Rockerbox vs Cometly
By Marcus Flynn, tracking and attribution editor. Updated 24 September 2026.
You are down to two attribution platforms that neither publish a price nor run a free trial, and that is where the similarity ends. Cometly ties your ad spend to Stripe revenue and a sales pipeline, built for B2B SaaS and standing up in hours. Rockerbox measures a whole marketing mix, including offline media a pixel never sees, and takes a six-to-eight-week build with a data team behind it. The pick turns on what kind of revenue you are attributing, not on a feature checklist.
Pick Rockerbox if you run an omnichannel budget that spans offline media like connected TV, direct mail and podcasts and want multi-touch attribution, media-mix modeling and managed incrementality on one SOC2 data foundation, with a data team to own a six-to-eight-week build; pick Cometly if your revenue lives in Stripe and a CRM pipeline and you want the strongest server-side conversion feed back to the ad platforms, tying every ad dollar to closed-won ARR, standing up in hours.
Quick answer
Cometly is our top pick for most people. The B2B SaaS attribution platform: it ties ad spend to Stripe revenue and CRM pipeline through to closed-won ARR, with a server-side Conversion API that is its genuine strength and setup measured in hours. No public price, no free trial, and it has stepped back from the DTC and ecommerce market it once served.
- Rockerbox. Best for Mid-market and enterprise brands running cross-channel media, including offline.
- Cometly. Best for B2B SaaS teams tying ad spend to Stripe revenue and CRM pipeline.
Side by side
| Tool | Core job | Built for | Revenue source | Offline media | Setup time | From |
|---|---|---|---|---|---|---|
| Rockerbox | MTA, MMM, testing | Enterprise omnichannel | Whole media mix | Yes (TV, mail) | 6-8 weeks | Not listed |
| Cometly | Attribution + CAPI | B2B SaaS teams | Stripe + CRM pipeline | No | Hours | Not listed |
Rockerbox: pros and cons
What works
- Three measurement methods on one shared data foundation: MTA for daily optimization, MMM for budget planning and forecasting, and managed incrementality testing to prove causal lift. You cross-check a decision instead of trusting a single number.
- Reaches channels a pixel cannot. More than 100 integrations plus offline and hard-to-track media such as connected TV, linear TV, direct mail and podcasts, filled in with promo codes and post-purchase surveys.
- Independent, deduplicated, user-level attribution that reconciles the double-counting across Meta, Google and TikTok, exports the cleaned dataset to your own warehouse in BigQuery, Redshift or Snowflake, and is SOC2-certified.
- Credible and backed. Reviewers praise the cross-channel visibility and responsive support at 4.6 out of 5 on G2, the platform reports tracking billions in spend, and it is now owned by DoubleVerify.
What to watch
- Implementation is heavy and time-to-value is slow. Reviewers call the initial setup tedious and complicated, often needing developer or data support, and MTA or MMM take roughly six to eight weeks to become actionable. That weighs most on a lean team without dedicated data ops; a brand with an analyst who owns it will find the payoff worth the ramp.
- Quote-based enterprise pricing with no public price and no free trial. Contracts are annual and scale with your spend, and third-party benchmarks put a typical deal in the tens of thousands of dollars a year. Below meaningful multi-channel spend the ROI rarely covers it, though at scale the wasted spend it uncovers can.
- Its numbers will not match the ad platforms and can shift after the fact. Rockerbox's own docs treat variance under 10% as expected because of API revisions, delayed conversions and backfills. That independent read is the value, but it means reconciling models against backend revenue rather than taking one ROAS as truth.
- View-based, walled-garden channels like TikTok and YouTube are the hardest for it to measure cleanly, and some reviewers mention dashboard bugs and reporting glitches. That matters most if those view channels are your largest line items; for click-led channels the attribution is its strength.
Cometly: pros and cons
What works
- Server-side Conversion API is the genuine strength. Cometly sends deduplicated conversions back to Meta, Google, LinkedIn and TikTok, and reports Meta event match quality up to 9.3 out of 10 where a manual setup sits at 4 to 5. Buyers on r/FacebookAds confirm it pushed more matched data to Meta than other trackers they had run.
