There has been a cacophony of chatter in the search world over Google's decision to deny websites some portion of their SEO referral data. People are stark raving mad at Google about this, especially due to their decision to violate commonly-accepted 'standards' of the web community: that data gathered in a secure session (with https) can be shared with other secure sites (using the same protocol). The double standard here (and slippery slope for Google) is that, provided you're paying Google and running paid search campaigns, you can still get the keyword referral data.
I understand the community's concern here, but my first instinct (rather than start throwing stones at the Big Bad Google machine) is to figure out what the real consequences are, and what it means for search marketing (specifically SEO).
What's The Impact So Far?
First the (obvious) piece of bad news: we will no longer see organic search query data for Google's logged-in users. It makes us a little bit blind for a small percentage of queries (Google reports that it's less than 10%, but most sites are reporting a number closer to 2%. More about that below, including numbers from a sample of our clients.)
Now the good news: searches are more secure. And even more importantly, folks who are using Google's API can no longer tie a search back to a specific user.
But what does it mean for our clients? Well, so far, the picture is best answered in two parts.
First the traffic picture: the segment sending "not provided" obfuscated data is quite small. Looking at a selection of 12 RKG clients (all very large sites across several industries), the average percentage of traffic "not provided" is just 0.76% (using a date range of October 18, 2011 to October 24, 2011). That's the percentage of "not provided" traffic relative to total organic search traffic, including navigational (brand) and competitive (non-brand) terms.
That's good news. At least so far (using a very small window of time, admittedly) there isn't game-changing traffic to worry about here.
Now for the bad news. This segment appears to convert at a relatively high rate across the board, and more importantly, tends to be responsible for a relatively large portion of SEO revenue. So far at least, it appears to be a valuable segment of traffic.
Looking at the same 12 RKG clients, the average revenue rank of the "not provided" segment in organic search was 8.2. Some sites had the segment as high as the #1 driver of SEO revenues!
A common picture: as a revenue driver, the "not provided" segment tends to be quite valuable.
There are a few possibilities as to why this is. First, these are queries that range widely in length, intent, and competitiveness. They're all across the board. Navigational queries (branded) are blended with competitive queries (non-branded), broad queries are mixed with long-tail queries, and queries with strong purchase intent are mixed with other types of queries.
Second, this may be a demographic that is more likely to purchase or convert. That is unknown right now, and purely speculation. It would make sense, however, because users logged in will likely be more savvy generally and fairly sophisticated.
SEO and PPC Integration is More Important Than Ever
It's changes like this that make SEO and PPC integration more important than ever. There are several ways we can leverage PPC analysis to glean insight into the SEO referral data that is now invisible. Here are a few simple examples:
- For a given URL, provide all navigational (brand) and competitive (non-brand) terms from PPC campaigns. Generate the same data from SEO traffic. A gap analysis should uncover terms generating traffic and conversions in PPC that are not available under the "not provided" segment.
- Perform the same exercise, but at a global rather than URL level. This should surface the same data, but globally for the domain rather than specific to a URL.
- Perform a gap analysis on SEO keyword coverage pre- and post- the Google change. This should disclose what SEO referral terms have "fallen off the map" and are no longer available in analytics.
What are some other ideas out there to help solve for this? Looking forward to the discussion.
Here's the data from this initial analysis.
(date range: 10/18 - 10/23)Site - SEO Traffic Percentage - SEO Revenue Rank
- 0.54% - #1 revenue
- 0.63% - #6 revenue
- 0.95% - no revenue
- 1.05% - #34 revenue
- 0.58% - #7 revenue
- 0.68% - #10 revenue
- 0.78% - #4 revenue driver
- 0.45% - #6 revenue driver
- 0.80% - no revenue
- 0.88% - #14
- 0.8% - #8 revenue driver
- 1.04% - #7 revenue driver