[Build Backlinks Online] Early Look at Google's June 25 Algo Update

Build Backlinks Online has posted a new item, 'Early Look at Google's June 25
Algo Update'


Posted by Dr-Pete

If you follow our MozCast Google "weather" tracker, you may have noticed
something unusual this morning â a record algorithm flux temperature of
113.3F (the previous high was 102.2, set on December 13, 2012). While the
weather has been a bit stormy off and on since Penguin 2.0 and the announcement
of 10-day rolling Panda updates, this one was still off the charts:




Iâm usually cautious about over-interpreting any single day's data
â measuring algorithm change is a very difficult and noisy task. Given the
unprecedented scope, though, and reports coming in of major ranking shake-ups in
some verticals, I've decided to post an early analysis. Please understand that
the Google algorithm is incredibly dynamic, and weâll know more over the
next few days.

Temperatures by Category

Some industry verticals are naturally more volatile than others, but
hereâs a breakdown of the major categories we track in order by the
largest percentage change over the 7-day average. The temperature for June 25th
along with the 7-day average for each category is shown in parentheses:



68.5% (125/74) â Home & Garden


58.2% (119/75) â Computers & Consumer Electronics

58.1% (114/72) â Occasions & Gifts


57.8% (121/77) â Apparel

54.8% (107/69) â Real Estate


54.1% (107/69) â Jobs & Education

50.6% (112/74) â Internet & Telecom


49.4% (112/75) â Hobbies & Leisure

49.4% (102/68) â Health


44.9% (105/73) â Finance

44.5% (116/80) â Beauty & Personal Care


43.0% (116/81) â Vehicles

39.7% (104/74) â Family & Community


38.0% (109/79) â Sports & Fitness

37.3% (89/65) â Retailers & General Merchandise


34.7% (101/75) â Food & Groceries

32.4% (107/81) â Arts & Entertainment


25.9% (92/73) â Travel & Tourism

25.6% (93/74) â Law & Government


25.5% (92/73) â Dining & Nightlife


Every vertical we track showed a solid temperature spike, but âHome &
Gardenâ led the way with a massive 51 difference between the single-day
temperature and its 7-day average.

Some Sample Queries

There are so many reasons that a query can change that looking at individual
cases is often a one-way ticket to insanity, but that doesnât seem to stop
me from riding the train. Just to illustrate the point, the query âgay
rightsâ showed a massive temperature of 250F. Of course, if you know about
the Supreme Court rulings announced the morning of June 26th, then this is
hardly surprising. News results were being churned out fast and furious by very
high-authority sites, and the SERP landscape for that topic was changing by the
hour.


Sometimes, though, we can spot an example that seems to tell a compelling
story, especially when that example hasnât historically been a
high-temperature query. Itâs not Capital-S Science, but it can help us
look for clues in the broader data. Here are a couple of interesting
examplesâ

Example 1: âlimousine serviceâ

On the morning of June 25th, a de-localized and de-personalized query for
âlimousine serviceâ returned the following results:


http://www.ultralimousineservice.com/
http://www.uslimoservice.com/
http://www.fivediamondslimo.com/
http://www.davesbestlimoservice.com/
http://www.aftonlimousine.com/
http://www.awardslimo.com/
http://www.lynetteslimousines.com/
http://www.chicagolandlimo.com/
http://www.a1limousine.com/
http://www.sterlinglimoservice.com/

The following morning, the Top 10 for the same query was completely rewritten
(yielding the maximum possible MozCast temperature of 280).
http://www.carmellimo.com/
http://www.crestwoodlimo.com/
http://www.dial7.com/
http://www.telavivlimo.com/
http://www.willowwindcarriagelimo.com/
http://www.asavannahnite.com/
http://www.markofelegance.com/
http://tomscruz.com/
https://www.legrandeaffaire.com/
http://www.ohare-midway.com/


One possible pattern is that there are no domains in the new Top 10 with either
the phrase âlimousine serviceâ or âlimo serviceâ in
them, which could indicate a crack-down on partial-match domains (PMDs).
Interestingly, the term âlimousineâ disappeared altogether in the
post-update domain list, although âlimoâ still fares well. This
could also indicate some sort of tweak in how Google treats similar words
("limo" vs. "limousine").

