Software Alternatives, Accelerators & Startups

mbuzz.co VS api-usage

Compare mbuzz.co VS api-usage and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

mbuzz.co logo mbuzz.co

Multi-touch attribution that shows the model behind the number. 8 models compared side-by-side, a SQL-like DSL to write your own, and open-source SDKs for Ruby, Node, Python, and PHP. Runs server-side. Your data, not theirs.
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api-usage logo api-usage

Track your OpenAI API token usage & cost.
  • mbuzz.co Dashboard: this week's budget moves
    Dashboard: this week's budget moves //
    2026-07-16
  • mbuzz.co Attribution dashboard
    Attribution dashboard //
    2026-04-14
  • mbuzz.co Conversions by channel
    Conversions by channel //
    2026-04-14
  • mbuzz.co Custom model in the DSL editor
    Custom model in the DSL editor //
    2026-04-14
  • mbuzz.co Blended ROAS vs platform
    Blended ROAS vs platform //
    2026-04-14
  • mbuzz.co Channel performance detail
    Channel performance detail //
    2026-04-14

mbuzz is multi-touch attribution for technical marketers who've stopped trusting their dashboard. Here's the thing nobody selling you attribution wants to say out loud: every tool runs a model under the hood, and the number it reports isn't "the data." It's that model's opinion of the data. Same touchpoints, different model, completely different "best channel."

mbuzz runs eight of them at once. First-touch, last-touch, linear, time-decay, position-based, Markov, Shapley, data-driven. You can compare them, argue with them, and write your own in a SQL-like DSL if none of the stock eight fit how your business actually works.

  • api-usage Landing page
    Landing page //
    2023-07-26

mbuzz.co

Website
mbuzz.co
$ Details
freemium
Platforms
Web REST API Ruby Python PHP Node JS Shopify
Release Date
2026 January
Startup details
Country
Australia
State
NSW
City
Sydney
Employees
1 - 9

api-usage

Pricing URL
-
$ Details
-
Platforms
-
Release Date
-
Categories -

mbuzz.co features and specs

  • Multi-model attribution
    8 models side-by-side: first-touch, last-touch, linear, time-decay, position-based, Markov, Shapley, data-driven
  • Attribution DSL
    SQL-like language for editing / writing your own attribution models
  • Lossless tracking
    Server-side capture of 30-40% more touchpoints than client-side trackers lose to ad blockers
  • LTV / CLV mode
    Toggle attribution reports between transaction count and customer lifetime value views
  • Open-source SDKs
    Ruby, Node, Python, PHP, Shopify, server-side GTM

api-usage features and specs

  • API Discovery
    Provides a centralized platform to discover and explore various APIs, making it easier for developers to find services that fit their needs.
  • Usage Insights
    Offers insights into API usage patterns, which can help developers and businesses understand trends and optimize their integrations.
  • Comparison Features
    Allows users to compare different APIs based on various metrics, aiding in more informed decision-making when selecting an API.
  • Community Contributions
    May include community-driven content such as reviews or ratings, providing real-world feedback on API performance and reliability.
  • Educational Resource
    Acts as a resource for developers new to APIs, offering explanations and guidance on how to effectively use various APIs.

Possible disadvantages of api-usage

  • Limited API Coverage
    The platform might not include all available APIs, potentially missing niche or newly released services that could be relevant to some users.
  • Outdated Information
    Information on the platform may not be updated in real-time, leading to discrepancies between the listed data and the actual current state of an API.
  • Lack of Personalization
    The platform may not offer personalized recommendations based on specific user needs or previous usage patterns, limiting its utility for tailored searches.
  • Dependency on User Input
    If the platform relies on user-generated content for reviews or ratings, the quality and reliability of this information can vary significantly.
  • Potential Overwhelm
    With numerous APIs and data points available, new users might find it challenging to navigate and extract the most relevant information for their specific use case.

Analysis of mbuzz.co

Overall verdict

  • I don't have verified, up-to-date information about mbuzz.co specifically, so I can't confirm its quality, legitimacy, or reputation. Before using it, I'd recommend checking independent reviews, verifying business registration details, looking for user testimonials on third-party sites, and checking domain age and trust signals via tools like WHOIS or Trustpilot.

