Case Study

How Intelligent Customer Service can Help You Drive Loyalty, ROI, and Revenue

A guest article by Reamaze, a customer communications platform designed to help eCommerce businesses support, engage, and convert customers. Reamaze helps businesses consolidate multiple channels such as chat, social media, mobile SMS/MMS, FAQ, email, and engagement automation with advanced data integrations to help teams amaze customers.

Customer service is still very much an untapped resource for eCommerce businesses when it comes to aligning and integrating with other business operations such as sales and marketing. Since customers are literally everywhere, how can eCommerce businesses take advantage of existing communications tools in order to deliver a customer service experience that’s cohesive with pre/post sales and marketing efforts?

The question ultimately comes down to this: What’s the most efficient way to help new customers love your brand and existing customers purchase more? Attracting new customers is not only time intensive but also resource intensive. Time spent on optimizing SEO, analyzing Facebook ad audiences, A/B testing store images, tailoring checkout flows, and fine tuning email marketing campaigns already address that question but rarely do they “close-the-loop” and rarely do they provide real ROI unless followed up by action. What happens when a new customer discovers your store? What do customers experience when they need help? And how do existing customer stay in touch with you about future needs, product updates, or promotions?

One way eCommerce businesses can “close-the-loop” is to adopt a multi-channel approach when it comes to customer service and leverage data with automation to help serve and service more contextual conversations with customers. While this all sounds like a lot, taking a step-wise approach to implementing a smart customer service workflow at the team level will make the process much easier.

Collecting Data for Conversations

The main goal for any multichannel customer communications setup is to have conversations with customers at the right time, in the right place, and about the most relevant issues. This starts with access to data and channels. Customer data can be collected in many different ways. Some are built-in and/or collected manually within the helpdesk environment (via chat, social media, mobile SMS, and email), some come from native integrations between, for example, the helpdesk of your choice and the eCommerce platform you’re using, and some come from data feeds implemented via API.

To expand the possibilities of “closing-the-loop”, it’s best for eCommerce businesses to consider using most, if not all, of these data sources. Adequate data enables you to describe customers. A highly descriptive profile will help your team respond to customers more intelligently and more accurately. In addition, good data will allow you to explore more advanced processes such as automation, syncing customer service data to external CRM platforms and analytics platforms natively or via 3rd party applications like Zapier, as well as empowering sales and marketing teams.

Using Data for Automation

Helpdesk has evolved beyond its origins as simply a way to respond to customer questions. With more channels than ever before it’s important for modern teams to leverage automation as much as possible without sacrificing the human element of customer service. There are three general categories for automating customer service:

1. Repetition based automation:

Repetition based automation can help your team respond to common questions quickly and accurately through automatic commands based on triggering events. For example:

  • IF [customer inquiry is about shipping] AND [conversation channel is Twitter or Email] THEN [respond with the following] AND [mark conversation as resolved] AND [assign conversation to John Smith]

2. Priority based automation:

Priority based automation can help your team address urgent conversations from priority customers. This use case can go beyond customer service and become a valuable asset for sales teams or marketing teams. For example:

  • IF [customer data attribute is VIP] AND [customer email address contains] AND [Shopify data is ORDERS > 10] THEN [tag conversation with URGENT] AND [assign to Chris Smith] AND [respond with the following]

3. Proactive automation:

Proactive automation helps put your customer service team on the offensive. Rather than waiting for inbound customer inquiries, proactive engagement effectively unifies your sales, marketing, and service staff into a cohesive unit to efficiently drive sales, boost conversions, and promote relevant content. For example:

  • IF [customer is on page for > 30 seconds] AND [this is the customer’s 2nd visit] AND [referring URL is Facebook campaign] OR [if customer is about to leave site] THEN [send cart discount 20%] AND [assign to Jacqueline Smith] AND [invite them to chat]

Automation does not have to mean “robot-ification” and proactive customer engagement does not have to mean hiring 5 more support agents. These automation examples are use cases where data plays a pivotal role in making a modern helpdesk work for you rather than simply being a tool. Customer service is becoming a core function in businesses that value intelligence, data, and workflows. Injecting data and automation into customer service drives greater marketing and sales ROI at the end of the funnel in an immensely measurable way. Common questions are handled faster. Important repeat buyers are met with prompt and accurate touch points. New customers are converted with friendly and timely engagement messages.

In this auto engagement message below, a wide range of data is required such as a number of visits, items in cart and checkout ID, customer data, associated coupon, and chat history. Having data on hand allows your team to create custom experiences like this one.

Delivering a Great Experience

Data and automation is great for your team and business but what does all of this have to do with customers? Outside of improved response times and accuracy, customers also value access and ease of use. Legacy help desk platforms that rely on features like ticket numbers and customer service logins do so for the sake of “sophistication” and as a means to reduce customer service burden (resources and cost) on teams.

A truly great business will understand the value of talking to customers as much as possible. Making it easier for customers and encouraging them to contact you takes courage and a systematic understanding of what human customer service should be. Human customer service is defined not only by a well-informed system of processes, workflows, and tools but also by culture and people.

Customers can only experience great service if you believe in the concept that customer happiness, loyalty, and lifetime value are interrelated units in a revenue generating machine. Great customer experiences don’t need to be complex either. There are simple things you can do to start driving immediate happiness.

  • Be transparent to customers and give your customer service an identity.
  • Allow everyone in your company to interact with customers so they understand the value they provide at ground-zero.
  • Humanize your customer service tools by removing barriers to entry. Stop hiding behind logins, bots, and tools that benefit only your team.
  • Adopt tools that encourage interaction and not the opposite.
  • Reward your customer service team in ways similar to sales or marketing to express your confidence in a customer-centric culture.

Reamaze was founded on the philosophy that better conversations create happier customers. In addition to having multi-channel support via chat, email, social media, mobile SMS, engagement automation, and CRM, the platform is designed to help teams operationalize data and workflows. Everything is designed with both the customer and the agent in mind. No customer logins, no complex ticketing system, and minimal setup. We believe awesome customer service is an extension of your ability to strike up meaningful conversations.

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