height=”100″ hspace=”5″ vspace=”3″ width=”100″> Last Monday, in a SEL post discussing the click quality by engine, I mentioned in passing an 89% drop-off between ‘phrases tested’ and ‘phrases actively generating good clicks’. Specifically, we posted 176,903 terms en route to discovering 20,152 active good terms for a client.
Today I’ll revisit that drop-off and analyze similar data from two other retailers.
I enjoyed the Q&A format with Danny last time, so I’ll do that again. I don’t expect any hardballs, as today I’m answering my own questions!
Q: It seems like a lot of work to post 176K terms just to find 20K good ones. Why not run fewer terms and use broad match?
A: Our experience shows PPC advertisers get better results by handling the long tail themselves. It can be dangerous to rely on broad match on head terms. Broad match and phrase match can make sense for long tail terms, when used judiciously. And explicitly handling the long tail gives you finer control of landing page and copy. Q: “Head terms”? “Tail terms”? What do you mean?
A: Chris Anderson introduced the Long Tail concept in a 2004 Wired article, then later expanded it on his blog and in his book. The Long Tail argues that virtual retailers with lower inventory holding costs can carry more SKUs, and that the aggregate sales from many non-best-sellers can top sales from best sellers.
The Long Tail is a merchandising idea, but the metaphor has been stretched to other areas (“paid search is the long tail of advertising,” “terrorism is the long tail of war,” “microbrews are the long tail of beer”). In linguistics, Zipf’s Law says the frequency of word use follows a power law, with a tiny set of popular words seeing huge usage and a huge number of words seeing small usage. In paid search, high search volume single- or double-word phrases are called “head terms,” and three- or four-word phrases with lower traffic are “tail terms.” Q: If that advertiser found 20K good terms, why run the other 156K “dud” terms?
A: Great question!
Yes, why run terms which haven’t generated orders?
As I wrote last week, “if you wanna to catch alotta fish, you gotta keep alotta hooks in the water.”
The fish are the orders. The hooks are the advertised phrases.
Looking past the head terms, many of the tail terms which generate sales this month won’t generate sales next month, and many of the tail terms which generate sales next month won’t have generated any sales this month.
Yes, high volume head terms enjoy consistent clicks and sales. But which tail terms generate sales in any given month is highly variable, given their low click volume.
Let’s look at data from two clients from last summer. They are different clients than my post from last week because the client in last week’s post started with our agency just last fall, and I wanted four clean summer months of data without the holiday surge. For this post, given Google’s dominant share in the industry, I’m just showing Google data. And for this post I’m aggregating ad-level results up to phrase-level results. For bidding and tracking, we call an “ad” each unique combination of client, engine, phrase, match-type, copy, and destination URL; the aggregation here summarizes away the details of copy and destination URL tests.
OK. Meet Client #1, a small-to-medium size direct retailer with no stores, web pure play, a small website, small SKU count, and 4K active phrases.
For client #1, only 4% of their phrases running in May generated orders (165/4356).
Now, what would have happened if, on the last day of May, we turned off the 4192 “dud” phrases which didn’t generate orders in May, and rolled into June with only the 165 “winner” phrases?
Sales in June would have dropped to $84K, down from the $118K that actually happened, a reduction of 27%!
Zounds. Let’s keep on playing this bad strategy.
What if on the last day of June, we turned off the 86 “dud” phrases within the remaining 165, rolling into July with only the 79 winners?
Had we done this, sales in June would have been $75K, 37% below what actually happened.
Here are those data for Client #1, recomputed with the assumption that at the end of each month we turned off all terms which hadn’t generated an order in that month.
What’s the takeaway here?
Tail terms have low click volumes. Typical PPC phrase conversion rates are a few percent. A phrase with a handful of clicks and no orders in a given month hasn’t proven itself bad. Turning off these phrases shrinks your program, leaving significant sales and profits on the table.
Q: Retailer #1 is only spending $50K a month on 4K terms. Does your claim hold for larger advertisers too?
A: Yes, even more so.
Meet Client #2, a large direct retailer with no stores, multiple call centers, multiple catalogs, a large website, large SKU count, and 83K tested phrases.
For Client #2, only 4% of their phrases running in May generated orders (3424/83655), coincidentally matching the rate for Client #1.
As before, what if we ended each month by turning off phrases which had zero orders that month?
We see the same phenomenon as before.
June sales would have down 42% versus what actually happened. July sales would have been off 51%. August would have been off 48%.
Again, ouch. Even bigger ouch, as the absolute numbers are so much larger.
Q: So, you’re saying large term lists are good.
Q: I’ve heard of two methods some SEM agencies use to bulk up term lists. Method one is prepend “BUY” to all your phrases, and then post-pend “ONLINE.” Shazam, that triples the number of phrases on your list. Method two is to use a product feed to cram all your product titles into the PPC engines. For example, advertise on phrase, “Nikon D40 Kit 6.1-megapixel digital SLR camera with 18-55mm zoom lens.” Shazam, that can add another few thousand terms. You said large term lists are good. What do you think?
A: No, no, no.
The goal isn’t to bulk up your term list just for the sake of bulking up your term list. The goal is to add relevant profitable ads.
Prepending meaningless words doesn’t help. Running absurdly long phrases doesn’t help. The game is won through quality, not quantity.
If someone is bragging about the size of their term list — “We have 189 gadzillion terms running on Google!” – the right next question is, “In the last 90 days, how many of those have had clicks, and how many of those have had orders?”
Q: What’s the right way to come up with extensive list of good phrases?
A: Here’s a secret: don’t start with phrases, start with URLs.
Take every selling page on your site – that’s the home page, every product category page, every subcategory page, and every product page – and for each page, develop a good set of unique phrases suitable for driving traffic to that page. Unless you’re testing destination URL, no phrase should go to to multiple landing pages.
Aim for testing 5 to 10 unique phrases for each URL you’re advertising on your site.
Q: If I understand your Client #1 and Client #2 examples, it makes economic sense to keep running phrases that have no orders, right?
A: No. Don’t waste your money like that. Bid down poor-converting phrases, and turn off the stinkers.
Q: If a typical phrase conversion rate is 1%, do I need to see 200 or 300 clicks before I turn off a phrase for no orders, as it takes that many clicks to prove it a loser?
A: No! You can use statistical techniques to make inferences about the conversion rate of low volume terms, and bid them or kill them appropriately. With good stats, you can be far more nimble.
Q: Ok. While the long-tail phrases are still collecting clicks, should I bid them all the same?
A: No, keeping all the low-volume terms at the same constant bid isn’t smart. Might as well send a signed blank check to Mountain View.
Even though they’re low traffic, it is very likely these terms are of different quality, and thus should be bid differently. Again, you can use statistical techniques to estimate the sales-per-click of low volume terms, and bid accordingly. Estimating SPC for low-traffic terms is the secret sauce of an effective bid management platform.
Q: This all sounds complicated. You’re saying that running large term lists poorly can be costly. Which is better:
A: Option 1 clearly beats Option 2.
Having a big term list and bidding poorly gives you that many more chances to waste your money. I’d strongly recommend Option 1.
But, if you can pull it off, the best choice would be Option 3:
- Have very large term lists and bid well.
Q: Do bidding algorithms matter? Aren’t they all about the same?
A: Yes. No.
Q: Final question: Do you often conduct Q&As with yourself?
Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.