30 Jun
Choosing your Conversational AI Platform
With the growing popularity of conversational AI as a facilitator delivering instant, personalized, and meaningful engagement to customers and employees, the market is flooded with constantly evolving tools and solutions that make this a reality. In fact, conversational AI is expected to mature into a $1.3 billion market by 2025, with no signs of slowing down.
With much ado around AI and so many organizations embarking on their first conversational AI journey, choosing the right vendor for your needs can feel nothing less than looking for a needle in a haystack.
So, how do you select your vendor when making a foray into the world of conversational AI?
Let’s explore more.
conversational AI platform - Capabilities
Improving customer satisfaction scores and empowering employees with exceptional experiences are the ultimate motives of conversational AI. Hence, choosing capabilities that help achieve these goals is the foremost criteria to be considered when selecting your conversational AI platform.
Even though user interest in chatbots, voice bots, and other digital assistants has grown by leaps and bounds, not everyone knows how to identify and select the optimal type of conversational AI solution amongst the plethora of options in the market.
Based on immediate needs and preferred use cases, organizations may choose from a wide range of conversational AI implementation approaches in the chatbot market: custom solutions, platform offerings, and targeted service/functional offerings.
- Custom Solution: Most suitable when deep technical customizations are needed to address unique business problems, a custom approach uses a complex framework of software development kits (SDKs) to build conversational AI platforms and bot solutions.
- Specific service/functional offering: Often used to target a specific business problem or the needs of a particular service or function, such as sales enablement or IT service desk optimization, a specific service/functional offering is usually built on top of an existing enterprise application.
- Platform-based approach: With a low-code, administrator-type GUI implementation and maintenance approach, platform-based conversational AI offers ease of use and a host of chatbot-building capabilities. The best part? A platform-based approach is uniquely versatile because it provides intuitive, low-code, template-based options to build and edit chatbot applications while offering complex, custom solutions built leveraging APIs and SDKs.
Irrespective of the approach you select, here is our 101 on some of the critical capabilities that define a next-generation artificial-intelligence-based conversational platform. However, please remember that not all conversational AI projects require all the functionalities, and leaders must always consider the requirements and capabilities needed to address those.
1. Ease of use with low-code platforms
Building and deploying a conversational AI platform is only 50% of the job done. As business needs evolve, it is essential to maintain and upgrade your conversational AI platform accordingly.
Business users inside your company must have a handhold over managing and improving existing virtual agents. In line with this need, more and more vendors are offering low-code platforms that allow employees without technical skills or coding knowledge to upgrade their chatbots quickly or even build new ones.
These platforms also offer predefined templates & reusable content such as domain-specific small talk and intents that expedite the bot-building process for both pro and citizen developers alike and accelerate the time-to-market.
2. Exceptional UX
A chatbot’s UX describes its accessibility, usability, and the pleasure derived from interacting with it. While a conversational AI platform must understand and execute a user’s request with a bare number of questions asked, interactions must always feel natural and human-like.
Your chosen conversational AI platform must possess best-in-class machine learning and natural language processing (NLP) technologies, along with intent and identity-defining technologies, maintenance tools, testing and version management, channel-based personalization, dialog management, and sentiment analysis.
Moreover, not every customer may be willing to speak to a bot in matters that are highly sensitive. So, if an issue goes beyond the bot’s scope, or if the customer seems dissatisfied or irritated and willing to talk to a human agent only, the conversational AI platform must offer the option to quickly take an escalation pathway and transition the case to a human agent.
3. Omnichannel presence and multilingual proficiency
You would want to be where your customers are. Therefore, ensure your vendor supports the channels where your customer is, and their platform is capable of quickly adapting to emerging channels when need be.
A platform that builds a single chatbot optimized for multiple channels, including email, IVR, web, and messaging applications, and can optimize bots to engage with voice, text, and multimodal channels would be best suited to any organization’s needs.
Moreover, a vital capability of any conversational AI platform would be the possibility of building bots that can remember critical details from past conversations, comprehend both simple and complex conversations layered with twists, turns, and entity changes, and enable users to switch channels without losing context.
Additionally, conversational AI platforms that support multiple languages (i.e., possess multilingual capabilities) like German, French, Italian, English, etc., would allow you to expand to global markets, serve customers from different geographies, and ensure employees in all parts of the world are satisfied and highly engaged with the organization.
4. Integrations with the client’s existing tech stack
No matter what approach you choose, your conversational AI platform must support integrations with your backend and legacy systems, including ERP, CRM, billing tools, live-chat and routing applications, and helpdesks.
Not only will such integrations provide the necessary data that is the heart and soul of conversational AI, but they will also help export and import entities, pull out relevant information for the user, and build conversational flows that automate a host of simple and complex processes and workflows (robotic process automation).
5. Reporting, analytics, and security
Last but certainly not least, your chosen conversational AI platform must support GUI-type dashboards, visualizations, and programmatic capabilities that generate custom reports on the chatbot’s functioning.
To build better and more seamless experiences for both customers and employees, organizations must monitor, study, and leverage data analytics and key KPIs and metrics, including goal completion rates, customer satisfaction scores, and bounce rates.
Additionally, platform administration and privacy functions offer robust security features in terms of the ability to manage user accounts and platform access. Such functionalities enable organizations to meet compliance requirements, protect PII, and prevent data intrusion.
How can Acuvate help?
Looking for a conversational AI platform? We are here to tell you what’s best suited for your needs.
At Acuvate, we follow a platform-based approach to help clients build and deploy chat and voice bots to provide exceptional customer and employee experiences with our enterprise bot-building platform, BotCore.
As a Microsoft Gold Partner, we leverage the best of Microsoft’s AI technologies that arm bots with powerful, futuristic functionalities like Knowledge Graphs, context management, dialog builders, machine learning, and an advanced NLP engine.
What’s more, you can offer customers and employees the convenience of interacting in the language of their choice with 90+ languages.
A low-code platform, BotCore can be deployed both on-cloud and on-premise and offers integrations with 100+ enterprise systems, including Office365, PowerBI, Oracle, SAP, and many more.
To know more about BotCore, please feel free to schedule a personalized consultation with our experts.
Abhishek is the AI & Automation Practice Head at Acuvate and brings with him 17+ years of strong expertise across the Microsoft stack. He has consulted with clients globally to provide solutions on technologies such as Cognitive Services, Azure, RPA, SharePoint & Office 365. He has worked with clients across multiple industry domains including Retail & FMCG, Government, BFSI, Manufacturing and Telecom.
Abhishek Shanbhag