How Maya Stalker Works: 7 Steps From a Social Mention to AI Visibility

Languages / Diller: English (this page) · Türkçe

Last checked: October 13, 2026

Most social listening tools stop at a dashboard of mentions. Stalker starts there. It scans 11 sources for your keywords, uses AI to throw away the noise, labels the tone of what's left — and then does the part that matters for AI search: it connects those conversations to how ChatGPT, Gemini and other assistants talk about you. Here's the whole pipeline, step by step. (Watch the 2-minute video.)

What is Stalker? (short answer)

Stalker is Maya's social listening engine: it finds brand mentions across social platforms and review sites, AI-judges each one for relevance and tone, shows which posts AI assistants actually cite, and turns the questions people ask into prompts you can track in AI search. The loop is UGC → Prompt → AI visibility.

1. You pick the keywords

A scan starts with a keyword set: your brand, products, competitors, category terms. Keyword allowances are per plan, and saving the list re-runs the scan. For Turkish brands, Stalker also expands suffixed forms automatically (searching "Pronet" also catches "Pronetten", "Pronete") — casual mentions written without an apostrophe are not missed.

2. Stalker scans 11 sources

Group	Sources	What it reads
Social	Reddit, X, LinkedIn, YouTube, Instagram, TikTok	Posts, threads, videos, Reels, captions
Reviews	G2, Trustpilot	Customer reviews of your company
Turkish UGC	Şikayetvar, Ekşi Sözlük, Kızlar Soruyor	Complaints, entries, Q&A conversations

Each source is searched the way it actually works: Reddit and X take OR-combined queries with a date window, Instagram and TikTok are searched keyword by keyword, Instagram additionally walks your brand hashtag feed, and the review and UGC sites are searched through the web index. You choose which sources run; the Turkish sources are available in every market.

3. AI reads every mention before you do

Raw keyword matching is where classic tools leak time: "apple" the fruit, a username collision, an unrelated acronym. Every post Stalker fetches is judged by AI with your brand context (name, domain, aliases, industry) and gets a relevance score — only genuinely on-topic mentions reach your feed.

4. Every mention gets a tone

The same judging pass labels sentiment: positive, neutral or negative. The feed's PulseBar compresses the whole listening window into one glance — the tone split of everything heard. Filters let you cut by platform, sentiment, keyword and day range.

5. Mentions are cross-checked against AI answers

This is the step classic social listening can't do. Maya already tracks which sources AI assistants cite when answering your prompts — so Stalker shows, per mention, how many times that exact URL appeared as a source in tracked LLM answers, and on which providers.

That column changes your priorities. A Reddit thread with three upvotes that ChatGPT cites weekly is part of your answer supply chain; a viral post no assistant ever reads is just noise with reach. There's a cited-only filter for exactly this triage.

6. Questions become tracked prompts (UGC → Prompt)

Stalker reads the relevant mentions and proposes the underlying questions as prompts: buying concerns, comparisons, "is X worth it" threads. Each suggestion comes with the real posts that inspired it as evidence — nothing is invented. One click adds the question to your tracked prompts, and from then on Maya measures whether AI assistants mention you when answering it.

This is the core value of the whole pipeline: the conversation already happening about you becomes the exact set of questions you measure your AI visibility against.

7. You act where it counts

A practical working order:

1. Filter to cited-only first. These posts already influence AI answers about you.
2. Handle negative-cited mentions at the source — respond, correct facts, or publish a better page that can outrank the thread as a source.
3. Reinforce positive-cited mentions — they're doing AEO work for you.
4. Watch competitor keywords — threads comparing you to competitors are tomorrow's comparison-answer sources.
5. Accept the prompt suggestions that match real buying intent and watch them in Prompt Lab.

Why this matters for AEO and GEO

Generative engines don't form opinions in a vacuum — they synthesize from sources, and user-generated content is heavily represented in those sources. Monitoring UGC without connecting it to AI answers tells you what people say; connecting the two tells you what the machines repeat. That's the difference between social listening as PR hygiene and social listening as a generative engine optimization input.

Try it

Every project gets a free first scan across all sources. Open Stalker, pick your keywords, and see your mention landscape in a few minutes — then decide what's worth tracking.

Appearing in AI answers is influenced by many factors; no tool can guarantee inclusion or rankings.