Everyone and their grandma knows customer service is important. Let’s discuss why.
Think about your online shopping experiences so far. Of all the websites you’ve purchased from, you repeatedly go back to a few and prefer to stay away from others.
The reason? Trust and loyalty built through exceptional ecommerce customer service.
77% of customers think good customer service is critical to earning brand loyalty and generating business. This makes it clear: if you want your customers to become champions for your brand, focus on gaining a competitive advantage rooted in customer service.
In this guide, we talk about how you can deliver customer service for ecommerce that differentiates you from competitors, six ecommerce customer service best practices, and key metrics to track customer service success.
Ecommerce customer service involves helping customers through and after the purchase. Buyers may have questions at multiple points throughout their buying journey — they may have questions about a product, want to know the order status, or return the product. Your job? Make them feel heard, answer their questions with transparency, and offer the best possible solution to address their concerns.
There’s a lot to gain by investing in great customer service for ecommerce. Here are some benefits to consider:
Fast response times and a responsive customer service team don’t make your customer service exceptional — they’re table stakes. Before we talk about ways to stay ahead of the curve, here are some basics you need to have in place:
To deliver truly exceptional customer service for ecommerce, you need to go beyond surface-level tactics. Let’s talk about how you can take your customer service game to the next level and leave your competitors in the digital dust.
Why is an AI agent the #1 way to deliver exceptional service?
Three words: Personalization. Speed. Scale.
50% of customers switch to a competitor after just one bad experience. This means scripted or free chatbots pose a major threat to your revenue and reputation — chatbots without machine learning capabilities and natural language processing (NLP) generate robotic and often inaccurate responses.
Suppose a frustrated customer, John, is interacting with your scripted chatbot. John shares his concerns with the chatbot. Here’s the conversation that follows:
It doesn’t take a triple-digit IQ to understand how this can fuel the customer’s frustration. That’s exactly why you need an AI agent — one that can interact with your customers just like a salesperson would in a brick-and-mortar store. Let’s see an experience your customer’s can expect after you implement Ada’s AI Agent, for example:
As AI agents become more popular, make sure you find one that can adapt your brand’s tone so your communication is always on-brand. The AI agent should also collect data when interacting with customers and use it to improve its responses over time and generate insights that help you make data-backed decisions.
Top ecommerce stores use technology to offer customer service that leaves a lasting impression. The type of technology you invest in depends on your product portfolio and operational challenges.
Take Warby Parker for example. What’s the most pressing challenge for an ecommerce store selling glasses? They can’t offer try-ons. Warby Parker addresses that challenge with virtual try-ons. Shoppers can try on glasses using the store’s Android or iOS app. The app tells you if a frame size will fit you and also recommends the best width and measures pupillary distance (PD).
Wayfair is another great example. The furniture ecommerce website offers a built-in AR Room Planner called Decorify . Shoppers can upload a picture of their living room or bedroom and ask the algorithm to create beautiful visuals that inspire shoppers when browsing Wayfair’s store.
In both cases, the customer service team can help shoppers find a product they’re looking for while giving them a preview of what those glasses or pieces of furniture, as the case may be, look like.
If you sell worldwide, multilingual support goes a long way. 70% of end customers feel more loyal to companies that provide support in their native language, and 29% of companies say they’ve lost customers because they don’t offer multilingual support. Here’s why multilingual support is a critical component of great customer service:
You can give your customer service team all the technology they need, but to deliver remarkable customer service, you need to follow best practices. Here are the six best practices your customer service team should follow:
12% of customers cite lack of speed — prompt answers and fast reaction — as the second most frustrating part of customer service. The modern customer wants your team to respond within minutes of first contact.
The best way to match your customer’s need for speed is with an AI agent that’s available 24/7 and responds in real time. But when a customer requests to speak to an agent, your agent needs to get on that call with zero waiting time.
Imagine a customer service team member blatantly denying that they messed up — makes you cringe, right?
In addition to keeping customer service cringe-free, being transparent is vital to building trust — more than 80% of customers consider trust a deciding factor when making a purchase decision. When customers ask about your processes or mistakes, keep it real and they’ll likely appreciate your honesty.
The right AI agent is coachable. You can train it to admit mistakes, use humor or compassion when responding, and align with your company’s values and principles. Of course, you can’t train an AI agent and call it a day. To make the most of your AI agent, you need a human who can coach it to near perfection.
To live up to their potential [AI] agents will all need human managers. The companies making the most out of AI right now have already grasped this fundamental principle. AI isn't just a piece of software you set and forget; it's an intelligence capable of taking feedback and learning from it.
Let’s say you have an excellent customer service team. But they don’t have an AI agent that takes care of all the repetitive queries. Traditional customer service representatives spend most of their time answering customers about order status and processing refund requests. The result? They have little to no chance to work on the strategic part of their job.
An AI agent can solve that — it can field almost all customer queries and free up your team’s time for more strategic tasks. For example, customer service employees can focus on improving conversion rates, finding bottlenecks in the customer journey, and interacting with customers to identify gaps in customer experience. Similarly, your customer service team also needs access to a CRM, invoicing software, and other apps where they might need to look for a customer’s information.
