The AI invasion: Breaking-in from the customer contact beachhead
In the past couple of years, contact centers have suddenly undergone an extreme character makeover, from asset-sweating tech laggard to leading light in intelligent automation. How has this corporate ugly duckling turned itself into a digital swan?
Under pressure to differentiate service offerings and add personalizaton, organizations have been quietly deploying key AI technologies – especially natural language processing (NLP), image recognition and data analysis. The contact center’s application of these general purpose AI technologies is transforming how they model and predict call volumes, enable new automated self-service channels, and evolve the role of their oft-maligned workers.
Thriving in a post-pandemic world
Fast forward to the global coronavirus pandemic, and contact centers that had pioneered the application of cloud-based AI technologies and decision tools were able to pivot at speed to benefit from the new normal, as consumers flocked online and onto their phones.
The disruption didn’t just serve to transform working realities for contact centers. Private sector and government organizations suddenly had to ramp up investment in cloud and AI technologies to upscale their operations, handle a tsunami of unanticipated workloads, and reinvent how they engaged with citizens and consumers.
As an early pioneer in the application of AI technology, much of this roll out has been modelled on the approach taken in customer contact. Let’s take a look at how some key industries responded.
Healthcare – operationalizing AI to serve a variety of needs
AI technologies were already being applied in advanced medical research to great effect. But with COVID-19, healthcare providers had to deliver connected services across the spectrum, from public health to family doctors to hospitals. At the same time, they were tasked with making critical decisions, in conjunction with government bodies, as to how best to deploy health and care resources in emerging coronavirus hotspots.
In the UK, parts of the National Health Service (NHS) took a pioneering approach in applying AI to automate call routing technology, bolstering the performance of its NHS 111 online and telephone urgent care service and responding faster and more effectively to patients seeking information about the coronavirus. The service already had the ability to track and prioritize patients with developing or known medical conditions and this now expanded to prioritize the routing of patients with complex or long-term health issues identified as most at risk of coronavirus. Directing these service users to the most appropriate professional first time, together with their relevant patient records and details, ensured these people received tailored medical advice and care from the outset.
This approach has also proved invaluable in enabling other health agencies to scale up and better target their responses to elevated service demands despite limited resources. At a macro level, the pandemic prompted the rapid deployment of AI technologies to evaluate multiple data sources. This allowed health providers to understand how the virus spreads at local level, identifying which members of the population are most at risk, and predicting how best to divert service users to the facilities best able to care for them. Crucially, all this is based on current demand, resources and staffing capacity – essential in a fast-changing environment.
Retailers – satisfying an uptick in omnichannel consumer demand
In the face of national lockdowns, shoppers had to head online to purchase non-essential items, place grocery orders and personalize how they took delivery of goods. Retailers were forced to redesign customer journeys as consumers embraced a digital-first approach en masse. For some the answer was to convert stores into virtual warehouses that could satisfy demand from consumers for a range of click-to-order personalized and safe shopping options; pick up in store, curbside pickup and home delivery.
That meant utilizing AI to integrate stock data from across their store and distribution networks to ensure they were able to optimize on-demand deliveries, minimize the risk of localized stockouts, and ensure complete harmonization between their online and physical channels.
With consumers now embracing omnichannel shopping on a massive scale, retailers are investing in advanced AI technologies to boost operational efficiencies, manage supply chain issues and initiate new engagement hubs that empower them to serve customers in multiple channels. In a Darwinian economic environment, those with the best-adapted tech are most likely to survive.
Looking to the future – adapting fast to new customer engagement preferences and expectations
The coronavirus pandemic has accelerated many of the digital CX and engagement trends that were already in motion, highlighting why operational agility is vital. The AI path carved out in the pursuit of improved customer engagement is the one that should be examined most closely by businesses in every sector.
One of the biggest learnings to emerge from our post-pandemic world is how customers are becoming more selective about which organizations they engage with, prioritizing firms that demonstrate versatility and the ability to cater to their needs, despite volatile circumstances.
A personalized and frictionless customer experience is proving to be the differentiating factor determining long term loyalty among customers. Fortunately, today’s cloud technology is proving key to enabling the scalability that organizations need to deal with rapid fluctuations in consumer demand and staffing models. It’s helping organizations transform their contact centers into sophisticated customer engagement hubs where data points taken from every market channel are integrated to deliver a 360-degree view of the customer.
For organizations that have already taken advantage of the democratization of AI made possible by cloud-based contact-center-as-a-service (CCaaS) models, the ability to apply such powerful technologies to both the customer journey and the wider organization is going to be a game changer. Within days, this can help any organization:
- Leverage all available data from across their universe to proactively engage with customers, right at their moment of need;
- Deliver highly personalized experiences that help create emotional connections which resonate with customers;
- Embrace the unexpected by enabling highly resilient operations that stay one step ahead of changing demands.
No longer just the provenance of contact centers, AI technologies are now breaking into the enterprise mainstream.