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Google keyword match type tournament: Place your bets on Exact

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Deciding which match type works per keyword is an age-old Google Ads question. After the latest exact match update, it’s in every paid search marketer’s interest to answer it. So we did.

On Sept. 6, Google informed the search community that the meaning of “exact match” would be open for interpretation from search engines. Ginny Marvin reported on the update explaining that aside from close variants like plurals and misspellings, exact match keywords would now also include synonyms and paraphrases. Google’s decision was reacting in part to the fact that people can search for something as simple as deodorant 150,000 unique ways.

Photo credit: Google

These changes are intended to be positive for advertisers who can have their ads show up for more terms without having to perform exhaustive keyword research (although it puts greater pressure on campaign managers to audit search terms reports). The extent of how this update has impacted Google search campaigns at large has yet to be measured.

But with exact match keywords now showing up for so many paraphrases and related queries, why bother with other match types at all? Before doing away with broad and phrase match however, we as a search community needed to actually sit down and prove it to ourselves. We set out to measure and analyze exactly how the same keyword with two different match types would perform. The battle unfolds below, but first let’s visit how this complex analysis went down.

What and how were match types measured?

Currently there are four different match types offered inside Google Ads:

  1. Exact
  2. Phrase
  3. Broad
  4. Modified Broad Match (MBM)

To measure the impact of the exact match relative to other match types we had to put them all under a microscope for the analysis. Aside from match types, we also focused our research on accounts in our database using Acquisio Turing machine learning (my employer) since its campaign level bidding data is unbiased to bids set for different match types of the same keyword.

Between January and October of 2018 there were 978,358 keywords that had at least 2 different match types among the machine learning-managed accounts.* (see research notes below) To make a valid comparison between different match types of the same keyword, they had to be used in pairs on the same day with the exact same bid. Filtering for this constraint reduced the number of candidates to 477,935 keywords.

Since a typical keyword has very little traffic on any given day, many of the keyword match type pairs had statistics on multiple days, which were combined to get a more robust measure. If the same keyword (e.g. “dog”) appeared with different match types in multiple different campaigns, those were considered as individual entries because their bids and other settings could have been very different.

It was observed generally that across the 470k+ keywords, people used mostly exact, phrase and modified broad match types. Broad match was used much less frequently on accounts inside our database.

Match-type showdown

Choosing a match type is the subject for PPC debates nationwide, leading us to this very showdown. Here to finally put some numbers to the conversation, in the midst of industry changes, is the match-type battle. First, we’ll announce the match type teams:

Place your bets and let the games begin!

Round 1: Broad vs. Modified Broad

There was a total of 19,182 keywords that had both broad and modified broad match types assigned (again pairs with the same bid on the same day).

  • Broad match keywords had a very similar average position to modified broad match
  • Broad match keywords had a 16 percent lower CTR than modified broad match
  • They had practically identical CPCs
  • Broad match keywords had 23 percent worse CVR
  • Broad match keywords had 33 percent higher CPA

Round 2: Phrase vs. Modified Broad

There was a total of 146,698 keywords that had both phrases and modified broad match types assigned. Here’s how they performed in the SERPs:

  • Phrase match keywords had a similar average position as modified broad match
  • Phrase match keywords had an 8 percent higher CTR than modified broad match
  • They had practically identical CPCs
  • Phrase match keywords had 6 percent higher CVR
  • Phrase match keywords had 9 percent lower CPA

Round 3: Exact vs. Modified Broad

There was a total of 149,355 keywords that had both exact and modified broad match types assigned. Here’s how they performed in the SERPs:

  • Exact match keywords had a similar average position to modified broad match
  • Exact match keywords had an 18 percent higher CTR than modified broad match
  • They had very similar CPCs
  • Exact match keywords had 10% higher CVR
  • Exact matched keywords had 22 percent lower CPA

Semi-final conclusions

After three intense match type battles we concluded that the only time MBM wins is when it’s up against broad. Otherwise, phrase match or exact match win, knocking MBM out of the competition.

Final competitor rounds

With MBM out of the competition, the final competitor rounds focused on unmodified match types.

