B2B Marketing Zone

3 Levels of Data Analysis to Revitalize Your Automated Email Programs in 2016

3 Levels of Data Analysis to Revitalize Your Automated Email Programs in 2016

Whether you’ve recently started using automated email programs or you’re a seasoned veteran of the practice, there is no better time than the end of the year to assess all your drip program activities. I just completed an extensive email program cleansing project, so it seems timely to share my method in doing so.

Optimizing for incremental percentage gains on your email statistics could make a monumental difference in revenue and brand perception in the following weeks and months.

data analysis

I’ve broken the process down into a three-pronged approach:

  1. Macro-Categorical
  2. Individual Program
  3. Individual Email/Subject Line

Here are examples and definitions of each of the stages:

1. Macro-categorical

Here you categorize your collection of email programs into broad, meaningful categories, such as:

  1. DemandGen
  2. Top of Funnel
  3. Bottom of Funnel

2. Individual programs

Within categories, look at each program. Pay particular attention to the amalgamation of steps and email templates for each. These should be complete, discrete programs, such as:

  1. Anonymous Website Visitors
  2. Top of Funnel Program – USA
  3. Middle of Funnel Program – EMEA

3. Individual email/subject line

Within each program, analyze each individual email and subject line for performance, such as:

  1. DemandGen – 2015 Happy New Year Email
  2. Top of Funnel  – Invitation to View New Video
  3. Customer  – All About the New Feature

Categorical analysis

Hopefully, you’re already using macro organization for your automated programs…that is, you will have already organized your email programs into broad general ideas/buckets.

For example, categories such as Top of Funnel, Middle of Funnel, and Bottom of Funnel sort programs by buyer stage. Categories such as EMEA and ROW sort by geography. Website, Webinar, and DemandGen are also perfect examples of macro-categorical buckets. These broad categories are perfect for this first stage analysis. This is important because not only will you want to see how multiple programs are performing in a single category, but this will give you a great birds-eye view of the bulk of your campaigns.

Programmatical analysis

Next up is the program level analysis. Each program is a combination of email templates, steps, and other programmable actions that make up a program. What we want to investigate at this level are how the different programs within one macro-category are performing. If there are programs that are similar, why is one performing better than others? Additionally, are there any ways for us to condense and consolidate our programs down to a smaller number?

If I were to give my humble opinion as to which of the three stages is the most difficult to assess, I would say that the program level is the most difficult. This is because the success of the program is contingent on the multitude of email templates contained within it. The only way to really look at the success of a program level stage is to either look at a program’s numbers vs another program in the same category (regardless of any other variables), or to examine the programs by what went wrong with individual email templates/subject lines. There could be several rotten apples in certain programs that are affecting the entire operation.

Individual email analysis

Finally, the last of the three stages is the individual email/subject line stage. This is where the purest information will be found.

It’s a great practice to have multiple subject lines on identical templates that are triggered to members of that program that do not open the first iteration of the email. By analyzing whether subsequent subject lines had success (i.e., the email was opened), you can now begin to chip away at failed subject lines and templates. Subject lines will get you opens, and templates will get you clicks; these are the two metrics that will help guide your decision making while cleaning up your programs.

email analysis

Getting the data

A question you might ask is, “How do I get the information to do this?” In the best-case scenario, your marketing automation platform can give you the data that will allow this kind of analysis to be completed. To do this for Act-On, I used our new Data Studio tool to render all the information needed to completely revamp every single email campaign for our 2016 initiatives.

In conclusion

More than ever, knowledge is power. With technology giving us new ways to get better data and human ingenuity organizing methods to analyze it, we have new opportunities to draw the conclusions that will power our marketing programs to new levels of success.

Take a video tour of Act-On’s Data Studio to learn how you can begin uncovering new insights about the performance of your marketing programs.


About

As the Marketing Operations Manager for Act-On Software, George is able to turn vast amounts of data into digestible and insightful narratives in order to enable his executive team to make strategic decisions. He is inspired by aligning marketing and sales teams through funnel measurement, strategic insights, and data analysis. Connect with George and check out his LinkedIn Group West Coast CRM & Marketing Automation Professionals.


  • Andrew Verey

    Very informative Blog – Thank you

  • Thanks for sharing your process, George, this is very helpful. I appreciate the difficulty of the pragmatic step, too. Like you said, so much goes into the success of each email, including the experience beyond the email itself (landing pages, etc.).