Almost every part of your ecommerce strategy relies on data, from monitoring conversions to personalizing user experiences. There are multiple ways information can flow into your dashboard — customers exploring your website, interacting with your AI agent, or adding items to cart — all help you collect customer-specific information.
But beware: your systems can house plenty of stale information. In fact, 82% of businesses use stale data from their ERP systems. That’s a recipe for disaster. Use the latest data to make decisions relevant to your business’s current condition.
When looking for insights specifically in the context of customer service, turn to your AI agent. It can tell you what problems your customers face, their most frequently asked questions, and what you should do next to improve customer experience.
Here’s another reason to add an AI agent to your tech stack: 67% of respondents prefer self-service over speaking to a rep. Advanced AI agents can field most customer queries while interacting with customers in a human-like tone.
Of course, there are more self-service options, such as a knowledge base for customer service that answers the most common customer questions. A knowledge base is an excellent resource when connected with your AI agent. When you update your knowledge base, the AI agent reads and learns from that information, allowing it to answer questions about that information moving forward.
For example, when you update your refund policy in the knowledge base, the AI agent ingests that information. It uses the updated information when customers ask questions about the refund policy in the future.
Customer service doesn’t end when the customer makes a purchase. Aim to develop stronger relationships with customers post-purchase with a thank-you email, satisfaction survey, or a discount on their next purchase. These small steps work wonders for your retention rate — one of the most powerful levers of revenue and profitability growth.
A 5% increase in customer retention can increase a company's revenue by 25% to 95%.
- HubSpot
Few levers produce results of this scale for your topline number. But there’s a challenge: you can’t build strong relationships by sending an automated email offering a discount post-purchase. Customers can sniff automated emails from miles away. And why wait until the user leaves your website and goes to their mailbox? Use an AI agent to generate a personalized response right on the checkout page to build a solid relationship with your customers.
When you’re spending a ton of money on improving customer service, how do you know if your money’s being put to good use? There are a few customer service metrics that tell how well your strategies are working and which areas need more work. Here are some metrics you can track:
Automated Resolution (AR) measures the percentage of conversations that were automatically resolved by an AI agent. To calculate AR, sum up the total conversations where the AI agent successfully delivered an automated resolution and divide it by the total conversations initiated by a customer.
For a conversation to be considered automatically resolved, it must be:
The customer satisfaction (CSAT) score is one of the most commonly used metrics out there. Though we believe there are times when it makes sense to not use CSAT , it can still provide great insights when used along with other metrics like the net promoter score (NPS) and customer effort score (CES).
CSAT is expressed as a percentage. If you ask 100 customers how satisfied they are with your customer service, and 50 of them say they’re very satisfied or satisfied (while 50 rate your service as neutral, dissatisfied, or very dissatisfied), your CSAT is 50%. CSAT is calculated as:
(# of customers satisfied / Total # of customers surveyed) * 100
The average ecommerce CSAT was 80 in 2023, but it’s hard to determine if your CSAT is impressive or abysmal. Instead of looking at the average, focus on bringing your CSAT closer to 100 from whatever it is currently.
The customer effort score (CES) measures the level of effort your customers had to put in to resolve a problem. Think of it as a scale from “piece of cake” to “pulled my hair in frustration.” A quick survey requested via an AI agent can help you collect data needed to calculate CES.
Ask the customers to rate the ease of resolving an issue on a scale of 1 to 7. Sum up all ratings and divide the total by the number of customers you surveyed to find your CES. For example, if five customers rated you 7, 7, 6, 4, and 1, respectively, your CES would be 5.
The net promoter score (NPS) measures the likelihood of a customer turning into a brand champion. If 75 out of 100 customers would recommend your brand to friends, family, and anyone who will listen, your NPS score is 75. The score ranges from -100 to 100. Anything above 0 is considered a positive sign, but you should aim to get as close to 100 as possible.
You can ask customers how likely they are to recommend your product to a friend or colleague through your AI agent after they complete a purchase. Suppose you ask 10 customers to rate the likelihood of recommending your brand on a scale of 1 to 10 and here are the results:
Your NPS score in this case is 50%, calculated as:
% of promoters - % of detractors
The average NPS for ecommerce brands is 45, but you need more context to interpret your NPS, such as your business’s stage in the lifecycle as well as previous NPS.
AI agents are a crucial part of your customer service arsenal. While an AI agent can’t take over your customer service department , it can augment your team’s ability to scale customer service as you grow and transform customer experience through personalized interactions and faster, more accurate responses — all delivered through AI.
At Ada, we’re on a mission to build the AI Agent that can resolve (nearly) every customer interaction, so you can focus on areas that require your expertise and core skill set — driving more revenue for your business.
Looking to better understand the difference between chatbots and AI Agents? Download this guide to become an expert on the topic, and discover the success criteria you should be testing to get the most ROI.
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