelerates visual content production across channels.
Social Post Generation agent – @social_post_generation
- Description – Takes a topic, URL, or key message and generates platform-native social posts for LinkedIn, X, Instagram, Facebook, and TikTok.
- Challenge – Adapting a single piece of long-form content for multiple social media platforms is a repetitive and fragmented process. Each network requires a specific tone, character count, and hashtag strategy. This makes it difficult to maintain high posting frequencies across LinkedIn, X, and Instagram without manual rework.
- Value – The agent eliminates the manual rework of adapting content for different platforms. It instantly multiplies the reach of a single idea. It accelerates distribution workflows. You maintain a high-velocity social presence that stays on-brand and optimized for engagement. Reformatting no longer slows you down.
Social Post Research agent – @social_post_research
- Description – Researches trending angles, hooks, and competitor post patterns for social content. The agent packages findings into a structured brief for handoff to social post creation.
- Challenge – Staying on top of trending topics, competitor activity, and audience sentiment across social platforms is time-consuming and fragmented. Manually monitoring feeds makes it difficult to plan post strategies that are timely and data-driven. Manual monitoring leads to missed engagement opportunities.
- Value – The agent shifts social strategy from guesswork to informed execution by automating the heavy lifting of trend analysis. The agent backs every post with current market data, increasing relevance and engagement rates, without hours of manual research.
Subject & Preview Text Ideation agent – @subject_preview_text_ideation
- Description – Analyzes email content from Optimizely Campaign. The agent generates three pairs of subject lines and preview texts, each focused on urgency, curiosity, or benefit.
- Challenge – Crafting email subject lines and preview texts that capture audience attention, drive open rates, and adhere to character limits is difficult. It requires significant brainstorming, an understanding of psychological triggers, and a clear marketing rationale. Marketers find this process time-consuming and challenging.
- Value – Marketers access a variety of high-performing subject line and preview text options without time-consuming brainstorming. This improves email open rates and engagement. It also deepens understanding of how different messaging strategies affect campaign performance.
Webinar Follow-up Email Creation agent – @webinar_followup_email
- Description – Generates two personalized follow-up emails after a webinar. One email drives next actions for attendees. The other encourages on-demand viewing for non-attendees.
- Challenge – Crafting personalized follow-up emails for webinar attendees and no-shows is repetitive and time-consuming. This often results in generic outreach that fails to drive next actions.
- Value – Marketing teams reduce manual follow-up effort and maintain consistent post-webinar outreach, driving pipeline from both attendees and no-shows.
Experiment and analyze
Agent Visibility Analytics Insights agent – @agent_visbility_analytics_insights
- Description – Analyzes an Agent Visibility Analytics dashboard in Optimizely Analytics. The agent surfaces trends, anomalies, and insights from your dashboard data and delivers a report.
- Challenge – Teams sift through Optimizely Analytics dashboards manually to identify what is meaningful. Teams miss trends, anomalies go unnoticed, and raw data is slow to become decisions.
- Value – The agent automates analysis of your data. Teams act on signals faster without a dedicated analyst for every review cycle.
Campaign Performance Digest agent – @campaign_performance_digest
- Description – Summarizes the performance of your sent Smart Campaigns in Optimizely Campaign, flags unusual results, and recommends follow-up actions.
- Challenge – Campaign metrics live in individual campaign reports. Marketers compare the numbers by hand to see which campaigns worked and what to do next.
- Value – Marketers read a decision-ready report in minutes and share it as is.
Experiment Backlog Prioritization agent – @experiment_backlog_prioritization
- Description – Scores each idea in your experimentation backlog using the Potential, Importance, Ease (PIE) framework. The agent generates a prioritized report with recommended experiments and the reasoning behind every score.
- Challenge – Experimentation backlogs grow fast, but bandwidth is limited. Teams struggle to decide which ideas to test next. Many default to gut instinct or stakeholder pressure rather than a structured, objective framework.
- Value – Removes subjectivity from backlog decisions with a consistent, repeatable scoring methodology. This methodology aligns experiment priorities with strategic key performance indicators (KPIs). It also surfaces the highest-impact ideas first.
Experiment Conflict Checker agent – @experiment_conflict_checker
- Description – Detects conflicts between a proposed experiment and any live experiments in the same project.
- Challenge – Running overlapping experiments on the same page corrupts your data, skews results, and leads to flawed conclusions. Flawed conclusions leave teams unable to trust their findings or ship with confidence.
