How AI Helps Ecommerce Teams Manage Spikes in Volume
If you have seasonal volume (e-commerce customer service teams: we’re talking to you), it can be difficult to offer a consistent level of service at peak times. It’s not possible to snap your fingers to grow and shrink your team at will. Hiring and training new customer service agents take time, and even if you do manage to grow your team in time for the busy season – what happens to those valued team members once the quiet season starts?
Because human power isn’t a feasible option for managing big spikes in volume, we need to look for other options. This is where artificial intelligence can lend a hand.
When quality-focused customer service teams implement a smart AI solution, they can greatly increase their capacity to deal with volume surges, without dropping their standards. AI tools don’t need breaks, they are available 24/7 and they don’t need overtime pay.
But heavy-handed automation doesn’t always make for the best customer experience. If you use AI to prevent customers from getting to a human and deprioritize giving customers a helpful resolution, quality is going to suffer. Instead, AI needs to be implemented in a way that’s thoughtful, well-designed and deeply integrated into your customer journey.
Read on to learn how AI can help your team manage spikes in volume, while still maintaining that great customer experience your brand is known for.
Find low hanging fruit for automation
Customers want fast responses. According to Salesforce research, “64% of consumers and 80% of business buyers said they expect companies to respond to and interact with them in real-time.” If the fastest way for them to get help involves artificial intelligence, they still think they are getting a great experience. It’s only when faced with a frustrating chatbot that customers are irritated by not being able to reach a human.
Finding the tasks that are suited to AI resolution is the first step to implementing a solution that works for both you and your customers. Repetitive tasks are often the most appropriate conversations to automate. Some common questions that ecommerce companies can automate are:
- Refunds and Exchanges
- WisMO or “Where is My Order?” questions
- Sizing inquiries
- Delivery updates
Almost half of customer service representatives agree that 30% of customer inquiries are repetitive and easily solved. And even more (80%) agree that at least 20% of all the questions they see are repetitive and easily solved. These inquiries are mind-numbing for your agents.
When volume spikes, most of that new volume is made up of basic, repetitive questions. You’re the expert in your team’s workload: how many incoming questions do you think could be managed by a conversational AI platform? Secondly, why are you making your customers wait for an answer from a human when automation would give them a better experience?
Once you’ve identified the types of questions that automation can resolve, it’s time to build out your workflows. Most AI platforms are limited to simply responding to customer questions with the best possible answer, developed from previous conversations or from knowledgebase articles. Automating conversation is a good first step. It looks something like this:
“Hi! Can I exchange this jacket that I bought? It’s too small.”
“Hello! I’m happy to help. We accept exchanges for 30 days after purchase as long as the tags are still attached. Did that answer your question?”
While the automation technically gave a correct answer, it’s not actually resolving the customer’s inquiry. In order to do that, the AI needs to automate processes, not just conversation.
Process automation involves integrating your AI platform with your backend systems so that the automation can take action. With access to the order system, process automations can retrieve delivery information, confirm refunds and even personalize suggestions based on previous customer behaviour.
Compare the example above with this process automation:
“Hi! Can I exchange this jacket that I bought? It’s too small.”
“Hello! I’m happy to help. Can I have your order number please?”
“Thanks! It’s #3458286.”
“Great. We have the same jacket that you bought available in a medium. Do you want us to ship it to the same address?”
“Okay, we’ve placed that order for you. Please return your previous order to 123 Brand Street, New York, NY so that we can confirm the exchange.”
The process automation workflow understands the customers’ intent, asks clarifying questions, takes the necessary action and confirms with the customer. If the issue was not resolved for whatever reason, the customer could easily be transferred to a live human for further troubleshooting.
Agent Guided Automation
Not all questions can (or should) be answered by an automation. For conversations that require that human touch, nothing beats a well-trained customer service agent.
Unfortunately, customer service teams are stretched thin already. The average customer service professional uses between 5 to 8 systems to resolve customer questions. From billing platforms to inventory management systems to CRMs, agents are constantly flipping between screens and tabs trying to find information. We call this “swivel chair” and it’s a recipe for slow response times and missing information.
For these cases, an integrated AI platform can become an agent’s best friend. On each incoming customer question, the platform can retrieve all the information needed, suggest the best answer and even perform the necessary backend tasks that the agent requires.
Agent Guided Automation might look something like this:
“My order #459872 is missing and I ordered it three weeks ago! This is unacceptable.”
[[AI detects frustrated sentiment and routes question to an agent]]
[[AI platform retrieves shipping information, customer order ID and customer history]]
“Hello! I’m so sorry to hear that, that’s not normal. I’ve had a look into our system and it shows as delivered and signed for on April 27th. Is there anyone else in your business that could have possibly received the order?”
The agent can review the information gathered by the AI, select a prewritten response composed by the AI, personalize if needed and then send to the customer. The agent has full oversight of what the customer receives, but their job is much easier.
Using Agent Guided Automation reduces average handle time, prevents agent burnout from swivel chair, and can help new agents get up to speed faster!
Use AI to Handle Volume Spikes with Confidence
Dealing with seasonal spikes in volume is one of the most challenging parts of running an e-commerce customer service team. While customers still expect an immediate response, stretching your customer service agents thin can result in quality standards being dropped.
Instead of relying on human agents, consider implementing an AI solution that can help keep responses times lightning fast, even throughout the busy season. By using process automation, teams can create workflows that deliver resolutions to customers without the need for human intervention. By providing agents with AI assistance, teams can become more productive and avoid swivel-chair burnout.
Learn more about how DigitalGenius can help your team manage seasonal volume by delivering automated resolutions, resulting in incredible customer satisfaction and operational savings.