Automated check-up messages give you a constant stream of valuable information into your inbox about your users, and their behaviors. Lots of our customers send these messages because they're so powerful. Setting these up puts a process in place to ensure that you're never caught off guard by your customers' behavior, and that's really valuable. Your goal with your check-up messages is to retain the customers that you've already got.
Once these messages are sending, you can sit back and your inbox will fill up with priceless data about your customers' behaviour. And this data should feed directly into your product roadmap. Here are the 4 basic messages you should start with:
Short-term check-up message
This will target your new sign ups who are active. You want to talk to these customers to find out how their first month went, what they liked, what could've been better, and what they're hoping to see from your product in the future. It’s ideal for gauging initial reactions to your features and finding out how your onboarding experience can be improved.
Your filters here should be something like:
'Signed up more than 30 days ago’.
You also want to filter for users who ‘Signed up after <today’s date>’. This will help ensure you don’t send your message to any old or experienced users.
'Last seen less than 5 days ago.'
'Sessions is more than 10'.
It’s important to use a ‘Last contacted at’ filter like ‘Last contacted more than 5 days ago’ to avoid annoying customers with too many messages at once.
Medium-term check-up message
Sending a medium-term check-up message gives you the chance to re-connect with customers who may have slipped between the cracks. For example, it allows you to reach those customers who don’t fit certain criteria for any product feedback messages or product announcements you’ve sent in the past month or so. And you can also re-connect with customers who have given you previous feedback to see if there’s anything they've grown to dislike or love about your product.
There are two types of check-up messages we send at Intercom; a time-based medium-term check up, and a behavior-based medium-term check-up message. Let’s look at each:
General medium-term check-up message
The first is a general check-up message that helps you assess how your customers are feeling about your product overall. Rather than forcing customers to focus on one feature, this message gives people a chance to be as general or as specific with their feedback as they like.
Your filters here would be something like:
‘Signed up more than 180 days ago’.
‘Sessions is more than 250’. This filter helps you target customers who are actively using your app.
‘Last seen less than 10 days’.
Add a ‘Last contacted at’ filter like ‘Last contacted more than 15 days ago’.
Behavior-based medium-term check-up message
You can also be super targeted with your filters and target customers who have taken specific actions in your product. For example, you can get feedback from people who have used a new, important feature in your product a certain number of times.
Along with the general medium-term check-up message filters listed above, you can add a behavior-driven filter like:
‘Exported files is more than 20' or ‘Used calendar feature is more than 35’.
Important: before you can add this kind of filter, you first need to track the specific behavior (e.g. File Export’) as an Event in Intercom.
Long-term check-up message
It's important to get feedback from your customers who have stuck around for a long time. These are your long term, loyal customers - their feedback is critical for the evolution of your product. As regular users of your product, they will likely have lots of useful suggestions for improvements that will help them do their jobs better.
Your filters for a long term check-up will be something like:
'Sessions is greater than 500'.
‘Sessions is less than 600’.
Make sure they're active too by adding a filter like 'Last seen less than 7 days ago' or 'Messages sent is more than 100'.
Use a Last Contacted at filter like ‘Last contacted more than 10 days ago’.