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Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis

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penguin 2.0 case study

Learn from a deep dive into a hard hit Penguin 2.0 Penalty

This case study is set out to analyze the reasons for the massive drop in visibility, that had to face right after the global rollout of Penguin 2.0 update.

In the deep dive fashion of our previuous deep dives on Home24 and CheapoAir we will look at their website like any professional SEO would conduct a SEO and link audit.

As uses various sub-domains in its web presence, the analysis will emphasize on the sub-domains as well, in addition to the root domain, which adds to the complexity.

This research will again look into Spammy Links, Redirect issues, Sitewide Links, Low Quality Links, Subdomain issues and much more.

There’s again a lot to learn in here, and I’m psyched to present you the next case-study by a Certified Link Research Tools professional as 3rd deep dive case study.

Tweeting is not required, but we sure appreciate you spreading the word on this quality piece of work by Christoph Hoffinger MA.

Christoph C. Cemper

How we will look into this Penguin 2.0 Penalty

At first, I will have a look at the loss in visibility on a root domain, sub-domain and keyword level. Following to that I will identify those areas mostly affected in order to derive the hypotheses for the detailed analysis


Quick Analysis

Detail Analysis

Conclusions & Outlook

1    Visibility of

1.1    Root Domain was chosen for this case study based on a list with the major Penguin 2.0 losers published by Marcus Tober (Searchmetrics). Searchmetrics was also used to analyze the changes in visibility after the Penguin rollout.

Looking at the visibility score, we can see a massive drop of about 41% (value differs slightly from the Searchmetrics blog post, as the list was publishes on May 23th, while the values shown in the graph are based on the data from May 28th).

There was a steady decline in Reeds’ SEO visibility from January onwards, but the drop last week was massive and not comparable to the slight variations throughout the year.

visibility score penguin

The drop seems even more striking when looking at some of Reeds competitors’ sites that even increased their visibility score in the same period. It may well be, that these sites could already benefit from Reeds’ drop and improve their rankings.

visibility score competitors penguin

Please consider that the drop is less visible in the chart including the domains of the main competitors as they have a much higher visibility than (e.g. 48.128 > 3.823).

1.2    Sub-Domains used and penalized

As already mentioned, uses various sub-domains that are also directly linked in the main navigation. It is therefore essential to have a look at them in more detail. In total there are 16 subdomains with a significant value for the visibility score, including the “www” version.

reeds subdomain main menu

I analyzed the changes in visibility for each sub-domain separately and summarized the results in the following table, sorted by visibility score:

Visibility Score Sub-domains

In the last column we can see that the top sub-domains lost between 34% and even 100% of their visibility. The absolute drop was largest for followed by and In relative numbers, and lost (almost) all of their visibility.

One striking fact is that sub-domains with a higher visibility score lost considerably more of their visibility (both in absolute and relative terms) compared to sub-domains with a lower visibility score. One exception is

Another striking fact is that a few weaker sub-domains see a considerable increase in visibility (e.g. or This means multiple penalties were applied to each a sub-domain separately.

1.3    Keywords that Reeds dropped for

I will now have a look at the keyword level in order to see if the drops in visibility occurred for the sun-domains as a whole or just for selected keywords.

Reeds had a considerable drop for two of its Top 3 keywords (engagement rings and pandora bracelets) that are related to two sub-domains with massive drops in visibility. Although also got hit massively, the keyword “pandora charms” could actually gain 17 positions. These are, however, changes that heavily affect the visibility score, but the consequences in traffic will be rather modest given that these rankings range from the second to the fourth results page.

Drops that will certainly hurt Reeds’ organic traffic include “kay jewelry” (8 > 35), “watch brands” (2 > 6) and “scott kay” (2 > 5). Apart from these drops, there are hardly any striking changes to point out, as the loss in visibility occurred for the sub-domains as a whole and often quite moderately with losses between 1 and 3 ranks. In total, however, these losses sum up to such a massive drop as we have seen in the chart for the overall visibility.

keyword drops of

1.4    Summary of Visibility Analysis

So far we know that lost a considerable amount of its organic visibility, while its competitors haven’t been hit at all. The loss has affected several sub-domains, while (few) others could even increase their visibility.

Based on the data we can exclude specific changes in the site architecture that only affect certain pages or one specific sub-domain. Always pay attention when judging a site’s seo performance based on metrics like visibility scores. I’ve seen cases in which the visibility score decreased just because there was a relaunch, because a certain product category was removed or because one sub-domain was de-indexed. Considering the time of the drop, the lack of changes in site architecture as well as the performance of competitors’ websites, we can assume, that the change is related to the penguin update.

