{"id":991,"date":"2021-02-05T12:29:03","date_gmt":"2021-02-05T12:29:03","guid":{"rendered":"https:\/\/www.digitalposition.com\/resources\/learn\/?p=991"},"modified":"2023-03-01T19:59:48","modified_gmt":"2023-03-01T19:59:48","slug":"google-ads-broad-match-modified-bmm-is-going-away-what-now","status":"publish","type":"post","link":"https:\/\/www.digitalposition.com\/resources\/blog\/ppc\/google-ads-broad-match-modified-bmm-is-going-away-what-now\/","title":{"rendered":"Google Ads Broad Match Modified (BMM) is Going Away. What Now?"},"content":{"rendered":"

In a further step to push advertisers toward smart bidding & automation, Google has announced the Broad Match Modified match type will be going away. This move aligns with their previous moves in 2018 to essentially make Exact Match not Exact Match by allowing \u201cclose variants\u201d to \u201cconnect more people with what they\u2019re looking for\u201d (translation: advertisers will spend more money).<\/p>\n

In a perfect world, this move would make sense if you could trust Google\u2019s algorithm to bid in your best interests. However, it simply doesn\u2019t and thus advertisers are forced to adapt in new ways to this shifting landscape.<\/p>\n

Below I\u2019ll outline why advertisers are worried about giving up more control, what is changing, and what you should do about it.<\/p>\n

Why Advertisers are Worried about Giving up Control<\/strong><\/h2>\n
Example #1: Google doesn\u2019t filter invalid clicks properly<\/h5>\n

In the last 5 months, Digital Position has been forced to deal with 3 separate blatant bot attacks on our client\u2019s Google Ads accounts. In the first 2 instances, we were able to get full credits for over $10,000 each because we could obtain the IP addresses of the traffic. Google effectively did not filter out this traffic, but eventually processed refunds because we could prove it.<\/p>\n

The third time, one of our clients on Shopify could not provide the IP addresses because Shopify only stores them for 30 days (which passed by the time Google got back to us & Shopify responded to us).<\/p>\n

Google\u2019s tCPA bidding model, over a weekend, spent over $20,000 on completely fraudulent traffic that it KNEW was unqualified.<\/p>\n

First, we were told that invalid clicks don\u2019t happen in smart shopping. We proved that wrong:<\/p>\n

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Then, we were told that the \u201calgorithms are allowed to spend up to twice the budget if there\u2019s an opportunity\u201d. Well, we were able to show that the conversion probability in Google Analytics illustrates that this traffic was incredibly unqualified. With a conversion probability of 7 on average, it tanked to 1 over this weekend as Google flooded the account with what it knew to be unqualified traffic<\/strong>:<\/p>\n

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Safari also jumped to 94% of the traffic magically during the same time (typically ~40%):<\/p>\n

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I can go on an on, but you get the point. In this example, Google argued even after escalation and being on a call with them that \u201cit\u2019s technically not fraudulent traffic\u201d.<\/p>\n

As a result, we were forced to move the shopping campaign to tROAS to regain more control, and also implement ClickGuard<\/a>, a software that in real-time (or close to it) detects invalid or high bounce rate clicks and blocks the IP\u2019s in your account. We as the advertiser had to take back control from Google\u2019s reckless behavior.<\/p>\n

Example #2: Max CPC Limits<\/h5>\n

Google has also illustrated to us that when using automated bidding strategies, they\u2019re inflating bids beyond what needs to be paid to capture certain clicks. This is something that, without an in-depth knowledge of PPC, most would not even know about<\/strong>. As long as Google achieves the goal you give them most advertisers are happy, but they don\u2019t know that there\u2019s inefficient spend happening within there!<\/p>\n

I\u2019ll let our case study do the talking here for Carpe<\/a>.<\/p>\n

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Carpe provides sweat solutions!<\/strong><\/em><\/p>\n

In that case study, we were able to leverage max CPC limits to save over $33,000 for the client. We found that branded CPC\u2019s were being wildly inflated unnecessarily to capture clicks. When we introduced max CPC limits, we reduced branded CPC\u2019s by 61% while maintaining the exact same amount of top line revenue. Insane!<\/p>\n

I could of course give many more examples, but these two were very glaring ones that illustrate just how raw Google\u2019s algorithm is. Too often we have to add hundreds of negative keywords to stop Google from bidding on completely irrelevant things. As advanced as we think their algorithm is, it still has many drawbacks. The convenient fact of all of these examples is that in every one \u2013 Google makes more money by capturing more clicks. Advertisers see a pattern of Google not doing what\u2019s in the best interest of advertisers, and this scares us.<\/strong><\/p>\n

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So What’s Changing?<\/h2>\n

Google actually did a pretty decent job at explaining this to those who understand PPC in their help article<\/a>. Here are the most important facts:<\/p>\n

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*This is Google\u2019s image from their help article<\/a>, not Digital Position\u2019s<\/strong><\/em><\/p>\n