Contrary to initial speculation, in the latest Google update, Google’s Medic Update has ramifications that go way beyond the health industry and establishing author expertise.

A year from now we may look back at August 2018 as a pivotal shift in how SEO works, on par with the introduction of Google Panda and Penguin (if less cutely named).

As more hard data emerges, we’re starting to see a clearer picture of which factors played a role in rankings changes, and how the big Medic Update was about much more than just Expertise, Authority, and Trust.

A lot of great websites lost rankings after the Medic update. If you’re among those affected and trying to understand why, we hope this list of influential factors will help you focus your search. If you need further help, let me know! Recovery from the Google Medic Update is possible.

Note: This is an edited version of research we put together for CanIRank Full Service clients. Part 1 explained What is a broad core algorithm update?, this is part 2, What changed in in the Google Medic Update?, and part 3 (coming soon!) explains How to Recover from the Google Medic Algorithm Update.

As a team that combines marketers with data scientists and engineers, we believe a key part of an SEO consultant’s job is to help clients understand how Google’s high-level objectives like “make great content” or “become the leading authority in your field” translate into actual machine-readable signals, and how you can improve your content marketing processes to strengthen those signals while still balancing other business objectives.

This 3-part series on Google’s latest core algorithm update (“Medic Update”) is our attempt to help elevate the conversation around algorithm updates to more of an evidence-based exploration focused on specific algorithmic signals rather than intangible high-level objectives.


Now that we have an idea for what Google was trying to accomplish with the Medic Update, and how they might have gone about making those changes, we can dive into better understanding how the update changed the importance of various ranking factors.

In order to identify which algorithmic signals are correlated with gains and losses in Google’s big Medic update, we identified approximately 100 sites that had seen significant changes in one direction or the other. Most of the examples are medium-large sites due to data availability, but we found sites impacted of all sizes, business models, and industries, including health, financial services, travel, SaaS, coupons, auto, and ecommerce.

Using CanIRank’s SEO Competitor Analysis tool, we analyzed keywords with large fluctuations to see how gaining URLs differed from losing URLs. Based on that preliminary analysis and initial reports in the SEO blogosphere, we came up with a list of 27 potential culprits to analyze further, such as the presence of contact information, quality of an author’s credentials, and link velocity.

The preliminary statistical findings are based on complete data for about a dozen URLs each from 51 different websites, 33 of which saw significant and sustained declines beginning August 1st, and 18 that saw significant and sustained growth during that period. For the remaining sites analyzed our data is still incomplete, but there were already clear enough patterns at 51 completed that we thought it worth publishing before more businesses waste time and money chasing the red herring of Expertise / Authority / Trust.

Study Limitations

Apart from the small sample size, the study has a number of additional limitations, and as such should be looked at more as an aggregation of anecdotes than statistically valid research (by comparison, CanIRank’s ranking models are based on analysis of almost 600,000 websites).

We’re not trying to imply weighting or even utilization of specific signals — our objective is to identify possible areas for further analysis and experimentation so that we can guide our clients (and you!) in how best to take advantage of Google’s new ranking algorithm.

As we’ve stressed before, correlation is a terrible way to gauge the relative impact of specific SEO ranking signals because different URLs rank for different reasons. Each of those 10 blue links on page 1 are playing the game by a different set of rules. Smart SEOs ignore those “Google’s 200 Ranking Factors Finally Revealed!” clickbait posts and instead spend a lot of time on competitive analysis to understand which factors matter for the specific keywords they’re interested in.

As applied to diagnosing and reversing traffic declines, this means that there was no single “smoking gun” that caused all the changes we see here (not even something high-level like E-A-T or content quality). Instead, we took the time to understand what the likely culprit was for most of the declining sites (and there was almost always at least one glaring issue).

For example, scored very high on measures of content quality, expertise, and authority, but they have some fundamental technical SEO issues. It’s hard to beat LonelyPlanet for content quality and expertise in the travel industry, but they have some hard to distinguish sponsored content that could be seen as deceptive, as well as thin UGC.

Situations like that don’t lead to strong correlations for any one factor; that’s the nature of a “broad” update.

Some of the factors we looked at were subjectively evaluated by our team of SEO consultants using common guidelines similar to Google’s Search Quality Evaluator Guidelines. Subjective evaluations are a recipe for bias, but given our team has no particular interest in any one factor “winning”, at least it’s plausible that we were all inaccurate in a randomly distributed way.