Of course, I will provide evidence to back up this assumption in the course of this case study.

2    Quick Analysis

The next step of the analysis process is to get a general idea of Reeds’ link profile. In the LinkResearchTools, you find several tools for quick analyses that I will use in order to derive my hypotheses for the detail analysis.

In my opinion the first quick analysis is a crucial step as it already guides me towards the most critical areas.

2.1    Root Domain Analysis

At first I want to have a look at the root domain. I ran a comparative analysis of and its major competitors from the first visibility score chart.

2.1.1    Competitor Analysis

The QDC displays the most important link metrics for up to 5 domains and enables a quick comparison of and its competitors. Don’t get stuck on the 8 wins for Macys is a huge brand in this industry and the large difference in the number and quality of links is very common for such a brand. Lower values for the several link metrics wouldn’t be a problem per se; we rather focus unnatural patterns when comparing the domains with each other.

What instantly draws my attention is the relation of the CEMPER Power and the CEMPER Trust metrics. The POWER value or Reeds is much higher than its TRUST value. All competitor sites either have a perfectly balanced relation or an even higher TRUST value. This could be a first good indicator for a link profile that is spammy and/or differs considerably from the link profiles of its competitors. We have seen similar patterns for Home24 and Cheapoair as well.

qdc root domain

2.1.2    Sitewide Links Ratio

The next metrics I’m interested in are the number of backlinks compared to the domain popularity in order to analyze the amount of sidewide links. This value is not displayed in the QDC. You can either calculate them yourself or switch to the JUICE Tool in order to get a more detailed insight into the number of sidewide links for each domain.

Select “Detail Analysis” and chose “Link Ratio Metrics” from the metrics.

juice report root domain competitor check

The results show the lowest Side-Wide-Ration (SWR) for Reeds compared to its competitors. It would be too early, however, to state that sidewide links haven’t been an issue at all. Don’t forget that this quick analysis focuses on the root domain in order to derive our hypotheses. The changes in visibility did not happen for all sub-domains consistently so it may well be the case that we find more striking differences in the sitewide ratio when comparing the sub-domains separately. These differences may be masked by the overall average of 18 right now.

juice report root domain competitor check results

2.2    How natural is’s link profile?

The sidewide ratio will therefore be covered again in the detail analysis. The difference in the POWER and TRUST values, however, will be examined in more detail at the root domain level using the Competitive Landscape Analyzer (CLA). I applied a sitewide links filter with a maximum of 5 links in order to avoid that sitewides dilute the different metrics.    Link Quality

The first set of metrics I have a look at is the Power*Trust Tab. It is quite easy to see that the link profile of Reeds (orange bars) differs substantially from the link profile of its competitors. Reeds has a much higher percentage for links from websites with a Power*Trust value of 1 (22% > 4%) or 2 (40% > 12%). The percentage of links from websites with higher values is much lower with only 3% for values from 5-7 (compared to 20%) and 2% for values from 8-12 (compared to 25%). The percentage of links from websites with even higher values is 0%.

It seems that both the high number of links from “weak” websites and the difference compared to the link profiles or its competitors has been one of the reasons for the massive drop in visibility.

cla quick power trust

The difference in the link profiles is even more obvious when analyzing the Power and Trust metrics separately, as shown in the chart below. In the Power chart, Reeds shows a huge peak for value 2 and in the Trust chart for value 1.

cla quick power trust separately    Anchor Text Distribution

Now I want to have a look at the keywords tab in order to see if Reeds shows significant differences in the distribution of brand (reeds, macys,…) compound (reeds engagement rings, jewelry at tiffany,…), money (jewelry, rings,…) or other keywords (website, link, here,…).

The results are very clear and show a huge difference in the link profiles of Reeds and its competitors.

cla quick keywords’s link profile only has 13% brand keywords compared to 84% of its competitors.
This leads to 82% money keywords compared to only 4% of its competitors.

I could classify more anchor texts above the chart but I think the results are already quite significant with 75% classified anchor texts.

The 3% labeled “other” may seem less relevant but blends in perfectly to an over optimized link profile. In the course of an organic link growth, there will be many websites linking to you with generic terms, as they just don’t think about anchor text optimization.

The low value of 3% “others” is another indicator that Reeds’ link profile consists largely of links generated through unnatural link building.