Why this product is good

  • No verified data available on this specific domain's services, pricing, or customer satisfaction
  • Unable to confirm business legitimacy, ownership, or operational history
  • Cannot assess user reviews, complaint patterns, or refund/support track record without current data
  • Website content and offerings may have changed since any prior indexing, making assessment unreliable

Recommended for

  • Users willing to do independent due diligence such as checking Trustpilot, Reddit, or BBB reviews
  • Those comfortable verifying site security (HTTPS, privacy policy, contact information) before engaging
  • Anyone considering a purchase or signup who should start with small transactions to test reliability
  • Users who can cross-check company registration and reviews through third-party verification tools

Analysis of api-usage

Overall verdict

  • Without independent verification, api-usage (apiusage.info) cannot be confidently confirmed as a good or reliable service since there is insufficient public information, reviews, or track record available to assess its quality, security, and support.

Why this product is good

  • Limited publicly available information makes it difficult to verify claims about the service
  • No substantial user reviews or third-party assessments found to confirm reliability or performance
  • Unclear track record regarding uptime, customer support quality, or data security practices
  • Potential newer or niche player in the API monitoring/usage tracking space with limited market validation

Recommended for

  • Users willing to conduct their own due diligence and testing before committing
  • Those seeking a possibly low-cost or niche alternative to established API usage tracking tools
  • Developers comfortable trying newer services and providing feedback
  • Not recommended for enterprises requiring proven, well-documented vendor reliability without further research

Category Popularity

0-100% (relative to mbuzz.co and api-usage)
Marketing Analytics
100 100%
0% 0
Attribution Tracking
100 100%
0% 0
Marketing Attribution
100 100%
0% 0
Advertising Optimization
100 100%
0% 0

Questions & Answers

As answered by people managing mbuzz.co and api-usage.

What makes your product unique?

mbuzz.co's answer

Every attribution tool runs a model under the hood and reports its number like it came from physics. mbuzz is the only one that shows the model. Eight of them side by side, plus a SQL-like DSL to edit or write your own. You stop arguing about which channel works and start arguing about which model you should trust.

Why should a person choose your product over its competitors?

mbuzz.co's answer

Dreamdata, HockeyStack, and Northbeam all ship with a proprietary "data-driven" model you can't see inside. You pay $1,400โ€“$5,000 a month to trust their math. mbuzz runs eight models you can inspect, lets you edit the logic in a SQL-like DSL, keeps your data exportable on every plan, and starts at $0. For a $1โ€“100M company spending $20Kโ€“$1M a month on ads, that's the difference between renting an attribution tool and owning an attribution stack.

How would you describe the primary audience of your product?

mbuzz.co's answer

Technical marketers, marketing ops, growth engineers, and data-savvy CMOs at startups and mid-market SaaS, DTC, fintech, and healthtech companies spending $20Kโ€“$1M a month on paid media. Specifically the ones who've stopped trusting their dashboard โ€” who want to audit the math themselves, not hear "trust our algorithm."

What's the story behind your product?

mbuzz.co's answer

Years of wrestling with the limitations of various existing solutions, platform-inflated ROAS, and enterprise attribution tools that cost more than the budgets they were measuring. Every tool I tried picked one model and hid the math. I wanted to compare models, argue with them, and write my own rules โ€” so I built one. mbuzz is the attribution platform I wished existed when I was trying to explain channel performance to a CFO who didn't believe the Meta pixel.

Which are the primary technologies used for building your product?

mbuzz.co's answer

Ruby on Rails (backend + dashboard), PostgreSQL, Sidekiq for background jobs, Stimulus/Turbo for the frontend. Open-source SDKs in Ruby, Node, Python, and PHP. Deployed via Kamal on DigitalOcean.

User comments

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What are some alternatives?

When comparing mbuzz.co and api-usage, you can also consider the following products

HockeyStack - Not just another simple analytics tool.

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.

Content Analytics by Dreamdata - โ€œDoes my content influence revenue?โ€ ๐Ÿคท Content Analytics stops the guesswork to show you whether your content is turning views into dollars ๐Ÿ’ฐand deals ๐ŸคDreamdata tracks the multi-user, multi-session B2B buyer journey to tie content to pipeline & revโ€ฆ

Attributer - Know what marketing channels are driving customers & revenue

Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.

Rockerbox - Rockerbox is a real-time user intent that developed the technology to determine user's intent based on recent browsing habits.