Lastly but most importantly, since none of these sites are CanIRank clients, we’re estimating the change in organic search traffic using 3rd-party SEMRush data, which unfortunately isn’t entirely accurate, especially for small websites and during times of high volatility. We did source some gainers/ losers by reading comment threads where webmasters claimed they were impacted, but apart from that we have no knowledge about the organic traffic performance of these websites beyond the publicly-available SEMRush estimates.

Ranking Factors Associated with Traffic Gains or Losses

Let’s get right to the good stuff: data! Here’s a scatterplot matrix of 20 numeric factors we evaluated at the website level:
Data on ranking factors changed in the August Core Algorithm Update
A steep upward sloping line suggests that factor was associated with rankings increases, and tightly clustered dots suggest good fit. Flat lines suggest that particular signal had no impact on rankings, and downward sloping lines mean sites scoring high on that factor were actually less likely to improve their rankings. For my fellow data nerds who like pretending SEO research is more valid than it really is, I also included correlation coefficients, R2, and P-values.

Let’s examine some of the most influential factors in more detail.

Content Length


  • Correlation w/ change in Organic Traffic: 0.50
  • P-Value: 0.00017
  • Example Sites Impacted:, Khan Academy,

Note that we looked at content length relative to other ranking content in that niche, not absolute content length. I think that’s an important distinction, because as Google themselves have pointed out, you don’t need necessarily want a 5,000 word answer to “what time is the Super Bowl?”

We knew already that there is a weak correlation between search ranking and content length, and I believe that’s stronger here due to the predominance of sites in niches like finance and health where in-depth content is preferred.

Mobile Experience


  • Correlation w/ change in Organic Traffic: 0.48
  • P-Value: 0.0058
  • Example Sites Impacted:,,

Nearly all of these sites passed Google’s mobile friendliness test with no errors. Instead, we subjectively evaluated mobile experience by looking at things like usability (font size, contrast), content visibility, and touch target size. Since we’re comparing these factors against changes in organic traffic for Google’s desktop index, I was surprised to see this strong of a correlation. I suspect that’s because sites executing well in this area are generally better at UI and web development, which may be measured by other signals.

Ad Experience


  • Correlation w/ change in Organic Traffic: 0.38
  • P-Value: 0.0064
  • Example Sites Impacted:,,,,,,,,

With all of the big names caught up in this update, some of the big traffic declines were really perplexing — until I disabled my ad blocker. Wow, what a scary place the internet has become to the unprotected.

Of course, we’ve heard about Google penalizing excessive ads before, but like we explained in part 1, August’s core algorithm update wasn’t so much about introducing new signals as it was shifting the weightings for certain query intents.

In particular, Google seems to be cracking down on deceptive ads that are too easy to confuse with content. For many of the most dramatic rankings drops, deceptive ads are the likely smoking gun:


Excessive ads also appear to have been a strong negative factor for some sites. Although we didn’t break out stats by ad type, some of the biggest sins appear to be obscuring content with persistent overlay ads, pushing content below the fold, and autoplay video ads (thank you for that one Google!!!).

Here are a couple examples of excessive ads on authoritative sites that saw rankings declines:



Content Quality


  • Correlation w/ change in Organic Traffic: 0.38
  • P-Value: 0.0067
  • Example Sites Impacted:,,, BonsaiMoney

Content Quality is amongst the most subjective factors we looked at, and we mainly included it to appease all the vainglorious folks who emerge from obscurity at times like this to say helpful things like “just write great content and you’ll never have to worry about a Google update again”.

Several sites with high-quality content saw significant drops, including,,,,, and

In any case “Content Quality” isn’t a single signal but some combination of lower-level factors like relevancy, writing quality, satisfying the query intent, and presenting the content well. Although we didn’t collect data on all of these individual factors, we did notice that content on gainers tended to have a few things in common:

Natural Language Processing has continued to evolve at a rapid pace the past few years, and while I don’t think we can yet algorithmically determine if a piece of content is beautifully written or useful or interesting, it certainly is possible to distinguish the casual “layman” tone of a mommy blogger (for example) from the professional tone of a journalist or the dense jargon-heavy tone of a scientist or other specialist.