2.2.2    Link Status

Let’s have a quick look at the remaining metrics. The link status displays the relation between follow and no-follow links (and disavowed ones, if you upload them to LRT).

cla quick status

Reeds link profile also differs in this area. The 96% of follow links (compared to 88% of its competitors) doesn’t seem very natural, does it? And again it’s both the high percentage itself as well the striking difference to its competitors that make this link profile stand out from the crowd.

2.2.3    Deep Link Ratio

Another metric that may give us another relevant insight is the deep link ratio (percentage of links to sub-pages). Given the data we have already seen in this CLA report, we would expect a relatively high deep link ratio due to active link building directed towards strengthening the power of important sub-pages.

cla quick deep link ratio

And yes, what we see is that Reeds has a higher deep link ratio (59%) as compared to its competitors (49%). The picture of an unnatural link profile gets more and more complete with every metric that has been analyzed.

2.2.4    Some Link Sources in Detail

The next step in this general analysis is a closer look at by using the Quick Backlinks (QBL) tool. I just want to examine some links in more detail before I move on to deriving my hypotheses for the detail analysis. I selected the sidewide links filter that will drop sitewides after 5 links per domain.

Sitewides haven’t been an issue in my previous analysis, but I still want to avoid that they influence the data too much, especially, when examining the distribution of anchor texts. The maximum number of 5 is a recommendation by Christoph C. Cemper and so far it has also worked out for me fine applying this default setting.

qbl data entry

Before we dive into the various link metrics, let’s have a quick look at the report summary. We instantly see that 1,119 links have been removed because of the sitewide links filter. We can also see the CEMPER Power and Trust values we have already seen in the QDC report.

By clicking on “11,084 Links” we get additional information about the links that show up in the reports (10,790) and the distribution by the number of pages, domains (=sub-domains) and Topdomains (=root domains).

qbl summary

2.2.5    Hefty Keyword Distribution for’s Links

The first view that we see by default is the distribution of anchor texts. When I first had a look at the anchor text cloud I was wondering, whether I forgot to apply the sitewide links filter. But the filter was set, which means that the anchor text distribution was not influenced by sitewide links. anchor texts

Even if you are new to link profile analysis, you would immediately get very suspicious.

Money keywords dominating? Hardly any brand keywords? How likely is it, that 486 websites link to you with the exact same keyword (jewelry)?

The same applies for diamond rings (443 links), scott kay (295 links) and tag heuer (260 links). Please consider that there is just a single real brand keyword among the Top 9 anchor texts (reeds jewelers). Doesn’t seem very natural to you? Me neither! And guess how these numbers appear to Google… Greetings from the Penguin!

2.2.6    Deeper Dive into Money Keyword Links of

Let’s have a look at some of the links with such overdone money keyword anchor texts. I start with entering “jewelry” in the anchor text filter field in the table below. The filter has to be changed from “like” to “equal” in order to display only those links with this exact anchor text. jewelry links

What is noticeable is the very low Trust values and the higher Power values, which corresponds to our previous finding from the QDC. Reeds was the only domain with a considerably Power value that was higher than the trust value, as compared to its competitors.

What we see in the details table is lots of links from archives (look at the URLs) which leads to the assumption that Reeds has probably engaged in blog spam for a while (at least since 2008).

Taking a closer look at some of the links listed here confirms my assumption: blog spam from thematically unrelated websites all over the place. Have a look at the links marked in the table:


These blogs contain hundreds of posts with low content quality covering a wide range of different topics. The first blog places up to 3 external links with money keyword anchor texts per post, while the second blog at least tries to cover its blog spam practice by also publishing some posts without external links in between. Still, both link sources are very good examples for blog spam geared to generate links with money keyword anchor texts in order to push the website’s rankings for those keywords.

The first example ( ):

qbl jewelry links blog spam 1

And the second one ( ): jewelry links blog spam 2

You can find many more examples like this not only for “jewelry”, but also for “diamond rings”, or “scott kay”. When filtering for the only brand term “reeds jewelers” you can recognize that the listed link sources are much higher in quality with higher Trust values (most of the time these values are at least as high as the Power values).

2.2.7    Reeds’ Higher Quality Links Slice

Want to see, what Reeds’ anchor text profile would look like analyzing just the higher quality links? Let’s apply a filter for a minimum Power value of 3, a minimum Trust value of 3 and a minimum Power*Trust value of 12 (an adaption of the default slice for “Good Links”) and save this setting as a new slice. I’m aware that this setting wouldn’t necessarily be referred to as “good links “in general, but given the link profile of Reeds, this should rather be seen as segmenting the data based on Reeds’ top links.

