As marketers, sending the right message at the right time is crucial. With Salesforce Marketing Cloud’s Einstein, Predictive Send Time Optimization (PSTO) allows you to pinpoint the optimal time to send emails to each individual recipient based on their historical engagement patterns. Einstein analyzes data such as when customers are most likely to open emails and interact with them, ensuring that each email reaches the recipient when they are most active.
In this article, we will explore how Einstein’s Predictive Send Times work, how to set it up in Salesforce Marketing Cloud, and the impact it can have on your email marketing campaigns. This topic connects with earlier discussions such as Day 61: Using Einstein Recommendations in SFMC and Day 60: Personalizing Emails Based on Customer Data, where we learned about using AI-driven insights to personalize and optimize marketing strategies. Let’s dive into how predictive send times can significantly improve email deliverability and customer engagement.
What are Predictive Send Times?
Predictive Send Times leverage machine learning and AI to predict when a specific subscriber is most likely to open or engage with an email. Rather than sending an email blast to your entire list at the same time, Predictive Send Times allow you to stagger email deliveries so each email is sent when it is most likely to be opened.
For example, if Subscriber A typically opens emails at 9 a.m. and Subscriber B is more active at 3 p.m., Einstein will schedule the email to reach each subscriber at their respective optimal time, boosting engagement rates. This creates a more personalized and efficient communication strategy, minimizing the chance of emails being lost in crowded inboxes.
How Does Einstein Predict Send Times?
Einstein uses several data points to determine the best time to send emails to each subscriber:
Historical Engagement Data: Einstein analyzes when a recipient has interacted with emails in the past, noting patterns such as the time of day or week when the recipient is most likely to open or click on an email.
Behavioral Insights: Apart from open times, Einstein also studies click behavior, the duration between an email being opened and clicked, and other behavioral patterns.
Cross-Channel Data: By analyzing customer behavior across channels (email, website, mobile apps), Einstein builds a holistic view of the recipient’s engagement habits, offering more accurate predictions.
Einstein’s AI engine continuously learns and updates its predictions, ensuring that the send times become more accurate as more data is gathered. Over time, the system gets better at identifying optimal send times for different recipients, allowing marketers to optimize campaign performance continuously.
Why Are Predictive Send Times Important?
Email marketing is all about timing. Even the most well-crafted emails can go unnoticed if they arrive when recipients are busy or distracted. Here’s why leveraging Predictive Send Times is crucial:
Maximizes Engagement: Sending emails at the right time increases the likelihood of the recipient opening and engaging with your email, leading to higher open rates, click-through rates, and conversions.
Avoids Overload: Customers often receive emails during peak times, which can cause your message to be buried. Predictive Send Times help avoid this by staggering email delivery and reaching customers when their inboxes are less crowded.
Personalized Communication: Predictive Send Times allow you to send emails based on individual preferences, providing a more personalized experience for each recipient. Personalization is key to increasing customer satisfaction and driving results.
Improves Deliverability: Sending emails in bulk can lead to deliverability issues, including bouncing and spam filtering. Predictive Send Times help to smooth out delivery rates, ensuring better inbox placement and improving overall deliverability metrics.
Optimizes Campaign Performance: By sending emails when recipients are most active, you can optimize your campaign’s overall performance and ensure that your emails don’t get lost in an overcrowded inbox. This ties into Day 52: Best Practices for Optimizing Campaigns Based on Analytics, where the power of data-driven optimization is explored.
How to Set Up Predictive Send Times in SFMC
Implementing Predictive Send Times within SFMC is straightforward. Here’s how to get started:
Step 1: Ensure You Have Sufficient Data
Predictive Send Times rely on historical engagement data. If you’re working with a new list or haven’t sent many emails to your audience, it might take time for Einstein to build accurate predictions. Make sure that your data is comprehensive and that you have a solid history of email engagement to work from.
Step 2: Access Einstein’s Predictive Send Time Feature
To begin using Einstein’s Predictive Send Time feature in SFMC, navigate to the Einstein Email Recommendations section in the platform. If you’re already using Einstein for email recommendations, it’s as simple as enabling the Predictive Send Time functionality within the relevant campaigns.
Step 3: Choose Your Audience
Once you have activated the Predictive Send Time feature, you need to select the audience that will benefit from this feature. Einstein will analyze the engagement behavior of this audience and determine the best time to send emails to each individual subscriber.
Step 4: Schedule Your Campaign
Instead of selecting a single send time for the entire audience, choose the Predictive Send Time option when setting up your email campaign. SFMC will automatically schedule the email to be delivered to each recipient at their predicted optimal send time.
Step 5: Monitor Performance
Once your campaign is live, track its performance using SFMC’s built-in analytics tools. You’ll want to monitor key metrics like open rates, click-through rates, and conversion rates to assess the impact of Predictive Send Times on engagement. This also links back to Day 44: Introduction to SFMC Reporting and Analytics, where we discussed how tracking metrics can help optimize campaign performance.
Testing and Optimization with Predictive Send Times
As with any marketing tool, testing and optimization are crucial to success. Here are some strategies for optimizing your use of Predictive Send Times:
A/B Testing: Test campaigns with and without Predictive Send Times to measure the difference in engagement rates. This will help you understand how much of a boost the feature provides and whether it’s worth implementing across your entire audience.
Segmentation: Not all segments of your audience may respond the same way to Predictive Send Times. Test different segments (e.g., high-engagement vs. low-engagement users) to see how the feature affects different customer groups.
Continuous Monitoring: Einstein’s predictions improve with more data. Make sure to continuously monitor your campaigns and assess performance metrics. Over time, you’ll be able to fine-tune your strategy and maximize the effectiveness of Predictive Send Times.
Benefits of Using Predictive Send Times
1. Increased Open and Click-Through Rates
By sending emails when recipients are most active, you can expect to see a significant boost in open and click-through rates. This personalized timing increases the likelihood that the recipient will engage with your content.
2. Better ROI on Email Campaigns
By improving engagement rates, Predictive Send Times can help drive conversions and increase the overall return on investment (ROI) for your email campaigns. This is especially useful for businesses with large email lists, where even small increases in engagement can result in substantial revenue gains.
3. More Efficient Use of Resources
Predictive Send Times allow marketers to get more out of their existing email lists without needing to invest additional resources. With AI handling the optimization, you can focus on crafting compelling content while Einstein takes care of the timing.
Use Cases for Predictive Send Times
Predictive Send Times are particularly effective for the following use cases:
E-commerce Promotions: Send promotional emails to customers when they are most likely to make a purchase, increasing the chances of conversion.
Newsletter Engagement: For content-based businesses, delivering newsletters at optimal times can increase readership and engagement.
Transactional Emails: Ensure that important transactional emails (e.g., order confirmations, password resets) are delivered when recipients are most likely to engage, improving customer satisfaction.
Conclusion
Predictive Send Times are a powerful tool within Salesforce Marketing Cloud that can help marketers improve engagement, optimize email delivery, and drive better results. By leveraging the AI-driven insights of Einstein, you can ensure that your emails reach the right audience at the right time, maximizing the impact of your marketing efforts.
Incorporating Predictive Send Times into your SFMC strategy builds upon the principles we discussed in earlier articles, such as Day 61: Using Einstein Recommendations in SFMC and Day 52: Best Practices for Optimizing Campaigns Based on Analytics, further enhancing your ability to deliver personalized, data-driven marketing campaigns.