We’ve all had annoyingly memorable experiences with websites — websites that invite you to subscribe to browser notifications or bombard you with pop-ups that ask for your email before you’ve even had a chance to look around. That’s no way to do customer service. Yet many brands still use these lead capture tactics, ones that often permanently turn off would-be customers.
The principle that underlies these tactics makes sense; brands want the chance to communicate with those visitors more personally on a channel like email. But a gap most brands never bridge is the one between how personal they want to get with a website visitor and how personal they are in their initial interaction with that visitor.
In my experience as a marketer, there are few better ways to bridge that gap than a thoughtful implementation of messenger tools, those chat bubbles many big brands use to offer real-time customer support.
Implementing this strategy alone has allowed me to help my clients recover millions of dollars in what would have been lost revenue — more than $5 million for a local dentistry I’ve worked with. Here’s how it works, starting with where to deploy it.
Picking candidate pages through observing user flow and bounce rates
When picking pages for where to deploy messenger tools, the one principle to keep in mind is that you don’t want to offer customer support to those who don’t need it. So every time I implement messenger tools, I think about four key customer segments:
- A recurring website visitor — potentially an existing customer.
- Website visitors who have no interest in the product or service.
- Website visitors who have feature-related questions.
- Website visitors who are on the fence about buying a product or service offering.
Sometimes it’s obvious which category a website visitor falls into; for instance, someone who clicks on your client login portal is obviously already a customer and someone who rapidly clicks off your site is obviously not interested in your offering. But for most other users, it’s a lot less clear. That’s where heat map software used in tandem with Google Analytics could be tremendously helpful in mapping user behavior to a profile.