Template
Content Funnel Segmentor
Segment your site content into bottom, middle, or top of funnel.
Trying to grow traffic is one thing—turning that traffic into revenue is another. Most websites are bursting with TOFU blog posts while MOFU tutorials and BOFU case-studies are scattered (or missing altogether). Manually opening every URL, skimming the copy, and updating a spreadsheet is soul-crushing and often skipped. Yet the data is clear: teams that nurture leads with funnel-aligned content drive 73 % higher conversions and 50 % more sales-ready leads at lower cost. The “Segment Content Funnel Stage” app above removes that grunt work by auditing any sitemap, giving you an instant TOFU / MOFU / BOFU map you can act on. For instance, our content automation examples offer a closer look at similar workflows.
Walkthrough: how the app works in Moonlit
1. Collect the URLs
We start with Extract Sitemap URLs. Drop in a sitemap, add an optional path filter (e.g., “/blog/”), and the node returns up to 100 rows with the URL, the page title, and its meta description. No crawling limits, no regex headaches—just a clean table ready for analysis. If you’re interested in streamlining your processes even further, you might want to automate content optimization for improved website performance.
URL | Page Title | Meta Description |
---|---|---|
https://example.com/blog/seo-basics | SEO Basics: A Beginner’s Guide | Learn the fundamentals of SEO and how to optimize your website for search engines. |
https://example.com/blog/content-strategy | Building a Winning Content Strategy | Discover actionable steps to create and execute a successful content marketing plan. |
https://example.com/blog/technical-seo | Technical SEO Checklist | A comprehensive checklist to ensure your website meets all technical SEO requirements. |
https://example.com/blog/link-building | Effective Link Building Tactics | Explore proven strategies to build high-quality backlinks and boost your rankings. |
2. Give the model brand context
Classifying funnel stage without company context leads to errors (a “pricing” page might be MOFU for one brand, BOFU for another). A second branch scrapes the main landing page you provide (Scrape Webpage with “page-summary” output). The summary tells the model what the product does, typical customers, and positioning—crucial signals when judging whether a blog post leans educational or sales-driven. Learn how to maintain a consistent tone in your content with advanced AI in our post Maintain Brand Voice across Thousands of Pages with AI.
3. Classify each URL
The Chat Model (GPT-4o) receives:
the sitemap table
the landing-page summary
clear definitions of TOFU, MOFU, and BOFU
It returns a strict JSON list such as:
4. Turn the JSON into a snapshot
A short Python Function converts the list into a dataframe, groups by segment, and outputs a count per stage. The app surfaces both the raw table and an auto-generated pie or bar chart so you can spot gaps at a glance (e.g., “79 % TOFU, only 6 % BOFU”).
Customization ideas
Custom segments: swap TOFU / MOFU / BOFU for your own lifecycle labels—Awareness, Consideration, Decision, Retention—by editing the prompt.
Add prioritization logic: extend the Python step to calculate a “gap score” (e.g., traffic × segment scarcity) and export a task list for writers.
Team notifications: pipe the JSON into Zapier or Slack via a Webhook node to alert the content team whenever the BOFU ratio drops below a threshold. You can also explore how content automation can further boost your team’s efficiency.