In the world of fashion commerce, customer service is a critical component of the overall customer experience. As brands strive to meet the growing demands of their customers, AI-powered customer service solutions have become essential. These tools help brands deliver prompt, efficient, and personalised support, enhancing customer satisfaction and loyalty.

Traditional customer service methods, such as phone and email support, often lead to long wait times and inconsistent responses. The rise of digital channels and AI technologies has transformed customer service, enabling brands to provide faster and more accurate support.

Very soon, it will not be a “competitive advantage” to offer superior customer service by employing an AI agent, it will be table stakes - and anyone not taking advantage of the efficiencies and CX which are possible with this technology will be left behind. So…

What is Artificial Intelligence?

Artificial Intelligence typically comes in three flavours:

• Conversational AI

• Visual AI

• Generative AI

Conversational AI:

Officially known as “Discriminative AI” or maybe “Traditional AI”, this is basically where a model has been trained on a specific set of data and has become very good at identifying common patterns within that data. It can then work out when a new piece of information is presented, how best to categorise and analyse that data. 

In the context of fashion commerce, imagine many of the world’s leading ecommerce brands gathering together and feeding millions of their customer service tickets to a bot, so it can look for the common “intents” and “sentiments” which are found within those customer messages… Imagine that 👀

Visual AI:

Very similar to Conversational AI, except with images instead of words! 

Visual models can be trained with images to identify commonalities and understand what’s going on when presented with new images. The easiest example to use in retail is ‘Product Defects’. When a customer receives a damaged item, the first thing Customer Service will ask for is usually an image of the product - to understand whether the damage falls into the warranty policies against the product and to ensure it isn’t a fraudulent claim.

Generative AI:

Generative AI (as the name suggests) differs from the other types of AI in that it ‘generates’ new data. The datasets used to train these models are very large and this AI has been allowed to work out all of the patterns within their training data, not just the common ones! This allows them to create new written content, new images and even new sound arrangements. 

The intensive training of these models means that they are generally not bad at digesting and categorising data too, certainly good enough to take an FAQs page and turn it into a chatbot. However, they’re still not as accurate as existing conversational models when analysing new pieces of data (like trying to work out the underlying reason why a customer has messaged you).

Key Benefits of AI-Powered Customer Service

Instantaneous Support

An improved first response time and full resolution time both lead to greater customer satisfaction, improved reviews scores and, ultimately, increased revenue.

Speed is one of the areas where AI is clearly not only on par, but vastly superior to humans. This not only answers the same problems quicker, but actually allows some problems to be resolved which would not be possible at all otherwise - for example, cancelling an order usually has a very short window of possibility which humans struggle to keep up with.

Example:

Club L London implemented a CX Automation solution to drive increased customer happiness and their TrustPilot score went from 3.9 to 4.8 in just 4 months!

24/7 Availability

Unlike human agents, AI systems are available round-the-clock, allowing customers to get help whenever they need it. This continuous availability is crucial for global brands that cater to customers in different time zones.

No sick days, no holidays, no sleep, no choosing a pension plan, no pretending to care about their daughter’s ballet class… Just pure service, all day e’ery day.

Consistency and Accuracy

One of the most underrated elements of implementing an automation solution is the consistency of the output generated by these systems. Humans are inconsistent: sometimes we’re feeling snappy or lacking patience, sometimes we’re ill or feeling forgetful - sometimes we just make a simple mistake; it’s ok to be human! 

Expecting your customer service agents to follow your Standard Operating Procedures every single time is unreasonable; expecting your AI agent to follow SOPs is anything but unreasonable.

Scalability and Peak Management

One of the most significant advantages of AI in customer service is its scalability. During peak shopping seasons, such as Black Friday and Christmas, fashion brands often experience a surge in customer inquiries with a 4x growth not being abnormal. 

Examples:

Roman Originals faced an overwhelming volume of inquiries during peak times that they struggled to manage, they couldn’t keep up with the phone calls. They hit a 63% automation rate in just 10 months after implementing a new AI automation solution - making peaks just another day in the office for the team! 

AI solutions can handle these fluctuations seamlessly, managing high volumes of inquiries without compromising on response times or quality. This scalability ensures that brands can maintain high service levels during peak periods without overburdening their human agents​​.

Happy Agents = Happy Customers

Our recent report on the mental health of customer service agents revealed that 71% of agents would prefer to handle fewer, more complex tasks. No one likes chasing shipping carriers, filling in internal documents and forms or responding to the same question 40 times a day. By eliminating the repetitive, mundane tasks from your agents’ day you can allow them to focus on the high value tasks which allow them to go above and beyond for your customers.

This reduces their likelihood to leave your business and cause you a hiring headache, reduces their likelihood of taking sick days, increases their job performance and, most importantly, allows you to make the best use of one of your most valuable resources - the knowledge and passion of your Customer Service team!

I've always maintained a healthy scepticism of Ai (as per some of my comments above). And I have been frustrated with many Ai bots. So much so that I've resorted to creating a screenshot scrapbook of me asking 'can I talk to a human please?'. There are currently 34 screen shots in the scrapbook. However, I think many of the points raised here are excellent use cases. Especially the power of letting Ai handle repetitive, low-level CS tasks. I think the brands that balance human-ness with Ai are the ones that will win, especially when it comes to CS.

The Importance of Deep Integration

Ecommerce brands often find that their customer service agents have 15-20 different tools open at any given time. The goal of an automation solution isn’t just to be fast, it’s to answer customer problems as effectively as a human agent would have. Whether it’s something as simple as retrieving tracking information from a shipping carrier, or modifying a customer’s subscription or maybe updating an ERP system… Customer service agents don’t just give answers; they take action!

Proactive Support

An exciting use of AI is being proactive in dealing with customer problems, instead of simply reactively handling inbound tickets. AI can identify potential issues, such as delays in shipping, and notify customers before they even realise there’s a problem. This proactive approach helps prevent dissatisfaction and builds trust with the brand​. This isn’t possible without deep integrations.

Internal Communication

Agents also don’t only speak with customers. Your Customer Service team is at the heart of your organisation, interacting with all of your departments to provide insights in the voice of your customer. Which shipping careers are performing best? Which products do our customers like best? Which manufacturers are causing us the most problems? 

All of these questions can be answered by your conversations with customers - AI simply helps you to listen.