A page can cover a topic without answering what someone actually needs to know. “Find a local plumber” doesn’t help a homeowner understand why the same drain keeps clogging or what to ask before booking another visit.
I built an n8n workflow to bring useful details from Reddit discussions into existing website content. The original project covered camping pages, but the same approach can help home service directories, a project I’m working on now to better align searchers and AI results with local service providers.
TL;DR
- Use relevant Reddit discussions to find concerns and details your pages leave unanswered.
- Keep each topic tied to a destination URL, then draft useful answers from the source material.
- Check the facts and write clear answers that readers and search systems can understand on their own.
Why I Moved Away From Automated FAQs
The project started with AlsoAsked and automated question-and-answer generation. After reviewing the initial questions, I removed AlsoAsked from the scope and shifted to Reddit, mainly because AlsoAsked didn’t fill the questions gap for the industry I was working on and we had already aligned many of those same questions with our existing UGC to create more helpful content for visitors.
But asking AI to turn every discussion into FAQs created another problem. Some questions felt manufactured or didn’t fit the page.
I changed the goal: extract useful commentary and turn it into one or two practical paragraphs. A discussion about camping access, road conditions, or finding a spot didn’t need to become five separate questions.
I still think FAQs have a place. I’d use them when there’s a distinct question worth answering, rather than requiring every topic to fit that format.
What the Reddit n8n Workflow Actually Did
The n8n workflow followed a straightforward process:
- Read Google Sheets inputs. Each row paired a search phrase with an existing page URL. H1s helped define the search topics.
- Search Reddit. The workflow searched for relevant posts and selected a small set for further processing.
- Retrieve posts and comments. The build used Reddit API credentials and comment requests, with batching and delays.
- Draft a summary with OpenAI. The prompt directed the output toward short, practical paragraphs.
- Return results to Google Sheets. The destination URL stayed associated with the output for review.
The page association came from the input sheet. The tool wasn’t independently choosing the best destination.
It also needed adjustments. After delivery, I reduced the posts and comments processed and changed parts of the workflow to get runs to finish. Keeping the amount of retrieved content manageable and tighter was as important as editing the prompt.
Examples: How The Reddit n8n Discussions Retrieval Could Improve Home Service Pages
These examples are illustrative applications of the camping workflow. They show the kinds of questions I’d investigate and how verified answers could improve thin pages within a home services directory website.
HVAC: Explaining Conflicting Replacement Quotes
Thin content: “Find local HVAC contractors for AC replacement.”
Questions to investigate: Why does one quote include ductwork? Is equipment removal included? Why did another contractor recommend repair?
Possible addition: “Compare the equipment and work included in each estimate. Ask whether removal, thermostat changes, proposed ductwork, and permits where required are included. If contractors recommend different work, ask what findings support each recommendation.”
That helps someone compare offers before calling another company.
Plumbing: Clarifying a Recurring Drain Problem
Thin content: “Book a plumber for drain cleaning.”
Questions to investigate: Does the charge cover clearing the blockage or investigating its cause? What happens if it returns?
Possible addition: “When booking, explain how often the blockage returns and what previous work was done. Ask what the quoted service covers, what could cost extra, and whether any follow-up terms are provided in writing.”
The page helps the visitor prepare without trying to diagnose the plumbing remotely.
Electrical: Comparing EV Charger Estimates
Thin content: “Find electricians for home EV charger installation.”
Questions to investigate: Is the charger included? Why does one estimate include panel work?
Possible addition: “Check whether each estimate includes the charger, circuit installation, proposed panel work, and permits where required. If a panel upgrade is recommended, ask what assessment supports it.”
Each addition addresses a specific uncertainty instead of adding another generic service description.
Use UGC to Find Gaps, Then Check the Answers
A Reddit discussion can reveal confusion. It doesn’t prove that a diagnosis, price, or recommendation is correct.
I’d preserve the source references during review, check factual claims, and leave out details the evidence doesn’t support. More specific AI output isn’t necessarily more accurate. I found this out through several revisions and trying to “tame” the large chunks being retrieved in the outputs.
The finished paragraph is editorial content informed by user-generated content. It shouldn’t appear as a customer review or imply firsthand experience with a listed business.
Make Answers Easier to Find and Understand
For AI Overviews and other answer systems, I’d focus on whether a passage clearly answers the question. Name the service, give the answer early, and include conditions that affect it. Keep local claims specific to evidence from that location. An HVAC answer/question in NC could be quite different from an HVAC company in AZ or CA.
That makes the content easier to understand and potentially retrieve, but it doesn’t guarantee selection or citation.
I’d also extend the research to check where the site appears organically and which competitors advertise around those buyer questions. That could guide page improvements and small paid search tests.
Start with one page and a few unanswered concerns. Add the explanation(s) someone needs before taking the next step.