You don’t know how to do that? Just take a look at the screenshot below. You can set up sliced based on any filters applied in the details table in order to segment date on basis of that filter also in other reports. setup good links slice

By clicking on the slice, you are redirected to another version of the QBL report only displaying links that correspond to the filter settings of the slice. This means you only see charts for that “slice” of links you have selected.

Have a look at the anchor text distribution. This looks quite different to the one without the slice and a much more natural.

Although these data are based on a small number of links, you can get an idea of how a more natural anchor text distribution would look like, just by excluding the low value blog spam links from the reports. anchor texts good links slice

2.3    Quick Analysis Summary & Hypotheses

So far we’ve already gotten a very good impression of Reeds’ link profile just by applying the quick analysis reports in the Link Research Tools. Let’s wrap up the major finding again before we derive the hypotheses for our detail analysis:

2.3.1    Findings at a Glance

Quick Domain Compare (QDC) supported by JUICE

  • is the only domain with a higher Power value compared to its Trust value in comparison to its competitors.
  • Its sitewide links ratio is the lowest among its competitors. That doesn’t mean, however, that this ratio applies to all sub-domains equally.


Competitive Landscape Analyzer (CLA)

  • Reeds percentage for links with a low Power*Trust value is considerably higher compared to its main competitors and considerably lower for higher Power*Trust values.
  • The percentage of money keyword anchor texts is massively higher (82%) than the percentage of its competitors (4%).
  • Reeds has a higher percentage of follow links than its competitors.
  • Reeds has a higher deep link ratio than its competitors.


Quick Backlinks (QBL)

  • There is only 1 (!) brand keyword anchor text in the Top 9
  • High number of exact match money keyword anchor texts (even with sitewide links filter applied)
  • Reeds has engaged in blog spam for a while characterized by money keyword anchor text links from low value link sources (Power > Trust)

2.3.2    Hypotheses

One could argue that deriving hypotheses may have already been done in the first place right before the general analysis. But I think that’s up to you. I personally prefer to apply the “funnel approach” going from broad to detail. I usually want to have an unprejudiced view during the general analysis and let the data guide me to the most striking findings rather than looking for specific patterns. Others might want to start already with specific questions in mind. Both approaches are perfectly fine!

We already got many strong indicators for what could be the reasons for the loss in visibility. But as Reeds relies on several sub-domains and given that some sub-domains actually increased their visibility score, I rather analyze based on hypotheses on the sub-domain level in the detail analysis. The different changes in visibility actually offer a great opportunity to analyze the degree to which certain factors affected Reeds’ rankings.

We’ve seen that has a very high percentage of money keyword anchor texts. It would be interesting to see whether this applies to all sub-domains equally or if those hit really hard fall more into this pattern while those with increased visibility don’t.

Based on the general analysis and the findings, I derive the following hypotheses:

  1. Reeds (meaning Reeds’ sub-domains) did not get hit by penguin because of sitewide links
  2. Reeds got hit by penguin because of its low quality link profile (Power*Trust)
  3. Reeds got hit because of its high percentage of money keyword anchor texts
  4. Reeds got hit because of its high percentage of follow links
  5. Reeds got hit because of its high deep link ratio


Further Research Questions

  1. Did an unnatural pattern for link types (text, image, redirects,…) cause the drop?
  2. Did redirects play a role in the drop in visibility?
  3. Did an unnatural pattern for site types (general, blogs, directories,…) cause the drop?
  4. Are there any differences in link velocity between losers and winners?
  5. Did links from suspicious websites cause the drop?

3    Detail Analysis of

We only just got started with our research. Read on!
We’ve gotten a first impression and some really good indicators for the reasons of Reeds’ drop after the penguin rollout. Let’s dig in deeper in order pinpoint the actually reasons by proving our hypotheses and examining further research questions.

3.1    Proving Hypotheses

As uses several sub-domains with differing performances after penguin, I’ll have a close look at how they differ for the various link metrics. I will always start with a sub-domain comparison and then proceed with specific cases at the keyword level.

3.1.1    Sitewide Links

As already stated, Reeds shows a comparatively low sitewide links ratio. My hypothesis was therefore, that sitewide links didn’t play a role in the massive drop in visibility. In order to backup this hypothesis, I performed several QDCs for all sub-domains. I exported the data into Excel to represent the data for all 16 sub-domains in one table.

