The "Marketplaces" phenomenon enables brands to expand their sales channels beyond their e-commerce sites to an endless array of options, from generalists like Amazon or Cdiscount to specialists like La Redoute or Bébé au Naturel. Every brand sees this as an opportunity to sell more and boost revenue. Yet, this multiplication of channels creates new challenges, particularly for customer service, such as meeting the response-time requirements set by each marketplace. It also adds operational complexity, introducing new communication channels alongside traditional emails, live chats, and social media. Beyond managing multiple accounts across these disparate systems, the risk of wasted time and errors is very real.
Two key trends are currently reshaping online sales for brands: first, the opportunity to sell products and services on generic or specialized marketplaces, both in France and internationally. At the same time, customers now have more ways than ever to communicate with customer service teams, and they expect to use the channels that work best for them. Alongside classic options like phone, email, social media, and WhatsApp, marketplaces themselves, payment systems like PayPal, and customer reviews have become standard. These new customer behaviors add complexity to after-sales service management, which can offset the growth opportunities offered by new distribution channels. Some brands even end up closing overly demanding communication channels (like phone or live chat) or stop selling on certain marketplaces altogether. Since customer experience is a key differentiator for businesses, they’re constantly searching for simple, effective solutions. Here are five ways technology is helping brands that have already adopted these innovations.
The "Marketplaces" phenomenon allows brands to expand their sales channels beyond their e-commerce sites to an endless array of options, from generalists like Amazon or Cdiscount to specialists like La Redoute or Bébé au Naturel. Every brand sees this as an opportunity to sell more and boost revenue. Yet, this multiplication of channels creates new challenges, particularly for customer service, such as meeting the response-time requirements set by each marketplace. It also adds operational complexity, introducing new communication channels alongside traditional emails, live chats, and social media. Beyond managing multiple accounts across these disparate systems, the risk of wasted time and errors is very real.
Just as there are aggregators to centralize product catalogs and orders (like Lengow, Neteven, or ShoppingFeed), solutions exist to handle customer requests from all your channels in one place. Beyond simplifying the user experience and restoring efficiency, you can then let your buyers choose their preferred channels, knowing that 60% of shoppers use multiple channels.
In the vast majority of cases, a human, not a bot, handles customer requests, regardless of their origin. This often requires juggling multiple systems (messaging, back-office, CRM, marketplace software, or logistics tools) to gather the necessary information and respond. Searching, copying and pasting, switching windows: all these actions waste time and offer little value to the person performing them.
Beyond having a library of template responses, "enriching" requests with all relevant information is the best way to address efficiency challenges and enhance the work of customer service agents. With all this data available as soon as an email arrives, there’s no need to waste time hunting for information across different systems. Everything is accessible in one interface. Simplified work for a more effective customer service.
90% of customer service teams process requests in chronological order. Yet, it’s clear that a delivery modification request is more urgent than a request for an invoice. Alternatively, someone might be dedicated to reading all messages to assign priorities or identify urgent cases. The same goes for determining which agent should handle which request, for example, those who speak English or Italian, or those who handle sales issues (promo codes, site access) or delivery problems. Just like detecting urgency, this initial assignment is sometimes handled manually.
Thanks to artificial intelligence, which can detect the language of a message and understand its content ("intent"), it’s possible to prioritize messages and assign them to the right people. Some companies already use AI-powered solutions to streamline their workflows. The result? A 30% boost in productivity and no more urgent requests handled too late.
It’s a very human feeling: we’ve all experienced the frustration of repeating the same tedious, draining tasks over and over, like generating a return slip or an invoice to send to a customer. After doing this all week, errors start to creep in. When these tasks add little value (like updating the same information across multiple systems), it’s even more frustrating. What a waste of time that could be spent selling or serving an important customer.
Automating these tasks is now a reality thanks to a technique called RPA (Robotic Process Automation), which can simulate human actions. Once programmed, it can repeat tasks endlessly without human intervention. Automating these repetitive tasks frees up time for agents to focus on high-value requests. Combined with AI, it’s even possible to trigger actions based on the content of a request. For example, when a delivery address change arrives outside customer service hours, the order is automatically paused, preventing logistics from sending multiple shipments. Beyond saving time, this also cuts real financial costs for the business.
Because collecting data takes too much time, many companies have only a vague idea of their customer service activity: exact number of requests, by channel or marketplace, average response or processing time, types of requests. Without this complete picture, it’s hard to identify problems and improve them. Are there a lot of returns on a particular marketplace? Are we meeting Amazon’s response-time requirements? Why are returns increasing for incomplete packages?
Data becomes a strength and a differentiator when you know how to collect, visualize, and extract insights from it. The goal is to make informed decisions about your organization (team size, working hours, or skills) and processes. Visualization tools are accessible; the real challenge often lies in centralizing information collection to extract true operational value.
