Contextual Street Signage

For

Marketing managers at outdoor advertising firms

Solves

Static billboards waste impressions on uninterested audiences and fail to prove engagement.

Delivers

Dynamic ad creatives, verified interaction metrics, weekly performance reports

Built in

about 5 weeks of creation time, MVP in 5 days

Investment

$9,500 for the MVP, $38,000 for the full product

Run it

Inside your business, or as part of your offer to clients

For marketing managers at outdoor advertising firms, turn live camera feeds and contextual data into dynamically personalized ad creatives with verified interaction metrics.

1. Capture and process camera feed locally.
2. Classify vehicle type and pedestrian demographics.
3. Select and render relevant creative in under two seconds.
4. Optionally ask a question and listen for verbal responses.
5. Log dwell time and interaction outcomes.
6. Generate weekly performance reports without storing personal data.

What goes in, what comes out

The workflow

1. In
   Start with

   Live camera feed, creative library, contextual data (e.g., pollen count, sports scores)

2. 1

   Install edge device

3. 2

   Configure camera and mic

4. 3

   Upload creative library

5. 4

   Set targeting rules

6. 5

   Activate live mode

7. 6

   Monitor interactions

8. 7

   Review weekly reports

9. Out
   Finish with

   Dynamic ad creatives, verified interaction metrics, weekly performance reports

AI does the heavy lifting, people stay in charge

AI uses computer vision to classify objects and estimate age/gender from gait, and natural language processing for voice interactions. It selects creatives based on real-time context. A human reviews interaction logs and creative performance to ensure relevance and adjust targeting rules before any data is used for billing.

What your team sees

Key screens: Live feed dashboard, creative library, interaction log. Use a live feed dashboard for real-time monitoring, a creative library for managing variants, and an interaction log for tracking dwell time and voice responses. Show alerts for high engagement and a status light for privacy assurance. In this product, the first view is live feed dashboard, followed by creative library and interaction log.

Accounts and administration

User roles (admin, editor, viewer), permission-based access, creative version control, approval workflow for new creatives, audit trail of all interactions and changes, and data retention policy ensuring no personal data is stored.

Integrations and data access

Camera hardware, digital screen APIs, weather and local data feeds, and ad management platforms for creative uploads.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   5 days

   One buyer segment, one recurring use case; first modules: live feed processing and creative selection. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   2 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will marketing managers at outdoor advertising firms use it to solve "static billboards waste impressions on uninterested audiences and fail to prove engagement"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Run a 30-day pilot on one screen with two advertisers.
4. Measure, then decide. Track average view time per person and interaction rate (voice responses or dwell >5 seconds). Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One buyer: an outdoor advertising firm. One use case: a single screen with 10 creatives for two local advertisers. First two modules: live feed processing and creative selection. Manual review of interaction logs and weekly reports.

After the MVP. After pilot, automate creative selection based on historical performance data, integrate with ad exchange platforms for real-time bidding, and add predictive analytics for optimal placement times.

What the build depends on. Reliable power and internet at screen locations, edge AI models for vision and NLP, and a library of creatives with targeting rules.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test pricing: $500/month per screen for the edge kit and software, plus $0.50 per verified interaction or $100 per 1000 impressions with engagement.

Message to test

Turn every passerby into a customer with ads that adapt in real time.

Where to find buyers

Industry conferences, digital advertising forums, direct sales to outdoor media owners, and partnerships with screen manufacturers.

Lead magnet

Free demo showing a simulated screen with live interaction metrics.

The first 30 days

1. Week 1: Finalize hardware specs and AI model selection.
2. Week 2: Build edge processing prototype.
3. Week 3: Develop creative library and targeting rules.
4. Week 4: Deploy on one screen and test with local advertisers.

Paid pilot

Run a 30-day pilot on one screen with two advertisers. Baseline: current average view time and interaction rate. Decision: proceed if interaction rate exceeds 5% and dwell time increases by 20%.

Success metrics

Average view time per person, interaction rate (voice responses or dwell >5 seconds).

Retention and expansion

Recurring monthly fee for software and analytics, plus per-interaction charges, creating ongoing revenue. Regular updates and new features keep clients engaged.

Why clients would pick it

Network effects from accumulated interaction data improve targeting accuracy over time, while proprietary edge AI models and partnerships with screen owners create high switching costs.

Alternatives and positioning

Static billboards, digital signage with scheduled content, or basic sensors without AI. This differs by offering dynamic personalization and measurable engagement, unlike traditional static ads.

Main delivery costs

Edge hardware ($200/unit), software development, cloud storage for reports, and maintenance support.

Local processing only, no cloud upload of raw video, automatic pixel deletion, visible privacy light, and strict access controls. Must not store any facial recognition data or personally identifiable information.