Can I vibe code Cometly?

cometly.com ↗·ad-attribution·$199/mo·tiered

NICHE — BUILD THE NICHE VERSION

You are paying for pre-built server-side event tracking (Meta CAPI, TikTok API) and automated ad spend data sync. The visual dashboard and basic attribution logic are trivial to write using Postgres and ClickHouse. However, identity stitching across Safari ITP restrictions, maintaining OAuth API connections with Meta/Google, and managing deduplication event IDs will consume ongoing engineering bandwidth. For active media buyers, maintaining custom tracking infrastructure costs significantly more in developer time than paying Cometly's monthly SaaS subscription.

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The verdict

NICHE

Replaces

$399/mo

Vibe code score

5/10

MVP build time

1 week

Full replacement

3-6 months, due to CAPI integration maintenance and browser identity resolution changes

Editorial opinion, produced with a published methodology from public information. Not a statement of fact about the vendor. How we score · Report an error · Pricing checked 2026-09-13

CometlyNICHE$199/mo

Why this verdict

Building a basic UTM recorder with a dashboard takes a weekend. Replicating multi-touch attribution, server-side CAPI event deduplication, and maintaining ad platform API connections against breaking changes across Meta, Google, and TikTok is a full-time engineering effort.

Verdict

NICHE

Vibe code score

5/10

Moat strength

2/10

What it really costs

Sticker price versus what a real store ends up paying.

Entry$199/moTypical store$399/mo≈ estimated · 2026-09-13

Starter	$199/mo	Up to $50k/mo tracked revenue
Growth	$399/mo	Up to $150k/mo tracked revenue
Scale	$799/mo	Up to $500k/mo tracked revenue and agency reporting

Pricing scales based on tracked monthly revenue and number of ad accounts.

Where this number comes from

Captured: 2026-09-13 (11 days ago)
Verified by: crawler
Source: cometly.com

Assumptions: Pricing scales based on tracked monthly revenue and number of ad accounts.

The one-shot build prompt

Paste it into your agent of choice. Nothing else needed.

The one-shot build promptbuild it on Lovable

Build a full-stack ad attribution tracking system using Next.js, Node.js, and PostgreSQL (or ClickHouse for event logs).

1. DATA MODEL:
- Trackers: Stores site_id, domain, and API keys for Meta/Google/TikTok CAPI.
- Visitor Sessions: Stores session_id, anonymous_id, ip_address, user_agent, fbp, fbc, first_utm_source, first_utm_medium, first_utm_campaign, last_utm_source, last_utm_medium, last_utm_campaign, created_at.
- Events: Stores event_id, session_id, event_name (PageView, AddToCart, Purchase), page_url, payload_json, timestamp.
- Orders: Stores order_id, visitor_id, total_amount, currency, items, utm_json, attribution_first_click_campaign, attribution_last_click_campaign.
- Ad Accounts: Stores ad_platform, access_token, campaign_id, campaign_name, spend_daily.

2. CLIENT-SIDE SCRIPT:
- Create a lightweight (under 5KB) vanilla JS snippet.
- Capture all URL parameters (utm_source, utm_medium, utm_campaign, utm_content, utm_term, gclid, fbclid, ttclid).
- Save parameters to first-party cookies with 90-day expiration.
- Generate a persistent UUID for anonymous_id and a session_id.
- Send POST requests to `/api/v1/track` on page views, button clicks, and cart actions.

3. INGESTION & CAPI SYNC:
- Build express endpoint `/api/v1/track` to handle incoming events asynchronously.
- On purchase event (or via Shopify webhook `/api/v1/webhooks/shopify/orders`), resolve session identity using browser cookies or email hash.
- Construct payload for Meta Conversions API (CAPI) including user_data (em, ph, client_ip_address, client_user_agent, fbp, fbc) and custom_data (value, currency, order_id).
- Send event to Meta CAPI endpoint asynchronously with unique `event_id` for client/server deduplication.

4. ATTRIBUTION LOGIC:
- Implement First-Touch, Last-Touch, and Linear attribution models using SQL views over the Orders and Events tables.
- Compute ROAS (Revenue / Ad Spend) and CPA (Ad Spend / Conversions) per campaign.

5. DASHBOARD UI:
- Build React table displaying Campaign Name, Ad Spend, Tracked Orders, Tracked Revenue, First-Touch ROAS, and Last-Touch ROAS.
- Filterable by date range and ad platform (Meta, Google, TikTok).

OUT OF SCOPE: Automated ad bid management, complex ML probabilistic attribution models, complex team permissions.

$ each button prefixes agent-specific run instructions · build your own product, never copy proprietary code, trademarks or designs

Scorecard

Deterministic scoring, same method for every product.

Vibe code score

5/10

Moat strength

2/10

Technical difficulty5/10

Operational burden6/10

Integration depth7/10

Data advantage3/10

Network effects0/10

Compliance load1/10

What you keep, what you lose

The honest trade of rebuilding it yourself.

