Are you the master of your search terms?

Or do they control you?

Here’s one way you can detect what situation you’re in. Read on.

Putting keywords in an ad group, and writing ads for that ad group is something that we do because we want to show a certain ad for a certain search query. An ad that matches that query (answers it), is relevant for that query, and entices the searcher to click on it.

But are we making sure that for the search terms that we attract we are showing the right ad?

Of course, if we have several ads in an ad group (and we should), and the ad group is set to rotate the ads more evenly (and it should be), a certain search term may be matched with any ad in that group.

But that’s ok. Because everything placed in an ad group (keywords, negative keywordsads and through them destination URLs, be they ad or keyword destination URLs) should be centered around the same theme. One theme to rule them all.

What we do not want to happen is to show, for any search term, an ad which is not related, or one which is less related than the ones we intended to show.

And it can happen. We can have an ad group with more general keywords, which runs for a while, builds a little history, and then, even if we have another ad group – more relevant for certain search queries – we see that ads from the former ad group still show.

The more we work on an account, the higher the chances of something like this to happen. Sure, we can diagnose our keywords, when we create a more specific ad group, to see if a search term triggers ads from the right ad group, but we don’t do it every time. And sometimes we need to wait quite a bit before the changes are active. And we cannot think of all the search queries which may match certain keywords to see if, for all of them, the right keywords are picked and the right ads are shown.

Search terms, keywords and ads

If you’re interested to see how Google AdWords’ system picks a certain keyword when more of them match a search query, here’s the document describing the algorithm.

What I wanted to find though was some kind of report which could tell me, periodically, if the search terms which triggered my ads stayed all within one ad group, or if they spilled across more than one.

And that report is a basic search terms report, adjusted a little bit in Excel.

I prefer to do it by generating an account-wide report, and to make sure that search terms don’t creep into ad groups across several campaigns.

Create a search terms report and create a pivot table containing the following:
– Search term and ad group as row labels
– Ad groups as values.

Set the value field settings for “Ad groups” to “Count”. This should show you the number of ad groups which contain a keyword that triggered a certain search term.

Then sort by count of ad group, descending. You’ll probably see that some keywords appear in three ad groups, or more. And when you look at the ad groups, you’ll see that they’re not different, but that some search terms are reported three times in the same ad group.

That’s because of the match type. Not the match type of that keyword, but the match between the search term and the keyword that was triggered by it. A broad match blue widgets keyword can attract search queries such as cheap widgets, which is a “Broad match” for it, cheap blue widgets, which is a “Phrase match” for it (the search terms include the keyword), and blue widgets, which is an “Exact match” for that broad match keyword (the search query and the keyword are identical, letter by letter).

So even if a search term only triggers keywords and ads from one single ad group, you may see it reported up to three times in the same ad group, due to the fact that in your downloaded report you may have three different rows in the same ad group, each containing a match type between search term and keyword.

Search terms and ad groups pivot table

Not good. You don’t want to scroll through rows and rows of data in your pivot table only to see if those search terms were linked to the same ad group several times or to more ad groups one time.

So what you need to do is to go to your report and select the search terms and the ad group columns, and filter that list, in place, for unique search term – ad group pairs (remove duplicates). Then create a pivot table which contains, again, search terms and ad groups as row labels and count of ad groups as values. Sort the table by count of ad groups, descending.

If, at this point, you see more than one ad group for a search term, it means that search term was able, through certain keywords, to trigger ads from different ad groups, and even campaigns. It also means you’re not in control. You can, if you want, see which keywords attracted those search terms.

In this situation, through negative keywords and bid variations – where appropriate – you can control which ad groups show ads for certain keywords, and master your search terms.

If you want to see where (in which ad group) certain search terms performed better, you should use the first version (before removing duplicates) of the pivot table, and see, per search term, which ad group (through its ads) suits a certain search term better. You can do that by including CTR, conversions and other relevant metrics in your pivot chart.

And you should tweak your settings until you make sure that each search term gets to be paired with the best ad, every time someone enters it in Google’s search box.


E-Commerce: pick your products, choose your bids

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?

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.

[Read more…]