Comment by gk1 | Hacker News Reader

Comment by gk1 | Hacker News Reader

Surprised that keyword selection wasn't mentioned. Any time you're dealing with programming-related keywords, you're going to catch A LOT of people who just want free answers or code samples to copy-paste.

They're going to click on the first search result automatically, and if that happens to be your ad, then you just wasted $0.50-$5.00.

Another issue is keyword match types. If you used the keywords exactly as in the spreadsheet, without any modifiers, then you're giving Google way too much leeway in how they interpret and match search queries to your target keywords. For example, your keyword might be UPLOADCARE REVIEW but your ad will show for the search "uploading review" (I'm just guessing).

You might think "well even if our ad shows for an irrelevant keyword, surely the user would see the difference and not click on it!" Wrong. People click the first X results automatically.

Case in point: A data science platform company I consult once targeted python programmers. Instead they were getting tons of clicks from snake enthusiasts, before I got involved. Oops.

Another company was selling monitoring software for mobile apps but was paying Google (inadvertently) for searchers of free mobile apps. Oops.[1]

Anyway, the other lessons mentioned are still valid, but I feel the biggest lesson (mistake?) was overlooked.

[1] Quick tip if you're running Google Ads now: Go to your Keywords Report and click on the Search Terms tab. You'll see the actual search terms people used before they saw your ad. If they vary wildly from your target keywords, you need to fix your keyword targeting.

PS - More fun "Oops" stories about Google Ads: https://www.gkogan.co/blog/selling-software-snake-charmers/

Was going to comment the same. I've managed a wide variety of campaigns over the years and the best money for jam in terms of optimization is always the search term report. For non-G-Ads enthusiasts, it's the actual list of queries that a user searched for when your ad was clicked. The problem is usually rooted in too many keywords (top of funnel, as their awareness ladder says) or use of broad match keywords--exactly as you said gk1.

My favorite point: "Lesson #1: Test and trim keywords sets before hiring an agency to scale things" - the number one indicator of a successful campaign and client relationship for me is whether the internal team has legitimately tried to use the marketing channel before. I think you can successfully test channels with freelancers but I think a simpler process that likely has a higher rate of success is to test internally before you move it to an external resource.

The core benefit is knowledge acquisition for your team. You'll make better decisions with that knowledge and leverage the time of your freelancer or agency better than if you had to ask about every detail you didn't understand about their work.

Thanks for pointing this: "The problem is usually rooted in too many keywords (top of funnel, as their awareness ladder says) or use of broad match keywords--exactly as you said gk1." Our case is definitely too many keywords, we used Exact Match and Modified Broad Match techniques for different ads in a campaign. Another lesson that we learned is that it's better to prepare content and campaigns from the bottom of the Awareness Ladder, and then shifting up.

There's a subtle point here that I want to emphasize, as it's counter to their "Lesson #2: Focus on page quality and CTR when doing paid tests."

The best way I found to qualify leads was, for things I was charging money for, to put in the price. That way people didn't click if they were looking for free. This actually worked pretty well.

The problem was that this means my ads were showing and not getting clicked. This reduced my quality score (although, in my mind, it provided a better experience for the user because they weren't wasting time going to a site that they did not want).

So Google's Quality Score is "quality" as measured from their point of view (high click/view), not yours nor necessarily your customers.

It's [supposed to be] quality as measured from their users' point of view, which may be a large superset of your customers. If the user wanted a free code snippet to copy & paste and they get an ad with a price in it, that's a bad result, even if they never click on it; that space on the page could've been devoted to a link that they would actually visit. It's good (from the users' POV) for that ad to never get shown again on that query, because it makes their results more relevant.

The right solution here is to refine your target market segmentation & keywords so that you're buying ads on searches that only people in your target market make. Then you get a good CTR & quality score and a good conversion rate. Optimize the funnel all the way down to the searcher.

That might be the idea, but my quality score goes up if the user clicks, even if it's not what they want- and Google gets paid. My quality score goes down if I am forthcoming and pre-qualify the clicks. (There are probably more ways to do this than price.)

If the user doesn't use the word "free" in the search then there's no way to know a priori that they wanted free. By me putting a price in my ad, I am making the user's experience of the search page better by not leading them astray.

Here's an example: Suppose somebody searched "fix my carburetor." The likely return will have services that fix carburetor for you, youtube videos showing you how, and for-pay pdf instructions. Let's say I'm selling the for-pay pdf instructions. How am I supposed to exclude my page? I could limit my keywords to "fix my carburetor pdf for sale" and hope someone types it into the search box, but I find that unreasonable.