I’m not saying Google uses tone as a signal and I definitely don’t think it would be a good way to establish expertise (one might even say that the best experts are those who are able to explain something in an accessible manner). However, it does seem that this update tended to shift things up the seriousness scale a bit:

We also looked at various automated readability scores like Flesch-Kincaid grade level, etc. but didn’t find any relationship.



  • Correlation w/ change in Organic Traffic: 0.33
  • P-Value: 0.0163
  • Example Sites Impacted:,,

As with Content Quality, we’re using a subjective human evaluation of design as catch-all for an entire category of potential signals. It was hard not to notice that some of the gaining sites had incredibly usable, elegant, and modern user interfaces. DietDoctor,, Consumerism Commentary,, and LonelyPlanet were some of the highlights for me.

How might we algorithmically distinguish sites like that from something that looks like it was built on Geocities?

It’s certainly plausible that given enough training data, a machine learning algorithm could learn to distinguish attractive, usable designs from cluttered, ugly ones, perhaps by looking at signals like a limited color palette, consistent styling, sufficient white space, appropriate visual hierarchy, etc.

Plausible…but not likely. My hunch is that Google doesn’t need to do this because good-looking sites are already being rewarded by so many other signals that are both more robust and easier to calculate, such as links, engagement, and brand metrics.

It’s also likely that businesses who care enough about their website to invest in a great design also care enough to invest in great content, a good SEO agency, consistent outreach, etc.

Site Speed


  • Correlation w/ change in Organic Traffic: 0.32
  • P-Value: 0.060
  • Example Sites Impacted: Vaping360,,

Though not statistically significant, there was a modest correlation between rankings improvements and site speed as measured by Google’s Lighthouse tool. I wouldn’t give too much weight to this as sites that perform well often execute well in other areas too. However, site speed is a worthy goal regardless of whether or not it brings SEO benefits!

For the Google Lighthouse fans out there (you’re among friends!), below are the graphs for the other Lighthouse scores. Although none reached statistical significance, the Progressive Web App and Best Practices scores had the highest correlations:
Lighthouse correlation
If your site scores low on automated performance measurement tools and some unscrupulous development agency is trying to convince you that dropping a few hundred Gs on a site overhaul will help your cover your lost rankings, I’d be skeptical. After all, even Google’s own — which increased organic traffic 107% in this update — only scored a 45 on their own performance tool.

Inbound Link Trust


  • Correlation w/ change in Organic Traffic: 0.25
  • P-Value: 0.07
  • Example Sites Impacted: VaporDNA, BonsaiFinance, AxonOptics, KetoDash

We’re below the level of statistical significance now, but it’s impossible to talk about expertise without mentioning links. Despite their many shortcomings and abuses, links have endured over 20 years as the most reliable signal of a web page’s importance, which is really remarkable.

When one looks at the link graph, there are millions of little clusters around each industry and affinity group. Bouldering websites link to other bouldering sites, cosplay sites link to cosplay sites, and both groups are perfectly happy that they almost never link to each other.

In certain situations those in-network links can be really helpful — who knows the best bouldering sites better than another enthusiast?

But in other situations, close-knit affinity groups can create a sort of “link filter bubble” where a bunch of closely-related sites essentially cite each other as sources.

For example, anti-vaxxers are much more frequently discussing and linking to vaccine-related content than the silent majority who trust vaccines.

To take a less extreme example, many in the paleo community love discussing and sharing the latest nutrition research, generally linking to other paleo blogs (and CrossFit workouts, of course).

Another closely-interconnected community is the green/natural/alternative health space.

In each of these examples, you have a passionate subgroup that is much more vocal online (read: linking more) than a silent majority that reflects mainstream viewpoints.

It seems that in the Medic Update Google decided they couldn’t risk passionate alternative viewpoints overwhelming the search results on sensitive YMYL topics.

Many of the alternative health sites that declined were leaders in their niche, like DrAxe, SelfHacked, Mercola, or WellnessMama. However, much of their authority came from other similar sites, and rarely did they manage to break into earning links from sites with extremely high TrustRank.

Sites that gained in the latest Google algorithm update, like,, HealthLine,, and all managed to earn a significant number of links from mainstream, high TrustRank websites.

However, there’s also another possible explanation that the Medic Update isn’t targeting alternative viewpoints at all: it’s targeting networks.

