Revenue rank on Toolify.
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Flim
A search engine for creative professionals to find images and video stills.
Market Data Board
373.4K monthly avgRead the market signal first
Traffic and channel data use SimilarWeb methodology; keyword metrics come from DataForSEO; ranking and revenue signals come from Toolify. Evidence snapshot 2026-07-06.Estimated monthly traffic (directional, not audited revenue).
Primary market category.
Non-brand search share indicates how much task-led discovery may exist.
Channel mix share of visits
Top countries traffic share
Competitor traffic three-month visits
Keyword Evidence
5 keywordsTask-keyword opportunity table
Score is Shipsite's opportunity score, blending the metrics on the left. Auditable inputs are Volume, KD, CPC, allintitle and KGR.| Keyword | Volume | KD | CPC | KGR | Score |
|---|---|---|---|---|---|
| flim ai | 590 | 10 | $0.68 | — | 44.9 |
| movie frame search | 10 | — | $1.81 | — | 9 |
| film still database | 480 | 25 | $8.52 | — | 54.3 |
| cinematography reference | 50 | 25 | $1.95 | — | 22.9 |
| shot reference tool | — | — | — | — | 0 |
KGR is shown once allintitle sampling lands for a keyword; Volume, KD and CPC are already auditable.
Product Evidence
0 capturesProduct and pricing captures
Only the product's own public pages are shown here.No public product screenshots passed the current evidence gate.
Strategy Frameworks
Business canvases and strategic analysis
Thirteen grounded views aligned with the site-building strategy desk: Business Model Canvas, Value Proposition Canvas, JTBD, ICP, Empathy Map, Customer Journey, SWOT, PESTAL, Porter's Five Forces, 3C, STP, 4P and AIDMA — opened by the insight brief.One-line positioning
Flim is a cinematic frame search engine letting creatives search movie stills by color, composition and mood for reference.
Target user
End users are creative professionals; buyer is the individual or team paying for the subscription to find reference frames.
Category role
A niche visual-reference/moodboard search tool, not a video editor or stock library — small, focused, steadily monetized.
THE VERDICTFlim is a durable but capped niche vertical-search tool, its growth ceiling set by shotdeck.com's larger reference library.
Non-obvious insights
- At 373K vs. shotdeck.com's 3.27M visits, same-job Flim trails by under 1/8, suggesting library scale — not product design — decides this niche.
- Direct traffic at 59% vs. Paid Search at just 5%, plus uniformly tiny keyword volumes, shows the category demand pool is too small to justify paid search spend.
- The near-equal US/India/France split, unlike typical single-market-dominant SaaS, shows demand comes from a globally scattered creative-professional community.
Mechanisms worth studying
- A tightly scoped vertical visual-search tool can sustain a stable paid base, proving precise niches can monetize even at sub-400K visits.
- Trailing same-job shotdeck.com by ~9x traffic shows library size compounds as the real moat in reference-search categories, not interface differentiation.
01 · Business Model Canvas
Business Model Canvas
- Supplier/tech: Stripe as payment infrastructure partner.
- No evidence of channel or ecosystem partners.
- No evidence of funding or strategic partners.
- Uses Stripe for subscription billing, standard card processing that's easier to extend to team/usage billing.
- Product/tech: maintaining and expanding the frame database and filtering algorithms.
- Ops/quality: maintaining the reference-only copyright disclaimer and licensing boundaries.
- Go-to-market: brand keyword 'flim ai' gets 590 monthly searches; no active marketing evidence otherwise.
- Category term "film still database" (480/mo) and brand "flim ai" (590/mo) push marketing toward creative communities, not broad paid search.
- Indexing others' film frames requires a copyright/ToS compliance and takedown-response process, a category-specific governance task.
- Functional value is precise color/composition/mood filtering for cinematic frame search.
- Pro subscription ~$12-29/month with a limited free tier; no evidence benchmarking value vs peers.
- No evidence of emotional/social value such as community or showcase features.
