Zum Inhalt springen
Dataxia: LTV Analyzer

Dataxia: LTV Analyzer

  • by Dataxia
  • Free plan available. Free trial available.
0.0 (0)
on
  • by Dataxia
  • 0.0 (0)
    on
  • Free plan available. Free trial available.

Predict customer lifetime value and future spend from your order history. Segment customers and export to Google Ads, Klaviyo, or your CRM.

Claim app

Verify your developer profile to earn a badge and build trust to your apps

  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot
  • Dataxia: LTV Analyzer Screenshot

About the Dataxia: LTV Analyzer

Dataxia: LTV Analyzer predicts customer lifetime value for every customer in your Shopify store. The app connects to your store, analyzes order history, and calculates how likely each customer is to make future purchases and their expected spend. Customers are automatically grouped into value segments like Champions, Loyal, and At Risk, then ranked by their predicted lifetime value. This helps you identify your most valuable customers and those who need attention. View customer segments and lifetime value forecasts directly in the app, or export data as CSV files. Use exports with Google Ads Customer Match, Klaviyo, or your CRM to target high-value customers with personalized campaigns. Order history imports happen automatically once you connect your Shopify store.
Launched: June 15, 2026

Hauptmerkmale

  • Predict each customer's lifetime value and expected future spend
  • Connect your Shopify store and import order history automatically
  • Export to Google Ads Customer Match, Klaviyo, or any CRM

Pricing of Dataxia: LTV Analyzer

Free plan

Free

  • Up to 500 customers

Pro plan

$99 / month

  • Unlimited analysis
Installation über den Shopify App Store

You might also like