Breaking down the overall data on the sub-domain level supports my hypothesis. Almost all sub domains have an equally low sitewide links ratio. The one outlier (diamonds, 160) is actually one of the winners. I did this additional analysis to see if there were some specific sub domains with higher values that had been hit, which, however wasn’t the case. It may well be the case that an overall low sitewide links ratio for the root domain masks more extreme differences on a sub domain value. I would therefore always validate overall mean values to be on the safe side.

subdomains sitewide links

3.1.2    Low Quality Link Profile

We’ve seen, that Reeds overall link profile shows a Power*Trust value of 15 generated by a Power value of 5 and a lower Trust value of 3. Let’s see how these values look like at the sub-domain level.

You see the visibility drop, and the Power*Trust, Power and Trust values as well as the difference between power and Trust for each sub-domain. With one exception, all sub-domains have a higher Power value compared to their Trust value. The difference, however, doesn’t seem to be one of the main factors for the drop as both winners and losers display similar proportions. This doesn’t mean, that the low link quality didn’t play a role at all, but it doesn’t serve as a reason why some dub-domains were affected and others not.

subdomains power trust

3.1.3    Percentage of Money Keyword Anchor Texts

One of the most striking findings from the general analysis was the high percentage of money keyword anchor texts, especially in comparison to Reeds’ competitors. In order to analyze the percentages for all sub-domains, I had to run separate Back Link Profile Analyses (BLPs) for each sub-domain. I will go through the process once and subsequently only show the aggregated results plus one specific example.

I selected on sub-domain at a time (please note that in LRT sub domains are referred to as domains, while root-domains are referred to as topdomains). I selected the sidewide links filter with the default settings and removed dropped links from the reports. Please also note that the screenshot is composed of 3 fractions of the BLP settings page.

blp settings for subdomains

It may be necessary to classify the anchor texts or some links (brand, compound, money, other) in order to obtain meaningful data for the distribution of anchor texts. You can do this right in the report summary, but I would rather do it via the keyword classification table as you can see in the screenshot below.

classifying anchor texts

Let’s have a look at the aggregated data that I compiled in Excel. These results are already more striking and confirm my second hypothesis, that 1. Reeds got hit because of its high percentage of money keyword anchor texts. The sub-domains with a high loss in visibility also display a high percentage for money keyword anchor texts. The only exception is “clearance”, showing a low percentage, but this percentage is also based on a lower amount of backlinks (177) compared to www (2,109) or scott kay (3,165).

All in all, it can be stated that the high amount of money keywords is one or the reasons for Reeds’ massive drop in visibility.

subdomains money keywords

3.1.4    Percentage of Follow Links

Another factor of interest is the distribution by link type. Based on the general analysis, I would expect that the losing sub-domains have a much higher percentage of follow links compared to their winning counterparts.

The data seem to back up the hypothesis, that Reeds got hit because of its high percentage of follow links. The top visibility losers are also the sub-domains with the highest percentage of follow links with values ranging from 86% to 98%. Clearance and Sale, as well as Store Watch don’t follow into this line. For me, there are two possible explanations for such exceptions:

  1. Some of these sub domains have a comparably low amount of links between 20 and 180 links which may mitigate the effect
  2. It is certainly not one single metric causing a hit by Google’s algorithms, but rather a combination of several metrics deviating from a certain threshold (or range that is considered to be natural)

subdomains link status

3.1.5    High Deep Link Ratio

The last of my hypotheses is concerned with the distribution of links towards the homepage and subpages (deep links). The data, however, don’t backup my hypothesis, that Reeds got hit because of its high deep link ratio. The results differ too much among winners and losers in order to derive a clear statement about the role of the deep link ratio. The deep link ratio is quite high for most of the sub domains. Please note however, that such high percentages may be common in one industry and completely out of line in another.

subdomains deep link ratio

3.2    Examining further Research Questions

After proving/rejecting the 5 main hypotheses, I want to take a closer look at some additional factors that might have played a role in Reeds drop.

3.2.1    Distribution of Link Types

The distribution of link types is such a factor. We’ve seen that Reeds has engaged in placing links in various blogs. I would therefore expect a higher ratio of text links for the losing sub-domains compared to the winners. Let’s see if that’s really the case.

