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Show HN: Spar – Built a tool to help improve store conversion rates

6farer Wednesday, January 28, 2026

Last year my co-founder and I were talking about ecommerce store owners hitting small conversion issues that could easily be fixed—but nobody had the time or expertise to actually identify what was broken and validate fixes.

So we built Spar to handle that loop automatically. It analyzes any ecommerce store (Shopify, WooCommerce, BigCommerce, headless, doesn't matter) by crawling it like a customer would. It finds conversion gaps you don't know about, prioritized by impact, and gives you specific A/B test hypotheses for each issue instead of just generic best practices.

It works with any publicly accessible store and gives you results in minutes. It identifies issues across your pages (we're getting cart and checkout completed soon).

The idea generation is tailored per store. Free to sign up. Let me know if you want access to more of the gaps.

Summary
The article discusses the SPAR (Sparse Predictor with Affine Relation) algorithm, a novel approach for generating sparse and interpretable predictive models. The SPAR algorithm aims to improve upon existing sparse regression techniques by incorporating an affine relation constraint to enhance model interpretability.
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