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How SBNRI achieved 16% higher open rates with Mailmodo's value-added services

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“We resolved our email health challenges which led to a 16% increase in open rates. Plus, we learnt how to monitor email health parameters for every campaign.”

SBNRI_DP_6a152a55ed

Muhet Gupta

Growth Marketing

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Challenge

Low deliverability and open rates

Solution

Email deliverability audit and fixes

Vector_6_90a8a5325716%
higher open rates

Key
learnings

  • Discover how to increase the open rate of your campaigns
  • Learn to maximize email deliverability

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Here’s the playbook that sbnri used

About SBNRI:

SBNRI is a fintech company providing seamless investment & advisory services to NRIs worldwide. They guide NRIs through online facilities such as sign-up, KYC, investment, advisory services, etc

Challenge: Low deliverability

  • Despite trying out multiple email tools, Muhet Gupta, Growth Manager at SBNRI, noticed email deliverability falling when they started sending emails to new contacts with a new domain.
  • Open rates were dipping, and many emails were landing in the spam or the promotions folder. The team realized this was also impacting domain reputation when the sales team reported low deliverability of one-on-one emails sent from the same domain.
  • So they readily looked for ways to improve their deliverability.

Approach: Chose Mailmodo’s value-added services

As one of the tools in use was Mailmodo, Muhet opted for Mailmodo’s value-added services for an email expert to help improve deliverability.

Step 1: Diagnose reasons for low deliverability

After initial analysis, the expert diagnosed the following

  • Low domain reputation
  • High spam complaints
  • Using a non-warmed-up domain
  • Lack of list hygiene (consisting of non-permission data)
  • Lack of a suppression list

Step 2: Warmup Domain

The expert segmented contacts and chose engaged contacts who had previously opened emails. Further, he divided the engaged contacts into smaller groups, and sent daily emails to warm up the domain. He gradually increased list size till complete list of 42K users was included. Google Postmaster was set up to monitor domain reputation.

Step 3: List Hygiene and Suppression List

He groomed the email list by removing bounced emails and invalid emails. A suppression list was put in place, which automatically suppressed bounced emails in the future. This brought down bounce rates.

“The Mailmodo expert assessed earlier campaigns sent and analyzed multiple email health parameters. With their support, we became aware of how to warm up a domain, maintain email list hygiene and manage a suppression list.”
Muhet Gupta, Growth Manager, SBNRI

Step 4: Email Template Optimization

Due to emails landing in spam earlier, content from those emails was flagged by the spam filters - impacting deliverability. Hence, content was replaced in the new templates to reduce spam complaints. To improve engagement, images and AMP widgets were added. Specifically, calendly widget was added to get more demo bookings from email.

Before optimisation

Screen Shot 2022-06-28 at 10.34.37 PM.png

After optimisation:

Results: 16.66% increase in open rates

Before Mailmodo:

  • SBNRI was also facing a bounce rate of more than 10%, due to which the IP got blocked.
  • Average Open Rate : 18% for an average list size of 9,789

Best performing campaigns

Screen Shot 2022-06-28 at 10.34.58 PM.png

The table shows that open rates declined when email list size increased and included non-engaged contacts.

After Mailmodo:

  • Average Open Rate- 21% for an average list size of 10,388

Best performing campaigns

Screen Shot 2022-06-28 at 10.35.05 PM.png

“We resolved our email health challenges which led to a 16% increase in open rates. Plus, we learned how to monitor email health parameters for every campaign. We also added the AMP Calendly widget, which increased demo bookings from email.”
Muhet Gupta, Growth Marketer, SBNRI

Results from email template optimization

The optimized AMP templates resulted in 2 Calendly submissions (demo bookings). The fallback HTML versions resulted in 23 clicks, which led to 23 leads generated.

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