What The Prompting Company users actually want
Mimir analyzed 15 public sources — app reviews, Reddit threads, forum posts — and surfaced 14 patterns with 7 actionable recommendations.
Top recommendation
AI-generated, ranked by impact and evidence strength
Build an AI-optimized content generator with prompt-specific recommendations and markdown templates
Rationale
12 sources identify measurement and tracking as critical, but 6 sources explicitly state that current tools provide visibility without actionable execution. Users want to move from seeing their Visibility Score to fixing it without hiring agencies. The gap between tracking and doing is the biggest friction point in the workflow.
Starter plan users must create content themselves but lack guidance on formatting and structure. 3 sources note that DIY teams struggle with structured markdown requirements, and 9 sources emphasize that AI models prioritize specific content characteristics (factual, structured, verifiable). Users know what content should look like but don't have tooling to produce it at scale.
This recommendation addresses the core workflow bottleneck. Pro plan users get 8 articles per month, but Starter users get zero content support despite needing it most. A guided content generator that produces AI-optimized drafts based on identified questions would convert more free report recipients to paid Starter users and reduce churn among teams who sign up but can't execute independently. Without this, the product remains a reporting dashboard instead of a growth platform.
More recommendations
6 additional recommendations generated from the same analysis
5 sources document that AI model retraining and algorithmic shifts cause unpredictable visibility fluctuations. Users receive a Visibility Score but have no way to know when it degrades until they manually check the dashboard again. One source explicitly notes that scores should be interpreted as directional indicators rather than absolute metrics due to answer variability.
5 sources describe the free report as the primary lead generation mechanism in a funnel that drives demo bookings and paid conversions. The report currently provides brand mention frequency, but users need context to understand whether their visibility is competitive. One source notes that client results vary by industry competitiveness, but prospects have no way to assess their standing before purchasing.
8 sources position the product as helping companies get cited across multiple LLMs (ChatGPT, Gemini, Claude, Perplexity, DeepSeek). 5 sources note that each model has distinct data sources and refresh cycles, causing visibility to differ across platforms. Users currently receive an aggregated Visibility Score but can't diagnose which models cite them and which don't.
7 sources describe the Analyze-Create-Route workflow, with the final step directing AI crawlers to structured markdown content. But there's no evidence that users can verify whether crawlers are actually accessing their content or whether indexing succeeded. 5 sources note that visibility scores fluctuate unpredictably with model updates, but users can't distinguish between content quality issues and technical access problems.
12 sources identify measuring brand mentions in AI answers as a critical capability, and 7 sources describe the Analyze step of identifying key customer questions. But there's no indication that users can see which questions are high-value or who currently wins those citations. Users must guess which prompts to optimize for without understanding the competitive landscape.
10 sources describe a tiered service model with fixed limits: Starter tracks 25 prompts, Pro includes 3 seats and 8 articles, Enterprise offers custom limits. But 5 sources note that client results vary by industry competitiveness and relevance to frequently asked questions. Users don't know which prompts matter most until they start tracking, yet they must commit to a fixed plan size upfront.
The full product behind this analysis
Mimir doesn't just analyze — it's a complete product management workflow from feedback to shipped feature.
Themes emerge from the noise.
Ranked by severity and frequency, with the original quotes inline so you can judge for yourself.
Talk to your research.
Ask questions, get answers grounded in what your users actually said.
What's the top churn signal?
Onboarding confusion appears in 12 of 16 sources. Users describe “not knowing where to start” [Interview #3, NPS]
A prioritized backlog, not a wall of sticky notes.
Ranked by impact and effort, with the reasoning you can actually defend in a roadmap review.
PRDs, briefs, emails — on demand.
Generate documents that reference your actual research, not generic templates.
Paste, upload, or connect.
Transcripts, CSVs, PDFs, screenshots, Slack, URLs.
This analysis used public data only. Imagine what Mimir finds with your customer interviews and product analytics.
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