What you can actually replace

✓UTM parameter capturing and first-party cookie tracking scripts
✓First-touch and last-touch attribution SQL query logic
✓Analytics dashboard displaying CAC, ROAS, and ROI per ad campaign
✓Shopify webhook receiver for sales conversion ingestion
✓Basic server-side event payload generation

What you lose

×Turnkey client/server event deduplication across Meta, TikTok, and Google
×Automated token refresh and API schema maintenance across ad platforms
×Pre-packaged identity stitching across multi-device user journeys
×Ad spend ingestion pipelines that handle API rate limits and currency conversions
×No-code Shopify theme app integration

Why people still pay — the real moats

Moats

— Maintained native integrations with rapidly evolving ad platform APIs
— First-party identity graph infrastructure optimized for browser privacy limits
— Turnkey server-side tracking bypassing Safari ITP and ad blockers without custom DNS configuration

Hard parts

— Implementing event deduplication using matching parameters (fbp, fbc, hashed email, phone) across client and server
— Managing ad network API rate limits, backoff strategies, and refresh tokens
— Designing a high-throughput event ingestion pipeline capable of handling sales spikes during promo events
— Storing and querying click-level time-series event data for real-time attribution reports
— Managing DNS CNAME records to maintain first-party cookie status under aggressive browser updates
— Monitoring Meta CAPI match quality scores and troubleshooting missing event parameters
— Updating API clients whenever Facebook, Google, or TikTok release breaking changes to their Ads APIs
— Handling GDPR/CCPA cookie consent flags across client-side and server-side pipelines

Build this instead

Custom ClickHouse + Meta CAPI Pipeline

Deploy a lightweight JS tracker that writes UTMs to local cookies, streams event payloads to AWS Lambda, stores them in ClickHouse, and dispatches events directly to Meta Conversions API.

Build this instead

Jitsu + PostHog Open Source Stack

Use Jitsu for web event ingestion, route purchase payloads to ad network endpoints, and dump raw tracking logs into PostHog for SQL-based attribution modeling.

Build this instead

Shopify Webhooks + BigQuery Data Pipeline

Stream Shopify order webhooks and ad platform spend reports into BigQuery, executing scheduled SQL queries for multi-touch attribution dashboards in Looker Studio.

Prior art — do not start from zero

Existing projects and paid alternatives worth pricing first.

PostHog↗

Open-source product analytics platform built on ClickHouse for tracking user events and sessions.

github.com

Snowplow↗

Enterprise-grade open-source event tracking engine for capturing first-party customer behavioral data.

github.com

Jitsu↗

Open-source data ingestion and event routing engine designed as an alternative to Segment.

github.com

Open source alternatives to Cometly

Self-hostable projects that cover most of the same ground. Free licence, your infrastructure, your on-call.

PostHog↗

MIT

Self-hostable event analytics platform with session recording and funnel tracking.

github.com

Tracardi↗

MIT

Open-source Customer Data Platform (CDP) for low-code event tracking and user segmentation.

github.com

Plausible Analytics↗

AGPL-3.0

Lightweight, privacy-focused open-source web analytics engine.

github.com

Have you actually replaced it?

One click, no account. It moves the ranking.

Community verdict

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Successful: 0
Failed: 0
Success rate: no data yet
Spend killed: $0/mo

Compare

Same category, different trade-offs.

AudienceProjectKEEP

An independent audience measurement platform providing cross-media reach, frequency, and demographic validation for publishers and advertisers.

$2,500/mo

ElevarNICHE

Server-side tracking that survives ad platform changes.

$150/mo

HotjarNICHE

Hotjar captures user sessions, generates click and scroll heatmaps, and collects feedback through in-app widgets.

$39/mo

Cometly vs AudienceProject Cometly vs Elevar Cometly vs Hotjar Cometly vs Intelligems Cometly vs Lucky Orange Cometly vs Mouseflow

FAQ

+Can I really replace Cometly with an AI-generated app?

NO — CAPI INTEGRATIONS AND IDENTITY RESOLUTION ARE A CONSTANT MAINTENANCE TRAP. Building a basic UTM recorder with a dashboard takes a weekend. Replicating multi-touch attribution, server-side CAPI event deduplication, and maintaining ad platform API connections against breaking changes across Meta, Google, and TikTok is a full-time engineering effort. An MVP takes roughly 1 week; matching the product properly is closer to 3-6 months, due to CAPI integration maintenance and browser identity resolution changes.

+How long does it take to rebuild Cometly?

A usable internal version: 1 week. A version you would sell or bet a business on: 3-6 months, due to CAPI integration maintenance and browser identity resolution changes, mostly spent on implementing event deduplication using matching parameters (fbp, fbc, hashed email, phone) across client and server.

+What do you actually lose by leaving Cometly?

Turnkey client/server event deduplication across Meta, TikTok, and Google Automated token refresh and API schema maintenance across ad platforms Pre-packaged identity stitching across multi-device user journeys

+Is it legal to build a Cometly alternative?

Building a competing product with your own code is normal competition. Copying their code, trademarks, brand assets or scraping their platform is not. Use the prompt to build your own implementation of common features.

Written by EcomReStack research agent — 18 years in the Magento ecosystem. Last reviewed 2026-09-13.

Sources consulted

cometly.com

Scores are computed, not typed. Read the methodology.

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