How would you analyze results for an entire automated email marketing campaign and decide whether or not to continue with the same strategy, or re-design a different one from the ground up?

Analyzing the results of an entire automated email marketing campaign is a crucial process for determining its effectiveness and guiding decisions about future strategies. This involves evaluating a variety of metrics, identifying patterns, and understanding the overall impact on business objectives. It’s not just about looking at the numbers, but interpreting them and using these insights to refine or overhaul your approach. Here’s a comprehensive explanation of how to analyze results and make informed decisions:

1. Establish Clear Objectives and KPIs:
Before you start analyzing any data, you need to revisit the objectives that were set at the beginning of the campaign. What were you hoping to achieve? Common objectives include increased lead generation, improved conversion rates, higher customer engagement, reduced churn rate, and increased revenue. The Key Performance Indicators (KPIs) should be directly tied to these objectives. For example, if the goal was to generate more leads, the key KPIs could be the number of new leads acquired and the cost per lead. Having clearly defined objectives and KPIs is vital, because that is what you will use to measure the overall success of the campaigns.

2. Collect and Centralize Data:
Gather all relevant data from your email marketing platform, web analytics tools, CRM, and any other relevant sources. This data must cover the entire period of the campaign and the entire series of automated emails. Key metrics to gather include:
Open Rates: The percentage of recipients who opened your emails. Segment by email type and list segments.
Click-Through Rates (CTR): The percentage of recipients who clicked on one or more links in your emails. Again segment by email and list.
Conversion Rates: The percentage of recipients who completed a desired action (e.g., purchase, sign up, download) after clicking a link in your email, segment this by type of offer or action.
Bounce Rates: The percentage of emails that could not be delivered. You need to look at both hard bounces and soft bounces.
Unsubscribe Rates: The percentage of recipients who opted out of your email list.
Spam Complaints: The number of recipients who marked your emails as spam, or junk.
Revenue Generated: Total sales or revenue directly attributable to the campaign.
Customer Lifetime Value: The long-term value of the customers who were acquired from this specific automated email marketing campaign.
Website Traffic: The volume of website traffic originating from the email campaigns.
It’s important to ensure that your tracking is accurate, reliable and provides data across all touchpoints. For example, use UTM parameters for tracking website traffic from email campaigns.

3. Analyze Key Metrics and Identify Trends:
Analyze the data to understand which metrics are performing well and which are underperforming. This requires a deeper level of analysis to identify patterns and trends. For example:
Compare Open Rates: Are open rates consistent across all emails in the series or are they varying significantly? Lower open rates for specific emails indicate problems with the subject lines or pre-header text. Also, low open rates for the entire sequence could indicate issues with your sending domain or your list.
Evaluate Click-Through Rates: Are the CTAs effective and are users engaging with the email content? Low click-through rates indicate issues with content, design or placement of the CTA buttons. You also need to look at where the user drops off in their journey.
Assess Conversion Rates: Which emails are leading to the highest conversions? Low conversion rates signal an issue with the offers, the landing pages or the overall experience after the user clicks on the link.
Examine Bounce and Unsubscribe Rates: High bounce rates indicate problems with the email list. High unsubscribes or spam complaints indicate the emails might not be aligned to user expectations, or the value provided might not be appropriate.
Analyze Revenue and CLTV: Assess the impact of the campaign on your revenue and the long-term value of the customers acquired through the campaign. Look at the ROI generated.
Look at Website Traffic: Identify the volume of traffic to your website originating from your emails, and determine if those users are engaging with the website content.

4. Segmented Analysis:
Do not just analyze data at a high level. Segment the data to gain deeper insights into the performance of different email sequences, and different user groups. This will help you identify the areas that need improvements. Segment by the following:
Email Sequence Stage: Analyze how each email performed at each stage of the funnel. See which stage has the biggest drop off. This will help you identify the bottlenecks and optimize the entire funnel.
Audience Segments: Analyze the data for different segments of your email list. Identify which segments have higher engagement rates, and higher conversions.
User Behavior: Segment the analysis based on specific actions like product views, browsing history, or other engagement metrics.
Time-Based Analysis: Analyze how engagement changes over time. This will show you how performance changes across the campaign.

5. Identify Patterns and Correlations:
Look for patterns, trends and correlations in your data. For example:
Are emails with personalized subject lines generating higher open rates?
Are emails with videos and other rich content getting better engagement?
Are email offers with limited availability and discounts getting higher conversions?
Are specific CTAs more effective compared to others?
Identify what is working well and what is not, and focus your efforts on the areas that perform best.

6. Compare to Benchmarks and Past Performance:
Compare your results against industry benchmarks and your historical data from previous campaigns. This will give you an understanding of how your campaign performs compared to others. This can identify if there is any variance, and if so you need to focus your efforts on improving those specific areas.

7. Qualitative Analysis:
In addition to metrics, also gather qualitative feedback. This can come from customer surveys, support tickets, or other customer interactions. If users are complaining about something, then you can use this information to inform your strategy, in addition to the quantitative data you already have.

8. Make a Decision:
Based on the analysis, make an informed decision on whether or not to continue with the same strategy. Here are the possible scenarios:
Continue with the Same Strategy: If the campaign meets your objectives, and the metrics are good, then there is no need to make any major changes. Keep monitoring performance and optimize incrementally.
Make Incremental Changes: If some metrics are performing well but some are not, focus on making smaller changes to address specific issues. For instance:
If open rates are low, test different subject lines and preheader text.
If click-through rates are low, optimize email content and calls-to-action.
If conversion rates are low, focus on improving the landing pages and the offers.
Re-design from the Ground Up: If the campaign fails to meet most objectives, has low ROI, or has significant issues, consider re-designing the strategy completely. This may involve:
Redefining your target audience or value proposition.
Creating new content for all the emails.
Completely overhauling the email sequence.
Changing the offers and the landing pages.

9. Document Changes and A/B Test:
Document all changes you implement and continue to A/B test different email elements such as subject lines, content, call-to-actions, images, and timing of emails, to improve performance. This approach is important for continuous optimization.

10. Continuous Optimization:
Email marketing is a continuous process, and requires constant analysis, refinement and optimization. Keep monitoring your results, use your data to improve your strategies, and make continuous improvements to your campaigns to ensure that you are always working towards higher returns.

In summary, analyzing the results of an automated email marketing campaign requires a methodical approach that combines both quantitative data with qualitative feedback. By looking at all the metrics, segmenting the analysis, and using those findings to improve your overall strategy, you can ensure that your email marketing is optimized for long-term effectiveness.