Step Wise SEO

There are two major types of paid for placement engine. There are those that run on a simple bidding process, i.e. if you pay one penny more than a site bidding on the same term a better position will be achieved.

This model, for sake of reference, will be known as the Overture model. The second type of paid for placement engine is one that focuses on bidding price, but also on daily budget to give the optimum performance, and for sake of reference this will be known as the Google AdWordsrM model.

Overture model
The Overture model is the simpler of the two bidding models. With the exception of Google, nearly all PFP engines utilize this model (with a few variations) in which a higher bid wins a higher placement in the search listing and therefore the higher rank.

The more advertisers there are bidding the more fraught and frenetic bidding becomes.

To succeed with PFP the skill is to relate the objective to be achieved with the service cost (or CPC) of the engine.

If a goal is to achieve a certain traffic number then a target CPC must be found; similarly if the goal is to achieve a conversion (such as a sale or lead generated), the amalgamated cost of all keyword clicks must be at the investment number for a desired return.

In other words if $1.00 was spent on clicks, $5 must be made back from the clicks in order to achieve the goal.

This is a simple principle but, in the PFP one that is extremely hard to achieve, the reason being that the market controls the price and not the search engine and as such a conversion parameter can change from one hour to the next.

Success from PFP comes from the management of keywords both in their singular existence and within a group or portfolio.

By managing the expectations of keywords against their desired goal, a goal that is ultimately set by the search marketing strategy, a greater handle on the performance can be determined.

It is important to follow these guidelines for PFP:

• Classify keywords by portfolio designation - depending upon your strategy (see later chapters) keywords will fall into different areas within a portfolio.

For instance, some keywords will be responsible for branding, others for driving qualified sales. It is in accurate classification that accurate measurement can be determined.

• Measure against conversion - measure PFP against a conversion point and optimize against it.

Bidding, whether it be manual or via a bid management tool can only be successful if the outcome is measured.

• Avoid ‘fixed’ bidding - unless the pros totally outweigh the cons (and this is most uncommon) avoid using the fixed bidding facilities on the engines with the Overture bidding model.

If fixed bidding is used and the bids are not monitored accurately then excessive budget may be spent needlessly for the same click.

As the auction mechanism allows bidders to up their bids but also to reduce them if a bid is placed when many bidders are vying for the same spot, the PC might be higher than an hour, day on week later when half the bidders are now competing lot that term.

This means that a $0.50 cent bid for position I on Tuesday at 1 pm might be $0.25 by Wednesday at 11 am but as the bid has been fixed at $0.50 double the amount is being paid for the term.

• Use ‘auto’ bidding - as the other mechanism to fixed bidding this option recognizes the changes in the bidding environment and ensures that bidders only pay 1 cent (or equivalent minimum currency) above the next placed company. This bidding is done up to a bid cap or maximum.

• Constantly monitor bids – The Overture model search engines require constant monitoring and adjustment.

 If left unattended the paid for placement engines can go one of two ways.
 
 (1) The bidding within the space is so frenetic that terms that were placed in the top positions (and it’s important to remember here that the top terms are syndicated out to the advertising network) have been demoted to the lower less advantageous positions.

 (2) The bidding within the space slows or fewer bidders exist and a listing gets promoted to a higher position where the amount of traffic drives up the cost and the cost vs. benefit ratio becomes undesirable.

Throughout the following chapters some of the more specific techniques associated with an objective(s) will be identified but following the cited rules a great deal of success can be found.

Google AdWordsTM Model
The Google AdWordsTM model is one of many variables. The ‘Overture’ model uses only a few basic variables, price being the determinant for position and is the case until the money runs out.

Despite releasing new models for controlling budget, the model is relatively simple. The AdWordsTM model is much more complicated.

Position is determined by bid price, click through rate (CTR) and budgetary elements such as daily cap amounts on campaigns and accounts.

Only when an understanding of all of these elements is found is it that true success from this medium can be found.

Daily budget cap
While testing new keywords, trying new creative and changing landing pages are all worthwhile efforts in maximizing returns or reducing Costs Per Acquisition, there is one specific feature in the Google AdWordsTM tool, that, if more carefully considered, can make significant improvements to your performance in only a few minutes; the low hanging fruit, if you will.

