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Vitaravinne

Competitor price intelligence system

94%

Reduction in manual monitoring time

Faster pricing decisions

12 h

Average alert-to-action time

340+

Competitor SKUs tracked daily

Manual price tracking was costing hours — and market share

Vitaravinne operates in a competitive supplement and health food market where pricing shifts daily. Their team was manually checking competitor websites and marketplaces several times per week — a process that consumed 15–20 hours of analyst time and was still missing critical window opportunities.

When competitors dropped prices, Vitaravinne often didn't find out until days later. By then, customers had already switched. The team needed eyes everywhere, instantly — without hiring more headcount.

An automated intelligence layer that never sleeps

AIVO² built a fully automated price monitoring pipeline that crawls 340+ competitor SKUs across multiple e-commerce platforms every 6 hours. When a price change breaches a defined threshold — up or down — the system fires an alert directly into Vitaravinne's Slack channel with full context: which product, which competitor, by how much, and a suggested response action.

The dashboard gives the commercial team a live heat-map of the competitive landscape, historical trend lines per SKU, and exportable reports for weekly strategy meetings. All data feeds into a Supabase database, with clean API endpoints so their e-commerce platform can eventually automate repricing responses directly.

The entire pipeline runs on n8n workflows deployed to their infrastructure — no proprietary lock-in, fully maintainable by their team with minimal training.

Real-time intelligence, without the headcount

  • 94% reduction in analyst hours spent on manual price monitoring
  • Average alert-to-action time dropped from 48+ hours to under 12 hours
  • Commercial team identified and acted on 3 major competitor price drops in the first month alone
  • Pricing strategy meetings shifted from reactive catch-up sessions to proactive planning
  • System fully paid back its build cost within 6 weeks of go-live

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