I don’t have a typical post today…

Rather, if you’ve read my previous tips and you want a deeper explanation and/or questions answered, please feel free to check out my webcast that will be airing LIVE tomorrow.  I will be directly addressing the tips I have just recently explained in this blog. 

Follow this link to register: http://searchmarketingnow.com/webcasts/wc091112

Below are the details as posted on SearchMarketingNow.com

Thursday, November 12, 2009 – 1 PM EST (10 AM PST)

Speaker: Dan Soha, CEO, Five Mill, Inc.

 

Webcast Details

PPC advertisers use geographical targeting to create more focused and targeted advertising campaigns. By limiting the geographic target, you can increase the efficiency of your advertising campaign, cut costs and increase conversion rates and ROI.

In this webcast, we’ll look at some advance tips and tactics for using geo-targeting in your PPC advertising campaign. Find out how, why, and when to use geo-targeting in your paid search campaigns.

You’ll learn:

  • how to maximize geo-targeting with keywords
  • how to geo-target by physical location
  • how to use geo-targeting to outbid your competitors
  • differences in geo-targeting among the main search enginesDan Soha is CEO of Five Mill, Inc, a San Francisco-based search marketing firm. He has developed innovative techniques that draw not only on his skills in marketing and advertising, but also on his academic background in the field of Algorithm Theory. As the Principal and SEM Specialist of Five Mill, he provides his expertise along with custom-tailored SEM strategies to clients in such varied fields as lead aggregation, retail, broker, brand advertisement, and more.

There are some really great things about Google’s ad display algorithm and there have been some VERY significant changes made recently.  Typically their changes with which keyword/ad combination is displayed are good… this time, not so much.

So, I’ve already discussed the Five Mill Tree Method, but it was a high level explanation.  In order to do the actual “slicing and dicing” of keyword traffic, you need to have the tools to make this possible.  Unfortunately, Yahoo doesn’t give you the tools to effectively and efficiently do so, but Google does.

Let’s first go through a couple quick basic rules of Google keyword matching…. and then I will explain how Google just recently made it better, then made it worse.

Match Type “Trumping”

Let’s say you are running:

- 2 Identical Ads

- 2 Different Match Types

- 2 Different Bids

We are dealing with 2 different Ad/Keyword/Match combinations.

#1

Keyword:  socks

Match Type: Broad

CPC: $3

#2

Keyword:  [socks]

Match Type: Exact

CPC: $1

Let’s now say that a user searches the query: [socks] (Exact match)

One might assume: The match type for combination #2 is the same, but the bid for #1 is the higher.  Due to the fact that both match types could address the query [socks], the corresponding bid/combination would be the higher bid; the higher bid broad match has cannibalized the traffic.  This assumption is entirely WRONG.   Google associates the keyword of closest match with the query. In other words, first Google notes that there are multiple keywords that are the same (but different match types) and matches the one with the most restrictive match type.  In this case, the keyword is [socks], and the bid corresponds to the lower bid because the match type is most restrictive.

Geo-Target “Trumping”

This time:

- 2 Identical Ads

- 2 Identical Match Types

- 2 Different Geo-targets

- 2 Different Bids

#1

Keyword: [socks]

Match Type: Exact

Geo-Target: USA

CPC: $3

#2

Keyword: [socks]

Match Type: Exact

Geo-Target: California

CPC: $1

User Query: [socks]

User Location: San Francisco, California

Similarly to Match Type “Trumping”, the query is mapped to combination #2 because the Geo-target is most restrictive, despite the lower bid.  No canibalization occurs (but it would cannibalize with Yahoo!).

There are a few caveats, but, for the most part, the above is correct.  Two major changes have been made, one for the better and one that is not.

Change #1: A Keyword Below Minimum Bid Threshold, is Still a Keyword

Previously, if your keyword was below the minimum bid threshold, it would not compete in the bid auction.  For example, let’s say that in combination #2 in the above examples, the bid was below the minimum bid requirement.  If this were the case, Google pretends that the keyword doesn’t exist and it would map to the higher bid despite the keyword of closer match.  This change NOW takes into account keywords that are below the minimum bid threshold.

This change is fantastic.  This gives us the opportunity to target keywords in as much granularity as we desire and bid based on our metrics of success.  We no longer have to worry about the effect of a keyword dropping below the bid threshold.

Change #2: Google Matches Keywords When it is Better “Quality”

So, everything I’ve said above blows up (although very marginally) based on this new caveat that Google adds to the equation.  The deal is that everything above is true, EXCEPT in the case when a keyword that is not a “closer match” has a lower max CPC and higher Bid x Quality Score (essentially Bid x CTR) value .