- Value – Eliminate the guesswork before you launch. Catch conflicts early, protect data integrity, and make faster, more confident decisions. You do not need to audit your experiment configuration manually.
Experiment Planning agent – @experiment_planning
- Description – Transforms raw ideas into a fully formed experiment plan, complete with hypotheses, key metrics, risks, and critical assumptions.
- Challenge – A poorly planned test results in few learnings. Running quality tests means teams get to deeper learning faster.
- Value – Create an experiment plan that enhances your team's overall testing framework.
Experiment Program Health Review agent – @experiment_program_health_review
- Description – Analyzes Optimizely Web Experimentation or Optimizely Feature Experimentation projects and routes to the correct interactive dashboard for each program type.
- Challenge – Experimentation programs generate large volumes of data. Translating that data into a clear, program-level story takes time and effort. Teams lack a single view of what is working, what is not, and where to focus next. This applies across Web Experimentation and Feature Experimentation.
- Value – The agent removes the manual effort of piecing together program performance across experiments. Teams and stakeholders get a clear, structured view of experimentation health. This view supports faster, more confident decisions about where to invest next.
Experiment Program Value Analysis agent – @experiment_program_value_analysis
- Description – Generates an executive value report from Optimizely Program Reporting for Experimentation.
- Challenge – Stakeholders struggle to quantify financial gains, losses avoided, and overall business value across an experimentation program.
- Value – Communicates the return on investment (ROI) of experimentation to executive leaders without manual calculations.
Experiment Value Estimator agent – @experiment_value_estimator
- Description – Generates a stakeholder-ready report with the projected annualized impact of rolling out a winning experiment variation.
- Challenge – Communicating the business impact of a winning experiment is difficult. You often struggle to translate test results into concrete, stakeholder-ready numbers that justify the investment. Lift percentages and statistical significance do not map directly to revenue.
- Value –
- Quantifies the ROI of experimentation in dollar terms stakeholders understand.
- Removes the guesswork from post-experiment reporting.
- Gives you copy-ready Slack and email blurbs to share the result with stakeholders.
- Includes an optional conservative discount factor to anchor stakeholders on a realistic, defensible number.
Experimentation Program Overview agent – @experimentation_program_overview
- Description – Analyzes experimentation performance within a specified timeframe. The agent generates an overview of program velocity, win rate, and top-performing experiments.
- Challenge – Compiling an overview of your Experimentation program, including win rates, top performers, and key learnings, is time-consuming and complex. It is difficult to assess program health and identify trends.
- Value – Removes the manual effort of compiling program performance data. Stakeholders get a clear, structured view of experimentation health to identify successful strategies and communicate impact.
Eye Tracking Auditor agent – @eye_tracking_auditor
- Description – Analyzes predictive eye-tracking maps to identify visual hierarchy issues in email designs.
- Challenge – Marketers struggle to identify where subscriber attention drops or diverges from primary calls to action.
- Value – Teams optimize email layouts and improve click-through rates before sending campaigns.
Feature Experimentation Governance agent – @feature_experimentation_governance
- Description – Analyzes an Optimizely Feature Experimentation project, generates a governance report, and offers chat actions to resolve findings.
- Challenge – Feature flags accumulate across environments, and teams lose visibility into which flags are live, stale, or abandoned.
- Value – Teams find and resolve flag cleanup and promotion work in one conversation, which reduces technical debt.
Feature Flag Implementation agent – @feature_flag_implementation
- Description – Generates a portable SKILL.md file to implement an Optimizely Feature Experimentation flag in a codebase.
- Challenge – Developers implement feature flags by hand and guess at flag keys, variable types, and version-specific SDK methods.
- Value – Coding assistants implement the flag correctly on the first attempt. This shortens implementation time and prevents runtime failures from incorrect keys.
GEO Readiness Scorer agent – @geo_readiness_scorer
- Description – Measures how ready your site is for generative engine optimization (GEO) and gives you a 64-point score to track over time, with a prioritized action plan.
- Challenge – Teams do not know whether AI search tools can find, read, and cite their website. Without a baseline, they cannot decide which fixes to make first or measure the impact of the fixes they make.
- Value – You get a measurable score to track over time and see which fixes recover the most points, so you can prioritize them.
Heatmap Analysis agent – @heatmap_analysis
- Description – Transforms a provided heatmap image and URL into precise, tailored test ideas.
- Challenge – Creating high-quality test ideas can be difficult.
