How redBus adapted to users’ behavior to improve email open rate
Emails are an important medium of communication with customers. While in the recent days WhatsApp is gaining popularity to have a more personalized, intent-driven communication with the customers, brands should be very careful in using this medium as they don’t want to be marked as spam and lose this powerful communication channel with their customers. Emails don’t get hyper personal and at the same time provides the flexibility for the users to organize them in the way that best suits their lives. So, in most cases emails do play an important role in getting information from the users and also updating information to the users.
At redBus, we send emails for ticket confirmation, support updates, journey updates, collecting NPS and collecting feedback on the journey. While NPS is something we ask a week after the journey date, all the other emails are real-time, dynamic and happen close to the date of journey. Also, we use other channels in parallel to send the same information so that passengers don’t miss out on important updates; except feedback emails. We ask customers for feedback on their journey using different channels in series instead of shooting all of them at once. The order we follow to collect feedback is to send push notifications first, followed by WhatsApp and then email if the user doesn’t respond to communications sent on previous channels with a few hours of gap between each communication.
While email is the last channel we resort to, 4.09% of the feedback responses were received from communication sent through emails and the open rate of the emails was on an average 7.03%. Although a feedback request email is related to one’s journey, it is not as critical as the other journey update emails. Since the journey is also completed by the customer, there is little intent to open the email and provide the valuable feedback. So, in principle it is equivalent to a marketing campaign and we can use the industry standard of open rate for marketing emails as a reference to evaluate the performance. On an average, the open rate of marketing emails ranges from 15–20%. So at 7%, we were significantly underperforming. This was an opportunity to explore. The ultimate goal is to improve the click through rate and eventually improve the feedback responses received from emails. However, the precursor to improving the click through rate is to first improve the open rate of the emails. While improving the click through rate is in itself a different problem to solve, in this article we will focus on the intervention we did to improve the open rate and its consequential impact on overall responses from email as a channel.
In order to optimize the email open rate, it was important to understand the nature of travel by our passengers. In India, most of the inter-city bus travel happens during the night with an average journey time of 6–8 hours and the passengers usually reach their destination early in the morning. Also, the majority of the travel happens on Friday, Saturday and Sunday nights. We extracted the data to observe the time of the day we were sending emails to our customers for feedback and this is how it looked (pre-COVID data for 3 months).
Clearly, there was a pattern.
- Most emails are sent on Saturday, Sunday and Monday. This is in correlation with the most travel days of the week — Friday night, Saturday night and Sunday night
- Period in which most emails are sent are between 0100 hrs and 0400 hrs GMT or 0630 hrs and 0930 hrs IST
We also looked at the data of how our customers are opening the emails.
Some observations from the above data
- Most days, the emails are opened between IST 0930 hrs and 1130 hrs
- Sundays have the lowest number of emails opened
- Monday mornings have the highest number of emails opened
- All the emails for Saturday night journeys that are sent on Sunday morning are either not opened or opened on Monday.
This gave us an insight into the user behavior of opening emails. So the solution to improve the open rate is to adapt to user behavior and adjust the times we send the emails. We simply changed the logic to send the emails when users were most likely to open them and hardcoded the time slots for each day of the week for sending emails like shown in the table below and made it dynamic instead of the a fixed delay after the arrival time of the passenger
An important thing to notice is that no emails were sent on Sundays after the change. For every user, a time slot was picked from the above table which is closest to their arrival time at the destination.
For example, if a passenger’s arrival time is 5AM on a Saturday morning, and the email had to be sent to the passenger on Monday (if there was no response for push notification and WhatsApp sent earlier), then the email should be sent between 9:30–10:30 AM on Monday morning.
The impact? — Increase in the open rate by 6 percentage points from an average of 7% in Dec 2020 to 13% in Jan 2021
With the overall improvement in the open rate, there was marginal improvement in the contribution of the email channel towards feedback responses as well. We saw an improvement from 4.09% to 4.9% on an average after the changes were made.
As an enhancement to this feature, the sent time can be further personalized to each passenger by capturing the email open times of each passenger. This is something we will look into and continue to work toward achieving better open rates to match the industry standards. Additionally, efforts to improve the click through rate and more direct impact on feedback responses will also be a focus area in the coming quarters.
