A conversation with a (junior) colleague this morning started off with “How did you decide to reformat your Best Practices Guide?” and moved on to things like “But how did you know that you should be working in Artificial Intelligence and VUI for this search stuff? I mean, how do you know it will work?”
I couldn’t help but chuckle to myself.
“Rest assured,” I said. “Part of it is just that you know what you know. Watch your customers. Rely on your gut. But more importantly, trust the data.” The response was something of a blank stare, which was telling.
All too often, tech writers – software writers especially it seems, although I do not have the requisite studies to support that claim – are too steeped in their actual products to reach out and engage in customer usage data, to mine engagement models and determine what their users want when it comes to their doc. They are focused on things, albeit important things, like grammar, standards, style guides, and so on. This leaves little time for customer engagement, so that falls to the bottom of the “to-do” list until an NPS score shows up and that score is abysmal. By that time, if the documentation set is large (like mine) it’s time for triage. But can the doc be saved? Maybe, maybe not.
If you’re lucky like I am, you work for a company that practices Agile or SAFe and you write doc in an environment that doesn’t shunt you to the end of the development line, so you can take a crack at fixing what’s broken. (If you don’t work for a rainbow-in-the-clouds company like mine, I suggest you dust off your resume and find one. They are super fun! But, I digress.)
Back to the colleague-conversation. Here’s how I knew to reformat the BP Guide that prompted the morning conversation:
I am working toward making all of my documentation consistent through the use of templating and accompanying videos. Why? Research.
According to Forrester, 79% of customers would rather use self-service documentation than a human-assisted support channel. According to an Aspect CX survey, 33% said they would rather “clean a toilet” than wait for Support. Seriously? Clean a toilet? That means I need to have some very user-friendly, easily accessible documentation that is clear, concise, and usable. My customers do NOT want to head over to support. It makes them angry. It’s squicky. They have very strong feelings about making support calls. I am not going to send my customers to support. The Acquity group says that 72% of customers buy only from vendors that can find product (support and documentation) content online. I want my customers’ experience to be smooth and easy. Super slick.
In retail sales, we already know that the day your product is offered on Amazon is the day you are no longer relevant in the traditional market so it’s a good thing that my company sells software by subscription and not washers and dryers. Companies that do not offer subscription models or create a top-notch customer experience cease to be relevant in a very short span of time thanks to thanks to changing interfaces.
I’m working to make the current customer support channel a fully automatable target. Why? It is low-risk, high-reward, and the right technology can automate the customer support representative out of a job. That’s not cruel or awful; it’s exciting, and it opens new opportunities. Think about the channels for new positions, new functions that support engineers. If the people who used to take support cal
ls instead now focus on designing smart user decision trees based on context and process tasks as contextual language designers, it’s a win. If former support analysts are in new roles as Voice of the Customer (VoC) Analysts, think about the huge gains in customer insights because they have the distinct ability to make deep analyses into our most valuable business questions rather than tackling mundane how-to questions and daily fixes that are instead handled by the deep learning of a smart VUI. It’s not magic; it’s today. These two new job titles are just two of the AI-based fields that are conjured by Joe McKendrick in a recent Forbes article so I am not alone in this thinking by far.
His research thinking aligns with mine. And Gartner predicts that by 2020, AI will create more jobs than it eliminates.
So as I nest these Best Practices guides, as I create more integrated documentation, as I rely on both my gut and my data, I know where my documentation is headed, because I rely on data. I look to what my customers tell me. I dive into charts and graphs and points on scales. The information is there, and AI will tell me more than I ever dreamed of…if I listen closely and follow the learning path.
You see, a few weeks ago, my development team here at my office had what we all an “innovation sprint.” That is where we get to blow off some steam and quit working on our traditional run of the mill development tasks and think, instead, about the kinds of things we would do if we didn’t have customer deadlines and goals. We get to open up our imaginations and play around a bit – so what we did was to imagine what would happen if we could get something like the Amazon Echo to talk to mainframe computers and therefore get mainframe computers to talk back to the Amazon Echo – the ultimate in automation processes, as it were. Now mind you, the entire team does not have to participate. This process is totally voluntary. Team members can catch up on overdue work or sketch out other projects that they may want to work on in the future. They can conceive of ways to make their workdays easier or to otherwise improve the customer experience, that sort of thing.
Have a Pint at the Tech Pub 