Your customers are used to immediate service. They order their favorite pizza with just a tap in an app, and binge their favorite shows their living rooms on their streaming service of choice. (Sounds like a great evening to us, don’t get us wrong!)

Those same customers expect the service they receive from your agents to be just as easy and seamless. Ninety-six percent say a negative customer experience would affect their decision to purchase from that company in the future.

IVR systems, self-service channels, and chatbots are part of the equation to delivering service that gets things right — fast. But those tools cut both ways… because by the time a customer lands on the line with one of your agents, they’ve already tried every other option to no avail. They’re frustrated, and it’s up to your agents to sort things out — again, fast.

And those agents are likely feeling frustrated, too. Their whole day is filled with more challenging cases since the easy stuff is already covered. Implementing stronger self-service options can take off some of the load, but you still need to grapple with the fact that the calls that do come in will always be the most difficult ones (with the crankiest customers) to handle.

With that in mind, the question becomes how do you best support them: with the traditional tiered support model, or by introducing case swarming?

Tiered Support: Playing Ping Pong

In a tiered support model, cases are moved from generalist agents to specialist agents in increasing steps.

It works like this: customers calling for help are ushered to a tier 1 agent who handles most of the known, most common issues. If tier 1 can’t resolve the problem, the case gets escalated to the next level of specialist who has more expertise to offer.

Step by step, customers rise through the ranks of knowledge and skill until they get the answer they need. In most organizations, the levels cap at three or four, though five-tier structures aren’t unheard of.

Pre-self-service and pre-on-demand everything, it worked. Generally speaking, most questions were basic ones that the initial agent could answer, and the upper-tier agents were fed only the new or complex cases. The majority of customers left satisfied after one call, with only a handful needing a bump up the ladder.

And Then Everything Changed

With self-service and other technology like IVR and chatbots deflecting many of those basic calls, tiered support falls apart.

Because the easy stuff’s been answered already, more customers need to move beyond tier 1 and get bounced up the chain. With all the shunting between tiers, customers end up frustrated with the process. Escalation is time-consuming, and it requires customers to repeat their story over and over again, with each new agent they reach.

Add to that, some of those customers would rather not be speaking with a customer support agent to begin with. While talking directly with a human being is a preferred method for some customers (52% of baby boomers say they’ll drop a brand if they can’t speak to a person to solve an issue), 40% of Gen Z say they will abandon a brand if they can’t resolve an issue on their own.

A graphic shows how different demographics want service delivered in different ways

Your support staff feels the pain, too. Tier 1 agents do little more than ask the same repetitive questions and forward calls up the chain — without ever learning the outcome or how to resolve them themselves. Higher tiers end up feeling overwhelmed with higher volumes than expected. Agents in lower tiers don’t get much opportunity to develop their skills or learn new ones via training.

That’s a major blow when it comes to employee satisfaction… because when employee satisfaction falls, so too does customer satisfaction.

Case Swarming: Playing Catch

Case swarming, or an Intelligent Swarming℠ model, disrupts this three-plus decade legacy of customer service practice — with good reason.

Pared down to its core, an Intelligent Swarming model (or case swarming) is a tier-less service structure where customer support tickets are pooled and agents pick the ones they’re best suited to handle. Agents who opt in then own the case until resolution, using two options:

  • Using their own skills or expertise to find an answer, or 
  • Collaborating with experts across your organization when they need assistance.

Go even further, and you’ll find service organizations using intelligent, AI-powered matching to pair individual cases with a swarm of agents who are most likely to have the interest, skills, or knowledge necessary to solve them.

It’s a perfect approach for those increasingly complex cases because it considers the talents of your service team. It also enables collaboration with other agents and subject matter experts, across areas like finance, product, operations, sales, legal and more.

No longer are agents compartmentalized, where those at the top of the hierarchy feel they’ve moved beyond customer interactions. No longer is knowledge hoarded away in departmental silos, unavailable to other agents who want to grow in their roles or for future self-service content. Agents have more… well… agency over their roles. Case swarming lets them choose what challenges they’d like to tackle, what they’d like to learn more about, and how they’d like to grow within the organization.

Customers win, too, because they don’t bounce around between agents. With agents self-identifying which cases they take, customers interact with just one agent — and are more likely to get an answer the first time, without all the waiting, queueing, and bouncing.

