From web signals to improvement actions
An analysis agent brings together technical, content, traffic and behaviour signals from your website and proposes concrete improvements.
Make the page clearer
Improve loading speed
Turn separate web signals into improvement actions.
Marketing and web teams review traffic in Google Analytics, search performance in Google Search Console or Bing Webmaster Tools and visitor behaviour in separate behaviour tools. Technical and content signals often live somewhere else entirely. This means they have to click through multiple dashboards and piece together the story for each page themselves before it becomes clear what deserves attention in the marketing process.
The analysis agent reads the agreed data directly from the sources and brings it together for each page. It identifies one pattern, shows the signals used and proposes concrete improvements to technology, content, traffic or conversion. A marketer reviews the supporting evidence and decides which actions go into the work plan.
Fewer dashboards to compare
Your team receives one or two improvement actions with the relevant signals, without having to click through separate interfaces for every analysis.
The whole page in context
You see how discoverability, traffic, content, technology and visitor behaviour affect each other on one page.
Actions with visible supporting evidence
The marketer sees which signals underpin the proposals and whether the main opportunities lie in technology, content, traffic or conversion.
How your team moves from website analysis to action.
The agent compares traffic, search visibility, behaviour, content and technical quality for each page. A marketer decides which proposed improvement actions go into the work plan.
- 01SYSTEM
The weekly data becomes available
The agreed traffic, search, behaviour and technical data together start one analysis.
Why: This ensures the agent always compares the same period, pages and definitions.
- 02AGENT
The agent connects the signals for each page
The agent combines discoverability, traffic sources, usage, conversion and technical quality for each page.
Why: A signal only becomes meaningful when it is clear what visitors expected, found and then did.
- 03AGENT
The agent proposes one or two improvement actions
The agent describes the patterns, lists the signals used and formulates one or two improvement actions for technology, content, traffic or conversion.
Why: The marketer gets a concrete starting point that can be traced back to the measured data.
- 04HUMAN
A marketer assesses the priority
The marketer checks the supporting evidence and takes campaigns, planning and the target audience into account.
Why: Measured data does not always show which event or decision influenced the behaviour.
- 05SYSTEM
The selected actions are recorded
Only approved proposals are recorded in the work plan.
Why: The team decides what is carried out and the agent does not change the website independently.
Connect the data sources your team currently reviews separately.
Traffic analysis shows how visitors arrive. Webmaster tools show search queries, impressions and indexing. Behaviour tools reveal clicks, scrolling and drop-off, while technical measurements flag problems with speed and page structure.
AI agent
Custom agent
Start with one weekly analysis.
Limit the first version to a fixed group of pages, events and follow-up actions. This lets you compare proposals week by week.
For this version, all you need is: Access to aggregated website data, A fixed list of pages and goals, A place for approved actions.
- 01
Choose which pages and which traffic, search, behaviour and technical signals the agent may compare each week.
- 02
Define when the agent has too little or conflicting data for a proposal.
- 03
Have a marketer review every proposal before the selected actions are put in the work plan.
Keep the first version's scope clear. One weekly analysis produces one or two improvement actions, provided the data offers sufficient supporting evidence. The agent does not change any website, campaign or measurement setting.
The agent drafts a proposal; your team decides what to save. Test a normal week with sufficient traffic on the selected pages. Test a week in which a known campaign, content change or technical incident affected the figures. Test sparse, conflicting or incomplete data and check that the agent flags the uncertainty. Check that only approved proposals reach the work plan.
Use a ready-made prompt.
Use this prompt in Claude, Claude Code, ChatGPT, Codex, Microsoft Copilot or Gemini. The agent starts with the questions below before building a clearly scoped first version.
Would you like en:twine to help you build it? Contact us.
- 01Which pages and desired follow-up actions do you want to track each week?
- 02Which traffic, search, behaviour and technical sources may the agent use?
- 03Which improvements fall under technology, content, traffic and conversion for your team?
- 04When is the data strong enough to support an improvement proposal?
- 05Who reviews the proposals and where do approved actions go?
- 01Read the agreed data for a fixed period directly from the chosen data sources.
- 02Connect traffic, search visibility, behaviour, conversion and technical quality for each page.
- 03Have the agent propose one or two improvement actions with supporting evidence and visible uncertainties.
- 04Have a marketer review every proposal before the selected actions are put in the work plan.
The full prompt includes the workflow URL, sources, AI solutions, integrations, questions, build steps and safety boundaries.
Does the weekly analysis produce good actions? Make it a regular way of working.
en:twine helps set up measurement definitions, exceptions, prioritisation and follow-up so that multiple marketers can work with them.