Big Commerce Datafeed Marketing for Price Comparison Sites

Big Commerce Datafeed Marketing for Price Comparison Sites

Big Commerce Datafeed Marketing for Price Comparison Sites

If you are a Big Commerce storefront owner, hopefully you have stumbled across this article in hopes to find an easier way in manipulating your datafeed for multiple price comparison engines.  Unlike some of the other well established managed shopping carts, Big Commerce doesn’t currently have any relationships with some of the large datafeed marketing providers like Singlefeed or GoDataFeed that are able to give you an edge in getting your products syndicated throughout the web.  However, don’t get too discouraged, because I’m going to unveil some secrets to save you a lot of painstaking time while leveraging the power of Big Commerce.

 

First, a couple of the pros of Big Commerce:

  1. It’s a great managed shopping solution
  2. It’s got a great user interface
  3. Out of the box it has tools for Google base (product submit) submission
  4. Has support for other shopping comparison websites like PriceGrabber
  5. Big Commerce has done a great job in making its product listings SEO friendly

 

Now the not so good:

  1. Although their system supports Google base, its very cumbersome
  2. All product exports (for shopping engines) are full exports
  3. Product based exports are time consuming especially if you have a lot of product SKUS
  4. Image URL’s and listing URL’s are not provided in an easy consumable format if you decide to export your entire product list
  5. Some fields in your product export include HTML tags that need to be stripped prior to using a datafeed marketing platform

 

Although no shopping solution doesn’t come with its inherit faults, the bottom above issues I just mentioned just make it slightly harder to work with from a datafeed perspective.  So less bitching and now on to a solution to help you create a great product feed.

 

First, you are going to have to do a full product export.  Make sure that you select “bulk edit” when doing this.  If you have done this step properly, you should hear a series of clicks and a progress bar that as it starts to build your export.  Once completed, download it to your computer and save.

 

Depending on your datafeed marketing provider (in this case its GoDataFeed), the header syntax is going to be different that what you receive from Big Commerce (AKA why were are having this conversation.)  For the sake of this writing, I’m going to focus more of this writing on how to deal with issue #4 above because I believe this to be the biggest time waster.

 

Lets start with the product images.  You’ll likely see a column that says product image number one (followed by several other columns), but you will not see a full URL to the product.  Rather, you’ll likely see an unfinished URL like /a/g/test/product.jpg or something like that.  Thus, it’s a an extension of an image folder and your job is to find the location of that folder.  In other words, you’ll need to find were the images originate from.  It should look something like this http://www.yourstorename.com/product-images/ (the folder is actually /product/images/ but you’ll need the whole URL structure to input into your datafeed) You can find what the URL structure looks like by simply right clicking on one of your images on your current website and seeing what it looks like.

 

For sake of simplicity, lets say the above URL is the root URL for all your images http://www.yourstorename.com/product-images/ and you need to add that to 10k+ products.  No problem.

 

Open a new spread sheet and copy and paste your unfinished URL in column “B.”  Next, copy your root URL all the way down to match the number of unfinished URL’s.  Now the question becomes, how do you combine the two?  Easy, just copy both columns, open word and “paste special” as unformatted text.  Now use the find and replace function of word and find ”    “ (AKA tab) and replace with nothing.  Congratulations, you just merged two columns into a single column.  Simply cut and paste into the appropriate field in your datafeed.  Follow the same procedure for building listing URL’s.  BTW- you’ll have to do some scrolling to the right to find these.  But when you do, you can employ the same technique as I just mentioned.

 

The rest should be pretty straightforward as most columns can be found in the export feed.  It’s just these two fields that need a little extra work that can be time consuming.  However, hopefully the above takes the sting out of that job while keeping your work locally on your computer.!

Comments

  1. Christian Del Monte says: