Monitoring outreach programs
A deep dive into monitoring and improving email campaign performance
In my Third quarter lessons article back in March, I briefly discussed new efforts to more systematically and effectively evaluate the performance of my email outreach campaigns. Today, I will go into this topic a little more to help you understand where I see such importance in knowing what is going on with your outreach efforts.
Today I will cover the following topics that will allow you to better harness the data in your hands:
Reporting limitations by large tools such as reply.io
Integrating your email performance data with your CRM
Tools and techniques to monitor performance
Reporting Limitations
Email sequencing tools such as Reply.io provide their own reporting capabilities with limited functionality and flexibility. At a high level, the reporting functionality is limited to charts that show the quantity of certain key metrics, usually deliveries, opened emails, replies, and interested replies. You also get a table view that shows these numbers and their respective conversion metrics (i.e., reply rate, bounce rate, etc.). Below is a look at what you might expect if you choose a sequencing tool like Reply.io, both the graph and table views.
While at a high level, these stats are helpful, there is a lot more we can do to improve our understanding of whether our emails resonate with business owners. Specifically, the data that Reply and other tools likely don’t articulate well are why emails aren’t converting to interested replies. Let’s consider two scenarios:
I send 1,000 emails to owners, and 250 of them reply with interest
I send 1,000 emails to owners, and 150 of them reply with interest
While at first glance, option 1 appears to be a much more effective campaign, can we say that with certainty? If all you’re concerned about is raw volume, then sure. But what if I were to give you additional information about the two scenarios?
Out of the 1,000 emails sent to owners, 900 were successfully contacted, while the others bounced or found the owner while they were OOO. The messages were relatively generic and may have included some guidance from ChatGPT to aid in writing the emails.
Out of the 1,000 emails sent to owners, only 300 were successfully contacted, while the others bounced or found the owner while they were OOO. The message was highly personalized for each individual and told a compelling story.
Under further investigation, option 2 looks much more compelling despite a glaring issue. Let’s run a few metrics to understand why:
Scenario 1 has a 10% bounce rate (100 failed emails / 1,000 total sent) and for owners contacted successfully, a 28% interested reply rate (15 interested replies / 90 successfully contacted)
Scenario 2 has a 70% bounce rate (700 failed emails / 1,000 total sent) and for owners contacted successfully, a 50% interested reply rate (150 interested replies / 300 successfully contacted)
While this is a pretty ridiculous example, and both have issues, I’d go with option 2, assuming that I still have a working domain and can work to reduce my bounce rate through more methodical email verification processes.
But the larger problem is that we cannot get to this level of detail in understanding our campaigns without better monitoring practices. And how do we do that?
Integrating Email and CRM Data
In the quest to minimize time spent on this weekly, integrating email campaign data with our CRM data has proven to be a game-changer. This process enables our team to access more granular insights into reply performance and streamline our reporting process. Here's a breakdown of how it works:
Step 1: Downloading Email Performance Data
Our first step is downloading the email performance data as a CSV file. This granular data provides us with valuable information on various metrics like contacted, opened, replies, sequence number, reply rates, and more. Each row is an individual email sent and its performance, so it provides much more insight than the template reporting. Upon downloading the email performance data, there are two core uses of the data set.
Step 2: Automated Reporting
First, I drop the CSV file into a specific folder that's set up for automated reporting using Python. The Python script is designed to automatically analyze the data and generate a detailed report in just a few minutes. More to come shortly.
Step 3: Joining Email and CRM Data
Parallel to automated reporting, I integrate email performance data into our CRM in Excel. By joining this data with the existing company data, we gain a much more detailed perspective on reply performance. To join the data set, there are multiple approaches but I go about it by linking the most recent email sent to a particular company and using a concatenation of email address and sequence number as the unique identifier.
Through this systematic approach, we not only boost our understanding of our email campaign performance but also enhance our team's efficiency and accountability. This integrated view of the data is instrumental in driving our ongoing outreach optimization efforts. While it may sound like a lot, this process takes less than 10 minutes to update on a weekly basis once the initial structure is set up.
Monitoring Performance: Tools and Techniques
Monitoring the performance of our outreach campaigns is key to making adjustments along the way. By leveraging both Python automated reports and CRM tools, we gain a comprehensive understanding of our campaign performance and identify areas where we can improve. Let's delve deeper into how we use these two essential tools:
Python Automated Reporting
Our Python automated report offers a four-page overview of our campaign's performance, each addressing a unique aspect of the outreach:
Email Performance by Week Chart: This chart provides a visual representation of how our emails are performing week by week. It allows us to identify trends, assess the effectiveness of our outreach efforts, and make data-driven decisions for future campaigns.
Not Interested Emails by Week: Similar to the previous chart, this chart instead focuses on the number of 'not interested' emails we receive each week. Although the data quality of these new fields is a bit questionable at this point, I am interested to see how this improves going forward.
Email Performance by Sequence Step: This section breaks down the performance by each step in our email sequence. Understanding which steps yield the highest response rates enables us to refine our strategy and maximize our outreach success.
Data Table of Weekly Performance: This comprehensive table aggregates our weekly performance data, offering a clear snapshot of our successes and areas for improvement.
CRM Reporting
Our CRM reporting, on the other hand, is geared towards evaluating the contributions of our interns to the outreach campaigns:
Intern Performance Tracking: By tracking individual contributions, we can assess whether our interns are meeting their goals and identify areas where additional support or training may be needed. This not only promotes accountability but also ensures that our team is equipped to contribute effectively to our outreach efforts.
Through these tools and techniques, we stay informed about our performance and are able to quickly pivot our strategies as needed. This systematic approach to monitoring is crucial in helping us continually optimize our outreach programs.
Conclusion
To wrap up, the importance of monitoring your outreach efforts cannot be understated. With a little bit of time and effort, you can harness the data at your fingertips to glean insights that can transform your campaigns. The integration of email performance data with your CRM, coupled with the use of Python for automated reporting and CRM for performance tracking, can equip you with the tools you need to evaluate your efforts more effectively.
However, it is important to strike a balance. As a searcher, your time is valuable, and you need to ensure that you're not sinking too much of it into managing and monitoring your outreach campaigns. The key here is to automate as much as possible and focus on gleaning the most critical insights. The initial setup may take some time, but once established, these processes can save significant time and effort in the long run while offering valuable insights.
The most powerful aspect of these approaches is the ability to understand your campaigns on a much deeper level - from understanding why certain emails are not resonating with business owners to tracking the performance of your team members. This level of insight allows you to make data-driven decisions that can significantly improve your outreach campaigns.
Remember, the key here is to continuously monitor and evaluate your outreach efforts, making necessary adjustments along the way. While the initial set up may take some time, the potential benefits in terms of improved campaign performance and team efficiency are well worth the investment.
I hope this post has been informative and useful for you. If you know a fellow searcher who could benefit from these insights, please do share this post with them. I also welcome any feedback, questions, or comments you may have - your input can only help to enhance the quality and relevance of future content. So, let's keep the conversation going.