Real-time marketing is a very powerful and effective way to engage your customers.  By understanding what they are doing and responding with an appropriate message, based on their behavior, you can intervene and save an at-risk customer.  In this article, I want to share with you two real-life examples where real-time marketing reduced churn.

The first example will be from one of our customers, SitterCity.  The second example will be one of Evergage’s very own success stories (we don’t just talk about real-time marketing, we also eat our own dog food).

Automater Intervention at SitterCity is a website and community where babysitters can network with parents that need someone to babysit their children. They sell a subscription-based service for parents in exchange for the convenience of always being able to find an experienced and trusted babysitter for their children.

SitterCity has a large nationwide customer base and because of this size, and their desire to keep the subscription service low cost and easily affordable, they have to be careful how much money they invest in customer success per customer.  If they spend too much this will negatively impact the profitability of their business. If they invest too little, they could potentially loose customers, increasing churn and hurting LTV (Life-Time Value) of their customers.

This is a perfect environment for real-time marketing as they can now communicate on a 1:1 basis with their customer base without investing in the head count to do so.  By setting up a few rules to auto segment users based on behavior, a single person can effectively communicate, on a personal level, with 10’s of thousands of customers (or more!).

In this example, SitterCity wanted to experiment with a campaign that would appear only to customers who indicated an interest in canceling. By identifying these users, they were able to track when someone hit the ‘cancel’ button.  Once a customer hits that button, they were taken to the cancelation page where an Evergage message popped up with an offer to convince them to remain a customer.  Through a simple automated intervention message, SitterCity successfully engaged and saved customers.

The above example is a great use case of capitalizing on low hanging fruit.  By simply testing out different messages as soon as someone hits cancel, you can learn what works and doesn’t work in order to save customers.  However you don’t need to stop there and limit yourself to experimenting with different pitches or offers to save customers.  Here are a few ways to take this campaign to the next level:

Change Message Based On Behavior – when you monitor user behavior, you can learn a lot about their interests.  For example, if SitterCity bucketed parents by persona (such as someone who likes to get babysitters at the last minute vs. someone who plans ahead) they could deliver a targeted message to each persona.

Be More Proactive – When you notice a user’s engagement is falling off, don’t wait for them to cancel, reach out now.  For example, if a parent used SitterCity to hire babysitters early on but then didn’t hire another for several months, on their next log in, engage them – you could make an exploding offer and add urgency for them to use your product again; or survey them to make sure they’re satisfied with the survey (or when they plan to hire another babysitter again, etc.)

Saving Customers That Claim, "We Don't Use Your Product"

The above example was all about delivering a campaign in-app.  While effective, you’re not going to save everyone that way.  What about the customers that ignore the offer?  Or what if you’re a B2B to company with high value accounts – maybe an in-app offer isn’t the right approach.  In these situations it can be important to actually speak directly with the customer in order to save them.

So, how does real-time marketing help in these situations since you’re not delivering behavior-based campaigns?  Well while you’re not delivering a campaign, you are still collecting information on the user and can use that to effectively engage them on the phone.

For example, about a month ago at Evergage, we received an email from a customer seeking to cancel their account.  When we followed up, the customer simply responded with ‘I don’t use your product.’  If you work in customer success, you’ve probably run into similar situations where a customer wants to cancel your service, but they don’t really want to get into the details. They simply say they don’t use your product and expect that to be enough.

What we did is take a look at the behavior we collected for this user over the past few months and we saw that they have indeed been accessing Evergage.  So I reached out to them and essentially said, ‘We hear what you’re saying about not using Evergage, but we don’t understand it as we can see you’ve logged in frequently,’ and I attached a screen shot of their usage.

That same day, the customer came back with the real frustration, which turned out to be a simple miscommunication around some features of our campaigns.  So, we quickly resolved the issue and that customer decided that they didn’t want to cancel.

Therefore, by accessing the customer’s behavior patterns, Evergage was able to intelligently engage the customer and learn the real source of their pain, even though they were reluctant to share it.  Combine this with the ability to automate interventions like SitterCity did and you’ll be able to pro-actively engage at-risk and churning customers and save them.