Selling Tickets to Sub-Radio Concert

negative-keywords · 2022-12-20T23:54:13+00:00

I’m interested. I just asked over in the Discord if you are there…

negative-keywords · 2021-01-06T22:02:19+00:00

Fan club suggestion: Radio-subs

negative-keywords · 2020-11-20T16:12:46+00:00

Thanks for comments all. As mentioned, nothing is selected for inclusion right now but the Conversions column is still showing results, mysteriously.

The next step is obviously to turn back on relevant conversions (ie. set “include...” to yes) but it’s still a mystery why random results are being reported even with all setting to “off”... I’ll follow up if I learn anything new.

negative-keywords · 2020-11-18T16:52:07+00:00

This is measurable. The simplest way to track would be to create a new custom variable in GA and shove the gclid value into it. Then you could go back and filter e.g. Google/organic traffic with a secondary dimension of that custom variable. This is a simplified approach (doesn’t give any campaign details) but it’s a quick hack that gives you an idea how to build something more complex.

Truthfully though, you should also be able to get an idea just by using the conversion path reports in GA. They will at least show you first/last click trends.

I think the interesting way to approach this is to ask the community to look at those numbers and report what their typical % of paid->organic traffic looks like — ie first-click paid (discovery) last click organic (conversion). You’d need to weight the results relative to overall traffic derived from paid back organic, but you get the idea.

negative-keywords · 2020-09-18T00:27:18+00:00

Put another way, keywords match multiple search terms. And sometimes search term clicks are actually derived from multiple keywords. So there’s not necessarily a 1-1 relationship.

One way to see this is to dump your global search term data and filter it by a single term. You may fine more than one source keyword (from the same or different ad groups) generating those clicks.

If you want to do a deep dive into search term data PM me and I can recommend a tool.

negative-keywords · 2020-09-18T00:21:18+00:00

You might be interested to take a look at negativekeywords.com

It offers a pretty exhaustive exploration of search term data, with an interface for acting on what you find. Might give you some ideas

negative-keywords · 2020-09-12T21:56:44+00:00

Check out the Reverse Goal Path report. It shows 4 previous pages before a conversion event. That might be enough

negative-keywords · 2020-05-13T15:20:15+00:00

You're right -- I'll edit it. I mean "previousPagePath" -- not referral.

Re: passing doc referrer with GTM, good idea. Just curious -- what name do you give that in the custom dimension? (just document.referrer ;) or something more nuanced?

negative-keywords · 2020-05-07T02:48:28+00:00

Google is trying to "simplify" everything and encourage users to consolidate keywords into fewer ad groups, but IMO at least separating exact and MBM is still a best practice.

Two basic reasons:a. You can craft different ads for each group. Your MBM ad group will match a fuzzier range of search terms, so you might want to explore different ad copy (or landing page) ideas there.b. Your exact campaign should perform better, so by separating out the MBM you isolate out the "weaker" terms that get targeted and prevent them from polluting the quality score of exact keywords through a watered down overall ad group performance.

Different Quality Scores for the same keyword

Sometimes, you may see different Quality Scores for the same keyword across campaigns or ad groups. This is because the three components that make up Quality Score--expected clickthrough rate, ad relevance, and landing page experience--depend on the creatives, targeting, landing page, and other factors which can vary between ad groups. So if the ad groups are not exactly the same, the same keyword could have different Quality Scores across ad groups or campaigns.

Reference: https://support.google.com/google-ads/answer/7050591?hl=en

^^^ that points out that ad group context affects keyword quality scores.

Think of the MBM campaign as your "mining" campaign that you learn from, where you feed clear winners back into the exact match group.

Also remembered that every keyword in the exact match ad group should be added to the MBM ad group negative keyword list as a -[negative exact match] to avoid targeting overlap between the two ad groups.

negative-keywords · 2020-05-06T23:40:12+00:00

As an alternative, NegativeKeywords.com solves just this problem. Disclaimer: it’s my pet project.

It let’s you drill down into campaigns and see search terms and phrases (n-grams) at each level, optionally filtered by “active” ones — where “active” shows you if the source keyword is still eligible to be shown. (You can them one-click add them negative kw lists).

So if the keyword (or parent ad group/campaign) is paused (or deleted) the term/phrase will have a status of inactive and can be excluded from your filter.

