Talking to Sharon Gee, SVP Sales & Partnerships at Feedonomics, it’s obvious she’s passionate about solving data challenges for brands and retailers and it’s a problem that’s rapidly scaling as the number of channels grows on a daily basis.
How do you take your internal data and prepare it to send a product feed to marketplaces such as Amazon, eBay and Walmart, search engines like Google and Bing, plus affiliate sites, your own websites and a growing host of retailer owned marketplaces through Mirakl and Marketplacer?
Feedonomics aim to cleanse and enrich your data from you own multiple sources, perhaps enrich it from external sources, and map it to the Google schema and present in any other formats you need to power your channels.
Some key stats:
- Raw data is usually between 60-70% accurate
- Feedonomics can normally categorise products to the Google schema to 96% accuracy rate
- On average Feedonomics customers see a 10-20% increase in conversion
If that’s whetted your appetite, in this video you will find:
- 00:00 Introducing Sharon Gee, SVP Sales & Partnerships at Feedonomics
- 00:32 What Feedonomics does for Brands and Retailers
- 02:01 How Feedonomics cleanses and enriches data for specific platforms at scale
- 04:09 The channels Feedonomics can send data feeds to
- 05:15 Driving growth through incremental conversion rates on existing channels
- 06:07 Powering local store inventory for instant commerce
- 08:02 How Feedonomics uses AI today and for the future
- 09:50 How AI can generate a 10-20% conversion rate improvement
- 11:29 Using Feedonomics without BigCommmerce
- 12:04 The advantage of BigCommerce with Feedonomics
- 13:18 What’s next for Feedonomics?
