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Consumers have a lot of choices in the world of ecommerce, and that abundance means they bring a lot of expectations to every purchasing experience. Price alone won’t cut it anymore. People want an excellent customer experience.
Did the brand answer their questions? Help them make the right decision for their needs? Explain the options and deliver the product or service as promised? Did they make an effort to address problems with an order immediately?
Your customer care team plays a pivotal role in the customer experience. They’re the first point of contact for your customers, and how they respond — and how quickly they do so — can be your brand’s defining factor in the eyes of the consumer.
But with thousands of visitors to your site, social media pages and stores on the global marketplaces, keeping up with the daily questions and comments can be daunting to even the most diligent customer care team.
Fortunately, the world has seen significant advances in automation, many of which have been designed to offer personalization at scale.
Robust helpdesk platforms like Gorgias offer a suite of smart automations that enable customer care teams to offer better, more personalized experience in less time and with a lot less effort. Better still, by automating routine tickets, team members have the time to focus on the customers who need extra attention.
Let’s take a look.
Many customers tend to ask the same questions: Do you accept Venmo? Do you offer free returns if it doesn’t fit right? When will a product be back in stock? Where is my order?
Macros and templates allow your brand to answer these questions faster, and free your customer care team to spend with customers who need to speak or text with a live representative.
What are macros? They’re pre-written responses to commonly asked questions. When a customer inquiry comes in, its assigned a ticket number and — with the help of machine learning discussed below — the content is analyzed. If it’s a commonly asked question and appropriate macro exists, a response is sent automatically.
Macros are highly functional, and can perform any number of actions on a ticket, including:
Leverage machine learning to track intent & create personalized experiences.
In the real world, assessing a customer’s mood and intent is pretty straightforward. Facial expressions, tone of voice or body language allow a shop owner or sales clerk to distinguish people who are happily browsing from those who are at wit’s end and need immediate assistance. That’s harder — but not impossible — to do in the online world.
With a machine learning helpdesk, you can detect the sentiment of customers on behalf of your customer care team, allowing them to respond in the appropriate tone right out of the gate. A helpdesk like Gorgias can detect a range of sentiments, including:
Overall the customer is feeling positive about your brand and your products, or even your latest post on social media. To assess this sentiment, track phrases like, “oh that sounds wonderful.”
The customer gushes over your brand or product, and may even be a good candidate for a nano-influencer.
These are customers who show disappointment in your brand, its products, or what you’ve posted on social media. These are comments and posts you will want to prioritize so that you can address their concerns as quickly as possible.
Customer is clearly at wit’s end and is desperately looking for assistance. Gorgias looks for comments like, “I ordered the wrong product and need to cancel ASAP” or “You charged me twice and now I have an overdraft.”
These are just a few of the growing list of sentiments machine learning can detect.
Here’s an example of how it can work for you: if a customer is a social lead, meaning they have high intent to purchase based on their sentiment, you can automatically sort them into a social leads bucket. This way, your team knows to customize their response to one that encourages a purchase.
Gone are the days when customers contacted you via an email form or placed a call to your call center. Today’s customers are truly omnichannel, learning about new products on Instagram, direct-messaging their bank via Facebook, chatting live with a customer care rep onsite, or even requesting product information via SMS.
Keeping track of these interactions can be a challenge, and can result in multiple customer care reps responding to the same customer with the same answer.
To drive efficiency for your team, and to support your customer’s omnichannel habits, use a helpdesk that merges all interactions into a centralized location so that if a customer reaches out via live chat and social media, your customer care team members can see it’s the same customer, merge the tickets into one, and respond in the appropriate channel.
Providing hands on support is an excellent way to learn a product line, listen to customers, and respond to what they’re truly asking quickly and efficiently.
But there’s no denying that it can be a difficult job, and that difficulty prompts talented young people to view customer service as a stepping stone until something better comes along.
Automation — applying smart use cases to customer service -- can greatly ease the workload of your customer care team, freeing them up to do what they do best and enjoy most: solving problems for customers, and putting your brand in a good light. Happy team members stay longer, letting your entire company benefit from that institutional knowledge.
If you’re looking for a helpdesk that will help you drive sales and automate commonly asked questions, try Gorgias. Gorgias is a leading helpdesk for Shopify, Magento and BigCommerce merchants where retailers can manage all of their customer communication and tickets in one platform (including email, social media, SMS, live chat, and phone). It’s powered with machine learning to automate up to 25% of commonly asked questions, and seamlessly integrates into your existing tech stack to deliver better customer support.
Speak to us to find out how Linnworks can connect and automate your commerce operations so you can capture every revenue opportunity.
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