This is how Google says it:

On rare occasions, the system will prefer to use a keyword that is cheaper (i.e., it has a lower bid), has a higher Quality Score, and has a higher Ad Rank. Here’s an example:

Query: plumber tool
Keyword 1: plumber tools (maximum CPC bid = $0.10, Quality Score = 30, Ad Rank = 3.0)
Keyword 2: plumber tool (maximum CPC bid = $0.15, Quality Score = 4, Ad Rank = 0.6)

Ordinarily, Keyword 2 would be preferred because it matches the query more closely than Keyword 1. However, Keyword 1 is cheaper, has a higher a Quality Score, and has a higher Ad Rank. Therefore, the system will prefer showing Keyword 1 in this instance.

Keep in mind that Quality Score is calculated every time your keyword matches a search query — that is, every time your keyword has the potential to trigger an ad.

As a result the ability to be extra granular gets thrown off, because at anytime Google can match your less granular keywords with queries when it gives Google an opportunity to make more money. (You can word this sentence however you want, but it will mean the same thing.)  Google will argue that you are getting a chance to appear on a better performing keyword combination.

So, here is where Google entirely fails.

1.  When you take away an advertisers ability to be as granular as they want to be and when you make advertising less clear, the ability to advertise most effectively gets impaired.  The venn diagrams that you see in my previous posts are now better drawn with dashed lines because it is now impossible to be definitively granular.

2.  The person/people at Google that came up with this one may or may not have thought they were doing advertisers a favor, but the reality is that they have created extra revenue for Google in the short-term and that’s all.  Personally, I advertise with so much granularity and analyze keywords at the keyword level, that changes like this will only make my advertising less effective.  In fact, any advertiser that is scientifically managing their bids will be hurt by this change.  By making advertisers less effective, advertisers cannot optimize for metrics of success as scientifically as they were previously able to do.  Assuming that advertisers are advertising with financial efficiency (which is a gross assumption with many advertisers), the long-term effect, by definition, is a loss of revenue for Google, a devaluation of Google advertising, and a financially negative effect on its advertisers (until they realize that less money should be spent on Google).

Keep in mind, though, that this change is very negative, but it’s effect will be barely noticeable.  But, in “advertising equilibrium”, as I like to refer to it, it is bad for everyone.

In short, I challenge anyone to find an example where this change actually benefits advertisers…

Ps. Check out this link: http://adwords.google.com/support/aw/bin/answer.py?hl=en&answer=66292 to read more information about Google Keyword Matching

Pps. in light of this post, i’m adding a parent category and a sub-category: “Google”, “Fail”

Five Mill Tree Method, explained

Let me now dive right into the “Five Mill Tree Method”, which has really been the impetus for 95% of my Search Marketing methodology.  In the previous post I discussed how we we were stuck in 1998, and as much as I loved that song by Next, there have been so many opportunities to optimize accounts that have been shadowed by “long tail” tunnel vision.

As I said, the advertising landscape changed from a list of keywords to one advertising space with many different ways to dissect it.  We have been given the opportunity to become more granular (my favorite buzz word).

I like pictures, so here’s my graphical explanation:

SEM Landscape Then & Now

[NOTE: At this point I'm starting to regret choosing "socks" as my example.  Oh weeelllllll... looks like we're committed to thoughts of warmer feet]

In the new keyword landscape you can cut the advertising landscape into as many parts as you want.  You can target by Geography, Match Type, Daypart, and Network.  Using just those few options, you can create quite a few different match types, but I’ll get to that later.

Picture Time!:

New Keyword Landscape

Previously, I noted that the way to build out and optimize campaigns was using the following methodology:

Step 1.  Build Adgroup(s) for “Head” word(s)

- Test ads

- Pick best performing ad

- Bid keyword

- Re-bid if/when performance changes

Step 2: Build Out “The Long Tail”

- Keyword tools: use whatever “proprietary” and non-proprietary tools to do so

- Spreadsheets:  form a dirty relationship with the concatenate function

- Web logs:  analyze the queries that actually bring users to the site and add them to the keyword list

With this very fundamental change in the the Search Marketing algorithm, I feel that it is absolutely necessary to throw out 1998 and look at and utilize the tools that are in front of us.   My methodology changed to one better explained by a graphic.  In the below graphic think of “KW1″ as the circle that defined Socks (in broad match).  As we develop more information, we break up the traffic source by performance, and performance alone.

Five Mill Tree Method

Now, let’s imagine we’ve gathered enough data for KW1, to make a decision.  In other words, let’s say we find out that after running the broad match for “Socks”, that [socks] performance better and the remainder performance worse.  We then branch out and bid accordingly.  Let’s say that we then look just at [socks] and find that traffic from California performs worse and, conversely, the remainder of the [socks] traffic must perform better.  Etc…. etc…  Of course, we are also adjusting bids accordingly.