Google does sometimes react to bad press, and Glen Allsopp AKA ViperChill did an excellent exposé showing how media conglomerates interlink their huge networks of sites to boost authority and dominate search rankings:
companies dominating google search
It’s hard to imagine Google wasn’t already aware of this problem, but having a prominent SEO point out that they’re being pwned by 131 year old media conglomerates probably poured salt in the wound, especially for a bunch of fixie-riding, vinyl-listening, SF hipsters like Google employees (just kidding, actually I don’t think I’ve met a single Hipster Googler).

Coincidental or not, a lot of sites that declined in the August Core Algorithm update were part of a network. To name a few:

  • -21%
  • -57%
  • -13%
  • -36%
  • -26%
  • -20%
  • -17%
  • -21%
  • -16%
  • -19%
  • -12%
  • -18%
  • -29%
  • -34%
  • -29%

Of course, most big online publishers are part of a network, so this is far from conclusive.

About Page


  • Correlation w/ change in Organic Traffic: 0.24
  • P-Value: 0.09
  • Example Sites Impacted:, LouderSound, NaturalLivingIdeas, MensHealth

Beefing up your About page to emphasize credentials, authority, and expertise is one of the actions frequently recommended to fix Medic traffic declines by SEOs focused on the EAT aspects of the update. Although not statistically significant, About page quality did have a modest positive correlation with ranking improvement.

We subjectively evaluated the quality of About pages specifically with an eye towards how well they communicated expertise and credibility. While improving your About page is an excellent idea for many reasons, the difficulty in objectively scoring About pages underscored my skepticism over its validity as a machine-readable signal.

Let’s look at a few specific examples: Men’s Health doesn’t have an About page at all (and would an About page increase credibility of a household name?). LouderSound doesn’t have an About page, but links to their parent company. Khan Academy and REI have weak About pages, but an entire section of “about” content.

At a content level, machines can’t “read” expertise in the way they can keyword relevancy. Even if you built an “expertise-scorer” that looked for things like professional and educational experience, awards, press, etc. — it would be easily fooled. And many of the most credible experts in every industry wouldn’t bother putting that kind of stuff in their About pages, either because they feel their reputation precedes them, or simply because they don’t like self-promotion.

Bottom line: yes, Google cares about your expertise and authority. But they’re looking at off-site signals to determine that, like links, brand mentions, branded search volume, and possibly social followers. You can’t just declare yourself an expert on your About page and expect Google (or anyone else) to believe it.

Other Influential Factors

Query Intent Fit

  • Example Sites Impacted:,,,,,

I hesitated to even include this as a factor because it’s more of a unifying hypothesis than a signal. We are working on collecting more data to determine what it means to have a good Query Intent Fit, and what can be done on a practical level to reinforce fit.

If early anecdotes are indicative, I would not be surprised if these are the types of questions that every good SEO will soon be grappling with on a daily basis.

So what is Query Intent Fit, and why do we feel it has become increasingly important following this update?

First, many of the health site fluctuations can be explained through this lens. If I search a serious health query like “symptoms of colon cancer”, it’s extremely important that I receive scientifically accurate, comprehensive, and unbiased information.

Sure enough, the declining sites for queries like this tended to be more lifestyle or alternative health oriented, and less scientific:
serious query
The query intent hypothesis also helps explain why high-quality ecommerce sites like REI, Crutchfield, or declined despite note having any glaring issues.

For some time, many marketers have considered it a best practice for ecommerce sites to add high-quality informational content to their websites. Sophisticated online consumers (particularly millennials and younger) want to know the story and “deeper purpose” behind that purple romper dress they’re buying. Where was it made, how does the company treat their employees, what is the company’s philosophy on fashion or environmental issues, can I wear this to Coachella?

Sites like RedBull, Patagonia, Huckberry, Madewell, FreePeople, REI, HomeDepot, or BetaBrand connect with their customers so effectively they start to blur the line between store and media destination.

Although it wasn’t rewarded in this update, I think you can make a strong case that if I’m trying to choose the right climbing rope or setup a home theater, the content on REI and Crutchfield will satisfy my query intent better than a catalog page. An educated consumer makes a better purchase decision. And the fact that these sites convey expertise gives shoppers greater confidence in their product quality.

But in other instances the value from mingling commercial and informational content is less clear.
ecommerce seo text
If I search “shoes” I probably don’t need a 500-word explanation of shoes like I get from Macys or — I just want the online or local shoe stores with the best selection, pricing, customer-friendly policies, and shopping experience.

