Sharon Owens

One of the most effective and affordable marketing strategies is WOM (word of mouth) getting other people to share your product and potentially spark curiosity or create a domino effect.

Over the past few days, several people:

have shared screenshots of my tool on social media,
sent me DMs saying they like it, or
left reviews on the Chrome Web Store.
I plan to use them in:
the landing page
 marketing materials (Chrome Web Store)
 possibly advertisement and "show off on socials"

Looking for something that can track, in one dashboard:

• Brand mentions and citations across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overview

• Keyword rankings and search volume, verified against live Google data

• Competitor tracking with an actual threat score, not just "similar companies"

• On-page/technical SEO audits with specific fixes, not vague advice

• Backlink monitoring, including newly lost links

• Review and sentiment tracking across platforms

• A hallucination check, for when an AI says something wrong about the brand

Right now I'm running separate tools for SEO, social listening, and manually checking what ChatGPT says about us. It's slow and nothing talks to anything else.

Has anyone found a platform that does this end to end? Open to both known names and newer tools.

I'm a veteran and solo founder with no formal coding background. Spent the last few weeks directing Replit's AI agent (with Claude as a strategic/QA partner) to build a real production app, entirely from my phone.

The part that surprised me: the "vibe" is the easy 20%. The other 80% was the same discipline any build needs catching bugs by hand (missing auto-capitalization, a timezone off-by-one, a file upload limit rejecting real phone photos), refusing to accept "it's fixed" without proof, running full walkthroughs section by section, chasing root causes instead of patching symptoms.

That's made me rethink what "vibe coding" even means. It's not skipping the engineering discipline it's relocating it. Instead of writing code, you're writing precise instructions, reviewing output critically, and doing QA like a hawk. If anything it demands more discipline, not less, because you can't rely on catching mistakes by reading your own code you have to actually test everything.

For others who've directed an AI agent instead of hand-coding: has your experience matched that, or did you find a different bottleneck? What ended up being the hardest part for you the instructing, the reviewing, or something else entirely?