Determine the “Why” of Conversion Rates with Web Analytics and Call Tracking

Whether you’re investing in a multi-faceted marketing campaign, or you want to evaluate the main calls to action on your website, one of the most important metrics in determining the effectiveness of your marketing efforts is the conversion rate of audiences to leads.

However, looking at the conversion rate alone is not enough information to help you determine how to improve campaigns and increase conversions.

Instead, you must look at the full scope of data available to you through web analytics and call tracking tools. Together, these will help you paint a detailed picture of how your target audiences interact with your marketing efforts, and give you the information you need to better evolve your campaigns.

What Conversion Rates Tell You – Using Web Analytics and Call Tracking

The conversion rate, or frequency at which someone takes a desired action and becomes a lead, gives you the percentage rate of success your calls to action yield.

Utilizing both web analytics and a call tracking solution will help to you track both on- and offline conversions—for example, lead form completions and phone calls—for an accurate representation of marketing optimization. This is particularly important when analyzing campaigns across several mediums, such as TV, print and online.

The conversion rate will help you answer questions about what is working: which aspects of your campaign are, and are not, successfully converting audiences into leads. But, it won’t explain why: why individuals respond better to one campaign over another.

It isn’t until you are able to answer “why” that you can make strategic adjustments to your campaigns that increase lead generation and increase ROI.

Answering the “Why” of Conversions with Web Analytics and Call Tracking

Let’s say your PPC campaign yields 10 percent more leads than your TV ad. While that number is useful for identifying one campaign’s effectiveness over another, it doesn’t tell you why this is the case.

To gather this information, you have to dig deeper into website analytics and call tracking data. Below are key metrics to evaluate that can help you identify why and how different elements of your campaign impact conversion rates:

  • Conversion Source (i.e. PPC ad or offline TV ad) — What sources drove conversions? Use this information to analyze the headlines, messaging, calls to action, or promotions that tend to result in lead activity, and which don’t.
  • Conversion Web Page — If a marketing effort drove visitors to your website, what was the last page they viewed before completing a lead form or calling? Again, look for headlines, messaging and calls to action that motivate visitors to convert.
  • Exit Rate / Bounce Rate — What pages are least likely to encourage a visitor’s conversion? Where are visitors leaving your site from, and how do these pages differ from those that generate leads?
  • Pages/Visit and Pageviews — On average, how many pages does someone view before converting, and what topics are they interested in? If multiple pages exist on the same topic, which of these pages perform best? Is there a way to consolidate information into one highly effective page?

How often do visitors click through your site and then exit, signifying that they couldn’t find what they were looking for? What content can be added to your site that will help prospects find what they need?

Use the Data to Evolve Your Campaigns

Use the information available to you through website analytics and call tracking tools, in conjunction with your conversion rates, to take a holistic view of your marketing performance. Evaluate what elements of your campaigns work, which need to be adjusted and how these pieces work together to yield conversions and sales.

By analyzing this data, you can extract valuable details about what your audiences like and dislike, what information they’re looking for and what messages resonate best. Then, you can create an action plan to better meet these preferences. Use A/B testing to further test your theories before full implementation.

What data do you use to analyze conversions?

 

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