If a store sells herbal teas, they may not be an impartial source for an article on “How herbal teas can cure your migraines”. Should Google trust a site like Dr. Axe, Mercola, or less because they have a store selling solutions to some of the health issues they discuss?
ymyl query intent mixing ecommerce
What about a natural treatments blog that monetizes via affiliate links to purchase the natural cures they discuss? Or a medical site selling ads to pharmaceutical companies? There’s clearly a spectrum here.

Regardless, once it’s time to make a purchase, for most people the educational benefits of content take a back seat to considerations like price, customer-friendly policies like free shipping and easy returns, reputation, and ease of purchase.

Thanks for the info Crutchfield, but I’m still going to buy this receiver from Amazon so I save $7 and get it in 2 days.

That would explain why sites like Costco, Kohls, Amazon, Ebay, and B&H Photo all appear to have gained in this update. Nobody gets excited about linking, sharing, or even reading what Costco has to say about that 5 gallon tub of cookie dough. But when it comes to the American Dream of buying a ton of crap we don’t need at fantastic prices, these sites make for satisfied searchers.

It also explains why ecommerce sites with best in class content are no longer being rewarded for that, as Brian Chappell noted in the medical device space:

These are not situations traditional information retrieval tools are designed to address. Perhaps the challenge of executing well explains why it’s also easy to find examples that contradict the query intent hypothesis.

For example, while REI and Crutchfield with their extremely useful content both lost ground in this update, Macys and are both still ranking well with their pointless 500-word definitions of shoes.

Many sites that integrate a store with content and also (arguably) lack expertise don’t seem to have been impacted by this update either, including,,, and Other major ecommerce retailers with high quality integrated content (including and didn’t see the declines that REI and Crutchfield did. Two of the biggest gainers in the health niche, and, are also ultimately selling a product (how else could they forego advertising and produce such high quality content?), albeit in a much more subtle way.

Clearly there’s more going on here than can be explained by a simplistic hypothesis. For more background on query intent, see part 1 in our algorithm update series. Further research will revolve around how shopping and ecommerce can safely be integrated, and which signals appear to support shopper satisfaction.

Technical SEO

  • Example Sites Impacted:, LonelyPlanet,

With all of the early talk about Expertise / Authority / Trust, many SEOs forgot about their fundamentals.

If we think about a Broad Core Algorithm update as primarily being about adjusting weightings for different query intents, it makes sense that technical SEO errors would play a significant role in the drops.

For example, site-wide Quality scores like Panda have always been impacted by technical SEO issues like thin content and duplicate content. If Google decides that a YMYL result, for example, must be on a high quality site, websites with mild technical SEO issues that previously went under the radar would see big drops.

And that’s exactly what happened.

The most clear-cut example is probably, which according to SEMRush dropped almost 40%. Given that SelfHacked’s articles are thousands of words long, meticulously annotated, chock-full of helpful information, and written mostly by PhDs and others with a high degree of expertise, I imagine they’re getting pretty tired of all the SEO gurus telling them this update is about E-A-T.

But if we assume that health-related sites now have a higher bar for Website Quality, the riddle becomes more clear. Despite nailing all of the “hard stuff” like content quality and great links, SelfHacked made a basic technical SEO error and didn’t configure their WordPress properly to prevent indexing of images on individual pages. As a result, they have hundreds of extremely thin image pages in Google’s index:

If the folks at SelfHacked read this, fix those (and a couple other issues), and I think it’s highly likely your rankings will recover.

Technical SEO also appeared to play a role in the drops of other high quality sites like Khan Academy (-13%), Lonely Planet (-12%), and My Protein (-40%).

Semantic Optimization

  • Example Sites Impacted: Most gaining sites did a good job with this on keywords where they gained

Although we didn’t collect optimization data because we weren’t analyzing sites at the keyword level, in our work for clients we have noticed a lot of examples where semantic “meaning-based” optimization techniques saw significant gains.

After the big Medic Update we’re seeing a lot more pages with high CanIRank Page Relevancy scores amongst the top results. Check out the change in the first and third column in these before-and-after competitive analyses:

“nicotine salts”before and after google update - has google had an update


“new cars”new cars keyword analysis


“powerpoint to pdf”SEO competitor analysis what is google medic


In all 3 cases, pages with higher Page Relevancy scores leapfrogged pages with lower Page Relevancy scores.

