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Posts related to Google Analytics, tips and tricks.

  • Anonymous AdWords placements

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    Calin Sandici

    Update 2 (august 2018): Should you still want to see specific placements that are sending you “anonymous” traffic you’ll need to leave the Google Analytics interface and use Google’s Analytics API. Three easy ways are Google’s Data Studio, Google Analytics’ Query Explorer and Google Sheets with a Google Analytics add-on.

    Update 1: as of June 2013, Google Analytics no longer “de-anonymizes ” URLs reported as anonymous by Google AdWords (see the comments below). It was fun while it lasted, though.

    Having a look at a placement performance report a few days ago I was both surprised and annoyed to see that I got the most clicks and incurred the biggest costs for some famous AdSense publishers, by the names of x65tw5263something.anonymous.google and such.

    Obviously, those placements only got me clicks and no conversions, otherwise I wouldn’t be writing this.

    AdWords anonymous URLs

     According to Google, “Some publishers choose to offer placements anonymously and not disclose their site names to advertisers.” (http://support.google.com/adwords/bin/answer.py?hl=en&answer=2471191). Which, to me, reads “you may find yourself spending money without knowing where your ads appear”.

    It’s like going out to dinner, asking for the bill and seeing, next to everything, from hors d’oeuvres to desserts, some items which requested to remain anonymous. In spite of representing a significant part of the bill. They just don’t like publicity, you know, so they chose to remain anonymous. In the background. Discrete. 🙂

    Luckily, every AdWords account I run is linked to a Google Analytics account, and AdWords related data is in there as well. And – lo and behold – Google Analytics knows no such thing as anonymous placement URLs. Every URL that got me at least a click is there, undisguised. In the foreground, for all to see. Transparent.

    Which means that I can see, per placement domain or URL:

    • bounce rate
    • pages / visit
    • visit duration
    • goal completion
    • revenue

    That’s enough for me to be able to judge whether a certain placement is worth my money or not. And although I won’t be able to say who is x65tw5263something.anonymous.google, specifically, I will be able to say that I no longer want my ads to show on a certain website or section of it.

    The image below represents filtered data; domains containing the string “anonymous”. As you can see, there are no such URLs in Google Analytics. All data is visible there.

    So, in the future, if you see a lot of x65tw5263something.anonymous.google in your placement reports, and do not know what to exclude, leave the AdWords interface and move to the Google Analytics one. Once there, see what placements are not performing according to your targets and expectations and exclude them.

    If you don’t have a linked Google Analytics account, get one and link it to your AdWords account. It’s free, and it’s the only way for you to access post-click data related to your AdWords visitors (data which is not in the AdWords interface).

    Unfortunately, you won’t be able to exclude placements with only impressions and no clicks, because those placements only appear in the AdWords interface, not in the Google Analytics one (obviously, as you need the visitor to reach your website in order for Google Analytics to be able to record anything). And those placements, if your ads keep showing without getting clicks, may drag your quality score on the display network down. But you can at least stop wasting money for placements that only get you clicks and no other benefits.

  • AdWords phone and verbal conversion tracking

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    Calin Sandici

    Stop making excuses and start tracking your leads and conversions, even if they happen over the phone or through e-mails.

    It’s pretty amazing how features which are available since long, long time ago are still neglected by both advertisers and their customers.

    And how customers and advertisers keep throwing money out the window without the faintest idea about the profitability of their “investment”.

    I’m not going to insert the famous Wanamaker “half the money …” quote here, because:

    • By now everybody knows it
    • It’s false (in many cases). It’s way more than half.

    Here’s a quick way to track conversions which start on the website and end on the phone (or in e-mails).

    Instead of hiding behind the “our leads/conversions are happening over the phone, and we cannot ask our customers which ad they clicked and what they searched for” poor excuse, talk to your webdeveloper, the person doing the advertising, and the one answering your phone / e-mail.

    Here’s what each has to do:

    • the advertiser has to tag his campaigns (auto-tagging, specific tagging, it doesn’t matter)
    • the web developer has to detect an AdWords visit and
      • switch to the AdWords phone number (show that number for AdWords visitors)
      • switch to the AdWords contact e-mail (send contact e-mails to that address)
    • the person answering phones / e-mails has to log them, together with their source

    Piece of cake, for any of them worth their salt. They’re not perfect, but you have an indication. You can tell if on one day you’re doing better or worse. And if you don’t have many campaigns, and you can use more extensions, you can track each campaign. You can even generate a code on the website and have the customer give it to you over the phone, or include it in the e-mail, and then you can track everything down to search term and ad level if you want to.

    If you can’t do that, the you can talk to your customer. You, the advertiser, can call him, as often as you can afford, and ask him how things went since your last talk.

    You can ask him how many phone calls he received, and how many orders / leads he got. You can ask him what kind of orders they were, and you can deduct which campaigns went well and which nose-dived. If you and your customer work as a team, you can do it.

    Not long ago, I convinced a friend of mine, the very first person whose account I managed, to use a different phone number for AdWords calls. And he agreed. Shortly after that, I was walking with him not far from his office, when I heard a phone ringing. He smiled, reached into his pocket and told me “AdWords”. And he went “Yes, that’s us. Sure, how many would you like? Ok, this is the price, you can pick them up anytime”. That was a live conversion, for the campaign related to the product he was talking about.

    He gave up carrying three phones (he already had two when we started using the AdWords phone) abouth a month later. By that time advertising costs were insignificant compared to his AdWords-related revenues. And it was him who made that conscious decision, I did not push him.