Often times, the daily budget caps of campaigns are arbitrarily assigned with little consideration, or are simply never adjusted to ensure that your advertising dollars are working at their peak performance.

Over time, you might find that the daily budget cap is more than an administrative decision to be made on the Campaign Settings tab, but rather the focal point of your AdWords strategy.

The strategy is simple. Maximize exposure on keywords that deliver the most value, and minimize the exposure of keywords that do not.

This may seem obvious, but as most advertisers must work within budgetary constraints, the challenge lays within sucking the most return out of your limited dollars as possible.

This involves assigning proportionally higher daily budget caps to campaigns which contain your best performing keywords and lower daily budget caps to campaigns which contain your less performing keywords.

The tactics and implementation of this strategy are demonstrated in the example below, which is reflective of numerous actual cases.

Scenario:
Our business is running 1000 keywords in one AdWordsTM campaign and we have appropriated $15K a month to spend in Google.

Our current daily budget cap is $500 a day ($15 000/30 days). We need to achieve an overall return of 5 x in the next month to reach our quarterly goals, and in this past month, we only achieved a 4x.

Challenge:
With all of our keywords in one campaign set at a $500 daily budget cap, our ads are not being served all of the time.

Our ads are not being shown on every search because the AdWords tool is using historical data to estimate how many times our ad needs to be served, in order that we only spend $500.

It then serves ads intermittently throughout the day. More importantly, and perhaps more frustratingly, the keywords which we know are the most valuable to us, are not showing ads as much as we would like.

If we could have our keywords, which routinely deliver over a 5 x show ads more often than our keywords that deliver below a 5 x, we might be able to get our historic overall performance of 4 x to become a 5 x in this next month.

Optimization Tactic:
While we do not have the financial means to have ads served on all of our keywords all of the time, we do have the power of choosing specifically which keywords should have ads served more frequently than others.

How do we do this? We will convert our one large campaign into multiple campaigns and assign them varying daily budget caps.

Before we can do this, we’ll need to do some research and see the ROI by keyword. We will then sort out 1000 keywords by ROI.

Perhaps only the top 50 keywords actually perform at or above a 5x. The next 100 keywords delver between a 1 x and 4x and the remaining 850 keywords are either costing more than they deliver in revenue or only drive traffic.

Implementation:
In this case, we will create three new campaigns. In campaign 1, we’ll place the 50 best performing keywords that drove over a 5 x.

Then we’ll check the Recommended Daily Budget tool on the Campaign Settings tab. It may recommend that we need to spend $300 a day to serve ads on these keywords all of the time in position 1.

We want to assign campaign 1 the full $300 daily budget to ensure maximum exposure on all of our best performing keywords.

We’ll then place the next 100 `medium performers’ driving between a 1 x and 4 x in campaign 2.

Again, we’ll check the recommended daily budget for the keywords in campaign 2. It may recommend that campaign 2 needs $400 a day to serve ads on these keywords all of the time.

However, we only have $200 a day left to work with ($500 - $300 = $200). Since these keywords are not delivering as much value as our best performing keywords, it is not as necessary for the ads to be served all of the time.

Determining how to break out the budget among campaigns 2 and 3 can be done in a number of ways, but to ensure higher returns, assign the majority of it to campaign 2, which contains the better performing keywords.

In this example, we’ll assign $150 to the `medium performers’ and the remaining $50 to the `poor performers’.

By investing more dollars in our better performing keywords, we should begin to see higher returns from this point forward.

While this is a fully simplest example, it does demonstrate how breaking down campaigns into smaller campaigns and appropriately assigning daily budget caps gives us more control over how our dollars are being spent.

This control allows us to give more weight to our better performing keywords, and therefore, increases our returns.

As this technique has demonstrated in the past, giving an extra measure of attention to the daily budget cap and applying a bit more thought to campaign organization can greatly improve the performance of your AdWordsTM account.

Keywords: bidding, bidding price, CPC, conversion, through rate, CTR, bid price,