Sending out emails in daily email broadcast waves for large send quantities, rather than sending them all at once, can have several advantages:

Avoiding Spam Filters: Sending a high volume of emails at once can trigger spam filters and result in your emails being marked as spam or sent to recipients’ spam folders. By sending emails in smaller daily waves, you reduce the risk of being flagged as a spammer.

Better Deliverability: Email service providers (ESPs) monitor the sender’s reputation and behavior. Gradually increasing your email volume can help maintain a positive sender reputation and improve deliverability.

Reduced Bounce Rate: If you send emails to a large list all at once, you may experience a higher bounce rate due to invalid or inactive email addresses. By sending emails in waves, you can identify and remove bad email addresses before sending to the entire list.

Improved Engagement: Sending emails in waves allows you to closely monitor recipient engagement and adjust your email content and strategy based on real-time feedback. This can lead to higher open rates, click-through rates, and overall campaign success.

Load Distribution: Email servers and infrastructure can be strained when sending a massive volume of emails at once. By spreading the load over daily waves, you reduce the risk of server issues and ensure consistent email performance.

Optimal Timing: Different recipients may have different optimal times to receive and engage with emails. Sending in waves can help you time your emails for maximum impact based on your audience’s behavior.

Testing and Optimization: With daily waves, you can run A/B tests, experiment with subject lines, content, and other variables, and optimize your email campaigns based on the results before scaling up.

Managing Responses: When sending in waves, you can more effectively manage and respond to recipient inquiries, feedback, or unsubscribe requests, which can be challenging if you send a massive number of emails all at once.

Avoiding ISP Restrictions: Internet Service Providers (ISPs) may have limits on the number of emails you can send within a specific time frame. By sending emails in waves, you stay within these limits and avoid any restrictions.

Reducing Complaints: Sending a large quantity of emails at once can lead to more complaints, which negatively impact your sender reputation. Sending in waves allows you to address complaints and unsubscribe requests promptly, maintaining a positive reputation.

In summary, sending emails in daily waves for large email databases is a best practice to ensure better deliverability, engagement, and overall success of your email marketing campaigns while avoiding common pitfalls associated with high-volume email sends.

An email address customer lookalike audience is a marketing term that refers to a group of people who share similar characteristics and behaviors with your existing customers, and who can be reached through email advertising campaigns. This audience is created by using the email addresses of your current customers as a starting point.

How it works:

1. Data Collection: First, you collect a list of email addresses from active customers. This list may come from your CRM (Customer Relationship Management) system, email platform, or marketing software.

2. Data Analysis: Once you have this list, you can analyze it to identify common traits, preferences, and behaviors among your customers. This could include demographic information, purchase history, online behavior, and more.

3. Lookalike Audience Creation: Using the insights gained from analyzing your customer email list, you can create a lookalike audience. This audience is generated by finding people who resemble your existing customers based on the identified characteristics.

4. Email Advertising: With your lookalike audience in hand, you can use email database enrichment tools to replenish this target audience. Then you are ready to send new contacts promotional emails, newsletters, and target them with digital advertisements.

The goal of using an email address customer lookalike audience is to expand your reach to potential customers who are more likely to be interested in your products or services because they share commonalities with your existing customers. This can improve the effectiveness of your email broadcasting efforts by reaching people who have a higher likelihood of converting into paying customers.

Customer matchback attribution is a method used in enterprise email marketing campaigns to attribute conversions or other desired actions back to specific email campaigns or touchpoints. It helps marketers understand which email campaigns are most effective in driving customer engagement and conversions.

How it works:

1. Collect customer data: To implement customer matchback attribution, you need to collect and store data on both your email marketing campaigns and customer interactions. This data typically includes information about the emails you send (campaign ID, send date, subject line, content, etc.) and customer actions (clicks, opens, conversions, purchases, etc.).

2. Track email interactions: Ensure that you have mechanisms in place to track customer interactions with your emails. This can involve using tracking pixels or unique links for each email campaign to monitor opens, clicks, and other interactions.

3. Monitor conversions: You also need to track customer conversions or other desired actions that result from your email marketing efforts. This could include monitoring purchases made through links in your emails, form submissions, app installations, or any other relevant actions.

4. Integrate databases: To attribute conversions to specific email campaigns, you need to integrate your email marketing data with your customer data. This could involve linking email campaign data with customer profiles in your CRM system or database. Each customer’s interaction with your emails should be associated with their customer profile.

5. Time matching: Customer matchback attribution often involves matching customer conversions to the email campaign that influenced them. To do this, you’ll need to establish a time window during which a conversion is attributed to a specific email. For example, you might consider a conversion as attributed to an email campaign if the conversion occurs within a week of the email being sent.

6. Attribution rules: Define attribution rules based on your specific goals and campaign strategies. For example, you might use “first-touch” attribution, where the first email that the customer interacted with gets credit for the conversion, or “last-touch” attribution, where the most recent email receives credit. Alternatively, you can use more advanced models like linear attribution, which distributes credit across all interactions.

7. Analysis and iterations: Once your data is collected and attributed to email campaigns, you can analyze the performance of your email campaigns. You can measure metrics like conversion rates, revenue generated, ROI, and other KPIs to assess the effectiveness of each email campaign.

8. Campaign optimization: Use the insights from your analysis to optimize your email marketing strategy. Identify which email campaigns and tactics are driving the most conversions and adjust your future campaigns accordingly.

Customer matchback attribution is a valuable tool for understanding the impact of enterprise email marketing campaigns on customer actions and conversions. It allows you to make data-driven marketing decisions to improve the effectiveness of your email efforts and maximize your ROI.