Human beings have a love-hate relationship with automation. Some of the time we love it, and the rest of the time we absolutely hate it — without much daylight in between.
We love DVRs, learning thermostats, and Dollar Shave Club. We hate subscriptions we don’t want, memberships we don’t use, and meaningless auto-reply emails.
“This event was off the charts”
Gary Vaynerchuk was so impressed with TNW Conference 2016 he paused mid-talk to applaud us.
But if you’re looking for our most hated automated thing in the universe, that’s easy. It’s the Interactive Voice Response (IVR) system, better known as a phone tree. The biggest reason we detest them is that we typically reach them when are already frustrated, worried, or annoyed about something.
Then IVR steps in, and its slow presentation of puzzling choices invariably makes things worse.
Luckily, help is on the way.
Chatbots, the intelligent apps coming to platforms such as Facebook Messenger and WeChat, may have the potential to make our interactions with brands more meaningful and precise than ever. If implemented well, they should be able to answer a huge range of questions fast.
There is, however, a caveat: Chatbots are not exactly off to a roaring start.
A few have launched, and as one reviewer eloquently put it, “they kinda suck.”
Part of the problem is that they need time in the field to develop their intelligence. But, in truth, some brands just aren’t leveraging the right information and processes to make them work.
We already have data, so let’s use it.
Brands have website traffic tracking data, search histories, even social media listening tools, and customer support records. These data sources already help bots anticipate questions and needs.
In the beginning, you need to leverage everything you can to create better responses.
Your bot should not merely know how to answer common questions and streamline bottlenecks. It should also do so in a personalized way.
By this, I don’t mean you’ll be able to identify your customer by name or CRM entry. But at least you can use basic data you have to color your responses.
You may know where an IP address is located and ask if the person wants to switch languages. You may want to reply differently depending on whether it’s early or late in the day. A mobile device may prompt shorter answers and an offer to email a transcript to customers.
If you can personalize an interaction — even in a small way — it will make your bot feel more responsive and personalized.
Trading up to humans
While bots may one day have the potential to replace customer support and e-commerce, human touch will remain essential to the experience for the foreseeable future.
Leverage bots to handle the basics, but also create easy opportunities for customers to connect with a live human (or have one call back) if the interaction gets stalled.
We most often measure the value of customer service by surveys, which are oddly enough delivered by an IVR system (“On a scale of one to five, how would you rate your satisfaction with today’s call?”).
Bots provide a new — and much better — data set we can learn from. We should use that information to optimize interactions and rapidly identify trouble spots as soon as we can.
Selling is a tricky one.
Look for smart opportunities to cross and upsell whenever it’s welcome, or requested.
In fact, not allowing people to buy could be a bad idea if a simple purchase will fix a problem.
Artificial intelligence is only truly intelligent if it improves over time.
The brands that want to succeed in the chatbot space should not treat it as a campaign. They should develop a long-term plan with iterative cycles in which data is gathered and analyzed, new functionality proposed, and development work done.
With this approach, bots will grow into every more powerful service tools that everyone will want to use.
So let’s help put an end to the “press 1 for…” customer experience.
Handled correctly and intelligently, chatbots should be a great, long-term solution to one of the most annoying aspects of modern life.