- Risk: content is licensed for reference use only, so users must confirm commercial-use rights themselves.
- Only Stripe payment infrastructure is evidenced; no API/plugin ecosystem evidence exists.
- Relationship is self-serve subscription; no evidence of human sales involvement.
- No evidence on support/service channels.
- No retention or churn data (renewal rate, cohort retention) is available.
- Trust evidence is limited to the reference-only copyright disclaimer; no reviews or case studies.
- The end-user job is searching movie frames by color/composition/mood as visual reference.
- Buyer is the individual or team subscriber; no evidence of a separate seat-management/admin role.
- Used during creative/pre-production work to find reference frames.
- Pain: finding cinematic references by visual style is hard; color/mood filters speed up reference gathering.
- Toolify revenue rank 271 with ~373K monthly visits suggests modest scale for a niche tool.
- Tech/data: a movie-frame database with color/mood-tagged search technology.
- Brand/distribution: ~373K monthly visits mostly from Direct and Organic Search; no social distribution evidence.
- People/physical/financial capacity: team size and funding status not evidenced.
- Ranked 271 with 373K monthly visits, similar scale to 10Web but only ~1/9th of rival shotdeck.com's traffic.
- Needs ongoing rights clearance for film stills plus color/mood tagging labor, not compute-heavy capability.
- Direct 59%/Organic 21%/Paid 5%/Referral 5%; growth relies on habitual creative-community return, not paid acquisition.
- Consideration traffic: Direct 58.74%, Organic Search 21.19%, Paid Search 5.38%.
- Transactions processed via Stripe subscription checkout; exact conversion funnel not evidenced.
- Delivery is a web-based tool used directly in-browser; no evidence of a separate client app.
- No evidence of service channels (support email, chat, docs).
- Product/R&D: engineering investment in the image search/filtering algorithm and database.
- Variable delivery: hosting/bandwidth cost for image storage and retrieval; amount unknown.
- No evidence on support/operations costs.
- Acquisition/compliance: copyright review and potential SEO investment; amounts unknown.
- Transaction-fee risk is low (Stripe standard rate, small subscriber base); real scaling cost is image-rights/library compliance.
- Charging unit: Pro subscription ~$12-29/month, with a limited free tier.
- Upgrade path: free-to-Pro conversion is the main route; no evidence of team/enterprise tiers.
- No evidence of additional service/licensing/usage revenue streams.
- The reference-only licensing hints at a plausible-but-unevidenced commercial-rights upsell; no ad/affiliate revenue evidence.
02 · Value Proposition Canvas
Value Proposition Canvas
Product side · Value Map
- Service: a film-frame search engine filterable by color, composition, and mood.
- Service: a limited free tier plus Pro-subscription tiered access model.
- The visual-attribute filter relieves the "can't search by look" pain.
- The free tier lets users validate before paying, relieving purchase-risk concerns.
- The color/mood filter creates the "instant precise match" gain.
- Shareable frame/board links create the "fast team-pitch assembly" gain.
Customer side · Customer Profile
- Functional job: precisely find a specific film frame by color/composition/mood for reference.
- Emotional job: feel confident presenting a pitch backed by professionally sourced visual references.
- Pain: generic image search like Google/Pinterest can't filter precisely by color tone/composition.
- Pain: the reference-only license blocks commercial use of frames in formal pitch deliverables.
- Gain: instant, precise frame matches by visual attribute rather than title keyword.
- Gain: speeds up assembling moodboard/pitch reference materials.
03 · JTBD
Jobs To Be Done
- When Creative professionals (directors, DPs, designers) stall on reference, they search 'film still database' or open flim.ai.
- Direct is 58.74% of observed visits, so 'film still database' is a repeatable reference situation rather than a one-off search.
- Measured demand for 'film still database' shows Flim is needed because the current stack cannot finish reference in one pass.
- A deadline and one-shot delivery pressure force Individual creatives or creative teams paying for the subscription to choose Flim for 'film still database' or an alternative now.
- The functional job is delivering usable reference in-session, not learning another full suite.
