The Optimizely Agent Platform organizes its directory around these stages. Here is how the work breaks down in practice, along with twelve agents worth setting up first.
How this changes day-to-day marketing
Connecting these tools into a single workflow changes what marketers spend their hours on.
Instead of spending the week copying text between tabs, reformatting docs, and compiling spreadsheets, the marketer's role centers on strategy and editorial judgment:
- You set the business objective and pick the positioning angle.
- The Campaign Brief Generation Agent sets up the project tasks.
- Content agents draft assets inside the CMS using shared brand rules.
- Experimentation agents build live variations to test on your audience.
- Reporting and GEO agents track results and surface opportunities for the next round.
That handoff work drops away, leaving your team free to focus on directing the strategy.
Stage 1: Research and planning
Before anyone writes a draft, someone has to decide what to build and why. In most teams, that means spending half a day bouncing between search consoles, competitor sites, customer notes, and spreadsheets to find an angle. When deadlines get tight, that discovery step usually gets cut short, which is how websites end up full of generic posts that never rank or convert.
These three agents handle that legwork upfront so planning starts from actual data.
Analyzes your topic, pulls search intent data, groups related queries into topic clusters, and hands back an organized brief structure.
- The good bit: Cuts out the routine of cross-referencing three separate SEO tools to build an editorial cluster.
- The catch: Results improve once you feed it your current content inventory and competitive baseline. Without that context, initial suggestions can lean broad.
- Verdict: The best starting point if you are launching an organic program or cleaning up a library that has drifted off strategy.
Generates vertical-specific messaging, industry pain points, and positioning angles across different target sectors.
- The good bit: Gives smaller teams credible industry depth without weeks of subject matter interviews or specialized outside copywriters for every market.
- The catch: Output depends on prompt detail. A prompt like "financial services" produces surface-level fluff, while "compliance tooling for mid-market fintech risk officers" gives you usable copy.
- Verdict: A practical install for product marketers and content leads covering several industries without dedicated vertical writers.
Tracks market shifts, competitor updates, and category trends across the web to pull out actionable talking points.
- The good bit: Automates the background research that tends to get skipped when deadlines loom.
- The catch: It gathers raw intelligence, but your team still needs to evaluate the findings and choose the angle that fits your brand.
- Verdict: Run this alongside the Keyword Research Agent whenever kicking off a major campaign.
Stage 2: Production and adaptation
Once an angle is set, the traditional workflow tends to stall out. Briefs sit in docs waiting on assignments. Writers draft in isolated tabs. When copy finally gets approved, someone spends hours pasting text into CMS components, fixing broken links, uploading images, and manually rewriting the core idea into social posts and email snippets.
These four agents turn approved briefs directly into assigned tasks and channel-ready assets where your team already works.
Takes a campaign concept and produces a seven-part brief where every required asset is broken into an individual, assignable task inside Optimizely CMP.
- The good bit: Goes straight from strategic input to assigned workflow without anyone building task cards by hand.
- The catch: The brief is only as thorough as your initial setup. You need to load brand guidelines and audience details into Instructions beforehand.
- Verdict: The first agent content leads should turn on to remove the blank-page bottleneck at the start of a project.
Drafts long-form editorial content using your established brand guidelines, approved terminology, and SEO parameters.
- The good bit: Drafts live directly inside your content platform where editing and publishing happen, eliminating copy-pasting between disconnected tools.
- The catch: It relies on your Instructions setup. If drafts feel off-brand, revisit your voice parameters and terminology rules.
- Verdict: Helpful for teams looking to take the friction out of building initial long-form drafts.
3. AI campaign kits
Builds a multi-channel asset package from a single campaign prompt, generating core copy, email sequences, and social promotional snippets in one run.
- The good bit: Keeps paid, email, and social teams aligned around the same messaging foundation.
- The catch: The kit provides the initial structure and drafts. Customer-facing copy still needs a quick human editorial review before going live.
- Verdict: Built for busy teams running high-volume campaign calendars who need consistent cross-channel assets fast.
4. Content refresh agent
Scans existing published URLs against current search queries, updated product facts, and fresh data to find sections that have decayed.
- The good bit: Unlocks organic traffic from older posts that used to rank well, without the expense of writing brand-new articles.
- The catch: Works best on articles with a solid underlying premise. Pages with weak foundational ideas usually need a full manual rewrite.
- Verdict: High return for teams with deep archives of published material that haven't been touched in years.
Stage 3: Discoverability and reporting
After publishing, content often disappears into a black box. Marketers log into Google Analytics, export CSVs, assemble pivot tables, and paste charts into slides to prove a campaign drove traffic. At the same time, search is shifting toward AI answer engines like ChatGPT and Perplexity, but most teams have little visibility into whether their pages are structured to be retrieved and cited.
These two agents automate reporting loops and audit your technical content structure for AI search engines.
Queries Google Analytics 4 data and generates clean, executive performance summaries from natural language questions.
- The good bit: Replaces manual CSV exports and repetitive slide-building with on-demand summaries.
- The catch: Built specifically for Google Analytics 4. Teams on other analytics stacks need custom connectors.
- Verdict: A quick win for marketing analysts who want to spend their time interpreting trends instead of pulling numbers.
Audits target pages against Generative Engine Optimization standards, reviewing entity clarity, crawler access, structured data markup, and citation readiness for answer engines.
- The good bit: Delivers concrete technical and semantic recommendations built specifically for AI search discoverability.
- The catch: It outputs a diagnostic task list rather than pushing live code changes. Your team still implements the recommended schema and copy updates.
- Verdict: Run this across your high-priority commercial and product comparison pages first.
Stage 4: Experimentation and optimization
In many marketing teams, optimization happens completely apart from content creation. Marketers hit publish and hope for the best. When conversion rates drop, someone files a ticket, waits weeks for design and front-end development, manually configures variations, and monitors test dashboards without a clear next step.
These three agents link directly into live user traffic to connect content creation with conversion optimization.
Evaluates live digital experiences, analytics context, and user drop-off points to generate prioritized A/B testing hypotheses.
- The good bit: Analyzes real user friction on your live site rather than relying on generic conversion checklists.
- The catch: Works independently. Pair it with backlog management agents so new ideas don't clash with active tests.
- Verdict: An immediate install for experimentation leads, growth marketers, and CRO teams.
Applies visual and copy adjustments directly into test variants based on an approved hypothesis.
- The good bit: Turns test ideas into deployable variations quickly, working around front-end development bottlenecks.
- The catch: Needs a clear hypothesis and defined metrics. It builds the variant, but the overall testing strategy still comes from your team.
- Verdict: The natural follow-up once the Experiment Ideation Agent is live.
Monitors experiments as they reach statistical significance, summarizing metric changes, revenue impact, and clear takeaways into a short readout.
- The good bit: Closes the testing loop with clear summaries ready to share with stakeholders.
- The catch: The readout depends on setting up reliable tracking and conversion goals before the test goes live.
- Verdict: Completes the testing pipeline alongside ideation and variant creation.
Building custom workflows with agent builder
Pre-built agents handle common marketing workflows, but every team has unique steps in their process.
The Agent Builder on the Optimizely Agent Platform offers a drag-and-drop workspace to create custom agents without technical help. You set the trigger, define brand instructions and guardrails, connect internal data sources, and test behavior in a sandbox before rolling the agent out to your team.
Explore all agents on the Optimizely Agent Platform.