Looking at the table, it seems that we’re onto something here. The percentage of text links is highest for the losing sub domains. Again, clearance and sale send conflicting signals, but I’ve commented on that already. Again, this doesn’t mean, that text links are bad! It means that an extremely high percentage of text links (or maybe also another link type leading to an unbalanced distribution of link types) may result in getting hit by penguin.

subdomains link types

3.2.2    The Role of Redirects

Even if it seems that redirects are not a big issue in the case of Reeds, I still want to have a look at them. The subdomain has the highest absolute number of redirects (90), so I will access its BLP report and filter for redirects in the detail table. 50 of these redirects pass link juice including 28 redirects from branded domains that just redirect to redirects

Most of these branded domains don’t have any links that could actually pass link juice to the main site. Only has an elevated number of links (95) at the domain level. I didn’t find any internal links that could be affected by the new way of how Google handles 301 redirects from 404 pages to the home page (Google now treats them as 404s).

Now I apply a reverse filter with for all redirecting links without the term “reeds” in them in order to see if Reeds works with expired domains that may have harmed the sites rankings. The links are again sorted by the number of domain backlinks. external redirects

The first link “” is twitter’s URL wrapper, so that looks fine. The following links from “” include redirects from selected URLs to the home page and subpages but it seems that these redirects are caused by intext ads (infolinks). Neither the redirects from “” now those from the various “” domains are considered to have any significant influence on, which leads me to the conclusion that redirects is not an issue in this case.

3.2.3    Distribution of Site Types

Analog to the analysis of link types, I want to further back up the argument, that Reeds’ blog spam tactic was one of the major reasons for the drop. Therefore, I analyzed the distribution of site types expecting a significantly higher percentage for blogs among the losing sub domains.

The results pretty much equal those of the link type analysis. The very high percentages of links from blogs correlate with high losses of visibility. The winning sub domains show a distribution that is way more balanced among the different site types. Link or article directories haven’t been an issue in this case.

subdomains site types

3.2.4    Link Velocity

I guess you have had a lot of these Excel tables for now, so let’s have a look at the link velocity of in comparison to our competitor set. seems to have engaged proportionally more in link building than its competitors, based on the data for domain popularity. There is a peak in February and March, but this peak applies to all domains equally. The question, if the higher link velocity over the past months has been a reason for the drop is difficult to answer. It will have contributed to a certain degree, considering all the other “bad” signals that I’ve already examined. link velocity

Let’s take another look at the link velocity for text links by switching to the respective tab, as this link type has been identified as one of the reasons for Reeds’ drop. I would expect a higher growth rate of text links for Reeds compared to its competitors. link velocity text links

Reeds generated proportionally more text links from June 2012 onwards than its competitors, which has influenced the proportion of link types in its link profile. It seems that -dotted line – has (intentionally?) reduced the amount of text links in mid-2012. This may have saved them from being hit by penguin.

3.2.5    Links from suspicious Websites

Finally, I want to check, whether links from suspicious websites play a role in Reeds’ visibility drop. I run DTOX reports for all sub domains separately in order to analyze the overall risk and further examine the proportion of toxic, suspicious and healthy links.

I then compiled all those separate Link Detox reports into the Excel sheet you see below. I thought it would be great if Link Research Tools would offer such a Competitive Link Detox. Christoph confirmed that this is indeed on the roadmap already.

The results of the compiled DTOX reports fall in line with previous reports as the losing sub domains generally have a higher average link detox risk and a higher percentage of toxic links and especially way more suspicious links than the winners.

dtox subdomains

This means the number of healthy links is considerably lower for the penalized sub-domains – in the twenties here, which is simply not enough.

Let’s have a look at one DTOX report in more detail. I chose for this purpose. Enter the domain and indicate whether the domain has already received an unnatural link warning from Google.

The report consists of a summary with the average link detox risk (quantitative and qualitative evaluation). In this case, we see a moderate risk with a risk value of 301. When scrolling down a bit, we see the distribution among toxic (10%), suspicious (76%) and healthy (14%) links.

dtox watch brands summary

You can access more detailed data by browsing through the different tabs. The link health breakdown basically displays the percentage of toxic, suspicious and healthy links. The link detox breakdown gives you an even more granular view on the different risk classes ranging from deadly risk to very low risk. In our case, the sub domain has about 5% of links with deadly risk that should be removed as soon as possible.

dtox watch risk breakdown

When we scroll down a bit, we can see a list of all links that can be sorted by their risk level.

dtox watch brands details

All in all, it can be stated, that the affected sub domains also show an elevated risk level, which also contributed to the drop in visibility.

