Email marketing: 3 ways to optimize results
Email marketing is the workhorse of digital marketing. Declared dead several times but alive and kicking. Email marketing brings ROI quickly but there is room for optimization.
1. Optimize with the return on email marketing KPI
If you determine the costs (t&m to send the email campaign) and benefits (transaction value for the customers who received the email) for an email campaign you can calculate the return on email marketing. Feel free to make this calculation as complex as you want, the point is that you have a KPI to benchmark your campaigns.
The calculation of this KPI after every sending allows to optimize an email campaign immediately:
- Increase/decrease the target group;
- Adjust the email: image / copy / call to actions;
- Change sending time;
2. Segment customers based on their response data
Marketers have been struggling with the idea for years: should we exclude or continue to approach inactive customers (who rarely open an email)? From a reputation point of view, it is better not to send email to inactive customers, but it can be very affordable if you can get this group active again. For this reason, you can choose to divide customers into activity segments.
Think of: group 1: opens almost every mail, group 2: sometimes opens an email, group 3: rarely opens an email and group 4: is completely inactive. By comparing the campaign results of these groups you will see differences. Some emails do relatively well in the inactive segments: and you can continue to send them. Don’t forget to update the activity segmentation after each campaign.
3. Define campaigns based on click- and web behaviour
For the above analyses, you need access to the complete database with e-mail results. Mailigo can provide you with export data files to find all approached customers with opens and clicks. If you also want to measure how a respondent converts on the website, use tracking tools like Segment(segment.com) or Google analytics 360(analytics.google.com) that provide you with the full click path at the customer level. This allows analyzing the visitor behaviour per customer in the full path from an email response to website behaviour.
With the analysis results, create automatic campaigns based on the combination of email response and web behaviour. Think of an automatic e-mail that recommends the products that the customer clicked in the first e-mail and looked at the website but did not buy.
Stephan van Heusden, co-founder Mailigo