    He now talks to his customers and asks them how they found out about him. And I talk to him, several times a week, sometimes daily. And he tells me what he sold, how many, what the approximate revenue is, how many customers were new and how many were return customers. In my turn, I tell him what his AdWords expenses are, which products spend more, which less, which cities are more active and which less. That’s verbal tracking. And it works. In any case, it works much better than no tracking at all. I learn about his business, he learns about what I do. And together we managed to turn a  secondary product into a main revenue source.

    A few days ago he asked me, for the first time “can you see how many people have downloaded my price list?”. I smiled, but he could not see me. I was tracking downloads and hits on the contact page since I set that website up.

    “Yes, I can. About X% of your visitors download your offer. That’s about Y a day. Most of them download it from product page A, then C, then B, and you also have some downloads from D and E.” They’re from city A, B, and C. “C, are you kidding me? Are people from C visiting my website and downloading my offer?”. “Yes they are”. “Amazing”.

    Amazing, indeed. Yet so simple, so affordable and so effective.

  • E-Commerce: pick your products, choose your bids

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    Calin Sandici

    You’re running an E-commerce shop, or are in charge of advertising it, and you’re looking at a loooong list of products. You have cheaper products, and more expensive products. Popular products and less popular products. High-margin products and low-margin products. And there are a lot of them. Analysis paralysis is what comes to mind.

    “I have over 8000 products on stock”, that’s what I heard from a shop owner. “I’ve tried to advertise some of them, which I knew were popular, but it did not work. In the end my cost per conversion exceeded my profit.”

    Well, truth be told, you may not be able to advertise all of them without some serious automation in place. But what you can certainly do is to pick the lowest hanging fruits.

    What you need for this is, of course, Google Analytics, your product database, and a bit of math. Nothing fancy, nothing scary.

    And it all starts with profit. You want to spend less for advertising than you’re making by selling a certain product. You want a popular product, one that people search for, otherwise your ad will not show. And you want, of course, a high conversion rate.

    Assuming that you’ve been running your website for a while before making the decision to advertise your products, you can filter, in the Content – Pages section of Google Analytics, all your product pages. Usually categories have some URLs, static pages have other URLs, and product pages have easily-recognizable URLs.

    Let’s look at Interspire, a popular shopping cart software. A product URL is something like /products/some-words-here.html. Which means that if you filter for pages matching the ^/products/.+\.html regular expression, you’ll only have your product pages showing in your content report.

    Product page views

    Export that URLs list, and go into the admin area of your E-Commerce solution and match those URLs to the corresponding products (SKUs).

    You’ll end up with a list of products, and their respective pageviews, for a certain period of time.

    Get the sales for that products, in the same period of time. Then get your margin, per product, from wherever you have it.

    You should end up with a table showing you views, sales, margin and margin per view, for that list of products.

    Now, a product is:

    • popular, if it has many views
    • high-converting, if the sales/view ratio (Bryan Eisenberg calls its inverse the “look to book” ratio) is high
    • highly profitable, if the margin is high

    When choosing your lowest hanging fruits, you’re looking for popular products with a high historical margin per view ratio. That’s the metric which combines conversion rate (sales per view), and margin.

    And that’s it. Sort descending by margin per view and by views, and pick popular products with a high margin per view, and go advertise them.

    Don’t know what the maximum CPC should be? You do know. It’s margin per view, which you may want to adjust a little to cover for the costs for running the business. That’s because the margin, i.e. the difference between the purchase price and the sales price, is not sheer profit.

    So take your monthly costs for running the business, take your total margin and try to compute an adjustment factor for margin/view, then use it as your maximum CPC.

    And if, through advertising and bidding a certain percentage of your margin per view you manage to attain the same conversion rate as your historical conversion rate, then your cost per acquisition -or CPA – should not exceed your profit per sale.

    Once you’ve launched your campaign, all you need to watch for is the cost per conversion, which should stay under the profit per sale. The initial, target cost per conversion, is (max CPC) / (historical conversion rate). If you manage to get clicks for less, or if you manage to convert better, through more precise targeting, then your CPA will be lower than the expected one.

    That’s it. No more analysis paralysis. No more “I think these products are profitable”. Your data knows which are profitable and which show potential.

    Furthermore, if you analyze the performance of your products from this angle, you’ll quickly discover which products are totally uninteresting, so you can maybe decide to get rid of the stock at a lower price and replace them with something else.

    Bonus: Don’t know which keywords to use when advertising those products you’ve just picked?

    Oh, but you do.

    Filter your product landing pages by the same regular expression as above (depending on your shopping cart solution), and add “Keywords” as the secondary dimension. Export that list and see which keywords are related to those products (which keywords were used in search by people who landed on those pages). Maybe use the keyword list splitter to separate more general keywords from the more targeted ones. The nice part about this technique is that if you’ve shown up in organic searches for that keyword, and got clicks, those keywords are relevant for that page. So the chances of seeing the dreaded “Keyword relevance: poor” in your keywords diagnostics are very, very low.

     

  • What keywords got me those search terms?

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    Calin Sandici

    Or, in other words, how broad is broad match?

    Any serious AdWords manager is watching the search terms attracted by her keywords religiously.

    And any serious AdWords manager has already been frustrated by the fact that he cannot see, in one table, side by side, the search term, the match type of the keyword, and the keyword which was triggered by it.

    Ok, it’s a known fact that you can go to your keywords tab, and select one keyword, and click on “See search terms”, so you can see only the search terms attracted by that particular keyword.

    But would you do it a hundred times a day? Click, “See search terms”, click, “See search terms”, click, oh, no, I’ve already clicked that before, back to square one …

    Disclaimer: the solution I’m going to provide only works for search terms which attracted at least one click.

    (more…)