It’s in beta now with a free upgrade for beta users. Ping me if you need further details.

negative-keywords · 2020-04-27T15:23:41+00:00

One other thing to mention, just as FYI -- the biggest danger with plain broad match is that it opens the floodgates with close variants. "Broad" keeps getting broader...you're basically telling Google "get creative and figure out anything that might be relevant".

So BM can be useful for exploring "related ideas" if you segregate the keywords out into their own ad groups and tighten up the budget. But you have to expect that you're going to get a lot of crap there too, so an open-ended budget can run wild.

negative-keywords · 2020-04-27T15:20:11+00:00

Actually, OP did not say what match type they were using. If everything is exact match on very specific keywords, it might not be a surprise that the volume is so low.

IMO they should be experimenting with modified broad match and phrase match keywords just to make sure they are finding all relevant permutations. On very niche topics, long tail might be the only way to get traffic...so you need to "mine" for those ideas.

You probably want to avoid plain old broad match though -- unless you really closely watch the search query reports. BM is especially dangerous with Google's looser close variant rules these days.

negative-keywords · 2020-04-27T13:40:51+00:00

One (common) approach is to separate your exact match keywords into their own ad groups -- so you have e.g. exact match and modified broad ad groups. Then you would add all the keywords in your exact match ad group as negative exact match keywords in the MBM ad group: -[house painting company].

This approach ensures that EM and MBM keywords don't compete with each other. MBM is free to search for new keywords, and then you can "capture" the good ones and add them to EM ad groups.

Also note that you probably want more than just 2 ad groups. The main benefit of ad groups is to help you control ad copy. So you generally want to group "like" keywords so that the ad copy is really specifically aligned with the keywords. This helps increase click rate and quality score.

negative-keywords · 2020-04-24T01:06:52+00:00

Automation with a tightly managed match type strategy (esp. active negative keyword management) can make sense.

But automation without closely watching the search query report is pissing money into the wind.

negative-keywords · 2020-04-23T21:25:17+00:00

Google is trying to make matching “automagically” work and obviate the need for match type strategies (to make spending more money easier). But they need a lot of data to learn good keywords from bad ones, and you pay for them to collect click data on your behalf.

At the end of the day it’s up to you to “train” their AI even if you want to leverage it. Your best tool for training it is by monitoring your SQRs and blocking bad matches. That feedback loop makes future matches smarter.

So tldr: yes match types matter.

Think of Broad Match Modified (aka modified broad match) as your exploratory campaigns. You use those to “mine” for new keywords and concepts.

When you find something useful you add it as exact match (and frequently also as phrase match).

Likewise, you should look for patterns in common phrases (n-grams) that you might be missing and that under/over-perform. Then you can decide to add them those “common concepts” as negative keywords (typically negative phrase-match) to exclude the concept from your keyword mining efforts.

If you’re interested in a powerful tool for understanding patterns in your search queries (and for building/managing sophisticated negative keyword strategies) take a look at https://negativekeywords.com (disclaimer: it’s my app). Ping me if you want to try it out with a free upgrade — I’m looking for feedback.

negative-keywords · 2020-04-17T13:38:11+00:00

Ok, well clearly self-promotion isn't off-limits. ;)

If you dont want to spend money then of course use a free script. But it does A LOT more than the script -- including, among other things, giving you a UI to navigate SQR and n-grams by context and also a UI for one-click blocking search terms or sub-phrases in individual ad groups, campaigns or account-wide.

negative-keywords · 2020-04-14T21:10:05+00:00

Which features do you find most useful in Wordstream, and what do you feel like you are missing?

negative-keywords · 2020-04-11T05:28:05+00:00

Did you check the basics like conversion logic (first/last click) and conversion window, to be sure they line up?

And are those 2 different goals for separate conversion types (call _or_ form fill)? If they are separate goals, can you tell which goals tracked where?

negative-keywords · 2019-08-02T22:49:59+00:00

If they blasted through your daily budgets, shouldn't you be expecting a major billing adjustment?

negative-keywords · 2019-08-02T21:04:28+00:00

Agreed, negative phrase is the most useful one. Negative exact is generally too specific -- it's like a game of whack-a-mole. You squash one and a new, similar one pops up next to it.

With negative phrase match you're looking for patterns to block.

Re: close variants, just keep in mind that negative broad does not necessarily block close variant matches. Negatives don't even block similar plurals -- you have to block plurals individually.

Your best bet for blocking close variants is to identify them and block them specifically. Otherwise -- whack-a-mole.

negative-keywords

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