ViewForge VS Spkwith

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.

Spkwith's answer:

Spkwith turns analytics into understanding. It captures what users do and why they do it by asking smart, in-product questions at the right moment. The new 360° user view brings everything together so teams can see what motivates each user and act on it right away.

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.

Spkwith's answer:

Most tools tell you what happened. Spkwith tells you why it happened and what will likely happen next. It adapts feedback in real time and translates user behavior into clear insights that help teams keep people engaged, reduce drop-offs, and make better product decisions faster.

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.

Spkwith's answer:

Spkwith is built for digital teams who care about their users but don’t have time for long research cycles. Our main users are people running e-commerce stores or booking flows who want to truly understand what drives or stops their customers.

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.

Spkwith's answer:

We started Spkwith after years of watching teams stare at numbers but still not know what their users were thinking. We wanted to bridge that gap, to make it easy for any company to ask the right question at the right time and finally see what really drives behavior.

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

Spkwith's answer:

Spkwith runs on AWS with services like Bedrock and Lambda, built in Next.js and Node.js with PostgreSQL for data. It connects directly with tools like Segment, Amplitude, and Auth0, and uses AI models to generate adaptive questions and motivation insights.

Spkwith's answer:

Spkwith is in its early launch stage and currently onboarding pilot users. We’re in active discussions with teams at National Geographic and The Hut Group about early access to our adaptive feedback platform.