Playback Stats VS ViewForge

Playback Stats's answer

Playback Stats combines YouTube watch-history analysis and Spotify listening-history analysis in one privacy-first web app. It works directly with exported Google Takeout ZIP/JSON and Spotify streaming-history JSON files, processes everything locally in the browser, and requires no account connection, API key, or server upload. Users get detailed rankings, trends, streaks, habits, and locally generated share cards without giving another service access to their private playback history.

ViewForge's answer:

Three things. (1) Data ownership: ViewForge writes fitment as Shopify metaobjects native to your store — most competitors store fitment in their own database. (2) 8 verticals out of the box: auto, motorcycle, tractor, marine, power equipment, bicycle, printer, electronics — most competitors are automotive-only. (3) Smart Parse: extract fitment automatically from your existing product titles and descriptions instead of re-typing everything.

Playback Stats's answer

Choose Playback Stats when you want useful personal analytics without connecting your YouTube or Spotify account to a third party. It analyzes your own exports locally, supports long-term history, and exposes detailed rankings, trends, streaks, and habits. The app is free and open source, and your history files are never uploaded to Playback Stats.

ViewForge's answer:

Data ownership. Fitment lives in your Shopify metaobjects, so uninstalling does not take your compatibility data with it. Convermax, EasySearch and PartFinder all keep it in their own databases, and getting it back depends on their export tooling on the day you cancel.

Cost at the low end. The search widget, the compatibility table on the product page and the saved-vehicle garage are all on the free tier, up to 50 products, with no expiry. EasySearch puts the table and the garage behind its $75/month Premium plan. Convermax starts at $250/month.

Automotive and non-automotive coverage. Eight built-in templates, and fully custom templates from $19/month, for catalogs that do not decompose into Year/Make/Model at all.

Playback Stats's answer

The primary audience is privacy-conscious YouTube and Spotify users who want to understand their own viewing or listening behavior. It is especially useful for quantified-self enthusiasts, data-curious media fans, and anyone with a Google Takeout or Spotify history export who wants long-term personal insights without sharing the raw files with another service.

ViewForge's answer:

Shopify merchants whose customers need to know whether a part fits before they will buy it — and who do not have an engineer on staff to build that themselves.

Concretely: auto and truck parts retailers, powersports and motorcycle dealers, tractor and agricultural parts sellers, marine and outboard suppliers, small-engine and power equipment stores, bicycle and e-bike component shops, printer supply merchants, and electronics accessory sellers.

Catalog sizes run from a few dozen products on the free tier up into the tens of thousands; it is running in production on a catalog of roughly 40,000 SKUs. The common thread is not the industry — it is that "does this fit my thing" is the question deciding the sale.

Playback Stats's answer

Playback Stats began in 2024 as an open-source YouTube History Analyzer: a practical way to turn hard-to-read Google Takeout watch-history data into clear personal insights while keeping the data on the user's device. It later expanded to support Spotify streaming-history exports, creating one privacy-first place for exploring years of viewing and listening behavior.

ViewForge's answer:

ViewForge came out of agency work. Normal View was building for a parts retailer running roughly 12,000 SKUs who needed fitment search, and every app we evaluated stored the merchant's compatibility data in the vendor's own database.

That is a strange trade when you look at it directly. Fitment data is genuinely expensive to produce — it is weeks of work — and the merchant would not own the result. It would belong to whichever app happened to be installed that year.

Shopify metaobjects made a different answer possible: write fitment as native structured data inside the merchant's own store. The theme reads it, the Storefront API queries it, Admin GraphQL exports it, and it is still there after an uninstall. That decision is what the rest of the app is built around.

Everything else came from real catalogs rather than a roadmap. Eight verticals exist because a tractor catalog is not Year/Make/Model. Smart Parse exists because that retailer had already written fitment into 12,000 product titles, and nobody was ever going to retype them.

Playback Stats's answer

• Next.js and React for the web application
• TypeScript for the application and analysis logic
• Tailwind CSS for the interface
• Recharts for interactive data visualization
• Browser-side file parsing and processing so history data stays on the user's device

ViewForge's answer:

• TypeScript
• Shopify metaobjects, as the fitment data store
• Shopify theme app extensions for the storefront components: fitment search, saved-vehicle garage, compatibility table, product-page fit notice
• Shopify Storefront API, for querying fitment from the theme
• Shopify Admin GraphQL API, for writing and exporting fitment records
• NHTSA vehicle database, for VIN decoding
• ACES and PIES XML parsing, for automotive catalog import