- Revenue attribution built around Stripe and the CRM, not just clicks. The native Stripe sync ties trials, new customers, recurring revenue and LTV to the originating ad, and HubSpot and Salesforce lifecycle stages map onto the same touchpoints, right through to closed-won ARR. That is the report a SaaS finance team will actually defend.
- Modern data plumbing under it. A cookieless Comet Pixel with cross-device identity, 70-plus native integrations, an Agent you query in plain English instead of writing SQL, and on Enterprise a warehouse sync to Snowflake or BigQuery plus an MCP server that lets an AI agent read your attribution data. The vendor puts setup at hours rather than weeks.
- Established and reviewed, not a new app. Comet LLC has tracked paid spend for years, with named case studies (ClickFunnels reports a 31% ad-return lift, Trainual a 40% improvement in 90 days) and aggregate ratings of 4.8 out of 5 on G2 across 36 reviews and 3.6 out of 5 on Trustpilot across 92.
What to watch
- It is not a route-through campaign tracker. Cometly attributes traffic to your own site and funnel; it does not rotate offers, split traffic across landers by rule, or distribute clicks the way Voluum, RedTrack or Binom do. That matters most to affiliate media buyers running many offers through a redirect. A SaaS team sending paid traffic to one funnel does not need routing.
- It has left the DTC and ecommerce market it once served. Cometly's own site now names Triple Whale as the ecommerce tool and positions itself for B2B SaaS. Shopify still integrates, but reviewers report weaker matching on cash-on-delivery and email-less orders, so an ecom brand should demand proof on its own orders before buying.
- No public price and no free trial. Every plan is usage-based on monthly pageviews and quoted on a sales call, and Cometly says it does not run a trial because attribution needs setup first. Buyers who want to test against their own numbers before paying, or just want a price before a call, get neither. One G2 reviewer wanted more transparent negotiation and flagged pricing changes over time.
- Support and journey timing draw the recurring complaints. The long-running r/FacebookAds thread reports support replies measured in business days and trouble seeing the full pre-purchase journey or getting purchases captured fast enough. The sample is small, but it is consistent enough that you should test response times and event latency during onboarding.
The real differences
What each one actually is
Cometly is a marketing attribution platform built for B2B SaaS. It sits over your funnel and answers one question well: which ad, audience and creative drove the revenue that landed in Stripe and your CRM. A cookieless Comet Pixel with cross-device identity records the touchpoints, its server-side Conversion API sends deduplicated conversions back to Meta, Google, LinkedIn and TikTok, and native syncs tie trials, new customers, recurring revenue and lifetime value through to closed-won ARR. HubSpot and Salesforce lifecycle stages map onto the same touchpoints. The vendor puts setup at hours rather than weeks. The full Cometly review has the detail.
Rockerbox is a measurement platform, not a funnel tool. It sits over your whole marketing mix and answers a bigger question: across Meta, Google, TikTok, email, affiliates, connected TV, podcasts and direct mail, which channels are actually driving revenue, and which are taking credit for sales that would have happened anyway. It does that with three methods on one SOC2-certified data foundation: multi-touch attribution for daily optimization, media-mix modeling for budget planning, and managed incrementality testing to prove causal lift. It reads its results out to your own warehouse, it is owned by DoubleVerify, and it is quoted after a demo. The Rockerbox review covers what that build involves.
The split that decides it
The honest way to choose is to name the business you run. Cometly is for the company whose revenue lives in a subscription: trials, conversions and renewals in Stripe, a pipeline in HubSpot or Salesforce, and paid traffic pointed at one funnel. Its whole design ties an ad dollar to closed-won ARR, and its server-side conversion feed is the part operators single out, pushing more matched data to Meta than a manual setup. It stands up in hours. What it does not do is model channels it never touches.
Rockerbox builds that model. Multi-touch attribution, media-mix modeling and incrementality cross-check each other, so you are not trusting a single number, and it reaches channels a pixel cannot: linear and connected TV, direct mail and podcasts, filled in with promo codes and post-purchase surveys. That reach is the whole reason to pay for it. If a meaningful slice of your budget is offline, or spread across enough channels that self-reported ROAS no longer adds up, Rockerbox is doing work Cometly cannot.