- Before paying, buyers still line up 'cinematography reference' quality, limits, and Pro on one comparison sheet.
- Creative professionals (directors, DPs, designers) want less panic after a failed reference pass, especially when 'film still database' misses the expected result.
- Self-pay users want proof the Stripe bill for 'film still database' will not jump next cycle.
- Creative professionals (directors, DPs, designers) want to look able to finish reference in front of peers, not still googling 'film still database'.
- Showing peers they can finish 'film still database' without help is the social job.
- Success is a pasteable, shareable, or editable reference result inside the same session.
- It also means holding 'cinematography reference' time, quality, and Pro inside a range Individual creatives or creative teams paying for the subscription can explain.
04 · ICP
Ideal Customer Profile
- The core profile is Creative professionals (directors, DPs, designers) doing reference, in the Cinematic Frame / Visual Reference Search category.
- Individual creatives or creative teams paying for the subscription pay for 'film still database', and administration may sit with No evidence of a separate admin/seat-management role.
- The buying trigger often shows up as a search for 'film still database', already present in the audited keyword table.
- United States is 10.98% of visits, so local work seasons can turn 'film still database' from latent need into a same-week must-solve.
- The primary pain is that reference is slow and error-prone, which is why 'cinematography reference' exists as a task query.
- Quota exhaustion and whether paying is worth it make Individual creatives or creative teams paying for the subscription hesitate after the first 'film still database' result.
- Budget signal for 'film still database': Pro; observed rail is Stripe.
- Self-serve subscription is the main path for 'film still database'; 373.4K traffic shows people already pay or keep trying.
- Decision criteria include 'film still database' sample quality, limits, and whether Stripe checkout is frictionless.
- They also shortlist shotdeck.com against 'film still database', and trust hinges on whether official pricing is self-serve readable.
- The repeatable reach path for 'film still database' buyers is Direct (58.74%), not a one-off campaign.
- The task query 'film still database' plus flim.ai is the second touch, better for content pages than brand ads alone.
- Large custom-implementation deals that are not buying 'film still database' are outside Flim's primary ICP.
- People who use shotdeck.com for a different job than 'film still database' are not same-budget buyers.
05 · Empathy Map
Customer Empathy Map
Primary personaA film/ad creative director or cinematographer racing to assemble a pitch deck or moodboard, needing precise visual references.
- They keep seeing 'film still database' result pages, flim.ai, and same-job generation UIs.
- The comparison set keeps shotdeck.com next to the incumbent 'film still database' tool.
- Peers talk in queries like 'film still database' and 'cinematography reference', not official handbook language.
- Users in United States also hear whether 'film still database' is worth the Stripe quota, not brand slogans.
- "Is there a film-still database I can search by color tone for a moodboard?".
- "This color/composition matches the look I want — find me a few more like it.".
- Filters by color/composition/mood rather than searching directly by movie title.
- Opens shotdeck.com in parallel to compare result quality before deciding which to use.
- Feels that Google Images can't nail the exact tone/composition, wasting time.
- Worries the found frame's reference-only license can't be used in a formal pitch deliverable.
- Feels time pressure as a pitch deadline approaches.
- Feels satisfaction and a sense of efficiency upon finding a precisely matching frame.
- They fear having to redo a failed reference pass; searching 'film still database' is already a frustration signal.
- A sudden end to the free quota on 'film still database' makes lock-in to Flim feel hard to admit.
- The ideal gain is finishing reference in-session and handing over an output that satisfies 'cinematography reference'.
- If Direct can find Flim again for 'film still database' (58.74%), a successful reuse becomes habit instead of another bake-off.
06 · Journey Map
Customer Journey Map
Discover01
Evaluate02
Onboard03
Retain04
Advocate05
Emotion curve (inferred)
Key behavior
Discovers Flim via a direct bookmark or organic search on terms like "film still database.".
Tests the free-tier color/mood filters, comparing results against rivals like shotdeck.com.
