Research and metrics with effective web analytics marketing formula for repeating winning online advertising campaign.

Achieving better results and great ad performance from your online advertising campaign is an important goal.

It’s a short term result if you’re not able to repeat success.

Taking time to set up proper testing makes a big difference in repeating successful campaign results again and again.

So what’s the next step in web analytics?

• Isolating different variables during testing defines which ads work best
• Utilizing a control group allows for a clear analysis of which elements work better or worse
• Find the best formula, consider testing again to continue to improve

Want to know how to create a control group and configure the campaign for multivariate testing?

And why multivariate tests enables you to replicate performance across your advertising campaign to achieve exceptional ongoing results?

Let’s demonstrate how applying testing practices can not only lead to outstanding results…

But also provide insight into what specifically made the marketing campaign so successful.

Firstly, it is useful to define what’s meant by a control group and multivariate testing.

Well, a control group is simply defined as a segment of people who will not be exposed to the marketing variables you’ll be testing.

Multivariate testing is defined as a process by which multiple variables for an online campaign.

You can be isolated and tested against each other to determine which defined variable performs best.

Applying two types of testing (best practices) insures you make the best optimization decisions for the performance of your advertising campaigns over time.

The following shows how to utilize a control group and multivariate testing to achieve better results.

You can use the information and insights from the results to further optimize and repeat performance across your campaigns too.

Step 1: Determine which campaign variables to test

For example:

• You can test the impact of time lapse between:
• Visits
• Promotional offer
• Language
• Creative size

To determine which combination gets the best results.

Time lapse: You want to re-target display advertisements to users who previously visit your site but did not complete a registration form.

Do you understand why the amount of time since the last visit to the site is an important variable?

The goal is to serve a specific banner based on a specific variable.

What’s the amount of time that passed since a visitor had left your site?

Visitors who had been to your website fewer than seven days ago were shown a different banner than those who had not visited for at least eight days.

Promotional offer: You want to test two different levels of promotional discounts in each banner.

You can test a 15-percent-off banner targeted to users who had been to your website within a week’s time.

Test this against a second 20-percent-off banner targeted to users who had not visited in more than a week.

Language: The preferred language of each visitor is another important variable to test.

This is in addition to the “time lapse” and “promotional offer” variables, and also to target users by preferred language.

For example… you can show re-targeted banners in a different  language to those who visit another language version of your website.

All other visitors are served banners in English.

Creative size: You can test two different creative banner sizes to determine if the size of the banner would impact the results.

Example banners to use are sizes: 300×250 and 728×90.

With so many variables involved in a campaign, you need a way to track and measure the success or lack of success for each variable.

In order to reach your campaign goals you can use multivariate testing configured in a controlled environment.

Step 2: Create a control group

You want to establish a baseline for which variables to test.

Tthe next step is to create a control group for the campaign.

A randomized 10 percent control test group can be served generic banners on the same media websites as the test creative.

Any conversions generated from the control group represented users who saw or clicked on a non-related banner.

You want to see if this happens by chance to also convert.

A control group can provide an excellent baseline for confidently analyzing your overall campaign.

Step 3: Develop creative and set up campaign placements

You can structure your campaign using nine total placements.

You want to test all combinations of variables:

• Creative size
• Language
• Offer type

By properly setting campaigns and placements up front, you can test configuration and be confident to launch your campaign.

Step 4: Analyze the results

After running campaign over a three-month period you can see the results.

Because you ‘re effectively testing in a controlled testing environment, you can determine which variables generate the most conversions and sales.

And be able to optimize future campaigns accordingly to achieve exceptional results.

Some key findings from the test campaign include:

• Click-through rates for entire campaign (is the average X amount of times higher than the control group?)
• What’s the best performing set of variables (728×90 creative with offer No. 2) What’s the click rate? How many times higher than the control group?
• What’s the average dollar spent per click?
• Compare other campaigns running during the same time frame to see if averages per click is better with highly re-targeted campaign…

Step 5: Optimize campaigns based on results for repeat performance

You want to move results in the right direction, right?

That’s why you want to setup a control group and make sure you use a large enough sample size to begin with…

Here’s why…so the results from your campaign are verifiable.

Since each combination for each variable is carefully tested:

• Banner size
• Offer type
• Language

You confidently know how to separate placements so you know which combination of variables are working together.

You know what is most likely to produce the best results in future campaigns.

Web analytics provides many answers so you can setup better performing advertising campaigns.

The results from campaign invariably raise more questions.

For example, if you find other language banners are performing better than English, should you test Chinese or French creative next?

The answer is absolutely as long as you use a control group with multivariate testing.

Now you know how to use web analytics for your winning campaigns.