Earlier in November, former state secretary Eva De Bleeker called on Belgium's energy providers to better support consumers, and address the overwhelmed call centers. She'd given them a week to fix the issue.
In response, most providers had gone on a short-term hiring spree to increase capacity at call centers. And while it did halve the waiting time at Elegant and Engie's call centers for instance, it's just not a viable solution long-term. A hiring frenzy only puts customer service departments further in the red in terms of ROI, further discouraging decision-makers to invest in building personal customer relationships. And that's no good in this day and age; CX is a vital success factor nowadays.
Switching to a different channel
That begs the question though, what can you do in a single week besides hiring more people? What can we leverage to unburden these call centers? To illustrate what's possible, we spent a single day designing a high-fidelity prototype. In context, this is similar to what you'd do during a week-long design sprint. An ideal format when time and market validation are of the essence.
So, we looked for digital channels we can leverage to unburden these call centers. Automate what you can, but keep a human in the loop. Hence, our first instinct went towards a WhatsApp chatbot in conjunction with a web app. A solid choice we figured, given WhatsApp's widespread usage and recently introduced Business APIs.
The use case for energy providers specifically, would be that this method of asynchronous support would enable customer support employees to become about four times as efficient. Meaning, WhatsApp would be four times less expensive than an actual phone call. On the other end, customers can be serviced in 5 minutes instead of the average 15-30 minutes spent hanging on the phone waiting.
Exploring the prototype
While customers are on hold, a pop-up appears, prompting callers to move the conversation to WhatsApp instead should they so desire. From there, a chatbot will guide callers through a conversational flow, and processing the user's queries as such.
Commonly asked questions, with regards to their increased monthly advance for instance, can be answered in-context and the user can also be redirected to the web app's FAQ section. Web apps are powerful in this scenario, given they don't require installing on the user's device but still have that native feel. Complementary to the FAQ section, users can also get a better idea of their energy consumption as a whole, and are triggered to further optimize it.
In addition, the app can also trigger the user to take action. In this case, investigating how they can optimize their energy consumption. We could achieve this by means of a simulator, which can process the effect of cost-saving measures like a heat pump or solar panels. This way, users can much more quickly estimate whether certain investments are worth it given their situation.
It bears repeating that this entire prototype only took a single day from a single UX/UI designer to create. Assisted by a strategist and copywriter, the flows came together quickly and the interfaces even faster. If this were a real client project, the prototype would also be informed by customer experts from the client's side, and we'd also run qualitative user tests using said prototype.
Testing flows as if they were real
To do this, we use Figma. Its greatest strengths come in the form of seamless, cloud-based collaboration and exhaustive prototyping features. That's right, beyond just designing, you can also stitch together screens to create shareable flows which users can try out for themselves. This also includes support for animations, videos, and more. The whole point of this, is to mimic the look and feel of a real, native app, without having to write a single line of code. Here's what that looks like for this prototype.
In other words, if you were to run a design sprint with us, you'd walk away with not only a high-fidelity prototype, but qualitative input from 5 real customers as well at the end of the week. Because that's the whole point, learning about the desirability of your idea before you start spending tens of thousands on development.
This way of working can really catapult innovation projects forward like you wouldn't believe. A small amount of work that can eventually make a big impact. It's how we de-risk projects by getting answers early.