Here’s a graphical explanation, as per usual:

Tree Method Example

Note:  *For the most part*, the most efficient and rapid way to optimize your account in this fashion is by making sure that each branch/split in traffic is a roughly 50%/50% split.  There are some caveats to that statement, but for the sake of not entering some complex match, let’s just try to keep splitting 50%/50%.

Everything I have explained above is simple.  In fact, it’s painfully obvious in many respects.  But, for some reason, many advertisers still think in terms of “head keywords” and “long tail” keywords.  One major added benefit of the Five Mill Tree Method, which should not be overlooked, is it’s ability to create awesome Barriers of Entry.

Barriers of Entry:

The Five Mill Tree Method is great for optimizing and becoming more granular.  But, it’s ability to form Barriers of Entry is just plain fun.

So let me give you a very simple example of the usual extreme case where the Five Mill Tree Method is “useless”:

“Why should I optimize?! I’m already #1 on my keywords and I’m #1 EVERYWHERE!”

I see this scenario often.  Occassionally, a “Mom & Pop” company will enter the Search Landscape (or for the sake of being SF PC, how about we say “Pop & Pop” or “Mom & Mom”?  Eh, I will maintain the more famous idiomatic expression “Mom & Pop” in order to make this story less confusing).  They typically come in, bid some arbitrary sum which, in fact, tends to be much higher than is typically worthwhile.  We’ve all seen it.  We typically then assume: “My product/offering is better than the next guy and they won’t last long”.

It’s really fun to make that assumption because it’s the easiest thing to do.  Unfortunately, though, it’s not always right.  Some one will come in, with a highly competitive product or offer at lower prices and rock your world… at least in the short term.

Dear Five Mill Tree Method, how are you going to help me here?

Well, let’s say we determined that the the northern half of the US converts at a higher rate when click on ads for Socks then does the Southern half.  So, what do you do?  You bid accordingly… obviously.  So, no we’re advertising $5 per CPC is in those colder Northern states and $1 in the Southern states.  Per our previous statements about always being “#1 Everywhere”, we are not shocked in this hypothetical scenario, that we will maintain the #1 position everywhere.

Let’s say “Mom & Pop” comes in and puts out a $3.50 Max bid per click.   Now, we have the #1 position in the North and “Mom & Pop” has #1 in the worse performing South.  The overall mix has left our competitor with worse traffic and you with the better traffic.  Overall, we are roughly ad position 1.5 and the competitor is roughly 1.5.  [NOTE: i'm making gross assumptions that our ad CTRs and Conversion Rates are relatively or proportionally the same and there aren't really many other true competitors on the landscape.  We can nit-pick this example all day, but it doesn't deny the barrier of entry that we have created].  Here’s yet another graphic to help explain.

Geo-targeting -- Five Mill Tree Method

As a result of this Geo-Targeting use of the Five Mill Tree Method, here are some important assumptions we can make:

1.  Competitor gets good ad position.

2.  Competitor gets relatively worse traffic.

3.  Competitor does not analyze traffic closely enough to realize that conversion rate has been worse due to disproportionate traffic.  Typically, competitors dip their toe in the water, run away, and call Search Marketing unsuccessful.

I can almost feel people rolling their eyes thinking that this little change doesn’t make much of a difference, but I really must disagree.  As you continue to Optimize, the Barriers of Entry pile on.  You constantly make the landscape more and more complicated for your competitors.  Imagine the complexity created by the Five Mill Tree Method in this purely Geo-targeted version of the Five Mill Tree Method:

Five Mill Tree Method: Geo-targeting Optimized:

1. As you “slice and dice”** …

a.  Competitor CPA will increase and/or conversions will decrease.

b.  Your CPA will decrease and/or conversions will increase.

2. Optimization will protect your margins from competitors who start to bid more aggressively.

3.  As a side effect…

a.  Your newly targeted adgroups will [hopefully] lead to the creation of better targeted ads.

b.  Your history with optimized ads will lead to high quality scores and low CPCs

c.  Increased granularity and profitability.

In sum, Optimization with the Five Mill Tree Method will nearly always lead to…

1.  Increased conversions (or revenue) at the same overall CPA

2. Decreased CPAs (or increased margins, depending on your “metric of success”)

3.  Increased Barriers of Entry.

ONE FINAL NOTE!!!: A very important reminder that the Five Mill Tree Method is not just match type manipulation or geo-targeting manipulation, it’s a combination of all these things.  Further, there are tricks you can utilize with this fairly simple method to make optimization even MORE interesting.

Next entry, I will explain some tricks and techniques that can be utilized with this method.  If not that, I will add in my most recent Google rant…. :-/