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Directed Attention Analytics
Build an analytics SaaS that tells marketers whether controversial or mistake-driven engagement actually improves meaningful outcomes like clicks, leads, and subscribers. The core value is separating profitable attention from vanity noise and showing which posts produce the right audience response.
Why this matters
You run social content and keep getting judged by likes, comments, and spikes in visibility, but you know those numbers can mislead. A post with a tiny mistake might attract hundreds of corrections, yet still fail to bring qualified traffic, signups, or buyers. Existing dashboards show volume and reach, but not whether the attention was useful. You end up manually reading comments, comparing follower jumps, and guessing whether the controversy was productive or just distracting. What you really need is a clear way to see which posts pull the right people closer to your offer and which ones merely create noise that looks impressive in a report.
- · Built for Small marketing agencies, creator-led brands, and in-house social teams running frequent content campaigns and judged on engagement plus business outcomes..
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You run social content and keep getting judged by likes, comments, and spikes in visibility, but you know those numbers can mislead. A post with a tiny mistake might attract hundreds of corrections, yet still fail to bring qualified traffic, signups, or buyers. Existing dashboards show volume and reach, but not whether the attention was useful. You end up manually reading comments, comparing follower jumps, and guessing whether the controversy was productive or just distracting. What you really need is a clear way to see which posts pull the right people closer to your offer and which ones merely create noise that looks impressive in a report.
Score Breakdown
Market Signal
Go-to-Market
Boutique agencies and in-house social leads managing 10 to 100 posts per month for brands that track both engagement and lead generation.
~50K-150K active teams globally in the initial SMB and mid-market segment
cold outbound
$79/month
15 paying teams connecting at least two social accounts and reviewing weekly post-level outcome reports within 30 days
MVP Scope · 1–2 weeks
- Define a directed-attention scoring model using comments, clicks, follows, and conversions
- Build a basic importer for one social platform plus Google Analytics
- Create a database schema for posts, comments, and attributed outcomes
- Implement comment tagging for correction, argument, praise, and intent
- Design a simple dashboard showing top posts by useful versus noisy engagement
- Add account onboarding and OAuth for the initial integrations
- Ship post-level reports with engagement-to-outcome comparisons
- Add weekly email summaries highlighting misleading high-engagement posts
- Test the score with five pilot users and refine thresholds
- Launch a landing page with a demo and self-serve checkout
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1The strongest risk is weak attribution because many social interactions do not map cleanly to revenue, reducing trust in the score.
- 2A second risk is that native dashboards may feel good enough if the product does not save substantial analysis time.
- 3A third risk is that API restrictions or pricing changes could make cross-platform coverage too thin for customers.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
Several participants drew a clear line between attention and useful attention, arguing that marketers often overvalue visibility without checking whether it advances the message or business goal. One example described a content mistake that produced comment wars, more views, and subscriber growth, suggesting a measurable pattern worth analyzing. Multiple remarks also pointed to client pressure for virality, reinforcing demand for reporting that translates noisy engagement into business relevance.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Directed Attention Analytics
Sub-headline
Build an analytics SaaS that tells marketers whether controversial or mistake-driven engagement actually improves meaningful outcomes like clicks, leads, and subscribers. The core value is separating profitable attention from vanity noise and showing which posts produce the right audience response.
Who It's For
For Small marketing agencies, creator-led brands, and in-house social teams running frequent content campaigns and judged on engagement plus business outcomes.
Feature List
✓ Cross-platform post and comment ingestion ✓ Directed-attention score tied to clicks, follows, and conversions ✓ Comment classification into confusion, debate, praise, and purchase intent ✓ Post-level reports showing when engagement helps or harms outcomes
Where to Validate
Share your landing page in r/r/marketing — that's exactly where these pain points were discovered.
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