Hits the free-tier limit mid-project and upgrades to the $12-29/month Pro plan.
Returns directly for each new project, driven by the 59% direct-traffic habit.
Shares found frame/board links with team members, generating referral traffic.
Friction / drop-off
"Film still database" gets only 480 searches/month, so most target creatives never find it via search.
Free-tier limits quickly expose the smaller library vs. larger shotdeck.com, risking early drop-off.
The reference-only license may stall upgrade decisions for users needing commercial rights.
Referral channel is only 4.7%, indicating weak internal team spread/seat expansion.
The narrow creative-professional audience keeps advocacy loops contained, unable to cross into adjacent audiences.
Product lever
The color/mood filter terms themselves function as a long-tail SEO discovery surface.
The limited free tier lets users validate search quality first, lowering evaluate-stage decision risk.
Stripe-powered low-friction checkout supports self-serve upgrade to Pro exactly when needed.
The 59% direct-traffic habit is the retention lever, not any proactive notification/re-engagement feature.
Shareable frame/board links act as the implicit lever driving the advocate stage.
07 · SWOT
SWOT Matrix
- Multi-dimensional color/composition/mood filtering differentiates it among frame-search peers.
- 59% direct traffic shows a solid bookmark-return habit, keeping acquisition cost low.
- The free-to-Pro low-friction funnel fits a narrow but stable creative-professional customer base.
- Narrow category inherently limits the addressable user base.
- Reference-only licensing restricts commercial use, potentially deterring customers needing usage rights.
- Direct traffic is 58.7% but Organic Search only 21%, indicating a weak SEO acquisition structure.
- Long-tail keyword 'film still database' (480 vol, $8.52 CPC) shows commercial-intent SEO opportunity.
- ShotDeck's 3.27M monthly visits far exceed Flim's, suggesting unmet demand in the segment.
- India and France account for notable visit shares, indicating international expansion potential.
- ShotDeck (3.27M/mo) and Frameset (1.61M/mo) continually compete for niche attention.
- Growing adoption of generative AI image tools may reduce reliance on reference-image lookup.
- If larger footage libraries add color-filtering features, they would directly copy its differentiator.
08 · PESTAL
PESTAL Macro Environment
- Indexing copyrighted film frames directly exposes the product to studio DMCA-style takedown risk.
- Tightening AI-content copyright law could directly threaten the legality of its reference-use frame scraping.
- Paying users are creative teams, whose subscription willingness tracks film/ad production budget cycles.
- A near-even US/India/France traffic split shows demand isn't tied to any single region's economic cycle.
- Moodboard-style visual referencing is now a normalized creative workflow, favoring the product's acceptance.
- But rising anti-AI-scraping sentiment could brand "frame search" as infringing and provoke industry pushback.
- The core tech bet is continued viability of color/composition/mood visual-similarity search models.
- Rivals like shotdeck.com can replicate the same search tech, so the technological moat isn't exclusive.
- Flim's reference runs on cloud generation; 373.4K monthly visits push GPU and transcode energy onto each 'film still database' request.
- If 'film still database' media assets stay on flim.ai, bandwidth and storage accumulate with return visits from United States (10.98%).
- Flim outputs generated media around 'film still database'; training-data and output copyright stay a standing issue in United States.
- Checkout runs on Stripe; platform rules plus likeness or music rights can limit how far 'film still database' may be published.
09 · Five Forces
Porter's Five Forces
Scraping/tagging tech has a low barrier, but library scale is the real moat — shotdeck.com's larger size shows first-mover advantage matters.
The real "supplier" is studios/rights holders' tacit tolerance of reference-use indexing, a dependency Flim doesn't control.
shotdeck.com and frameset.app are directly substitutable same-job tools, keeping buyer switching costs low.
The substitute is manually gathering references via Pinterest/Google Images, a free workflow creatives already use.
shotdeck.com's 3.27M monthly visits (~8.8x Flim's) and frameset.app's 1.61M make Flim the smallest of the three same-job rivals.
