Create Seamless Contact Center Experiences with AI Application Integrations

When customers have great experiences with agents, they don’t have an inside view of the orchestration that takes place in the background to make it so seamless. To a large extent, this is due to various types of integrations that pull data from across the organization in support of each customer inquiry. Artificial intelligence (AI) application integrations also have a role to play, especially in extracting specific data points across massive data sets and doing so in real-time.

As contact centers transition to the cloud, there are several areas where AI is poised to play a leading role, including providing seamless customer experiences (CX). This outcome is, in part, the culmination of integrations across three main levels. AI is the common thread that brings these integrations into focus for agents so they can provide great CX.

Omnichannel Data

Most organizations have each department or line of business closely manage their own data. This serves them well in terms of operational efficiency. The more strategic their information is, the better it will be for overall business success.

In today’s hypercompetitive markets, organizations need to be agile and more customer centric. The silo model isn’t well-aligned with this, and some businesses are making progress in being more open and transparent with their data. When it comes to supporting CX, there is a lot of relevant data across those silos, but very little has been tapped.

One reason is that many contact centers are more focused on internal performance than the customer. This model isn’t customer-centric enough to recognize the value of pulling data from across multiple sources. A second reason is legacy technology constraints – both within the contact center and all the proprietary platforms used for each silo. Even if various departments want to share data to support the contact center, they have limited technical capabilities to do so.

All of this plays well into the rationale for both cloud migration and AI. Cloud platforms are more open, making it much easier to share data. AI applications bring new capabilities to process large volumes of data and then extract the relevant pieces needed by agents during each customer interaction. This is central to the omnichannel value proposition, where data inputs can be pulled from across the organization – including the silos – then aggregated on a common platform, and served via the agent desktop with everything integrated in one place.

Contact Center Applications

In an omnichannel contact center, integrations within the contact center are just as important as the integrations needed from across the organization to support CX. With the legacy model of customer service, most interactions were telephony-centric, so there wasn’t much integration needed. Today, customer service is omnichannel, and that brings more challenges and opportunities for integrations.

First, there are integrations with communication channels and applications – voice, email, chat, messaging, video, co-browse, social and bots. Not only do agents need all these channels so they can engage with the customer’s preferred channel, but also across them, as many sessions end up switching or escalating from one mode to another.

But it’s not enough just to switch between channels; the content and context must go with it to make it a seamless experience and ensure agents don’t have to start over with each mode. This is where AI applications have a critical role to play, especially when going from automated self-service chatbots to live agents. Without AI, chatbots are little more than friendly IVR prompts, but they cannot integrate intelligently into the overall flow of a customer service session.

The second type of contact center integration is across the applications that support customer service, including CRMs, WFM/WEM, call routing, and IVR. Legacy contact center integrations for these applications are complex and not very flexible.

For today’s CX requirements, more integrations are needed as more applications are being used to map the customer journey and provide a seamless experience. These integrations are much easier to do in the cloud, and given the volumes of data now being managed, AI is becoming integral for leveraging the right data at the right time for each customer.

Multi-Party Customer Support

The two integrations outlined above are technology based and are essential for seamless CX. However, since customer service is still very much a human-to-human experience, there’s a third integration plane to consider. This is the human element, where multiple parties must be aligned for all forms of customer service. The most important party here is the customer, who needs to have a singular experience for CX to be great. Ideally, they should only have to deal with one agent, one-time – but through that interaction, many other human integrations need to be orchestrated.

Three in particular must be noted for providing seamless CX – agents, supervisors and IT. Customers should only ever have to deal with agents, but these other parties play a key role in supporting them. Supervisors must ensure agents are on-script and be ready to intervene in real-time when escalations arise. IT wears many hats to support the contact center, including ensuring that all relevant applications are running and that the network is secure. These can be particularly challenging for home-based agents who may not have great connectivity.

It’s important for IT leaders to recognize the role AI applications play in allowing real-time responses and the data inputs needed for the agent desktop. This could involve an alert when compliance requirements aren’t being met, a fraudulent interaction, or a supervisor patching in a subject matter expert (SME) to support the agent.

All of these require AI capabilities, but each is a distinct application that needs to be developed and integrated separately. The takeaway here is IT cannot take a one-size-fits-all approach with AI, where a single application or partner will do the job. AI-based applications can bring solid business value, but only when developed and deployed with specific use cases in mind. This may be a new way of thinking and doing things, but as digital transformation unfolds in the contact center space, these are the capabilities required for seamless CX.

Learn more about Upstream Works AI application integrations capabilities here.