
Sign up to save your podcasts
Or


Clare and Ben discuss the four essential steps teams should take before committing to a PIM implementation or e-commerce re-platform, focusing on product data readiness.
They share practical insights on why so many projects run late and over budget, and how proper preparation around product data almost always costs less than fixing problems after go-live.
Keywords: product data, e-commerce, PIM implementation, data audit, data dictionary, data migration, channel mapping, data enrichment, ROI, digital transformation
Key topics:
• Auditing where your product data currently lives
• Mapping output channels before building your data model
• Defining what "good" data looks like with a data dictionary
• Filling data gaps before go-live — not after
• Why a PIM won't fix your data for you
Chapters:
00:00 Investing in product data: the challenge
02:49 Step 1 — Audit where your data lives
04:28 Step 2 — Map your output channels
06:57 Step 3 — Define what good data looks like
10:19 Step 4 — Fill the gaps before go-live
12:04 Listener challenge & close
Resources
Product Data Weekly Newsletter - https://productdataweekly.com
By Ben AdamsClare and Ben discuss the four essential steps teams should take before committing to a PIM implementation or e-commerce re-platform, focusing on product data readiness.
They share practical insights on why so many projects run late and over budget, and how proper preparation around product data almost always costs less than fixing problems after go-live.
Keywords: product data, e-commerce, PIM implementation, data audit, data dictionary, data migration, channel mapping, data enrichment, ROI, digital transformation
Key topics:
• Auditing where your product data currently lives
• Mapping output channels before building your data model
• Defining what "good" data looks like with a data dictionary
• Filling data gaps before go-live — not after
• Why a PIM won't fix your data for you
Chapters:
00:00 Investing in product data: the challenge
02:49 Step 1 — Audit where your data lives
04:28 Step 2 — Map your output channels
06:57 Step 3 — Define what good data looks like
10:19 Step 4 — Fill the gaps before go-live
12:04 Listener challenge & close
Resources
Product Data Weekly Newsletter - https://productdataweekly.com