Round 4: Broad vs. Exact

There was a total of 23,012 keywords that had both broad and exact match types assigned (again pairs with same bid on the same day). Here’s how they performed in the SERPs:

  • Broad match keywords were placed in 5 percent better position than exact match
  • Broad match keywords had a 40 percent lower CTR than exact match
  • Broad match keywords had slightly higher CPC
  • Broad match keywords had 15 percent lower CVR
  • Broad match keywords had 40 percent higher CPA

When Broad match went up against Exact match, it lost big time! While broad match keywords had better ad placement overall, this is likely an artifact of the bidding algorithm because having the same bid for both match types can put the less expensive match type in a better position.

Aside from ad position though, broad match keywords were more expensive and performed worse than exact match keywords.

Round 5: Broad vs. Phrase

There was a total of 18,325 keywords that had both broad and phrase match types assigned. Here’s how they performed in the SERPs:

  • Broad match keywords had very similar average position to phrase match
  • Broad match keywords had a 23 percent worse CTR than phrase match
  • CPC between broad and phrase match was very similar
  • Broad match keywords had 17 percent lower CVR
  • Broad match keywords had 27 percent higher CPA

When broad match went up against phrase match it also lost pretty bad. While average position and CPC was similar, phrase match came out on top with better CTR and conversion rates at lower prices.

Round 6: Phrase vs. Exact

There was a total of 121,363 keywords that had both phrase and exact match types assigned. Here’s how they performed in the SERPs:

  • Phrase match keywords had very similar average position to exact match
  • Phrase match keywords had a 9 percent lower CTR than exact matched
  • Phrase match keywords had slightly higher CPC
  • Phrase match keywords had 4 percent lower CVR
  • Phrase match keywords had 20 percent higher CPA

While exact match and phrase match won their individual battles against broad match, when they went head-to-head exact match was a clear winner. With lower costs to advertise and better performance exact match is the way to go.

After three intense match type battles we concluded that the only time MBM wins is when it’s up against broad. Otherwise, phrase match or exact match win, knocking MBM out of the competition.

After the semi-final and final match type battles, there was a clear winner that will be announced in the next section. However, the tournament also surfaced another conclusion. It’s safe to say broad match is the least used match type and the lowest performer. However broad match can be good for discovery, effectively populating search query reports with potential keyword opportunities.

While the broad match type team lost, there was one match type that stood out above the rest in this tournament.

Use exact match for best performance at lowest cost

The data is in, the bets have been settled. According to our findings, the cheapest and best-performing match type is exact every time!

The latest exact match update from Google looks promising for search marketers who are hoping to capture more relevant traffic, but hesitant to switch away from phrase or broad match keywords. But if the update hasn’t inspired you to get more granular on match-types than hopefully the data presented here has. Even before the update, exact match keywords were performing better than every other match type and costing campaign managers less

The one caveat with exact match is low volume, despite impressive ROI. It can be hard (i.e., impossible) to scale your campaigns when you’re cherry picking only the very best queries using exact match.

While broad match should be used for discovery, phrase match and MBM can also generate decent quality results – and yet exact match came out on top in this analysis based on costs and performance. The key lies in understanding the role of each match type and using them strategically to scale and maintain profitability.

TLDR summary: Exact match FTW!

All graphics made by Acquisio.

*Researcher Notes: The results are based upon the median value of the comparison statistics. The comparison for different metrics narrows the initial numbers further. Average position only requires impressions, CTR and CPC further requires having clicks, and CPA and CVR conversions as well.

 


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About The Author

Marc was co-founder and CEO of Acquisio until it was acquired by web.com in 2017. He is now Senior VP at web.com where he continues to lead Acquisio as well as other advertising related efforts within web.com. He’s been named one of the top 25 most influential Marketing Technology experts, has contributed to industry publications like Ad Age, and can also be found speaking at industry events like SMX and Hero Conf.





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BrightLocal launches ‘Local RankFlux’ Google local algorithm tracking tool

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BrightLocal has launched a new free tool called “Local RankFlux,” designed to alert marketers to changes in local search rankings across multiple industries.

Exclusively focused on the Google local algorithm, it offers tracking for 26 verticals. The ranking fluctuations of individual industries can then be compared to the overall sample.

Tracking over 14,000 keywords. Local RankFlux tracks roughly 560 keywords per industry vertical in 20 cities, according to BrightLocal’s blog post. It “plots the ranking position of each business in the top 20 search results and compares that ranking to the previous day’s position to determine the daily change.” 

