Managing the customer technology deluge

How businesses can contain the sprawl of CX technology while delivering meaningful experiences to their customers

By Ganpath Thanumoorthy, SVP Customer Experience, Firstsource

The recent flood of new customer service (CS) and customer experience (CX) technology is making it hard for business leaders and operations professionals to separate the true value-adds from the hype. If your job is to do with CS operations, you’ll have noticed one thing over the last few years, above all: an awful lot of noise when it comes to new tech.

Whether it’s the adoption of genuine omnichannel capabilities; AI-powered chatbots taking care of frequently asked questions; better natural language processing (NLP) designed to identify the customer’s issue faster; or agent-assist technology providing guidance and solutions in real time. The market is inundated with a host of new technologies and an even bigger number of vendors promising to make CS operations more efficient, and customer experiences more delightful.

Beware the hype trap

There is nothing wrong with wanting to become more customer-centric, of course. Except for one thing: that customer expectations – shaped by the CX pioneers – are putting pressure on businesses to adopt new technological capabilities fast. And that’s where many customer companies are in danger of tripping over their own feet – and potentially falling victim to the tech hype. Because with the promise of automation and streamlined operations comes risk and several unknowns: a crowded market full of similar products and vendor overclaim; the need to assess, procure, and integrate new technologies into an existing stack; the challenge of designing new customer journeys around it: all these things are costly, time-intensive, and require specialist skills. Simply adding random new tech could break operations in a big way.

But ignoring or delaying change isn’t an option either.

A considered approach to CX transformation

So, what’s a business to do if it wants to meet customer needs while preserving the integrity of its operations (and the sanity of its employees)?

Here are some tips – distilled from dozens of consulting engagements – that I hope will help business leaders in charge of CS wrangle the tech before it wrangles them.

They’re all based on the principle of “CX realism” – i.e., the belief that in order to achieve an ambitious customer service vision, it’s best to be brutally honest about the realities of your operations and business. Anticipating the obstacles that might stand in your way is the first step to overcoming them. Here’s what that means:

• Acknowledge that tech is only a means to an end. The biggest danger that comes with a tech hype is that it confuses the “nice-to-haves” and the “need-to-haves”. Every business is different, and not everything that’s new and shiny makes sense for yours. Don’t buy “AI” or “chatbot tech” because everyone else does. (chatbots, for instance, aren’t yet sophisticated enough to resolve billing queries). Be clear on what you’re trying to achieve for your customers and which bit of tech is most likely to do the job.
• Get help with tech selection. You can’t be expected to know all the new tech that’s out there and how good it is compared to the competition. It’s not realistic for you to be an analyst in addition to your day job. It’s worth appointing an independent, tech-agnostic consultancy that specialises in CS operations for the job. It can save you a lot of trouble further down the line.
• Rigorously align tech to business goals. Build a business case for each new piece of tech and hold yourself accountable to it.Prioritise the apps and systems that promise to deliver the best ROI. And even though your CFO may tell you otherwise: ROI doesn’t have to be purely financial. Net promoter score (NPS), customer retention, or first-time resolution (FTR) are valuable KPIs in CX.
• Remember that you’re working with an existing tech stack. Realistically, you’re going to be complementing it, rather than ripping everything out and replacing it. This will determine some of your tech choices – think filling the biggest gaps, think ease of integration, think continuity. (This may also mean you can’t always go with your first choice of vendor or product).
• Acknowledge that automation won’t solve all CS problems. Let’s be honest here:automation works best on standard, low-complexity customer requests. If a chatbot can take care of those for you – great! It’ll free your agents up to deal with the complex issues that need a personal touch. But if your biggest challenges lie e.g., with broken processes, you’ll need to get to the root of the problem first. Automation can help with a lot, but it can’t do miracles.
• Re-engineer your customer journeys. When your service delivery mechanisms change, you need to let your customers know. This could mean highlighting self-service options on your website, or prominently offering a chatbot in-app. CX journeys will need re-building around your new capabilities. Again, this is something that a specialist consultancy can help with. They have ways of analysing your existing CS data to determine the best channel and response for each customer and issue.
• Always test before you scale. Run a proof-of-concept before committing to any new software or system. See for yourself if it delivers on its promises. Try out new tech with a single (non-critical) process or in just one geography before you roll it out across your operation. Pro tip: when you negotiate, get vendors to contractually commit to a business outcome, not just to implementing the technology. It holds them accountable and stops them dropping the reins along the way.

What sort of return can you realistically expect?

Businesses that follow the principles above are much less likely to fall victim to tech hype. But more importantly, they can also expect to see tangible outcomes for their CX operations. As I said above, what that looks like will vary from business to business – but here are three examples of the sort of improvement that’s achievable:

• A fintech was desperate to reduce onboarding times. Its process took close to three weeks and put it in danger of losing customers to the competition. So it set about forensically analysing their current workflow (by talking to agents, customers, process owners). This project identified several inefficiencies, as well as manual and email-based steps that could be removed, or automated. Re-engineering the process, integrating third-party data sources, and making use of Intelligent Automation (IA) helped get onboarding down to four days, and save 25% of costs.

• A telco found a way to use chatbots to route standard support requests more effectively. Its new digital assistants can now handle tasks such as line number porting, amending field technician appointments, or refunding customers who cancel during a trial period. This has freed its highly trained associates to focus on more complex activities.

• A utility was keen to boost customer retention and win-back. It enlisted a consultancy to look at its historic data to predict which customers were most likely to stay on. This work helped establish a model which was then used to help associates tailor their conversation to the customer type and situation, and quickly land the most relevant arguments. The result was a 60% increase in win-backs, as well as positive feedback from associates.

In all these cases, the ultimate success was down to a considered approach that eschewed the “fashionable thing to do” in favour of a considered, tailored, test-and-learn approach with a defined and realistic goal – which I’ve found to be the best remedy for tech hype, every time.