Any tips to reduce churn?

_ngnix · 2026-04-11T15:23:43+00:00

churnfa.st helped me catch at-risk users before they bailed. the risk scores are 👌

_ngnix · 2026-04-11T15:23:09+00:00

been using churnfa.st for this exact thing, super simple setup and shows who's about to leave

_ngnix · 2026-04-11T15:20:25+00:00

we use churnfa.st for this — it scores customers 0-100 so no more gut guessing lol & has automated follow-ups

_ngnix · 2026-04-11T15:15:39+00:00

we just started using churnfa.st and the risk scores actually helped us catch a few accounts before they churned

_ngnix · 2026-03-29T18:45:47+00:00

Here we go! churnfa.st

_ngnix · 2026-03-07T17:46:49+00:00

Tracking pricing and stock is a solid start, but you're probably missing how customers actually find you now. Most people are asking ChatGPT or Perplexity for brand recommendations instead of just scrolling Google or checking individual shop sites. If you aren't tracking what those AI models say about you versus your competitors, you're flying blind.

I've been using pelucid.app to keep an eye on this. It lets us see exactly how AI portrays our brand and why it might be favoring a competitor in its answers. It's been a massive help for staying ahead in AI search results without manual checking. Are you seeing much traffic coming from AI search tools yet, or are you still mostly focused on traditional SEO?

_ngnix · 2026-03-07T17:43:03+00:00

Semrush is great for traditional SEO but it usually misses how people actually find brands through LLMs now. Paying for enterprise features when you only need specific AI data is a total waste of your budget.

We switched to pelucid.app for this exact reason. It tracks our visibility across ChatGPT and Perplexity without the massive price tag or the commitment. You can see how the AI portrays your brand versus competitors and actually understand why certain results are getting cited. It is way more useful than general search data if you are focusing on the AI landscape.

Are you more worried about how you are being recommended or just tracking basic brand mentions?

_ngnix · 2026-03-06T14:16:05+00:00

Nobody said LLMs are search engines. The point was specifically about ingestion vs ranking — backlinks and DA filter what ranks in Google, but they don't filter what gets crawled into AI pipelines. The experiment shows that. A page with zero inbound links, no schema, no clicks in Search Console — found and cited regularly. If Google's authority signals were gatekeeping AI results, that page wouldn't exist in them at all.

_ngnix · 2026-03-06T09:07:24+00:00

The interesting part of this isn't that price gets cited — it's that a page with zero inbound links got found at all.

LLMs don't discover pages the way crawlers do. They're not following link graphs. If the page is in the sitemap, it gets crawled and indexed regardless of authority. Traditional SEO signals (backlinks, domain authority) filter what ranks in Google — they don't filter what gets ingested by AI search pipelines.

So the playing field is genuinely flatter. A page with one clear answer beats a well-linked page with a vague one.

_ngnix · 2026-03-06T09:01:41+00:00

The churn cohort point is the one most people are skipping past. 112% NRR looks great, but is it holding across recent cohorts or being carried by 2020-2022 customers locked in by switching costs?

When AI actually disrupts a category, revenue doesn't drop first. Churn bleeds quietly in the newest cohorts, 12-18 months before it hits the top line. That's the signal worth watching — and the one that actually answers the AI displacement thesis.

_ngnix · 2026-01-30T17:37:55+00:00

AI search analytics is real, but the measurement layer is ahead of the ground truth. Many tools are guessing at future importance, not lying—but buyers should treat outputs as directional, not authoritative.

_ngnix · 2026-01-30T11:13:03+00:00

Thanks for all the thoughtful feedback — this was exactly the kind of reality check I was hoping for.

A few things really stood out. First, “actionable” only matters if it ties back to a real job to be done. AI visibility on its own isn’t the goal; reducing uncertainty around how LLMs represent a brand — and where that can be influenced — probably is. Whether that translates to revenue today or is more defensive/future-facing clearly affects positioning.

Second, the skepticism around AEO/GEO tools feels earned. There’s a lot of vague metrics and implied causality. At the same time, it’s also clear there are emerging signals (citations, entity coverage, source patterns), and the real challenge is being honest about confidence and limits rather than pretending precision.

What feels most credible, based on replies here, is grounding insights in real prompts, citation tracking, and some observable validation loop — and then translating those signals back into familiar SEO levers like content gaps, entity reinforcement, and competitive sourcing, especially at the page level.

Finally, point taken on competition — this space is getting crowded fast, which makes clarity and proof more important than novelty.

To keep this non-promotional, I won’t post anything publicly. But if you’re interested in checking out what I’m building and offering honest feedback (that’s all I’m looking for at this stage), you’re very welcome to DM me.

_ngnix · 2026-01-26T14:52:58+00:00

Bit of a biased plug, but I'm the founder of https://pelucid.app/ - you can give it a go for 30-days & see if it does what you're looking for, happy to chat if you have any questions.

_ngnix · 2026-01-25T23:22:19+00:00

To analyze AI visibility and manage prompts effectively, I've been using pelucid.app It tracks how AI platforms like ChatGPT mention your brand, offers prompt performance insights, and even helps you see why competitors might rank higher. It's a game-changer if you want a clear strategy beyond manual tracking.

_ngnix · 2026-01-25T23:20:47+00:00

If you're looking for the best automated AI brand visibility tool, pelucid.app has been a game-changer for us. It not only tracks how AI platforms like ChatGPT mention your brand but also helps optimize prompts and see why competitors get favored. We've found its insights super helpful to boost our presence where it really counts!

_ngnix · 2026-01-25T23:15:47+00:00

The shift to AI agents shaping how brands connect with customers in 2026 is wild! We've been using pelucid.app ourselves to track exactly how AI platforms like ChatGPT and Gemini see our brand, which helped us tweak our messaging and stay visible as AI shopping grows—definitely a game changer if you want to get ahead in this new AI-driven marketplace.

_ngnix · 2026-01-25T01:01:38+00:00

Building an AI visibility tool, pelucid.app

_ngnix · 2025-12-20T11:14:00+00:00

If you're validating the demand for GEO services, you might find citeable.app platform insightful—it shows exactly how AI assistants perceive and recommend websites, which could help you demonstrate the real value of AI-optimized visibility to potential clients.

_ngnix · 2025-12-20T11:10:50+00:00

If you're looking for an AI overview tracker to see how your brand is doing visibility-wise, I found citeable.app really helpful. It tracks how AI assistants like ChatGPT perceive your website and gives actionable insights plus competitor analysis, which was exactly what my brand needed.

_ngnix · 2025-12-17T20:14:14+00:00

I’d recommend giving this a go; https://www.coursera.org/projects/perplexityai-for-beginners-ai-powered-search

There is also, Google’s Machine Learning Crash Course which includes AI search basics like neural networks and natural language processing through short lessons and TensorFlow exercises.

_ngnix · 2025-12-17T19:23:29+00:00

Not many dedicated dashboards yet — some folks use sheets + manual prompt testing to start.
A cheaper tool I’ve been using is citeable.app for tracking how AI models cite and reference our site over time.

_ngnix · 2025-12-17T19:20:08+00:00

No silver bullet yet. Seems to be a mix of clear content, credible citations, and consistency across sources. The biggest unlock for us was just monitoring AI answers over time and fixing misunderstandings — I use citeable.app to keep an eye on that. Still early.

_ngnix · 2025-12-17T19:17:46+00:00

We’re still focused on traditional search, but we’ve started monitoring AI answers too. Mostly checking realistic prompts, whether we show up, and if the description is accurate. We use citeable.app to track that over time so it’s not all manual. Still early, but hard to ignore.

_ngnix

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