Winning customer experiences must be created around the customer’s desired outcomes first versus those of the organization they’re doing business with – in other words, insight-based customer experience. Insight-based customer experience is all about taking actionable information you have on a customer and refining your infrastructure around what they want and what’s most valuable to them. 

It’s a simple concept in theory, but it requires companies to reset their culture and restructure their operations to focus on a truly customer-centric approach. Doing so creates the ultimate win-win; it keeps customers happy and likely to repeat business while improving key performance indicators (KPIs) like customer effort, first- contact resolution (FCR), and time to resolution (TTR). Here’s how organizations can start competing on insight-based customer experience.

You must focus on what the customer wants, not what you think they’ll want – or worse, only what benefits you

We see this a lot in the contact center, which many organizations still consider a cost center versus a value center. Think about your last experience calling a company’s customer service number when you had a time sensitive request. While you called to speak with an expert, chances are you immediately encountered some sort of interactive voice response (IVR) system that asked you to press a number on your dial pad or to speak your request. Is this what you wanted? Considering most voice interactions today are reserved for more complicated requests – ones that most IVR solutions are not yet sophisticated enough to process – probably not. 

If you were handling a more basic task like bill pay or a password reset perhaps automated assistants make sense, but when your issue is time sensitive, important, and/or complicated you want to speak to an expert. Instead, you go ‘round and ‘round with the IVR until you finally get so frustrated you start yelling “receptionist!” or repeatedly press zero. If you’re not allowed to skip the IVR, the experience gets worse. 

From the organization’s perspective, they have implemented a cool, new, modern virtual agent solution that checks all the technology buzzwords like Natural Language Processing (NPL), Artificial Intelligence (AI), and Machine Learning (ML)– why aren’t customers excited about it, let alone using it? The incentive to invest wasn’t based on what businesses think the customer wants, but rather because the business wants the customer to use it to achieve their desired business outcomes (i.e., lower costs through minimized human interaction). Remember, you only get one chance at a first impression. From the customer’s perspective, the adage of “fool me once, shame on you, fool me twice, shame on me” comes into play when you try to get them to use this all-new virtual agent. 

At some point in the past, you’ve probably told your customers to “please listen to this menu as the prompts have changed”, your customer listened to the prompts, and nothing changed. Now when they hear this new virtual agent ask why they’re calling, they likely feel like this is a “gotcha” moment. They fear jumping through hoops without any guarantee of a resolution…because remember, they called to speak to an expert, not conduct transactional business. 

In the end, this will hurt customer effort and still require companies to use human resources to assist – now with the customer being frustrated or upset. 

You must apply social engineering, not technical engineering 

As opposed to technical engineering – this goes here, that goes there – social engineering focuses on what’s most likely to get usage of a platform to grow. This requires companies to analyze data that’s harvested in a customer’s service journey with the purpose of gaining actionable insights that can be used to evolve and optimize infrastructure, which is not the norm in today’s customer engagement world: data harvested and analytics used to measure performance is focused on lowering costs and keeping customers away from live agents, the most expensive, and important, element of any customer engagement. Running with our virtual agent example, an organization could see an uptake in its contact center virtual agent if it puts the customer first by learning what’s most valuable to them. 

Imagine instead of forcing customers to go down the automation rabbit hole if the VA solution greeted the customer by saying “Hi, I’m the virtual assist from XYZ company. Your place in the queue is secured and you have XX people ahead of you. Is there anything I can help you with while you’re waiting in line?” At this point you’ve acknowledged the customer’s purpose for calling, being placed in queue, and they’re likely more willing to try it out while they wait since there’s no risk to their goals, only potential rewards. 

To compound the benefit, and increase adoption of automation, if the virtual agent is built to collect helpful information about the customer – for example, automatically verifying them and gaining context around their request or issue – that can be passed to the agent so when the customer is connected the two can get right down to business. With this methodology we see automation being structured in a way to assist with the customer’s objective, not to divert to things that only matter to the company. The customer gets answers faster, and the company gets what it wants too: lower costs, faster first call resolution, and increased Net Promoter Scores. If you apply social engineering to your investments, solution usage will go through the roof – guaranteed. 

You need to get over the trust-fall barrier

If you’re going to tout investments that will blow your customers’ minds, how confident are you in customer adoption? If you invest in automation and, for example, put a dedicated phone number for the solution so customers can call it directly with strong marketing (“Call our speech agent at this number 24×7; you’re going to love it!”) would it get used? If you’re not confident that the answer to that question is yes, I’d suggest the strategy may be flawed.

Great technologies don’t’ need “gotcha” tactics. Transparency and trust are key for succeeding with insight-based customer experience. 

Ask yourself: are your infrastructure and metrics designed around your business, or your customers? If you’re putting solutions in front of your customers as a speed bump, they’re going to drive right over it. 

Resource: Adapted from Internet