- Value – Pinpoint high-impact optimization opportunities and reduce the time to translate user behavior data into testable experiments.
Real-Time Audience Builder agent – @rts_audience_builder
- Description – Creates, updates, and troubleshoots Optimizely Data Platform (ODP) real-time audiences. It answers expert questions about audience purpose, overlap, and Real-Time Segment (RTS) expressions.
- Challenge – Creating, updating, and troubleshooting RTS audiences in ODP is difficult. Common challenges include identifying audiences, understanding overlap, building expressions, and diagnosing unexpected behavior.
- Value – Manage RTS audiences in ODP more efficiently by creating, refining, and troubleshooting them through natural-language requests.
Standard Audience Builder agent – @standard_audience_builder
- Description – Builds and troubleshoots standard Optimizely Data Platform (ODP) audiences through natural language.
- Challenge – Standard ODP audiences require manual configuration and specialized schema knowledge. Troubleshooting takes time when segments break or produce unexpected results.
- Value – Target the right customers faster by removing the technical barriers of audience creation. Automate repetitive variant work.
Test Ideation agent – @test_ideation
- Description – Generates a prioritized package of experiment ideas for any page.
- Challenge – Identifying high-impact experiments is time-consuming. Without historical context, you risk repeating dead ends or missing obvious wins.
- Value – Accelerates your experimentation pipeline with ideas that build on what you know, not what you guess.
Optimize
Campaign Status Insights agent – @campaign_status_insights
- Description – Creates a real-time dashboard of the active Smart Campaigns in Optimizely Campaign, with previews of upcoming messages and recommended send times.
- Challenge – Campaign managers open each Smart Campaign individually to check what is sending, blocked, or in configuration. Campaign managers also lack data to choose the next send time.
- Value – Campaign managers see what is going out and what needs attention in one view. They choose send times based on past campaign data.
Competitor PageSpeed Analysis agent – @competitor_pagespeed_analysis
- Description – Runs a Google Lighthouse audit for your page and a competitor's page. The agent then delivers a side-by-side gap analysis with prioritized recommendations.
- Challenge – Teams rarely have a clear, side-by-side view of how their page performance stacks up against competitors.
- Value – Teams stop guessing and start acting with precision. Benchmark performance directly against competition to prioritize the technical improvements with the most impact. Acting on these insights turns page speed from a liability into a competitive advantage.
Conductor AEO Gap Finder agent – @aeo_gap_finder
- Description – Finds high-priority answer engine optimization (AEO) content gaps by analyzing your website against tracked competitors.
- Challenge – AI citation gaps are invisible. SEO and content teams cannot see which topics drive competitor citations or what to write.
- Value – AEO competitive gap analysis in one run, without piecing together data across tools and engines.
Conductor AI Brand Visibility Report agent – @ai_brand_visibility_report
- Description – Delivers a snapshot of your brand's visibility across ChatGPT, Gemini, and Perplexity.
- Challenge – AI search visibility is a blind spot. Marketing and SEO teams cannot see where their brand wins, where it loses, or what to fix.
- Value – Specialist-level AI search visibility in one run, without custom dashboards or manual data pulls.
Content Adaption agent – @content_adaption
- Description – Repurposes existing content for a new channel. The agent reformats your source content to fit the destination channel's best practices and delivers it in a canvas.
- Challenge – Repurposing content for each platform, while keeping brand voice and following channel best practices, is complex and time-consuming.
- Value – More content reuse, a consistent brand voice, and better engagement across channels.
E-E-A-T Checker agent – @eeat_checker
- Description – Evaluates any piece of web content against Google's E-E-A-T quality signals. The agent rates experience, expertise, authoritativeness, and trustworthiness with concrete evidence from the content.
- Challenge – Search engines and audiences increasingly demand content that demonstrates Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T). Manually auditing every article for these nuanced signals is a meticulous and inconsistent process. Signals include primary research, expert citations, and verified data. This process often leaves high-value content underperforming in search results.
- Value – De-risks your search strategy by architecting every piece of content for maximum visibility and trust.
Email Performance Comparison agent – @email_performance_comparison
- Description – Analyzes and compares email campaign performance using KPIs to identify success factors and performance differences.
- Challenge – Comparing multiple email campaigns across KPIs demands manual data gathering and analysis that slows decision-making.
- Value – Faster identification of top-performing campaign strategies enables data-driven decisions. These decisions improve open rates, click rates, and overall email marketing ROI.
