The central premise of proactive support.
There’s a gap between when a customer experiences a problem and when they raise their hand to seek help and/or say there’s a problem. Proactive support is the effort to close this gap.
Proactive support improves product development by harvesting high-signal-to-noise feedback from customers — feedback that without proactive support would likely be only surfaced later, if at all.
The payoff: improved customer experience through better products and fewer frustrated users.
“Smart” support != proactive support.
Let’s engage in a thought experiment. Imagine you’re receiving emails from users that ask, “When will my drip program start?” You deduce your users are creating new lead qualification campaigns in your app, and those campaigns are triggering to start. Yet for whatever reason(s), your users are not actually seeing any kind of results. How do you help them?
One solution is to put together a chatbot that listens for several variations on the phrase “drip program start.” If users enter that phrase, they are automatically fed articles from your knowledge base that theoretically address the problem. The emails you were receiving reduce in frequency, so the chatbot solution appears to be working.
This “smart” support solution was easy to implement and relatively elegant: if [x] happens, then do [y].
Except maybe everything is not so great. For one, it puts the burden of solving the problem on the customer — the very customer who justifiably-if-not-rightfully thinks the problem is with the product. What more, you’ve sent them to your knowledge base, a place many customers liken to purgatory.
Pray your users don’t get stuck there forever.
Speaking of forever, this intelligent, chatbot-based solution will have to run indefinitely. It doesn’t strike the root of the problem.
We give this a 3/10 for proactive support.
The second option is to take these signals and dive into your campaign tool and figure out if there’s a way to make the experience more intuitive. Help users understand if a campaign has started or if there’s been an error. Through putting in the extra work, the experience is improved for all users and the reported problem ceases to exist.
This is closer to proactive support — 6/10.
This is also more like how proactive support is done today. There’s a third possibility.
What proactive support looks like to users.
Let’s try a new thought experiment. Imagine you’re a customer using a product you love. Something isn’t working. You struggle against what seems to be an error before moving on. You decide to try again later.
Later comes and you return to the product. This time, you try again and — wait a second — the problem you ran into before is gone. Something has been fixed.
You, the user, go your merry way, forgetting the problem entirely, blissfully ignorant that you were the recipient of proactive support.
The third option — 10/10 proactive support.
The third option is to get out in front of user problems before they are reported, find those problems proactively, and fix the problems for customers without them asking.
That’s 10/10 proactive support.
If that sounds hard, it’s because given the tools available today, it is hard. Successfully executing proactive support is hard because discovering problems that aren’t reported is next level.
To pull it off, you need ways to find customer pain without them saying a thing. You need tools that surface the quantitative and qualitative aspects of the customer experience — without customers having to jump up and down and do a bunch of hand-waving.
Do tools like the ones needed for proactive support even exist?
The impossible (?) omniscience of proactive support.
In thinking about the future, the late science-fiction writer Arthur C. Clarke penned three laws, the second of which is:
The only way of discovering the limits of the possible is to venture a little way past them into the impossible.
Imagining future tools — the kind you need for proactive support — requires us to think beyond present-day limitations and toward future possibilities.
The problem is clear: how do you know when a customer is having an issue with your product without them telling you?
- Such a feat would require intimate knowledge of the sum total of specific customer experiences with your product for each and every customer your have.
- Once you had all that data, you’d need a way to mine it to identify and isolate the customers who show signs of distress. (Smartly surfacing signs of distress without requiring the customer to take explicit actions i.e. contact support.)
If the above reads a bit like having powers of omniscience—that is, impossible — it just means we’re on the right track. We’re imagining the future.
The FullStory of Customer Experience.
What we’re describing — customer experience omniscience — may just not have been possible yet, but FullStory is building a platform that gets us closer.
That’s because we start with something that is possible: we capture the entirety of user interactions with a website or web app, index it based on events, and make those events discover-able through search.
The second step for proactive support — it’s a doozy — is taking all that information and finding the distress signals of consumers. And we’re just starting to tackle it. Consider that you can use FullStory today to:
- surface error messages that users see but don’t report,
- search your user sessions for rage clicks — where users are furiously “punching” the elements of your website with their cursor, and
- intelligently surface dead clicks and error clicks.
The above is just the beginning. Imagine if we used machine learning to mine customer experiences for distress signals. There are many, many more possibilities we’ve only begun to explore. Yet even with our meager beginnings, we’re already hearing feedback that tells us we’re on the right track:
What if you never again had to ask yours users to explain a problem they encountered? @fullstory feels like magic.— Wes Winham (@weswinham) October 5, 2016
Magic. That’s what we’re really talking about. And that takes us to Clarke’s better known third law:
Any sufficiently advanced technology is indistinguishable from magic.
Proactive support tools are a bit like magic.
Fantastic products require better tools.
Feedback may be a gift, but customer feedback has a price. Proactive support gets more of the feedback businesses need without asking customers to pay up their frustrations.
Pulling off proactive support will take hard work behind the scenes. But hard work is what it takes to create incredible customer experiences.
Let’s turn the impossible into possible. To the future!
This is the conclusion of our three-part series on Proactive Support.