Domain Migrations: Surviving the "Perfect Storm" of Site Changes |
Domain Migrations: Surviving the "Perfect Storm" of Site Changes Posted: 02 Jul 2013 07:23 PM PDT Posted by Ruth_Burr Last week, I held a Mozinar talking about the SEO steps involved in transitioning from SEOmoz.org to Moz.com, and sharing some of the results we got. We got some great questions on the Mozinar, and I wanted a chance to answer some more of them as well as expand on some points that didn't fit into the Mozinar. | ||||||||||||||||||||||||||||||||||||
The Right Keyword Data for the Right Job Posted: 02 Jul 2013 05:40 AM PDT Posted by russvirante This post was originally in YouMoz, and was promoted to the main blog because it provides great value and interest to our community. The author's views are entirely his or her own and may not reflect the views of Moz, Inc. Keyword data sources have long been a key tool in the pockets of search engine optimizers. There is little argument that know what people search for and how often has and will continue to be an important knowledge set in nearly any SEO endeavor. However, like most things in SEO, the devil is in the data. The problemThere are myriad keyword data sets available for consumption on the web. More often than not, we need keyword data and predicted search volumes in order to make decisions about content prioritization. The go-to product is normally Google's own Keyword Suggestion Tool, but it leaves much to be desired for those of us who need more data accessible in a programmatic fashion. So, which keyword data sets help us the most in getting keyword data, and how do they differ. The providersVirante, the company I work for, has used pretty much every keyword discovery tool or API out there. However, for our purposes here, we have to limit ourselves to providers that give Exact Match Local Search Volume data or estimates. This means we have to ignore one excellent keyword tool out there, Keyword Spy. This also ruled out popular tools like UberSuggest which does not provide search volumes. Finally, I looked only at web services, not standalone keyword tools like MarketSamurai or Xedant. Whenever possible, we used "fresh" data rather than historical indexes. Please bear in mind that I am just judging the data here. Each of these data sources have tools associated with them that make their data more valuable and in different ways. I will touch on these differences in the conclusions, but understand that I am just judging one feature of the overall offering, not the tools as a whole. Earlier in May, I reached out to the community to ask for every online keyword data set out there that provided search volumes and here is what I came up with: SEMRush - http://www.semrush.com This is an incredibly popular tool which I am quite familiar with. Virante has used their API now for quite some time. SEMRush presents search volumes as reported by Google. Wordstream - http://www.wordstream.com This data set is tied to a series of paid search tools that are excellent in their own right. Wordstream does not use Google's search volume data and instead provides their own relative number. Keyword Discovery - http://www.keyworddiscovery.com This huge data set has been a staple at Virante for some time. GrepWords - http://www.grepwords.com This is a newcomer. A simple tweet from what appears to be an empty twitter account reached out with beta access. As of writing this the tool still isn't available for purchase. WordTracker - http://www.wordtracker.com Perhaps the most well-known, Word Tracker has a huge database of keywords and their own proprietary search volume data. As a paid user, you can get Google search volume as well powered by SEMRush. Getting a baselineThe first thing I needed to do was to create a "source of truth" to compare against these data sets. Using the Google Keyword Suggestion Tool, I grabbed the top 100 keywords for each of the DMOZ categories. I think converted their local search volumes into an index from 0 to 100, where 100 is the highest-trafficked term in the list and 0 was the lowest-trafficked term. Finally, I took the LOG of each for visualization purposes. One quick caveat: I am making a big assumption here. Google may report very inaccurate numbers for search volumes. We certainly know they at least round these numbers. However, it is the best I've got for now. Method 1: Log of indexed search volumesThis most straightforward method of visualizing the differences in the data sets is to look at the comparison of the log of indexed search volumes for each data set. I looked up either by API or by hand the search volumes for every keyword returned via the Google Keyword Suggestion Tool baseline data. From left to right on the graph are the keywords of the highest search volume (according to Google) to those with the lowest.
There were several key takeaways. First, both SEMRush and Grepwords returned a line nearly identical to that from Google. This was to be expected. Unless their data was wildly out of date, it was likely that they would perform best on this type of metric. A few interesting takeaways:
Method 2: Average errorI began by putting each of the data sets on to the same 0 to 100 index, where 100 is the most popular keyword and 0 is the least popular. I then subtracted the keyword index values from each of their corresponding Google Keyword Suggestion Tool indexed volumes. This resulted in the following:
This doesn't really tell us much more about the performance, simply that SEMRush and GrepWords perform as one would expect, in line with Google's numbers, that Keyword Discovery trends closest to Google and that the error rate for WordStream and WordTracker are fairly similar. Method 3: Coverage rates What percentage of keywords are actually found in each index? We know that some indexes are larger than others, but this doesn't necessarily mean that they match up with searches performed on Google. Below are the coverages for the head/mid-tail terms:
It is worth pointing out that even though Keyword Discovery had a lower coverage rate and a lower average error, the average error statistic ignores when words are not present, scoring them as null rather than 0. As expected, SEMRush and GrepWords get high accuracy rates for head and mid-tail keywords. But, upon further examination, we can see that their indexes degrade in coverage as you move down the keyword search frequency scale. Long-Tail Coverage for Adwords Data Aggregators
As you can see, there are great coverage disparities among long tail for Adwords data aggregators like SEMRush and GrepWords. This is where services like Keyword Discovery, WordStream and WordTracker tend to shine. Because they get their data from sources other than the Adwords tool, they are able to pick up many more variations of keywords that might never show up in a Google Keyword Suggestion Tool query, even though the searches do actually occur on Google. So which provider is right for which problem? 1. I want obscure, long-tail keywords that are less likely to be found by my competitors. 2. I want as valid of data as possible, so that I can easily compare with competitive metrics. 3. I want data that can easily tie into PPC optimization. 4. I want data fast, accurate, and programmatic. 5. I want every possible keyword, period. Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read! |
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