• Section: Increase Traffic - Category: SEO/SEM
• Written by Jerry Work

When preparing to begin a pay per click marketing campaign, it really helps to go into the situation with an idea of what the numbers look like. By "the numbers", I mean what kind of return on your investment you can expect assuming different bid levels and different conversion rates. It's really all just conjecture because you don't know what your click-through rate will be, what your bids will have to be to generate adequate traffic, or what your conversion rate will be. But you don't want to go into the situation blind. So the following technique is a way for you to at least apply some logic to the situation, rather than just guessing.

ROAS ("Return on Ad Spend") is defined as the total dollars generated by the advertising divided by the cost of the advertising. The following discussion and data illustrate an ROAS-based approach to setting a baseline bid level for your campaign. Every ad group and possibly every keyword will have its own bid once you actually set the a

d groups up. But this type of analysis will give you an idea of what your average click price needs to be in order to generate a positive return on investment, assuming various conversion rates.

Below are two examples of the kind of analysis we often do when beginning a new campaign to give the client and ourselves an idea of what he might expect his return on ad spend to be. It also helps us establish a benchmark average bid.

The first thing you're going to need is some data to plug into your spreadsheet. So log into your Google, Yahoo!, or MSN account and create a new campaign or ad group. When you get to the keywords section, add a large group of keywords related to your industry. You are not going to actually use this campaign; you just want to get an idea of how much traffic there is for the keywords and how much you might have to pay for clicks. Going through the process of setting up a campaign lets you generate some data to work with.

The data for the examples below was generated in the Yahoo! Search Marketing interface. Yahoo! is convenient for this kind of analysis because of its sliding scale bid tool that gives immediate feedback about expected traffic and costs at different bid levels by just moving the slider around. We used a single broad set of related keywords to generate the necessary data. In reality, your keywords will be divided up into logical groupings, or ad groups, but for analytical purposes a single ad group was sufficient.

For our first analysis, we are going to assume a bid level of $.75, which Yahoo! estimated would result in 21,993 monthly clicks at a cost per click of $.50. For illustration purposes (and to make the math easier), we assume average revenue per sale of $100.

We know that our total cost is going to be $10,997 (21,993 clicks X $.50), so we can use this information to estimate what our total sales, and thus return on ad spend, will be at different conversion rates:

Bid: $.75
Est. Monthly Clicks: 21,993
Avg. Cost per Click: $.50
Total Cost: $10,997
Avg. Revenue per Sale: $100.00

Performance per Conversion Rate

Conversion Rate: 0.25%
Estimated Sales: 55
Revenue: $5,498.25
Return on Ad Spend: 50%

Conversion Rate: 0.50%
Estimated Sales: 110
Revenue: $10,996.50
Return on Ad Spend: 100%

Conversion Rate: 1.0%
Estimated Sales: 219.9
Revenue: $21,993.00
Return on Ad Spend: 200%

Conversion Rate: 2.0%
Estimated Sales: 439.9
Revenue: $43,986.00
Return on Ad Spend: 400%

Conversion Rate: 3.0%
Estimated Sales: 659.8
Revenue: $65,979.00
Return on Ad Spend: 600%

As you can see, if we convert at 0.25% (1 in every 400), we are going to generate a return on ad spend of 50%, meaning we are bringing in fifty cents for every dollar we spend. That is not very good. We probably need to convert at a rate between 1% and 2% to show a reasonable return on our investment.

Now we might want to see what the numbers look like if we lower our bid. If we bring our bid down to $.50, Yahoo! estimates our estimated monthly clicks to be 14,948 at a cost per click of $.38. So now the retur

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