Supaboard VS ViewForge

Supaboard's answer

Supaboard doesn’t just show data, it actually understands your business.

Most BI tools give you dashboards and expect you to figure things out Supaboard acts like an AI analyst that knows your metrics, definitions, and logic It gives you direct, clear answers,not just charts

Example:

Instead of building dashboards, just ask: “Why did revenue drop last week?” Supaboard explains the reason instantly.

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.

Supaboard's answer

Supaboard is used by modern, data-driven teams across industries:

SaaS companies → track MRR, churn, and product usage E-commerce brands → monitor sales, inventory, and customer behavior Marketing & growth teams → analyze campaign performance and attribution Sales teams → track pipeline, conversions, and revenue targets Operations teams → improve efficiency and identify bottlenecks Finance teams → monitor revenue, costs, and business health metrics Product teams → understand user engagement and feature adoption Mid-market & enterprise teams → align departments with consistent, trusted data

Supaboard's answer

Supaboard is designed for both technical and non-technical teams—making data simple, fast, and accurate for everyone.

Founders & CEOs → get instant clarity on business performance Sales & Marketing teams → track pipeline, campaigns, and revenue in real-time Operations teams → optimize efficiency and uncover bottlenecks Analysts → explore data faster without repetitive queries Mid-market & enterprise teams → align across departments with a single source of truth and trusted metrics

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.

Supaboard's answer

Supaboard is built for speed, simplicity, and trust.

No SQL or technical setup required No waiting on data teams No confusion from conflicting reports Get answers in seconds, not hours.

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.

Supaboard's answer

Supaboard was built to fix a simple problem: Getting answers from data is too slow and too complicated.

Teams spend hours building dashboards Data is scattered across tools Insights are delayed and often inconsistent

Supaboard flips this by making BI AI-first and instant

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.

Supaboard's answer

Supaboard combines modern AI and data infrastructure:

AI/LLMs → understand questions and generate insights Semantic layer → ensures consistent metrics and logic 600+ integrations → connect all your data sources Cloud infrastructure → fast, scalable, real-time performance

Example:

You ask a question Supaboard understands it, queries the right data, and returns a clear answer instantly.

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