10 · 3C
3C Analysis
- Capability: a film-frame search engine supporting color/composition/mood multi-dimensional queries.
- Economics: ~80% combined direct+organic traffic keeps paid-acquisition cost minimal.
- Structural position: the smallest of three same-job rivals, trailing both shotdeck.com and frameset.app.
- The end-user job is searching movie frames by color/composition/mood as visual reference.
- Pain: finding cinematic references by visual style is hard; color/mood filters speed up reference gathering.
- Toolify revenue rank 271 with ~373K monthly visits suggests modest scale for a niche tool.
- Same-job: shotdeck.com, cinematic frame reference search, 3.27M monthly visits, far larger than Flim.
- Substitute: frameset.app, similar composition/color reference tool, 1.61M monthly visits.
- Traffic-adjacent: whatismymovie.com (301K/mo); whether it directly competes is unclear from evidence.
11 · STP
STP Marketing Strategy
- Segment first by job: Creative professionals (directors, DPs, designers) doing reference, versus evaluators who only search 'film still database' to compare.
- Then cut by who pays for 'film still database' and geography: Individual creatives or creative teams paying for the subscription versus free riders, and United States (10.98%) versus the rest.
- Target the layer that can be reached again via Direct and will pay for 'film still database', not every visitor.
- Win the single-player 'film still database' job first, then consider team features; see ICP exclusions.
- A niche visual-reference/moodboard search tool, not a video editor or stock library — small, focused, steadily monetized.; in the customer's mind it should mean 'film still database', not generic AI.
- The reason to believe 'film still database' is revenue rank #271 and about 373.4K monthly visits, framed against shotdeck.com.
12 · 4P
4P Marketing Mix
- A visual frame search engine filterable by color, composition, and mood.
- A reference-only, non-commercial licensing model for retrieved frames.
- A limited free tier, with Pro subscription at ~$12-29/month.
- Beyond the official pricing note, no evidence of a team/enterprise pricing tier; needs on-site verification.
- Primarily direct access via flim.ai, with a 59% direct-traffic share.
- Organic search on niche cinematography/composition terms drives a 21% traffic share.
- 'film still database' gets 480 monthly searches at $8.52 CPC, showing professional-buyer search intent.
- 58.7% direct traffic suggests word-of-mouth/bookmark-driven acquisition with minimal paid-search spend.
13 · AIDMA
AIDMA Decision Journey
- Attention arrives through Direct (58.74%) and high-relevance entries like 'film still database', not broad brand noise.
- Organic Search at 21.19% is the second attention surface for 'film still database'; flim.ai must make that job obvious to Creative professionals (directors, DPs, designers).
- Interest comes from translating 'film still database' into a readable reference demo, not a feature dump.
- 'cinematography reference' shows they also want limits, price, or usage detail — the next page has to answer those.
- Desire holds when Flim finishes 'film still database' clearly faster than doing it by hand in one try, and feels closer to that job than shotdeck.com.
- A free or limited trial lowers the cost of wanting 'film still database', otherwise desire dies in the bookmark bar.
- Heavy direct traffic means the brand can be recalled together with 'film still database', or they will search again next time.
- Revenue rank #271 and 373.4K visits become a memory hook only if people also recall 'film still database', not just the brand.
- Action is the first result on flim.ai plus Stripe checkout; an extra signup step drops 'film still database' traffic.
- Let the free quota finish 'film still database' before the upgrade wall to turn interest into payment.
EVIDENCE BOUNDARIESNo revenue, LTV, or conversion-rate data exists to assess business health.; No evidence of team/collaboration seat features to confirm team-based pricing.; No support, retention, or renewal-rate data exists to assess churn risk.; Exact licensing terms for commercial use are unknown, affecting feasibility for institutional customers.
Sources & Method
Evidence boundaries
Official website: https://flim.ai
Ranking and revenue signals come from Toolify; traffic, channels and country distribution use SimilarWeb methodology; keyword Volume, KD and CPC come from DataForSEO. This is a research snapshot, not investment advice.
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