Thanks to all those who joined us on Thursday! We got a lot of questions and though we answered quite a few at the time, there were many more we just couldn’t get to. We want to answer them all but also want to make the answers visible to other attendees, so we’ll be answering a few at a time via this blog. If you didn’t get a chance to ask a question on Thursday or have thought of one since then, feel free to post as a comment or email to csestrategies at channeladvisor dot com.
Notes: You may see only part of your question appear on one of these posts. If some part of your question is very specific to your business, expect an answer via email to that part. If some part was already answered, we likely will not repeat it. Also, if you have an experience that differs from what you read here (which wouldn’t surprise us considering the fluidity of the GPS system) please share!
First a few links.
Google Base help form: This will help guide you through some commonly encountered issues with Google Base/Product search.
Google Help Forums: Community driven forums but Google folks do participate.
Google Error form: Use this if you are getting an error and can’t get it cleared up through help form or the forums.
Google Webmaster Video on GPS best practices: There are a few valuable nuggets of info in here.
List of Google Rating Sites: The most complete list I’ve seen and some good conversation about GPS in general, courtesy of SEOmoz. I can’t say I agree with everything on this page but since the GPS algorithm is hard to pin down, different omerchants are likely to see different results.
Now on to questions:
Q1) Is GPS scraping the web reviews or in active feed partnerships with the review sites?
A1) I’ve never asked this directly but I read on the forums once that it is done every so often, i.e., not regularly, suggesting it is a scrape. I would say this is consistent with what we see. Sometimes a merchant’s ratings are totally missed even though they are easy to find (via Google of course) and sometimes they lag behind significantly in terms of freshness. I just saw a merchant rating on PriceGrabber from the 18th that is not appearing on the merchant’s GPS review page more than a week later.
Q2) I recently saw that the Google tag product_type is now being used in the Google product search as categories in the filter options. Do you think it is important to map categories to google product_types, rather than use out current categories as custom product_types?
A2) My guess is that most users don’t use the filter options on GPS pages. For one thing, the GPS pages are probably not the main source of traffic for GPS listings. The “one-box” we talked about on Thursday, which appears on regular Google SERPs, likely comprises a much larger percentage of traffic and those pages don’t have such filters. Second, the Google user experience is all about searching, so I think users are more likely to alter their query than they are to look for/use filters. Finally, Google used to place such filters on the top of GPS pages but moved them to the bottom, probably because they were rarely used. That being said, Google definitely wants merchants to use the existing taxonomy. Consistent classification makes data much easier to organise and use. Google hinted a long time ago (before the new taxonomy rolled out) that creating your own product type was not a great idea but I’m not sure if this is still true. Doing so won’t cause the item to fail but I would suggest not creating your own values if you can avoid it.
Q3) When Mark and Scot were talking about ways to structure variation relationships I didn’t quite under stand what they meant when talking about separated by comma. Our data feeds are built and adjusted using excel, but saved as text files (tab delimited). One of our big sellers is bedding, including sheets, would it make more sense to continue to have each colour, each of which has a unique MPN, in a separate line or do something more connected? And if it would improve our ranking to connect the different colours of each item, what would be the best way to do that? Finally, if the product type doesn’t exist in the GPS taxonomy, does it do any good to make your own?
A3) The reference to the use of a comma as a delimiter was not intended to refer to the delimiter of the entire feed. We just meant that submiting variant options in a comma separate list in an attribute and/or the description was a good idea if you choose to send parent SKUs in the feed. So if you had a sheet set in five sizes, instead of sending five line items, you could send one line item and include in the “size” attribute “king, queen, twin, full” or whatever sizes are actually available. If you did this, you could also include a comma separated list of MPNs in the mpn attribute (though you only want to send one ID value). The potential move from parents to children or vice versa is a significant change and shouldn’t be taken lightly. I don’t do a ton of shopping for bedding so I’m not sure how the typical bedding shopper searches. However, when I search on “blue sheet set” in GPS, almost every item in the first ten results also has the size, even though I did not include the size in the query. This makes me think the size is primary for consumers. Try the same with “king sheet set” and see that most top results do not include colour. Doing what competitors do isn’t always the best answer but I think it’s unlikely you’ll rank well on queries with the size only if you also include the colour in titles. If you have any data that suggests how bedding customers shop, I would consider that in your decision, but based on this quick test, I would say you definitely don’t want to send separate colours with comma separated lists of sizes for sheets. With regard to the product_type attribute values, see question 2.
Q4) Strategy 5 talks about expanding into low risk CSE’s and specifically talked about Bing. Given that Bing shopping is buying a product feed from shopping.com (and we send product to shopping.com) I am wondering how helpful this would be? I would love to get some insight into: (a) how the purchased feed results would rank on Bing vs. a feed sent direct to Bing (if the feeds were basically the same) and if they might cancel each other out (duplicate listing are sometimes eliminated or punished in the rankings) And (b) the economics of the CPC shopping.com feed being sent to Bing vs. the CPA direct to Bing model (in your experience which is really more profitable)
A4) Bing is displaying your shopping.com data because the old MSN Shopping platform, which is no longer visible at shopping.msn.com, is still active behind the scenes. That platform has used data from shopping.com and pricegrabber for a long time and it continues to be used for any merchant not sending data directly to MSN/Bing. They aren’t allowing for duplication – Bing listings appear in lieu of anything coming through the old msn shopping platform (which as I said includes shopping.com and pricegrabber). In terms of rank, the answer can vary depending on whether or not there are other merchants selling the exact same item. If so, your listings sent directly to Bing would likely appear higher than your current shopping.com listings because the default sort on product pages on Bing is price low to high, but (here is the important part), the price displayed is NET of the cashback to the consumer. Look at this page and expand the little plus symbol. You’ll see the actual price is higher than what Bing is displaying, meaning the Bing advertiser is getting a boost by participating in the cashback program. In this case, it didn’t have an impact on the rank of that item within the page, but if they increased their cashback offering from 8% to 15%, they would rank first.
For items where there is no direct competition on the product and therefore no matched page, I would guess Bing still gives weight to merchants in the cashback program, but the final ranking is likely heavily determined by the user’s query and some sort of popularity (historical traffic/CTR). This probably applies to how the product pages themselves are ranked in search results as well.
With regard to profitability, I would say the majority of the time, a CPA model is preferred. As mentioned in the webinar, it limits risk, but also because of the nature of the Bing model, it gives you a lever for testing the Bing market specifically. What I mean is, you can try increasing your cashback from 7% to 10% on Bing, effectively lowering the price just for Bing users, and seeing if that drives an increase in volume. Even at a lower margin, the higher volume may mean more total profit.
More to come!