3.3    Summary of the Detail Analysis

After performing the detail analysis, it can be stated that several sub domains of Reeds’ web presence got hit by the penguin update. There are several factors responsible for the overall massive drop in visibility as well as the drops on the sub domain level:

  • High percentage of Money keyword anchor texts
  • High percentage of follow links
  • Unnatural distribution of link types with a high percentage of text links
  • Unnatural distribution of site types with a high percentage of links from blogs
  • Elevated link velocity in general (Domain Pop) and for text links
  • Bad neighborhood: Moderate risk with comparatively higher percentage of toxic links
  • Losing sub-domains have considerably lower percentage of healthy links

4    Conclusions & Outlook is another victim of penguin 2.0 and you can be sure that there are already many more victims with similar issues like Reeds.

As Matt Cutts has already confirmed by twitter, there are more penguin updates to come.


If Reeds’ link profile looks familiar to yours, then you better get ready to make some radical changes to your link profile – regardless if you have or haven’t been hit yet!

In the case of Reeds Jewelry, there is lots of work ahead in order to get back on track. One of the most urgent tasks is definitely to get rid of toxic links and further lower the percentage of suspicious links. The next step centers around re-shaping the link profile towards a more natural appeal – in several regards: anchor text distribution, link type, site type, follow/no-follow and on top of that performing these tasks without generating significant peaks in the link velocity trend.

This case study was written by Christoph Hoffinger MA, now Christoph Hoffinger MA,CLRTP reviewed and approved by Christoph C. Cemper for publishing as Certification work for the Certified LRT Professional level.

A word from Christoph C. Cemper

Certified LRT Professional

This analysis was conducted and post written by our LRT Associate Christoph Hoffinger MA,CLRTP, Founder of Adwordize, an Austria based Online Marketing Agency. I highly appreciate and recommend his work reading, learning and further research and discussion.

I am amazed what Christoph put together, and appreciate his hand in. is a complex case with all their sub domains, and Christoph Hoffinger went the extra mile to combine a lot of separate reports from Link Detox, Competitive Landscape Analyzer and others in Excel sheets to get a fuller picture. This research was definately a lot of work, but there’s a lot more work ahead for Reeds…

I therefore grant Christoph our Certified LRT Professional status by approving and publishing his research on our site.

This is Christoph’s next step towards the Certified LRT Xpert level which is pre-requisite for the Certified LRT Agency certification. Both will qualify him to receive consulting leads for free, i.e. without any referal kickbacks of commissions to us. Our goal is to provide our community and clients a high quality service, and our certified experts are key to that.

I am sure Christoph will be there soon. As you can probably judge from his work already, I can already wholeheartly recommend him to work with you whenever you get a chance!

Christoph-Hoffinger Certified Link Research Tools Professional

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Christoph Hoffinger

Christoph Hoffinger the is the founder of adword!ze, a Vienna based agency for search engine marketing, conversion optimization and web controlling.

Christoph Hoffinger

Christoph Hoffinger

Latest posts by Christoph Hoffinger


  1. @lnkresearchtool June 2, 2013

    Deep Dive Analysis of the Penguin 2.0 Penalty of

  2. @harrogateseo June 2, 2013

    Penguin 2.0 Penalty Analysis of #harrogateseo

  3. @Ammad_Ali June 2, 2013

    Deep Dive Analysis of the Penguin 2.0 Penalty of via @cemper

  4. Eureka-Webdesign June 2, 2013

    Thank you for emplainig a Deep Dive Analysis of the Penguin 2.0 on an example Domain. This is a very powerfull tool!

  5. La MarkeTeam June 2, 2013

    Thanks a lot for your case studies, always full of insights, i particularly like the way you have to identify the full range of unnatural caractiristics of the link profile. Very powerful, this really gives a great checklist to work with…

  6. Jetlir June 2, 2013


    Thanks for this detailed study, show’s some good insight & the problems are obvious now.

    Is there also a .PDF version available of the recent 3 analyzes that you have made?


  7. Gijs June 2, 2013

    It is very interesting to read this case, one client did slightly rank worse before last Penguin, and he is having a few toxic links, but when i take a better look at those links, they are 100% perfect.

    So you should use the Cemper tool for finding toxic links, but always check also for yourself.

