Lily AI vs ScreenplayIQ

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-10-08
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At a glance

DimensionLily AIScreenplayIQ
Target UsersE-commerce marketing teams, enterprise retailers, agenciesScreenwriters, producers, studio executives
Core FunctionProduct catalog enrichment for ad feeds and AI shoppingScreenplay analysis and box office prediction
Key DifferentiatorGoal-based AI agents, A/B testing, measurable revenue liftFinancial ROI prediction, narrative structure analysis
IntegrationsGoogle Ads, Meta Ads, Google Merchant Center, etc.PitchTrailer
Best ForPerformance marketing, large catalogs, AI surface readinessFeature film analysis, studio decisions

Lily AI and ScreenplayIQ serve entirely different audiences — one optimizes e-commerce feeds for measurable ad lift, the other predicts screenplay box office returns. If you're a retail marketer seeking to boost Google Shopping or Meta ad performance with AI enrichment, Lily AI is your tool. If you're a screenwriter or producer needing data-driven script feedback and financial forecasts, ScreenplayIQ fits better. The choice is purely domain-based.

Lily AI
Lily AI

Agentic product intelligence that enriches retail catalogs and proves lift with matched-spend tests on Google Ads, Meta Ads, AI discovery and onsite search.

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ScreenplayIQ
ScreenplayIQ

ScreenplayIQ runs AI screenplay analysis on your draft — logline, comps, character emotional journey charts, and inline proofread fixes for

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Pricing
Contact Sales
Paid
Plans
Custom
~$24 TV / ~$38 Feature
~$48 TV / ~$78 Feature
~$60 TV / ~$98 Feature
~$24 TV / ~$38 Feature
Popularity
6 views
7.5k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
WebAPI
WebAPI
Categories
🛒 Ecommerce & Retail💰 Ad Creative & Media Buying
📖 Fiction & Screenwriting
Features
Goal-based AI agents that enrich, evaluate and republish catalog data continuously
Overall enrichment scoring (0-100) with per-field and per-dimension gap analysis
Google Shopping attributes: five core attributes generated per SKU for feed approval and match quality
Meta catalog ads copy generated and quality-checked before it ships
Organic SEO and AEO metadata: titles, descriptions, alt text and schema markup
Conversational commerce attributes for chat and voice shopping assistants
Item setup and classification: category mapping and structured field population
PDP consumer product copy written on-brand for the storefront
Agent-ready, schema-validated payload generation for AI shopping surfaces
Google AI Performance Insights gap analysis surfacing high-demand search terms per product
Matched-spend A/B testing with holdout groups to isolate revenue lift
Difference-in-differences analysis with confidence intervals for finance-ready reporting
28-day holdout testing across Google Shopping, Meta and onsite search
Multi-surface optimization across Google Ads, Meta Ads, AI discovery and onsite search
Human approval workflow before changes reach any live feed
Generate a logline from a full screenplay draft
Surface comparable films and TV shows for market fit
Break a script into structured story points
Produce a full synopsis without reading the whole draft
Write character synopses for the full cast
Create visual representations of characters
Chart each character's emotional journey across the script
Deliver a full assessment analysis of the draft
Break down the story's themes
Proofread report with inline highlights on every issue
Recommend a fix for each flagged issue
Build a custom analysis package outside the presets
Price analysis by page length, quoted separately for TV and features
Store uploaded scripts in encrypted, siloed storage
WGA-compliant handling of submitted scripts

Who should pick which

  • E-commerce performance marketer
    Pick: Lily AI

    Lily AI’s Google Shopping and Meta ad integrations, plus A/B testing for feed changes, directly improve ROAS and revenue, as shown in their 28% uplift results.

  • Screenwriter seeking script market feedback
    Pick: ScreenplayIQ

    ScreenplayIQ provides structural analysis, genre classification, and box office predictions, helping writers refine scripts for commercial appeal.

  • Film studio executive
    Pick: ScreenplayIQ

    Its comparative market data and financial forecasting aid slate decisions, with Studio tier supporting team collaboration.

  • Agency managing multi-brand e-commerce
    Pick: Lily AI

    Lily AI’s agent-based enrichment and multi-channel optimization align with agency needs for scalable feed management across clients.

Frequently Asked Questions

Lily AI vs ScreenplayIQ: which should you choose?

Lily AI and ScreenplayIQ serve entirely different audiences — one optimizes e-commerce feeds for measurable ad lift, the other predicts screenplay box office returns. If you're a retail marketer seeking to boost Google Shopping or Meta ad performance with AI enrichment, Lily AI is your tool. If you're a screenwriter or producer needing data-driven script feedback and financial forecasts, ScreenplayIQ fits better. The choice is purely domain-based.

Which tool is cheaper?

ScreenplayIQ has transparent pricing starting at $19/mo; Lily AI requires contact, though it offers a free trial.

Can Lily AI help with AI shopping assistants?

Yes, Lily Max generates agent-ready payloads for LLM assistants like ChatGPT and Gemini, aligning with trends in Agentic commerce.

Can ScreenplayIQ analyze TV scripts?

No, it currently supports only feature films (under 150 pages).

Do these tools integrate with each other?

No, they serve entirely different domains with no integration.

Is there a free version?

Lily AI offers a free 30-day trial (500 products). ScreenplayIQ has a free tier (1 analysis/month).

Which tool offers A/B testing?

Lily AI features controlled A/B testing for feed changes; ScreenplayIQ does not.

Does ScreenplayIQ predict box office earnings?

Yes, it uses narrative and market data to forecast box office performance.

Does Lily AI require a product feed system?

Yes, it enriches existing product feeds, so teams need a basic catalog infrastructure.

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Last reviewed: July 3, 2026