MaspartsAutomotive & E-commerce

84% accurate quote prediction with AI-driven sales intelligence

Quotes judged on gut feeling, and parts that sell together without anyone seeing it: that is how the sales team at Masparts, the specialist in exclusive car parts for Maserati, Ferrari, and Lamborghini, used to work. Three calculation models for cross-sell, quote scoring, and early customer signals now run directly in the system the team already works in. Sales knows in advance which quotes are likely to convert and which parts sell together.

84% accurate quote prediction
with AI-driven sales intelligence
  • 84%Accurate quote prediction
  • 1.2MProduct relations analyzed
  • 9.445Quotes scored automatically
  • 3Live AI models
Sector
Automotive & E-commerce
1Background

The challenge

Masparts grew fast with a vast catalog of exclusive parts, linked to thousands of vehicle models. But the valuable data in its webshop, such as orders, quotes, and customer behavior, remained largely untapped. Quotes were judged on gut feeling and cross-sell opportunities were missed.

Key problems

  • 01Which quotes would convert was estimated manually and on gut feeling
  • 02Cross-sell opportunities went unused across thousands of part-vehicle combinations
  • 03No early signal when a loyal customer was about to drop off
  • 04Rich webshop data sat unused in the system
Magazijn met kratten vol voorraad in hoge stellingen
2Methodologie

Our approach

We built three AI models directly into Masparts' existing management system. The sales team sees the outcomes in the system it already works in, without separate tools.

  1. 01

    Recommendations on every order

    From 1.2 million part-vehicle relations and 20,800 order lines it is clear which parts sell together most often. Those combinations appear as a recommendation per order and quote.

  2. 02

    A probability score on every quote

    A model with 84% accuracy automatically gives every new quote a probability score and priority, so sales follows up on the most promising ones first.

  3. 03

    Early customer signals

    If a customer deviates from their normal ordering pattern, a signal arrives in time for proactive follow-up.

  4. 04

    All in the existing system

    Three overviews and score columns sit in the existing management system: visible, maintainable, and without extra software.

3ImpactAutomotive & E-commerce

Results

Within four weeks everything was live in Masparts' management system.

  • 84%Accurate conversion predictionSales knows in advance which quotes will convert, instead of guessing afterward
  • 100%Quotes prioritized automaticallyEvery new quote instantly gets a probability score and a place in the follow-up list
  • 1.2MProduct relations used for cross-sellRecommendations based on 1.2M part-vehicle relations, live per order and quote
  • 4 weeksFrom data to liveFully integrated into the existing management system
“Stratalytic turned our own data into something we steer on every day. Our sales team now instantly sees which quotes are promising and which parts sell together, and it lives right in the system we already use. It was live within a month.”
Nick HelferrichFounder, Masparts

Technologies

Tools & platforms used

  • Python
  • XGBoost
  • Pandas
  • Laravel
  • MySQL
  • Redis

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Rutger Geerlings, solution architect at Stratalytic

Rutger Geerlings

Solution architect

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