GA4 Web Traffic Report Generation agent – @ga_traffic_reporter
- Description – Pulls Google Analytics 4 (GA4) traffic data. The agent delivers an executive-ready HTML report with period-over-period metrics, top pages, channel breakdowns, and recommended actions.
- Challenge – Pulling multiple reports manually to understand traffic trends, user behavior, and conversion performance is time-consuming and difficult.
- Value – The agent delivers insights in an executive-ready format, accelerating data-driven decision-making.
GEO Auditor agent – @generative_engine_optimization_auditor
- Description – Audits any webpage for AI search readiness. The agent generates a Generative Engine Optimization (GEO) report. The report covers AI crawler accessibility, Core Web Vitals, schema markup, content structure, and citation readiness.
- Challenge – Manually conducting comprehensive audits, obtaining actionable insights, and prioritized plans for AI search readiness is complex and time-consuming.
- Value – Improves visibility in AI-powered search engines with repeatable GEO checks across any page type.
GEO Recommendations agent – @generative_engine_optimization_recommendations
- Description – Runs a GEO audit on any page and delivers a branded report with prioritized recommendations.
- Challenge – Organizations struggle to optimize content-heavy pages for AI-powered search engines like ChatGPT, Perplexity, and Google AI Overviews.
- Value – Less guessing, more insight and actionable improvements you can make today to improve AI visibility.
GEO Schema Optimization agent (CMS SaaS) – @geo_schema_optimization
- Description – Lets you enhance your content's visibility and large language model (LLM) discoverability by automatically identifying opportunities for structured data markup.
- Challenge – Ensuring that GEO-specific content has correct schema markup is complex. This often leads to under-optimized local search performance and missed opportunities for rich search results.
- Value – Optimizing your GEO-schema improves your visibility in local search results. It increases the chances of appearing in rich snippets and drives more relevant local traffic to your business.
GEO Schema Optimization agent (CMS 13) – @geo_schema_optimization-paas
- Description – Lets you enhance your content's visibility and large language model (LLM) discoverability by automatically identifying opportunities for structured data markup.
- Challenge – Ensuring that GEO-specific content has correct schema markup is complex. This often leads to under-optimized local search performance and missed opportunities for rich search results.
- Value – Optimizing your GEO-schema improves your visibility in local search results. It increases the chances of appearing in rich snippets and drives more relevant local traffic to your business.
Google Ads Account Auditor agent – @google_ads_account_auditor
- Description – Performs a full Google Ads account audit. The audit covers baseline metrics, n-gram theme analysis, search term waste, duplicate keywords, and best performers. It also includes a strengths, weaknesses, opportunities, and threats (SWOT) analysis and a prioritized action plan.
- Challenge – Manually auditing a Google Ads account for wasted spend, underperforming keywords, and missed opportunities takes hours.
- Value – The agent recovers wasted ad spend and surfaces high-impact optimizations in minutes instead of hours.
Keyword Research agent – @keyword_research
- Description – Takes a topic and uses data from Optimizely Content Marketing Platform (CMP) Idea Lab and the broader web. The agent returns a curated list of keywords to maximize content visibility and search traffic.
- Challenge – Identifying the most effective keywords to maximize content visibility and search traffic requires extensive research and analysis.
- Value – Improved SEO, increased visibility, higher rankings.
Page Conversion Optimization agent – @page_conversion_optimization
- Description – Performs a full conversion audit on any live web page. The agent returns a prioritized list of fixes ordered by expected conversion impact.
- Challenge – Teams often rely on gut instinct when deciding what to change on a page to improve conversions. Without a structured audit process, optimization efforts scatter and miss high-impact fixes. Teams then waste resources on low-impact changes.
- Value – By focusing on the highest-impact changes, teams eliminate guesswork, accelerate experimentation, and maximize the return on every optimization effort.
Page Copy Optimization agent – @page_copy_optimization
- Description – Analyzes your live page copy and generates optimized versions for clarity, conversion, and message-market fit.
- Challenge – Writing high-performing page copy is difficult without a clear benchmark. Without visibility into how your messaging compares to competitors, your copy fails to resonate, differentiate, or convert.
- Value – Move from competitive insight to stronger on-page messaging in minutes. By replacing guesswork with audience-specific, goal-driven copy, sharpen your value proposition and improve conversion rates.
Page Performance Evaluation agent – @page_performance_evaluation
- Description – Runs a full Google Lighthouse audit on any live URL, covering Performance, SEO, Accessibility, and Best Practices. The agent then cross-references findings against a visual screenshot. This pinpoints root causes and delivers specific, ranked fixes with real metric values.
