Keith Dawson's Analyst Perspectives

Self-service has changed immensely in recent years. It has gotten better, qualitatively, in delivering answers and resolutions to customers. But it has also gotten extremely complex, relying on a basket of new technologies to achieve results. It helps to look at it through the eyes of the three main constituencies that are affected by it: customers, contact centers and the businesses they sit in.

Customers are clearly warming up to modern self-service. When all you got was an IVR or a hold queue, there was almost no value to it from the customer point of view. The limited range of things that it could resolve up to about five years ago made it the go-to customer whipping boy for as long as there has been service. But with the options expanded and “smart,” customers can use it to transact, research, purchase and effectively take control of their side of the relationship.

Contact centers are also beneficiaries. When you care about costs, and your costs are largely based on how many agents you employ, then doubling the rate of interactions handled by the automated system can potentially save a lot of money.

But it’s at the company level that things get weird. First, because when you raise the rates of interactions deflected away from agents, the business then expects the costs associated with the contact center to decline, and that decline is expected to be manifested in a reduction in headcount. But the resources required to achieve those cost reductions are significant: deflection rates are going up because artificial intelligence (AI), knowledge management and automation tools are being deployed. Those represent a cost increase for the general contact center tech stack. And until a business can fully build out those systems, populate them with appropriate information and determine how agents will interact with a differently informed set of customers, that business can’t cut costs within the center. You need to spend widely on technology and process reform before you can expect to see the benefits and then reduce costs. It’s something of a catch-22, in that you have to spend more to save more, and no one yet knows whether that’s a good deal for customer management in the long term. Contact center buyers (including IT and business teams) are growing increasingly concerned about the cost impacts of embedding AI and automation into the customer experience (CX) application stack.

One way through this trap is to see self-service as a bigger opportunity for monetizing customer engagement than most organizations realize. Even if contact center leadership sees it as an engine of deflection, others (CX teams especially) should be viewing it as a window to capture information about customers, including using it for surveys and voice-of-the-customer research, or as an engagement mechanism that allows them to put different, personalized offers and information in front of customers based on data.

In addition, when you step back from the center and look at self-service as a CX project, you can see that the same information reservoirs and systems that power front-end chatbots can also work with other customer modes that don’t, at first blush, come to mind as “self-service”—retail kiosking, for example, or web content that dynamically adjusts based on customer intent and behavior.

It is notable that a lot of these extended contexts in which customers work with self-service don’t actually look like self-service, which in the customer’s mind still means “talking to an agent.” These engagements look more like research, or shopping, or account management. Doing an automated password reset on a shopping website is certainly self-service, but it’s not the kind of self-service that annoys a customer because they can’t talk to a human.

The point here is that depending on what lens you use to look at the changes in self-service, you can perceive it as either a cost-saver, a cost-sink, an engagement opportunity or a monetization strategy, or some combination of all of those. That’s why I think companies need to look well beyond containment to understand the real benefits of self-service. Contact centers still have control over many of the specific interactions via the communications modules that agents use, but others, like marketing teams, are using and providing the information that flows through that communication, like knowledge resources in service contexts, AI platforms and data tools.

Today’s self-service is more likely to be multi-modal, longer lasting and seem less like “service” and more like a process of finding something out (pre- or post-purchase) that ultimately leads to greater engagement with the customer, including more agent involvement. That agent involvement ultimately comes at a different point in the process and requires a different skill set than a typical first-tier triage agent.

Looking again at those three constituencies that are impacted by the changing landscape, businesses should view self-service more expansively. They should lean heavily on these new communications mechanisms to increase the value of their customer relationships. The key to this is to educate customers on the value they gain from engaging with automated systems. They get faster, more accurate answers that are consistent across channels. They can take their time to ask and re-ask and explore what interests them without being exposed to the call center pressure of time and cost that forces interactions into predefined times and procedures.

Contact center leadership needs to understand the complex dependencies among previously separate types of technologies. Modern self-service depends on the careful integration of customer data, company data, transaction processing, knowledge management and conversational AI, and that counts just what is relatively new in the toolkit. Those who decide on tools for the contact center need to adjust their views: given how complex and costly AI and automation projects are, the rationale for self-service must go well beyond containment and the possibility of headcount reduction. Decisions around use cases and deployments need to build in revenue enhancement opportunities and greater access to meaningful data that can be used to predict customer behavior and guide it in the direction they choose.

This is how contact center and broader CX teams should be coming together to coordinate plans and goals. They need to bring a solid understanding of how much more expansive today’s self-service is, and how much more valuable to the organization when it is made intelligent and integrated into broader engagement processes.

Regards,

Keith Dawson