The catch is what that work costs to stand up. Rockerbox is a six-to-eight-week build that wants developer or data support, and its price is quoted in the tens of thousands of dollars a year. Cometly asks for a demo and a few hours of setup. So the split is simple: are you tying ad spend to subscription revenue in one funnel, or measuring a whole media mix, including channels a click never touches, with a team to run it?
Why your numbers will not match the ad platforms
Both tools will disagree with Meta and Google, for different reasons, and neither disagreement is a bug. Cometly deduplicates the conversions it captures and reports them server-side, so its counts will not line up cell for cell with a native pixel firing beside it; that matched, deduplicated feed is the point, and buyers report it lifting Meta event match quality well above a manual setup. Rockerbox goes further and reports fewer conversions than the platforms on purpose, because each platform claims the same sale if someone clicked or merely viewed an ad. Rockerbox's own docs treat variance under 10 percent as expected, given API revisions, delayed conversions and backfills. Treat either as a decision layer you reconcile against backend revenue, not a single source of truth, and keep the pixel, syncs and integrations in place or the tool under-reports through no fault of its model.
Who each one is for
Cometly is for the B2B SaaS team that wants ad spend tied to pipeline and ARR, the strongest server-side CAPI it can get, and a platform live in hours rather than weeks. Note the fit before you buy: Cometly has stepped back from the DTC and ecommerce market it once served and now names Triple Whale as the ecommerce tool, so an ecommerce brand should demand proof on its own cash-on-delivery and email-less orders first, and support response times and event latency are worth testing during onboarding. If you are weighing Cometly against its real peers, see Hyros vs Cometly and the Cometly alternatives.
Rockerbox is for the mid-market or enterprise brand running many channels at once, including offline media, with the spend to justify a real measurement contract and the data ops to own it. Below that, it is over-scoped: a team that just needs to tie ad spend to one funnel will pay for reach they never use. If Rockerbox is on your shortlist, the closer fights are against other measurement platforms. See Northbeam vs Rockerbox and the Rockerbox alternatives. Either way, our full ranking of ad tracking and attribution tools puts both in context.
What each one costs
Cometly publishes no price and runs no free trial. Its two plans, Core and Enterprise, are usage-based on monthly pageviews and quoted after a demo, with annual billing about 20 percent cheaper than monthly. Cometly says it does not offer a trial because attribution needs setup first, so you are quoted on a call before you see a figure or test against your own numbers. Because the meter is pageviews rather than revenue, size the plan to your traffic.
Rockerbox also publishes no price and offers no free trial. Contracts are annual and quoted after a demo, scaled on your spend, channels and data volume, and a third-party benchmark puts a typical deal in the tens of thousands of dollars a year. Neither tool lets you see a number without a call, so the honest cost comparison is scope, not sticker: Cometly is the lighter contract of the two, Rockerbox the enterprise one.
Prices read from each vendor's own pricing page, current as of 24 September 2026.
Our pick
Cometly
The B2B SaaS attribution platform: it ties ad spend to Stripe revenue and CRM pipeline through to closed-won ARR, with a server-side Conversion API that is its genuine strength and setup measured in hours. No public price, no free trial, and it has stepped back from the DTC and ecommerce market it once served.
Frequently asked questions
Rockerbox or Cometly: which should I pick?
Do Rockerbox and Cometly do the same thing?
Is Rockerbox or Cometly cheaper?
Can Cometly measure offline channels like TV and direct mail?
Sources
Other sources
5 discussions and reviews read for this page. Quotes are excerpts; open a link to read the original in context.
- [rb-unified] Rockerbox: Multi-Touch Attribution, Marketing Mix Modeling, & Testing
- [rb-dedupe] Rockerbox: Multi-Touch Attribution, Marketing Mix Modeling, & Testing
- [rb-implementation] Rockerbox: Multi-Touch Attribution, Marketing Mix Modeling, & Testing
- [cometly-home] Cometly | Marketing Attribution Software
- [cometly-stripe] Cometly | Marketing Attribution Software
How we compared these
We do not run paid campaigns through either tool. We read each vendor's own documentation and pricing, verify every number against the source, and weigh the long-term reports of operators who run them at real spend. The full rubric is on the methodology page.