- Challenge – Teams struggle to diagnose why pages underperform. Audit tools surface scores but rarely connect them to root causes, and automated checks miss visual issues entirely.
- Value – The agent eliminates guesswork by pinpointing exactly what to fix and why. Teams prioritize the improvements with the most impact on page speed, search visibility, and user experience.
Product Catalog Auditor agent – @product_catalog_auditor
- Description – Scans products and variants to detect data inconsistencies, missing attributes, and publishing gaps in Optimizely Commerce Connect.
- Challenge – Catalog merchandisers struggle to catch unpriced items, missing media, broken variants, and placeholder copy before products go live.
- Value – Merchandisers resolve catalog defects early to maintain data quality and protect storefront revenue.
Profound Citation Gap Analysis agent – @profound_citation_gap_analysis
- Description – Analyzes competitive citation performance for any topic using Profound's AI search tracking data.
- Challenge – Identifying citation gaps and determining which blog topics to prioritize is difficult. The decision depends on AI citation performance against competitors across platforms like Perplexity, ChatGPT, and Google AI.
- Value – Makes it easy to identify citation gaps and determine blog topics to prioritize. This helps improve content strategy and visibility in AI-powered search.
SEO Metadata Implementation agent (CMS SaaS) – @seo_metadata_implementation
- Description – Analyzes Optimizely Content Management System (SaaS) webpages and generates optimized SEO metadata. The metadata includes meta titles, descriptions, and OpenGraph tags. The agent applies updates directly in CMS (SaaS).
- Challenge – Creating and maintaining optimized SEO metadata across CMS (SaaS) pages requires manual effort and specialized knowledge.
- Value – The agent improves search engine visibility and drives more qualified organic traffic without requiring dedicated SEO expertise.
SEO Metadata Implementation agent (CMS 13) – @seo_metadata_implementation-paas
- Description – Analyzes Optimizely Content Management System (CMS 13) webpages and generates optimized SEO metadata. The metadata includes meta titles, descriptions, and OpenGraph tags. The agent applies updates directly in CMS 13.
- Challenge – Creating and maintaining optimized SEO metadata across CMS 13 pages requires manual effort and specialized knowledge.
- Value – The agent improves search engine visibility and drives more qualified organic traffic without requiring dedicated SEO expertise.
SEO Metadata Optimization agent – @seo_metadata_optimization
- Description – Evaluates a URL for existing SEO properties, identifies optimization opportunities, and recommends improvements.
- Challenge – Optimizing SEO metadata for content to improve search engine visibility is difficult.
- Value – Improved SEO metadata leads to better search engine rankings, increased organic traffic, and a more effective digital presence.
Technical SEO Auditor agent – @technical_seo_auditor
- Description – Analyzes website performance using Google PageSpeed Insights data and evaluates pages against Google's ranking factors. It delivers an audit report with prioritized issues, developer-ready fixes, and effort estimates.
- Challenge – Google PageSpeed Insights reports are technical. Marketers struggle to tell which issues affect search visibility most, and developers need specific fixes instead of scores.
- Value – Marketers get issues ranked by their impact on search visibility. Effort estimates separate quick wins from larger technical projects. Developer-ready fixes speed up hand-offs.
WCAG Compliance Auditor agent – @wcag_compliance_auditor
- Description – Audits Optimizely Content Management System (SaaS) content against Web Content Accessibility Guidelines (WCAG) standards. The agent applies approved accessibility fixes.
- Challenge – Accessibility issues accumulate across CMS (SaaS) content, and manual reviews miss them before publication.
- Value – Teams reduce accessibility risk and resolve recurring issues faster through reusable fix patterns.
Web Accessibility Evaluation agent – @web_accessibility_evaluation
- Description – Checks a URL against the WCAG Accessibility 2.2 Standards and Google Lighthouse.
- Challenge – Manually checking website URLs against WCAG 2.2 accessibility standards and Google Lighthouse is a complex and specialized task.
- Value – Accessibility compliance, improved inclusivity.
Productivity
Content Summary agent – @content_summary
- Description – Summarizes lengthy documents and PDFs, extracting key points from complex content.
- Challenge – Reviewing lengthy documents and extracting critical insights is time-consuming and slows down decision-making.
- Value – Faster understanding, streamlined reviews, informed decisions.