Maybe you can walk me through how I'm wrong. But I submit that Google is working on the hypothesis that more clicks = better user experience, and I believe that hypothesis is false.

Not wrong, just incomplete. It's better for you to put a price on the ad than not put the price on the ad and get the bogus click. However, it'd be even better to fix the targeting & keywords and not show the user the ad in the first place if they're not going to click. Google's trying to align your incentives with its users; after all, you're the only one who knows your business well enough to understand if there're subtle differences between what your prospective customers search for vs. what window-shoppers in your industry shop for.

There are often other keywords that can indicate purchasing intent - just thinking back to my own search habits, "buy", "product", "cost", "pricing", "comparison", etc.

And it's true that more clicks doesn't always = better user experience, but it's also true that more clicks in the absence of other information usually = better user experience. Google works off the data it has - for many cases, that's only CTR, bounce rate, and time on site. I suspect (I don't have any inside information how Ads Quality works) that when they have information about conversions - like when you've chosen to link your Google Analytics account with AdWords and set up conversion funnels in the former - they use that information too for determining quality score.

I agree with you. I always try to disqualify traffic with price.

Many people optimize for CTR but that's not usually good when you're doing leads and/or sales.

It's easy to write ads that get higher CTR. Then your CPC will usually go down but that doesn't mean you'll get a higher ROI.

So best to focus on CPA not CTR.

Good point, we now have the target CPL we use to qualify paid ads hypotheses.

Agree on that, the problem was about target market segmentation & keywords. The insight is that we shouldn't focus on a broad market (and test hypotheses for different product parts separately).

That's a good point. We didn't trigger that mechanic because we have a Free plan. However, by doing that we weren't targeting our "ideal customer" which is definitely a paid one.

On the other hand, if we would lower the CTR by defining the price, we would have higher CPCs or lowered the number of impressions due to a low Quality Score. Even if we WOULD get lower CPLs, that won't bring ROI since users still won't activate on our platform.

The problem wasn't about Google Search Ads settings: we hired skilled SEMs and everything. The problem was about the product-market fit understanding and segmenting potential customers based on related value props and keywords.

Got it. Great piece, by the way.

Traffic source matters too. You could end up with a bunch of junk click from the search network while Google.com is doing just fine. If things are really unfavorable, google might start sending you youtube clicks. The more you are able to segment every possible variable, the more likely you are to catch problems and isolate out what is actually working.

I think the most important things are realizing that there is a ceiling on search traffic. For some markets, it is a very, very low ceiling once you’ve optimized out all of the garbage. The giant burst of clicks in the very beginning may be misleading.

VC backed startups often are able to dump a tremendous amount of money in to paid acquisition. If you take an already narrow search channel, the “winner” may end up being whoever raised the most money.

Definitely, traffic source matters. We always analyze the funnel broken down by referrals. However, the case was largely about wrong target market segmentation & keywords.

Yes, it seems like they didn't handle that part of the job properly. From what I read, it looks like they provided an SEM agency with a pre-chosen list of keywords. That doesn't seem like a good idea when you have little experience with paid marketing. In fact, I'm surprised the agency didn't push back to suggest they do that research.

There was a pre-chosen set of keywords and the research as an ongoing process involving the agency. We would quickly trim the set, exclude irrelevant words, etc. The insight we got was that we should advertise product value props rather than test keywords at scale. The research that wasn't in place was the one matching value props with different keyword sets. I mean we scratched the surface of it, but scaling things up was too early in the process.

As someone trying to wet my feet in SEO, what kind of a process would you apply to determine the "best" keywords for a project. I can list a load of terms I'd like to rank highly in, but they're most likely too competitive to actually be pursuable.

Is it possible to figure out what your competitors are doing, obviously without access to their Google analytics? I'd like to see how they've solved their problems, learn from it and know how to differentiate from their approach.

you can execute searches based on your "best" keywords and see which competitor content appears in the search results. that won't give you info on their spend, but will definitely help you understand which type of content converts for the keywords. you will then be able to structure the "content" column of your Awareness Ladder accordingly

Regarding your question specifically, you can gather the stats on your competitors using:

https://seranking.ru/ https://serpstat.com/

The keywords in the Awareness Ladder are just examples of what we used. We did craft the keyword list and the SEM agency helped us filter it. We would dump the irrelevant keywords too. The second point is we used both Exact Match and Modified Broad Match for different ads in a campaign. Here's an example: http://prntscr.com/m7erv2 (CTR/CPC are decent)

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