IDC Spotlight Report: The Power of a PX Strategy in Omnichannel Commerce

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Whitepapers

Nov 01, 2023

Measuring the ROI of AI-Powered Product Data

In this checklist, we break down the various expected returns on investment from implementing an AI solution to structure and cleanse data, along with concrete customer examples that demonstrate the profitability.

Type

B2B

B2C

Challenge

AI-based Product Data Enrichment

Want to read the results?

Are you an eCommerce Manager or PIM Manager struggling with unstructured data?

You’re not alone; effective management of unstructured data is a major challenge faced by many businesses, big and small.

Many organizations try to use a home-grown , manual solution to structure their data, but that results in inaccuracies, inconsistencies, and inconveniences for the customer.

The good news is that we’re here to help!

If you’re interested in the concrete results you can expect from using an AI solution to make your product data more reliable, we’ve got you covered.

In this checklist, we break down the various expected returns on investment from implementing an AI solution to structure and cleanse data, along with concrete customer examples that demonstrate the profitability.

6 Metrics to Measure AI-Powered Product Data

  1. Reducing time-to-market
  2. Optimizing conversion rate
  3. Minimizing manual work
  4. Simplifying supplier onboarding
  5. Reducing the rate of return
  6. Improving search optimization

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