Content Translation agent – @translation
- Description – Converts existing content to a different language, taking into account cultural, company, and grammatical differences.
- Challenge – Translating content and PDFs into multiple languages while maintaining cultural and company-specific nuances is complex and costly.
- Value – Global reach, accurate communication, streamlined efforts.
Image Alt Text Generation agent – @image_alt_text_generation
- Description – Audits up to 20 images on a page URL. The agent scores existing alt text against WCAG 2.1 AA standards. It delivers ready-to-use alt text copy with a prioritized fix list.
- Challenge – Manually reviewing images for alt text compliance across pages is time-consuming and error-prone.
- Value – Marketing teams meet WCAG 2.1 AA accessibility standards and strengthen SEO without manual image scanning.
Image Resizer agent – @image_resizer
- Description – Resizes and reformats uploaded images to exact pixel dimensions for marketing channels.
- Challenge – Marketing teams must resize images for multiple channels. This requires repetitive manual work across different tools and platform specifications.
- Value – The agent eliminates manual image production steps, freeing marketing teams to focus on creative work instead of asset formatting.
Image Text Remover agent – @image_text_remover
- Description – Removes overlaid text from an uploaded image and fills the cleared area with the surrounding background.
- Challenge – To remove captions, labels, or burnt-in subtitles from images, teams must manually edit them in dedicated design tools.
- Value – Marketing teams repurpose images without opening external editing software.
Meeting Follow-up Email agent – @meeting_followup_email
- Description – Takes meeting notes, a summary, or a transcript and produces a structured follow-up email with decisions, action items, and next steps.
- Challenge – Teams spend time writing follow-up emails after meetings and often miss key decisions or action items.
- Value – Faster post-meeting communication ensures accountability and keeps projects moving forward.
Meeting Notes Summary agent – @meeting_notes_summary
- Description – Turns meeting notes or a transcript into a one-page summary. The summary includes key decisions, action items by owner, and a parking lot.
- Challenge – Manually writing meeting notes takes time and often produces incomplete or inconsistent records.
- Value – Teams get a ready-to-share meeting record without manual write-up work and stay aligned on outcomes and next steps.
Meeting Preparation agent – @meeting_preparation
- Description – Synthesizes an agenda, prior notes, project context, attendees, and an optional URL into a scannable one-page meeting brief.
- Challenge – Preparing for meetings requires gathering context from multiple sources, which takes time and often results in incomplete preparation.
- Value – Teams walk into meetings fully prepared in under two minutes, leading to more focused discussions and faster decisions.
Newsletter Body Editor agent – @newsletter_body_editor
- Description – Drafts email body copy based on a topic, target audience, and preferred brand voice.
- Challenge – Writing high-conversion email copy requires specialized copywriting skills and significant time.
- Value – Accelerate email production cycles and increase click-through rates with conversion-focused copy.
Presentation Outline Generation agent – @presentation_outline_generation
- Description – Transforms a topic, goal, or raw content into a structured, slide-by-slide presentation outline.
- Challenge – Structuring a presentation from scratch or from unorganized notes takes significant time and narrative expertise.
- Value – Teams reduce presentation planning time and receive a consistent, goal-aligned structure ready for visual development.
QR Code Generation agent – @qr_code_generation
- Description – Creates Quick Response (QR) codes for various purposes.
- Challenge – Manually generating and managing QR codes for various marketing materials is inefficient and error-prone.
- Value – Enhanced engagement, tracking, and marketing efficiency.
Quote Extraction agent – @quote_extraction
- Description – Takes a source document or text and extracts important quotes.
- Challenge – Manually sifting through long documents to extract the most important and relevant quotes is inefficient and time-consuming.
- Value – Time saved, efficient content creation.
Target Group Guidance agent – @target_group_guidance
- Description – Creates a visual, step-by-step guide for building a target group in Optimizely Campaign.
- Challenge – Mixed logic, action filters, and nested condition groups make target groups difficult to configure in the Campaign UI.
- Value – Teams configure accurate target groups faster and reduce segmentation errors before they send mailings.
UTM Creation agent – @utm_creation
- Description – Simplifies the creation of UTM parameters. UTM parameters are tags added to the end of a URL. They help track the source, medium, and name of a marketing campaign in website analytics.
- Challenge – Manually creating and checking UTM parameters for campaign tracking is complex and error-prone.
- Value – Ensures accurate attribution tracking, improves data quality, and simplifies campaign analysis.
Note
If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applications.