The Multi-Channel Advantage: Meeting Customers Where They Are

Customer-facing teams know that communication is key, but that doesn’t mean it’s easy. Thoughtful communication takes attention, time, and effort. This is true whether you are talking to someone in-person or over a digital channel like email, SMS or web chat.

While technology can help scale communication over digital channels, it has to be the right kind of tech to get the results we’re all looking for.

Marketing automation platforms, for example, are great for reaching a large audience. And while traditional email campaigns and nurture programs sent through MAP can include a few elements of personalization, these types of messages are meant to inform recipients about something rather than engage them in a conversation with a brand.

Think about it: how often does a prospect or customer actually respond to a batch or nurture email?

Along the same lines, basic chatbots are often pre-programmed with FAQ-type responses, but no one mistakes them for live, two-way conversations.

It’s important to note that email and website chat are just channels, not solutions in themselves. Many companies cobble together a few of these tools to check the box saying they can reach customers via different channels, but without one overarching, connected, truly multi-channel solution in place, the conversation doesn’t get carried through from one to the other. It becomes a disjointed, frustrating experience that doesn’t serve the customer or the team.

For organizations seeking a more robust solution to engage their customers and prospects, the only solution is an all-in-one Conversational AI platform that can support two-way conversations across channels and funnel stages.

How It Works

A truly omni-channel Conversational AI platform powers conversations that can seamlessly cross from one channel to the next, keeping the context and referring back to previous interactions without the prospect or customer needing to repeat themselves. The platform powers an intelligent virtual assistant equipped with Natural Language Processing and trained to hold outcome-driven conversations that move contacts toward a revenue-generating action.

These assistants are known as Revenue Digital Assistants™ (RDAs) for their expertise in unlocking opportunity at every stage of the buyer journey. This runs the gamut from delivering a personalized first touch to incoming leads, persistently pursuing or nurturing a lead over time, autonomously identifying and elevating a Sales-ready lead at the moment they express interest, driving customer health and retaining and growing existing accounts.

In other words, RDAs help organizations manage the entire customer lifecycle through unlimited capacity for human-like conversations across digital channels. Revenue Digital Assistants Assistants can be deployed across GPT-powered webchat, SMS text messaging and email to deliver an engaging experience for customers and prospects while simultaneously driving them to the next best action.

What Multi-Channel Looks Like

Here’s what a three-channel conversation powered by an RDA looks like in practice.

A prospect named Jane lands on your website. She’s a Sales leader who’s heard about your company but isn’t sure how the products work for her area specifically. But before she can go clicking through the pages, she’s greeted by a chat message from a Revenue Digital Assistant.

Jane requests information about the value of your product for Sales. The RDA—using Natural Language Understanding (NLU) and GPT-powered Natural Language Generation (NLG)—appropriately reacts to her request with a message outlining the value of the product and offers more information.

Jane prefers to watch videos to get information, so she asks about a webinar. The RDA understands the request and remembers the context of the conversation—that this prospect is interested specifically in Sales content. So the RDA gathers contact information naturally through conversation, and then passes a link to the prospect to the right webinar. The prospect opens the link and closes the chat window.

With a standard chatbot, Jane most likely would not have been able to type her own message at the start of the conversation—she would have been offered a few options of standard messages to send that may or may not apply to her, like “Send me information about Marketing products” or “I want to schedule a demo.” She might have even been asked to enter her contact information at the very beginning of the interaction, before she knew if the product was a good fit for her needs.

And if she did persist with the chat until she got to what she was looking for, the interaction would end when she closed the window. Her email would hopefully be added to the company’s marketing database and pulled into a nurture stream, but the mass emails would not reference her previous conversation.

The Conversation Moves to Email

The Revenue Digital Assistant, however, automatically sends all the information gathered in the conversation to the CRM and then follows up with Jane immediately after the chat conversation ends. The RDA sends Jane an email with the link to the webinar to make sure she has it handy and checks if she has more questions about the Sales product.

Jane, who hadn’t finished the webinar after the chat interaction, sees the email a few hours later and remembers to go back and watch the rest. She’s impressed with what she sees and decides she wants more information, so she replies to the RDA’s message with a very specific question: “How quickly can this be deployed and what’s the price?”

The assistant recognizes that this question means that Jane is very interested in the product. The RDA replies to Jane offering to set up a meeting with a rep to give her all the information, then sends an alert to the assigned Sales rep that Jane is a hot lead.

Jane schedules the meeting with the Sales rep. A few days later, the RDA follows up via email with the prospect to make sure the Rep got in touch with her and that she’s satisfied with how her meeting went.

Jane responds, “Yes, I got what I needed. Let’s revisit this next week.”

The Revenue Digital Assistant understands the various intents and matches these intents to the best possible actions. Namely, reminding the prospect about your company at a later time. Again, this information is automatically saved into your CRM or marketing automation platform.

Switching to SMS

A week later, the Revenue Digital Assistant autonomously follows up with Jane as requested, delivering a personalized email. This time, Jane doesn’t respond.

Never discouraged, the RDA follows up a few days later. This time, Jane does respond, saying she missed the previous email because she’s traveling at the moment. “Could you text me instead?”

The RDA nimbly moves the conversation to SMS where Jane asks if the Sales rep can join the wider team for a meeting.

Roughly 48 hours after the scheduled meeting, the RDA follows up with Jane just to make sure she got everything she needed. She’s happy to report she and her team have decided to move forward with your company and look forward to onboarding as a new customer.

Building a Growth Workforce

From the first touch to conversion, the Revenue Digital Assistant delivered a powerful customer experience, consistently moved the conversation toward the next best action, and assisted the Sales team in closing a deal.

This is just one example though. Beyond versatility across channels, Revenue Digital Assistants can augment a number of revenue-generating teams including Marketing, Sales, Customer Success, Automotive Sales and Service, Student Success, Admissions and more.

By covering the entire customer lifecycle, Revenue Digital Assistants drive topline growth and accelerate revenue opportunities, all while freeing revenue teams to focus on the things they do best—building relationships, driving strategy and closing deals.