    • Christoph Hoffinger June 2, 2013

      Hi Gijs,

      Thanks for that interesting insight. What do you mean by “they are 100% perfect”? There are 2 types of toxic links in the LRT: TOX1: domain is not indexed by Google (either because of a penalty or because its a new domain) or TOX2: the theme of the domain is considered as dangerous (malware, malicous or virus).

      Did you have a look at those factors when checking those toxic links? Would be interesting to know!

      Best Regards,

  8. @osandacooray June 2, 2013

    Deep Dive Analysis of the Penguin 2.0 Penalty of via @cemper

  9. @WilliamRock June 2, 2013

    Deep Dive Analysis of the Penguin 2.0 Penalty of via @cemper

  10. @seodvize June 2, 2013

    SEO: Je zoekwoord nog in je linktekst (anchor text) vermelden = big no!

  11. Reqsta June 3, 2013

    Wow, a ton of good work! Very nice deep analysis, thanks.

  12. @dfaltz June 3, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis via @cemper

  13. @Diana_Sch June 3, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis via @cemper

  14. @Nathan_Khan June 3, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis via @cemper

  15. @Blackterril June 3, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis via @cemper

  16. @JimWatson9 June 3, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis via @cemper

  17. Amit June 3, 2013

    Hi Christoph,

    I loved the complete analysis. I have a client whose links looks similar to this pattern and is probably hit by penguin.

    Now my question is that What steps to be taken now? I would be glad if you can share some detailed resource (as you already mentioned brief above) like this, to remove penguin penalty.

    Thanks in advance.


    • Christoph Hoffinger June 3, 2013

      Hi Amit,

      Thanky for your feedback and insights into your client project.

      General answer: reshape your clients’ link profile so that it gets more natural (consider competitors, as “natural” varies from industry to industry)

      Detailed answer:
      I would start with removing bad links, tackle the toxic ones first, then continue with suspicious ones. If you have ressources, I would also start looking for healthy links so that you can start building up the links that you need (again see results of the CLA what “good” links are in your case. This will certainly take a while, as you may have to contact many siteowners, which often turns out to be quite difficult/time consuming.

      I would also consider using the disavow tool, especially for those links that you can’t remove. There are different opinions about the disavow tool, you may have a look at the following post by Cyrus Shepard on moz: “”

      I you didn’t have time for building up good links yet, then you should definitely start with this task after you’ve removed/disavowed a significant portion of your bad links.

      As already mentioned in the case study, please always have a close look at the CLA and closely monitor the distribution among the different metrics (follow/no-follow, deep link ration, link type, site type) and try to get your link growth in line with the one of your competitors.

      I hope that helps a bit! In my opinion, it is primarily about getting a healthier link profile. If the site has “only” been hit by the update (and if there is no manual penalty involved) you have to get rid of those signals that Penguin is looking for.

      Hope you can “save” that site, as there are more Penguins to come…

      Best regards,

  18. @Hayhay09 June 3, 2013

    Another fantastic piece of analysis that I loved getting stuck in to on Penguin 2.0 losers via @cemper

  19. @changerdesite June 4, 2013

    Reeds Penguin 2.0 Penalty – the 3rd Deep Dive Analysis #SEO #penguin #webmarketing

  20. @Emarketeers June 5, 2013

    Penguin 2.0 Penalty Analysis Case Study. Well worth the read! #SEO

  21. @NickRinylo June 5, 2013

    If you haven’t already seen @lnkresearchtool case study on Penguin 2.0 get reading.. #SEO

  22. @dnespo June 7, 2013

    Reeds #Penguin 2.0 Penalty – the 3rd Deep Dive Analysis

  23. @pagusmedia June 11, 2013

    Reeds #Penguin 2.0 Penalty – the 3rd Deep Dive Analysis | #SEO

  24. セイコー5 June 21, 2013

    Wow, this paragraph is nice, my younger sister is analyzing these things,
    therefore I am going to inform her.

  25. netyc June 30, 2013


  26. jan February 5, 2014


    i dont understand the metric site wide ratio. If the sitewideratio is low this means there are lot of backlinks from different domains. But you write a high sitewideratio is good and so the domain wins. but this means there are a lot of sitewidelinks from same domains?? maybe you can explain this to me?


  27. Nathan February 18, 2014

    Thanks a lot for your case studies

  28. Cyrek February 19, 2014

    Nice case study! Thanks!

  29. Arshad Rehman March 15, 2014

    Thank you so much for this case study. We found ourselves in a hole after finding our situation to be the same. Were you planning on having a follow up to this case study. We want to know if Reeds ever bounced back from following these fixes.


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