The type of high-touch customer support that you can offer when you sell subscription software with (reasonably) high margins is not always feasible in other situations. For example, support at the scale of Netflix or Gmail has to be done differently. They could never practically staff up to achieve the same ratio of support to customers that we can at Help Scout. The numbers would not work and the business would not be sustainable.
As volume rises and margins thin, an effective support model has to change. In the past, this has meant that contacting high-volume businesses has been almost impossible. Emails sent into a black hole of support where the crushing gravity prevents any response from escaping for days or weeks. Self-service or community-based support is the only practical option.
Does that mean their support is poor? Well…yes. Or at least, compared to what you can get when you contact Help Scout or your own support team, friend. But then, Help Scout’s support isn’t some Platonic ideal of service either. You can imagine something more expensive. Having a dedicated support staff member on call, or a person to come visit your office and work alongside you. It’s just not a reasonable option given Help Scout's financial model.
There is no perfect support model. Going all the way to the highest of high-end service, even if it were feasible, still doesn’t represent perfection. Too much service can be a problem. If you’ve ever stepped into your hotel room at the end of a long travel day, only to be forced to wait, exhausted, as a man tediously explains to you where the television is in your room; you know what I mean.
Our challenge is selecting the right level of service for the specific combination of financial model, customers, products, and environment, and then executing that service consistently at high quality.
That’s actually where I think AI-based support may have its first big wins. If you’re starting from a black-hole-of-email level of support, having an AI agent which can direct you to the right answer even 60% of the time could be a huge improvement. The average could improve greatly even if, at the top end, human support is still far more effective.
Change is coming, and change creates opportunities as well as risks. We all judge customer support through our own lenses, but trying on some other glasses from time to time can help us see things differently.
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