Example 2: âauto auctionâ

Hereâs another query that shows a similar PMD pattern, clocking in at a
MozCast temperature of 239. The morning of June 25th, âauto auctionâ
showed the following Top 10:


http://www.iaai.com/
http://www.autoauctions.gsa.gov/
http://www.americasautoauction.com/
http://www.copart.com/
http://www.interstateautoauction.com/
http://www.indianaautoauction.net/
http://www.houstonautoauction.com/
http://www.ranchoautoauction.com/
http://www.southbayautoauction.com/
http://velocity.discovery.com/tv-shows/mecum-auto-auctions

Just one day later, all but the #1 spot had changedâ

http://www.iaai.com/
http://www.copart.com/
http://www.autoauctions.gsa.gov/
http://www.barrett-jackson.com/
http://www.naaa.com/
http://www.mecum.com/
http://www.desertviewauto.com/
http://www.adesa.com/
http://www.brasherssacramento.com/
http://www.voaautoauction.org/


In the first SERP, eight of the top ten had âauto auction(s)â in
the URL; in the second, only two remained, and one of those was an official US
government sub-domain (even that site lost a ranking spot).

Top-View PMD Influence

Ultimately, these are anecdotes. The question is: do we see any pattern across
the broader set? As luck would have it, we do track the influence of
partial-match domains (PMDs) in the MozCast metrics. Our PMD Influence metric
looks at the percentage of total Top 10 URLs where the root or sub-domain
contains either âkeywordstringâ or âkeyword-stringâ, but
is not an exact-match. Hereâs a graph of PMD influence over the past 90
days:




Please note that the vertical axis is scaled to more clearly show rises and
falls over time. Across our data set, thereâs been a trend toward steady
decline of PMD influence in 2013, but today showed a fairly dramatic drop-off
and a record low across our historical data (back to April 2012). This data
comes from our smaller (1K) query set, but the pattern is also showing up in our
10K data set.


For reference and further investigation, here are a few examples of PMDs that
fell out of the Top 10, and the queries they fell out of (including some from
the same queries):


"appliance parts" â www.appliancepartscenter.com
"appliance parts" â www.appliancepartscenter.us
"appliance parts" â www.appliancepartssuppliers.com
"bass boats" â www.phoenixbassboats.com
"campagnolo" â www.campagnolorestaurant.com
"divorce papers" â www.mydivorcepapers.com
"driving school" â www.dollardrivingschool.com
"driving school" â www.elitedrivingschool.biz
"driving school" â www.ferraridrivingschool.com
"driving school" â www.firstchoicedrivingschool.net
"driving school" â www.fitzgeraldsdrivingschool.com
"mario game" â www.mariogames98.com
"monogrammed gifts" â www.monogrammedgiftshop.com
"monogrammed gifts" â www.preppymonogrammedgifts.com
"nickelback songs" â www.nickelback-songs.com
"pressure washer" â www.pressurewashersdirect.com
"tanzanite" â www.etanzanite.com
"vibram" â www.vibramdiscgolf.com
"wine racks" â www.wineracksamerica.com
"yahtzee" â www.yahtzeeonline.org

Iâm not making any statements about the quality of these sites (except
nickelback-songs.com), since I havenât dug into them individually. If
anyone wants to take that on, though, please be my guest.
The âMulti-Weekâ Update

Recently, Matt Cutts warned of a multi-week algorithm update ending just after
July 4th â could this be that update? The short answer is that we have no
good way to tell, since Mattâs tweet didnât tell us anything about
the nature of the update. This single-day spike certainly doesnât look
like a gradual roll-out of anything, but itâs possible that weâll
see large-scale instability during this period.

Some (Quite a Few) Caveats

This is an imperfect exercise at best, and one day of data can be misleading.
The situation is also constantly changing â Google claims Panda data is
updating 10 days out of every 30 now, or 1/3 of the time, for example. At this
early stage, I can only confirm that weâve tracked this algorithm flux
across multiple data centers and there is no evidence of any system errors or
obvious data anomalies (we track many metrics, and some of them look relatively
normal).


Finally, itâs important to note that, just because a metric drops, it
doesnât mean Google pulled a lever to directly impact that metric. In
other words, Google could release a quality adjustment that just happened to hit
a lot of PMDs, even though PMDs werenât specifically the target. I would
welcome any evidence people have seen on their own sites, in webmaster chatter,
in unofficial Google statements, etc. (even if itâs evidence against
something Iâm saying in this post).

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