It’s no wonder companies like Salesforce are adopting (and sticking) with case swarming over tiered support. The Technology and Services Industry Association (TSIA) reports that 30% of its members currently use case swarming, a number that’s grown more than 8% in the past year.

And It’s Gaining Ground

Fifteen years ago, customer service simply wasn’t backed by the kinds of tools we have available today. But with service innovation around advanced collaboration and AI, service is shifting quickly. Particularly when it comes to cracking that difficult nut: delivering quality service at scale, the way customers want it, without wasting their time.

Let’s illustrate that in the context of Knowledge-Centered Service, or KCS.

In a tiered support model, all that juicy knowledge about complex cases and never-been-seen-before issues gets locked away in silos. And in a silo, it may never be captured and used to improve your self-service content or internal knowledge database. If you don’t have a way to surface those solutions, they’ll never serve your agents in the future when the same issue pops up again.

Beefing up your self-service channels to deal with the increase in upper-tier cases isn’t in the cards, either. If you aren’t connecting all of your relevant data — including case information and resolutions — you’ll struggle to identify where your team members need a boost, much less provide content that’ll help customers solve their own issues.

A graphic illustrates how behavioral analytics fits into a larger picture of providing relevance on an individual level and at scale

On the other hand, within an Intelligent Swarming model, Slack and search make for a powerful duo that allows for the creation and maintenance of organizational knowledge. Here’s how they work together to make customer service more effective:

  • Slack connects agents with expertise from around your organization. When agents need assistance with customer issues, they have immediate access to the people with the right knowledge. A quick back-and-forth later, and the agent has the answer they need.
  • AI-powered search then indexes those conversations, so the next agent who looks up that issue on your knowledge database can access that conversation and get their answer right away. Not only that, but connecting information about resolved issues from Slack with your knowledge database can help you build stronger self-service content.

No black holes of knowledge. No frustrated customer support agents. And no (well, fewer) cranky customers.

Get the scoop on Slack SwarmingEbook: Combining Slack & AI-powered Search for Intelligent Swarming

Is There a Happy Medium with Case Swarming vs Tiered Support?

Short answer: Yes, but…

A hybrid support organization works like this: a traditional tier 1 agent takes the initial call, and if it’s a basic question, it gets answered right away. 

If not, that agent gathers information and then routes the case through to a swarm and then acts as a middle person between the customer and the swarmers. There’s still friction, but it’s less than you’d get in a fully tiered system.

But that doesn’t solve the issues of satisfaction or speed. Customers are still left waiting for answers, and tier 1 agents are still limited to repetitive work with few professional development opportunities.

Basic case swarming alone isn’t the answer, either. Tossing every customer case willy-nilly into a generalized pool and expecting agents to pick and choose from the chaos? A rather noisy approach.

To be truly effective, your swarming model needs to be intelligent. That means it’s backed by technology like:

  • Swarmer identification and intelligent case assignment that understands who your agents are, what the customer issue is, and funnels cases through to only the support agent whose profiles are best fit to answer
  • Knowledge management that wraps around all of your most valuable troves of knowledge, including real-time conversations on platforms like Slack
  • Unified search that surfaces only the most relevant information to your customers when they’re looking to self-serve — and to your agents when they’re checking their knowledge database

The Intelligent Swarming methodology, while certainly innovative and effective, isn’t a cure-all. It also isn’t perfect for every company and every situation. Making the move from a tiered support model to an intelligent swarm requires quite a shift in terms of company culture, workflow, processes, technology and more. 

But when your customers can access the support they need with the same effort that it takes to choose a movie to watch, you’ll see the benefits first-hand.

Learn more about the impact AI search can have on your customer serviceCoveo AI lifts CSAT as customers & ​agents find what ​they need

Dig Deeper

Looking for ways to offer better self service? Check out our research-backed tips for building an effective case submission process, one that bakes in case deflection.

And if your company uses Slack, you should think about looking into indexing all of that valuable (or at least hilarious) conversational content.

*Intelligent Swarming℠ is a service mark of the Consortium for Service Innovation™.


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About Jackelyn Gill

Jackelyn Gill is a tech storyteller at heart. As a journalist and writer, she’s curious about pretty much everything that crosses her path… and as a marketer, she loves sharing it with everyone who reads her words.

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