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AI Conversational Marketing. ROI 10:1? Tell me more!

Updated: Feb 3, 2021

Huge ROI possible using AI Conversational Marketing. How a new generation of AI automation is driving sales.

By slashing HR support costs on the one hand, and boosting sales revenue on the other, there’s no doubt that the ROI from Conversational AI implementation is substantial.

But how substantial you may ask?

In this article, we dive into the return on investment you can obtain from implementing conversational marketing tactics into your business.

Conversational AI has taken off in a big way over the last few years, specifically for use in a sales and marketing capacity. This use is projected to become a $15 billion market segment by 2024, with a TAM (total addressable market) of $1 trillion according to research firm Markets and Markets. An ever-increasing number of enterprises across verticals such as BFSI, Retail, Telecom, Travel & Hospitality are adopting this use of Conversational AI.

Traditional chatbots with their static scripts and rigid flows have given way to the likes of Rayon AI’s Synthetic Service Agents that leverage the power of advanced Machine Learning (ML) and Natural Language Understanding (NLU) to accurately pinpoint customer intent and do whatever it takes to fulfil the customer’s requirement end-to-end. More than ever before, Conversational AI has the ability to truly put customers first.

Needless to say, there’s a lot of excitement about the use of Conversational AI Marketing. But excitement alone cannot justify the investment that brands need to make to implement a truly effective Conversational AI solution. Ultimately, the decision to implement a Conversational Marketing solution will depend on the difference it makes to a business’s bottom-line.

How does Conversational AI drive ROI?

Customer care is one of the key use cases for Conversational AI. A major challenge enterprises face when it comes to scaling up their customer support capacity is the high cost of recruiting, training, and maintaining large teams of customer service agents. An AI-powered Live Chat & Messaging solution can automate the resolution of routine repetitive queries and FAQs, which typically comprise 80% of incoming query volume. This means that human intervention is only required for the remaining 20% of more complex queries (and over time, the Synthetic Service Agents will learn how to resolve many of these complex queries as well!)

Essentially, Conversational AI enables a brand to exponentially scale up its customer support capacity, while keeping the headcount of their customer support team down!

Sales is another area where Conversational AI has proved to be promising. Intelligent prompts and conversational lead forms have proven to be effective in converting passive website visitors into active buyers, boosting lead conversion rates by as much as 30%. Moreover, with an AI-powered Synthetic Service Agent, a brand can simulate the behavior of an in-store sales agent — understanding customer requirements, making relevant product recommendations, increasing purchase consideration, and ultimately, driving sales and revenue.

So for an example ROI calculation here we’ll use the most simple formula and fill in the blanks.

(Additional attributed Sales + HR savings) – Conversational AI Investment


Conversational AI Investment

So let’s assume the following i) rather than adding a new sales rep to Joe’s Security Systems sales team for $45k loaded cost per annum ii) A Rayon AI Synthetic Service Agent is added to the sales team instead for a cost of $9k per annum and iii) the Synthetic Service Agent is able to add/help the existing team to add only 2 sales every month at an average sale value of $2k each.

($48,000 + $45,000) – $9,000

____________________________ = ROI of 9.3:1


Is Conversational AI suited to your industry?

When organizations are considering implementing AI in their contact center it is imperative to be clear about its purpose. Purpose affects the choice of technology and how ROI can be measured.

Below are some examples of the Conversational AI implementations:

Transactional – with the primary intent is to sell, for example, online sales.

Communicative – With the primary intent is to inform, for example, transportation organizations and the hospitality industry.

Diagnostic – With the primary intent is to identify, for example understanding medical issues or providing a customer support desk.

Educative – With the primary intent is to learn, for example creating a knowledge base where new agents can ask questions and receive responses.

To be a bona fide player in the Conversational AI space, the service provider’s underlying technology needs to demonstrate consequential use and advantageous outcomes that are related directly to the system’s overall purpose.

When you have identified the purpose of the Conversational AI in your organization, you then have the ability to measure its value.

Once you have established what the purpose is and how you are going to track the outcomes of the Conversational AI service to be deployed, you are ready to build your business case to secure your budget.

How to get started with Conversational AI or Marketing

There is no doubt that the market is still at the early adopter stage when it comes to Conversational AI but things are moving quickly and the early majority is beginning to realize that if they don’t take advantage of this fast evolving technology they risk being left behind.

Organizations should start by identifying use cases that are a good fit for Conversational AI. For example, think about your own customers or employees with regard to where conversational AI will see the best use, save the most time or provide the most convenient customer engagement. Here are a few Conversational AI use cases that can meet the following user needs:

  • Reducing friction - Use conversational AI to simplify complex workflows by turning them into a natural chat.

  • Convenience - Embrace voice to reach your users when they need to be hands-free, or engage them in a messaging app they already use.

  • Decision support - Adopt conversational AI to walk users through a decision or task that might feel overwhelming.

  • Trust - Leverage conversational AI to develop a relationship with your customers over time.

Once you’ve selected a good use case to get started, the project will always need a champion and supportive team. Then it comes down to selecting the right AI technology partner. Not all Conversational AI or service providers have what it takes under the hood to deliver the results you need for success. Even the largest players with the slickest material should be carefully vetted to make sure you’re not buying into old technology with a good paint job. Today, there are emerging new communication and NLP platforms, like Rayon AI, that make it faster and easier than ever to get up and running quickly at very low cost .

It is always recommended to implement Conversational AI with a single-use case. Be it an internal process like customer-facing Support, Sales, lead generation etc. Based on our recent market studies and experience to date below are some of the typical aspects common to successful implementations of an organization’s first conversational AI deployment .

  • A good use case was identified where the results could be measured and compared to the pre-automation situation.

  • The technology service provider was actively involved in the planning, testing, deployment and ongoing support of the service.

  • The service was a genuine learning service and evolved over time based on its experience.

  • The initial deployment was used as an example use case for others deployments across the organization.

Rayon AI was recently identified by respected Aragon Research as a Hot Vendor of Conversational AI. So if you’re looking to add digital labour to your workforce Rayon AI’s synthetic service agents are ready and waiting to help!

#chatbots #customerservice #marketingandadvertising #onlinebusinesses #customerexperience

#artificialintelligence #digitallabor #customerservice #retail #insurance #banks

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