Trying to find some case swarming best practices? Let’s start by thinking about what your customers want.
There’s a reason 72% of customers say they prefer self-service. When done right, it gives them the answers they need, right away, without ever picking up a phone or opening a chat window with a customer support agent.
But self-service is a bit of a double-edged sword. On one side, customers generally leave satisfied, deflecting the more repetitive questions from your agents.
On the other, the cases that do make it to your agents are either ones you haven’t seen before or ones that are too complex for self-service.
That means your customer support agents have a much more difficult job to do. Customers who can’t find answers themselves are reaching out already frustrated.
With so many customers willing to jump ship after even one bad experience (a trend we’ve been seeing more of lately), the stakes are high for your agents to get things right the first time.
That’s exactly what case swarming, or an Intelligent Swarming℠ methodology, aims to address.
What is Swarming in Customer Service?
The last time you contacted support, you probably connected with a tier 1 representative. You explained your issue, and that agent bumped you up to someone in tier 2.
Great — except that you had to wait a while to connect and then explain your issue all over again. Lather, rinse and repeat until you finally get in touch with that one person who finally solved your problem in about five minutes.
Enter the Intelligent Swarming methodology. Think of it like ‘service without tiers.’ Instead, your ticket is shared with a group of agents, where it gets picked up by someone who says, “Yep, I can handle that one!”
And that one agent sticks with you through the whole process, until it’s resolved — even if they need to ask for help along the way.
Because case swarming is an opt-in process, it allows agents to opt-in to cases that spark their interest or align with their individual skills.
It also provides individual autonomy — a key ingredient of an engaged workforce. And it gives agents a way to develop within their role, as they learn from the people they collaborate with to solve each ticket.
But most importantly, it gets customer problems solved more quickly and with less friction… and leaves customers feeling so satisfied they’ll gladly come back for more.
What is Swarming in Slack?
Slack is one (and may we say highly effective) method of making the Intelligent Swarming model even smarter.
First, you can use it as a platform on which you assign tickets and for agents to connect with other teammates when they need assistance. More on that below.
Second, it’s an often-overlooked goldmine of support knowledge. Yes, there’s the “official” documentation you’ve put in place for your service agents, but what about all the relevant knowledge that’s passed between employees on chat? The stuff you may not even know exists?
Indexing Slack content and making that content available in your search means you can bring knowledge gleaned from past conversations and resolved cases to light, so your intelligent swarm can put it to good use.
Not only that, but you can surface the most relevant and current knowledge since Slack chat happens in real-time and in context. By capturing it automatically, there’s less hassle and less time wasted in the post-resolution documentation process.
How Would You Implement A Swarming Support Model?
No two organizations do an Intelligent Swarming method exactly alike, but we can provide some best practices to help you make your implementation a success.
1. Identify your support workflow
How will you manage the cases that come in once you adopt an Intelligent Swarming structure? There’s no one-size-fits-all approach, but we can outline a few options:
- Collect every ticket into a central pool and let your agents have at it, all-hands-on-deck-style. This might work well enough on small teams, but you run the risk of overwhelming your agents with a lot of noise all at once.
- Use multiple swarms based on skills and interests and feed tickets more selectively to the right groups. After all, not every team member needs to participate in every swarm.
- Let AI do the matching, so only the most suited agents receive a notification (and then it’s up to them to take it on). We’re fans of AI-powered skill-based routing because it cuts down on noise and distractions.
You’ll also need to consider your workflow around tickets that sit unattended for too long with no takers, and how you’ll expedite high-priority tickets that simply can’t wait.
2. Double-check your routing tools and processes
First things first. If you’re moving to an Intelligent Swarming model from a multi-tier support organization, you’ll need a way to assess your agents’ skill levels and interests across various products, solutions or other competencies. These are often called people profiles. Then you need to assess the case to figure out what’s required from your team.
Sure, you can do this routing manually… but there are technology solutions out there to help you along the way. CRMs, LMSs and HRMSs can help figure out who’s strong at which types of tickets, and AI-powered expert finders can help pull the right people into the swarm for quick resolution on each ticket.
3. Double-check your collaboration tools and processes
An Intelligent Swarming model depends on a self-organized team of autonomous agents who opt-in to solve customer problems. That means you need strong collaboration support set up to make sure agents have what they need to connect with each other when they need to work together on cases.
Chat applications like Slack are invaluable in this regard, as they can synchronously (or asynchronously) connect agents one-on-one.
That said, while swarming depends on collaboration, your agents shouldn’t have to collaborate too often — after all, the whole point of swarming is to connect customers with a knowledgeable agent right off the bat.
Agents will rely on collaboration to help resolve issues for which they need assistance, but that should remain the minority of cases.
4. Start small
Implementing the Intelligent Swarming methodology is, at least in part, a change management initiative. An all-or-nothing, big-bang approach may lead you to future struggles with adoption.
Agents used to working in lower tiers may feel intimidated or anxious about owning such a broad range of issues, while agents in upper tiers who feel they’ve “moved beyond” talking with customers may feel reluctant to jump back into the fray.
We recommend starting with a pilot — nothing too large, but significant enough to test and prove the benefits an Intelligent Swarming concept can have within your organization.
With a few key metrics and believers on your side, you’ll find it easier to build momentum in the future.
5. Pinpoint your metrics
The Intelligent Swarming method is about as far away as you’ll get from a tiered support approach. So it makes sense that the metrics are quite different, too.
You’ll find some overlap in KPIs like resolution times, first contact resolutions, callbacks, and customer satisfaction scores.
But in a successful swarming model, you’ll also see improvements in areas like:
- Employee participation in tickets and assistance requests
- Employee engagement and job satisfaction
- Collaboration between employees
- Organizational learning
- Employee reputation and trust
- Time to help others on the team
We could go on! But suffice to say, you’ll need to be prepared to shift how you define success with the Intelligent Swarming method compared to how you’ve done it traditionally in a tiered method.
Make The Intelligent Swarming Model Smarter with Search
Slack is one vital source of information that your support agents have at their fingertips. But it’s made exponentially more powerful when combined with other sources, like your CRM or your ERP.
Bring that real-time data all together in a unified search experience, and you’ve turned your customer support agents into superheroes.
That’s because they now have an incredible amount of knowledge at their fingertips – something that’s key in Knowledge-Centered Service.
But it doesn’t stop there, because that search can also be made more intelligent by applying another layer of intelligence on top, this time to surface just the most relevant answers for your agents based on what’s helped customers like them in the past.
Imagine searching for a product solution in your knowledge database and immediately finding the most relevant answer in a Slack chat from when someone else in the swarm handled a similar issue last week. Or last year. Or an hour ago.
With the right practices and tools in place, you can join companies like Salesforce in making an Intelligent Swarming model an innovative and powerful way to leave your customers smiling — and your agents, too.
Get a peek behind the curtain as to how combining Slack and search to craft powerful swarming sessions.
* Intelligent Swarming℠ is a service mark of the Consortium for Service Innovation™.