Unlike other SEO software that scores on-page SEO based on keyword usage, CanIRank’s Page Relevancy scores are a semantic “meaning-based” measure of optimization. Google has been moving more and more towards semantic relevancy since the introduction of Hummingbird 5 years ago, the trend has intensified with the rise of voice search, and with the August update they appear to have taken yet another big step in that direction.

We’ll dive more into semantic optimization best practices in our guide to Medic recovery, but in the meantime know that these scores are based on the usage of Related Terms and entities that help search engines understand what the page is about.

Related Terms are sometimes mistakenly referred to as “LSI keywords” by SEOs who want to sound smart, in reference to a specific algorithm (Latent Semantic Indexing) that is almost 40 years old and has likely never been used by Google or any other web-scale search engine.

The Revenge of Anchor Text

  • Example Sites Impacted: Ask your friendly neighborhood Black Hat

One group that doesn’t appear to have suffered in the August Core Update is Black Hat SEOs. We’ve seen some significant (and unfortunate) gains in low quality sites that aggressively use keyword anchor text (see the third column in the competitive analysis tables above).

In the majority of cases, the keyword anchor text came from PBNs or obviously paid links.

This seems like a reversal of the trend over the past few years, where keyword anchor text was becoming less important (and even harmful if overdone, thanks to Google Penguin).

I would show you examples, but you’d probably throw your laptop out the window in frustration over the inequity and hypocrisy of Google making things so much harder for businesses who follow their rules while rewarding those who don’t.

Factors that didn’t seem to make a difference

Author Profiles or Credentials


did prominent author expertise and credentials help rankings

  • Correlation: -0.17 (Profiles), -0.18 (Social), 0.18 (Credentials)
  • P-Value: 0.25 (Profiles), 0.22 (Social), 0.23 (Credentials)

Some of the early articles focused on E-A-T recommended things like hiring the very best experts you can afford to write your content, and then creating robust author profiles detailing their credentials, expertise, and social media profiles.

So for everyone wondering how they were going to afford paying an MD $700 / hr to write paleo brownie recipes, I have good news: both robust author profiles and links to author social media profiles were actually negatively correlated with rankings improvements in the August update.

Author credentials had a small positive correlation.

However, none of these correlations were statistically significant, and a good SEO should be able to help you identify more robust expertise signals than author profile pages, credentials, or social media profiles.

If you’re still convinced that expertise and author credentials are a factor, consider that a large number of sites with questionable science or outright fake news did NOT see a decline in this update: (+10%), (+15%), (+7%), (-3%), (+352%), (+35%), (+3%), or (+10%).

If this is an attempt to reward author expertise, Google missed the mark.

Remember, Google’s Quality Rater Guidelines measure outputs, not inputs. In other words, the Quality Rater Guidelines tell us the types of sites Google wants their signals to boost, not the signals themselves.

Of course, that doesn’t mean that adding robust author profiles and hiring authors with a high degree of expertise in your field is a bad idea — quite to the contrary, in many cases. But if you’re looking for a more direct path to recovering your lost rankings, you’ll have better luck if you consider the inputs search engines are looking for as well as the outputs.

Contact Information


what is medic update in seo

  • Correlation w/ change in Organic Traffic: -0.02
  • P-Value: 0.87

Another recommendation from the E-A-T crowd was to add contact information on every page, or at the very least have a robust Contact Us page with phone, email, physical address, etc.

This, too, is a fine idea but not something that seems to have impacted rankings during the latest update.

Google does have an identity layer, but as local SEOs will tell you, it’s determined by a lot more than your Contact Us page. It may be that the identity layer played a role in this update for certain sites. For example, we noted a handful of non-US based ecommerce sites losing rankings in US This fits with the “Query Intent” hypothesis: location doesn’t matter much if I’m researching measles, but it does if I want to buy a new mountain bike. Next time someone asks you, “What is the Google Medic update?” we hope you’ll have enough data to answer accurately.

Up next: how to recover from the Medic Update?

In the third and final post in our series on Google’s August Core Algorithm Update AKA the Medic Update AKA the Query Intent Update, we will get into specific action steps you can take to identify which of the above signals may be responsible for your site’s decline, as well as what you can do to reverse the damage and recover your lost rankings. Diagnose, fix, and repair any damage done by the Google Medic update.