At the end of last year we were approached to help a client with managing their eBay presence, normally we wouldn’t get involved with setting up ebay stores and the like but this one was interesting.
Our client wanted to list over 300,000 products on eBay so clearly manually listing products wasn’t an option and the anticipated volume of orders would be hard to manage effectively using eBay’s standard processes.

Some kind of listing and order management software seemed like the only sensible way of tackling this so we did a bit of homework and chose to use Blackthorne, eBay’s enterprise level software – think turbo lister on steroids.

The main functions that led us to choose eBay Blackthorne were it’s ability to define data maps for importing large volumes of products from csv files and it’s ability to bulk process orders.

The data mapping means that even if suppliers provide data in all sorts of different formats and layouts it’s possible to import the data quickly and with minimal fuss if the data changes.

The order processing functionality means that you can print invoices and address labels en masse.You can also export data relatively easily with the customisable exports for use in book keeping, CRM systems or other third party software.

We’re not going to review eBay Blackthorne here other than to say that by and large it’s very good, the documentation leaves a little to be desired but the support forums more than make up for it.

If you’re thinking about using Blackthorne, you won’t be dissapointed, but do yourself a massive favour and follow this one piece of advice:

Upgrade the database from Access to SQL Server right away.

By default, Blackthorne uses an underlying MS Access database, it works, but as you add more products and records it becomes so grindingly slow that you’ll think it’s crashed everytime you try and do anything. You can upgrade the database to run on SQL Server, it’s not that hard and took us about half an hour. Once it’s done, you’ll notice that Blackthorne runs literally 10 times faster, this get’s more and more important the larger the database gets.