Source: BrightLocal

Changes in higher SERP positions (e.g., 1 – 2) are weighted more heavily and are treated as more significant than changes in lower rankings (e.g., 19 – 20) in its scoring. “Local RankFlux then multiplies the change in position between today’s and yesterday’s rankings by the weighting to create a total daily fluctuation. This total is then converted into an average based on the number of keywords that returned meaningful results^ and a score produced for All Industries and for each individual industry.”

Scores above 6 suggest an update. BrightLocal explains that scores between 0 – 3 indicate nothing meaningful has happened – given that there are regular, even daily fluctuations going on. Scores of more than 3 but less than 6 indicate a minor change in the algorithm, according to BrightLocal, while scores of 6 to 10 suggest a local algorithm update. The spike in the chart below (industry average of 6.1) on August 8 suggests a meaningful change in the algorithm.

Local RankFlux score: legal category vs industry average

Source: BrightLocal

In early August Google made a core algorithm update. But the last time there was a significant local impact was in August of last year (and possibly in June, 2019 after another core update). In August 2018, SterlingSky’s Joy Hawkins detailed the ways in which her small business customers were impacted by that 2018 core algorithm update.

Why we should care. This free tool will be a useful way for local SEOs to reality check against broader industry benchmarks, to confirm whether there was indeed a local algorithm update. Informally, a number of local SEOs praised the tool based on early exposure.

Take a look and provide feedback on whether it aligns with your observations and experiences. And be sure not to miss SMX East’s full–day track on local SEO and location-based marketing for brands.


About The Author

Greg Sterling is a Contributing Editor at Search Engine Land. He writes about the connections between digital and offline commerce. He previously held leadership roles at LSA, The Kelsey Group and TechTV. Follow him Twitter or find him on LinkedIn.

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Google’s John Mueller on Where to Insert JSON-LD Structured Data

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In the latest instalment of the #AskGoogleWebmasters video series, Google’s John Mueller answers a common question about JSON-LD structured data.

Here is the question that was submitted:

“Is it possible to insert JSON structured data at the bottom of theinstead of the? It seems to work fine for many websites.”

In response, Mueller says “yes.” JSON-LD structured data can absolutely be inserted in either the head or body of the page. Just as the person who submitted the question assumed – it will work fine either way.

JSON-LD can also be inserted into pages using JavaScript, if that’s what happens to suit your pages better.

What’s the Difference Between JSON-LD and Other Structured Data Types?

Before answering the question, Mueller gave a brief explanation of each type of structured data and how they’re different from each other.

There are two other types of structured data in addition to JSON-LD. Here are the differences between each of them.

  • JSON-LD: A JavaScript notation embedded in a script tag in the page head or body.
  • Microdata: An open-community HTML mspecification used to nest structured data within HTML content.
  • RDFA: An HTML5 extension that supports link data through additional attributes added to existing HTML tags on the page.

Although all of these types of structured data are acceptable to use, Mueller has gone on record saying Google prefers the use of JSON-LD.



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Subdomain leasing and the giant hole in Google’s Medic update

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ConsumerAffairs provides buying guides for everything from mattresses to home warranties. But they also direct consumers on purchasing hearing aids, dentures, diabetic supplies, and even lasik surgery. Many have questioned the legitimacy of ConsumerAffairs buying guides, largely because top-rated brands often have financial relationships with the organization. ConsumerAffairs’ health content has been hit in the post-medic world, but now it seems they’ve found a way to circumvent the algorithm update by hosting slightly modified versions of their buying guides on local news websites around the country. Google “hearing aids in Phoenix” and you’ll discover just how well this strategy is working. Local ABC affiliate station ABC15 hosts all of ConsumerAffairs’ buying guides, including those in the health category, on their new “reviews” subdomain. So far, I’ve counted almost 100 of these ConsumerAffairs content mirrors. Despite cracking down on low-authority medical advice and subdomain leasing, Google seems to be missing this huge hack on their ranking algorithm.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About The Author

Abram Bailey, AuD is a Doctor of Audiology and the founder of HearingTracker.com, the leading independent resource for informed hearing aid consumers.

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