White Paper
3 Ways AI Can Boost Conversational Intelligence Across Your Enterprise
Artificial Intelligence can both help and scale human effort in building the conversational intelligence across the enterprise that drives successful business outcomes. In this eBook, we will explore three common use cases of AI applied to customer conversations:- Contact center insights - to drive improved customer interactions and call center efficiencies
- Social media insights - to bring stronger brand awareness and competitive advantage
- Conversational compliance - to ensure better compliance to company, industry, and government regulation
What can AI do for my organization?
The human capacity to discover and innovate is what shapes the power of AI as it emerges into its greatest potential within mainstream use. The biggest questions that face organizations now are, Where can I use AI most effectively, with the highest chance of success and the least amount of risk? Will AI be difficult to develop, refine, and maintain? Will it be accepted within the ranks of my organization? These are all valid concerns, which is why the most successful AI initiatives are those that can be built quickly, scale in production, and demonstrate a clear, demonstrable ROI, while taking humans from being “in the loop” 100% of the time to being “on the loop” where AI works side by side with humans to produce optimal results. Human in the Loop Human involvement is required for the process to occur. No digital workers are available to help the human worker become more productive. This is the most inefficient and costly approach to extracting information and insight from content.
Human on the Loop With aiWARE, digital workers come alongside the human worker to make their job easier, more productive and efficient. The human moves “onto the loop,” reviewing, verifying and using data insights surfaced by digital workers. 
Human out of the Loop AI will progress to a point where human involvement is no longer required. Digital workers have become fast, accurate, economical and self- sufficient enough to operate independently, freeing up humans for higher value tasks. 
AI works alongside the human to ingest content, identify the speaker or writer, process the conversation, analyze the conversation, and fulfill the request for information or insight. 
AI discovers unmined and unstructured data from everyday devices and information – videos, phones, texts, and email conversations with your customers, just waiting to be discovered and utilized. While AI analyzes the numbers or words, AI also finds the emotional context of data. More importantly, it learns how customers interact with the data, and then how the data relates to the customers. AI puts the Human on the Loop, producing a symbiotic relationship between man and computer. What Can Happen? From this simple yet powerful process, we are unlimited in our ability to mine and use any conversational data. AI can scale human effort around conversational intelligence in three key areas: • Contact Center insights
• Social media insights
• Conversational compliance Let’s explore each of these in turn.AI FOR CONTACT CENTERS:
How can AI Scale my conversational insight?
Currently, the standard experience for call and customer service centers is to analyze interactions between the agent, the customer, and the product manually. This takes a lot of time, and only a small portion of information and insights can be examined to develop future call center protocols, and to provide a better experience. But with AI, you can now transcribe every call and analyze all written communications across any channel. Hundreds of conversations can be transcribed, aggregated, and analyzed in minutes, surfacing never-before-possible insights.
Who is Speaking? What are they saying and when are they saying it?For Instance… There is a product in the inventory that is phenomenally successful. Customers are calling because they want to know when there will be a replenishment of inventory on this product. Not only will AI comprehend how customers are continually happy with this product, but it can also provide the measurements behind how satisfied customers are, because the AI also tracks emotional sentiments.
Simultaneously, there is another product in the inventory where customers are recognizably dissatisfied with the performance, cost, features, etc. AI picks up not only on the consistency of the product names and features, but also the tone around how the product is described within the phone call or chat.
These insights can help you train your customer call and service center agents with more examples and experiences across product lines.
AI can find and measure keywords and phrases as they are spoken or written in chat. AI can monitor both successful and unsuccessful situations, locating keywords that are relevant to a particular feature, or product within a brand. The results provide greater insights as to how customers and agents interact, as well as how customers feel and react to your products and services. Access more results faster in days or weeks instead of monthly or quarterly. Integrate these insights into your call and customer service protocols easily. Find new ways to handle dissatisfied customer calls and empower your agents to keep customers loyal by understanding your entire customer base, not just a small sample size. Successful calls and chats between agents and customers become the model to follow in your enterprise. Unsuccessful calls and chats between agents and customers become learning opportunities on how to develop agents’ skills in the future. You will be able to see where they need support and confidence building, so you are not wasting time on irrelevant scenarios or unnecessary skills that will not mitigate the conflict with the customer and the product or service. Even better, for underperforming agents, these insights from AI can help strengthen their skills.Retain your customer service agents by helping them succeed in their job.
What is the text about? Is its tone positive or negative? what key words presons, places, amounts, locations or dates appear in the text, and where? 
Who is pictured, and what are they saying? What does the text in the image/video say, and when does it appear?AI FOR SOCIAL MEDIA INSIGHT:
How can AI help me track, change and improve my market presence?
Currently, companies can track their market presence through focus groups, surveys, and small sample sizes to gain feedback on how customers view a product or service within a brand. This approach limits understanding of who is interested in a product and/or service, and most importantly, why. The brand is everything to your company. Using AI to understand how your customers react to your brand in the marketplace will help guide you to find new opportunities, new consumer bases, design marketing plans, and tailor your social media posts. AI can track how many sales are being made from a social media post, or how many negative situations are resulting from information in market about your product. AI can help companies gain insight into market presence for a product and/or service within a brand.
For Instance…
Use AI to track how competitors’ brands are doing in marketplace. There is no need to make guesstimates as to how customers are responding to their brand versus yours from a few social posts. Instead, you will be able to see the real-world analytics and emotional context behind social, advertising, affiliate, and marketing channels.
Use AI-based analytics to refocus brand guidelines. Track certain phrasing for a product that is coming through keywords on unsuccessful calls in the customer call center, providing immensely powerful insight as to how consumers are interacting with your brand. Adjust marketing and promotion campaigns to strengthen brands and products, instead of having to rebrand the entire product line, or even the entire company.
Instead of spending millions on advertising overhauls, with AI you can pinpoint the issue and make a small shift in image, tone, and style, instead of an entirely new appearance. AI can also show you untapped markets in new customer bases. If you have a group of customers that are burgeoning, but you have neglected to market directly to them, you can use AI to identify top keywords, and positive emotions around your product and service within your brand. Drive sales by learning and understanding their motivators as customers, and why they love your product or service. Add this information into marketing and promotion campaigns, support SEO functionality and reinforce brand identity. Sales teams can also benefit from conversational insights. Sales video and audio calls can be recorded, transcribed, and analyzed by AI for keywords and sentiment, and correlated with sales outcomes to understand what is working, and what is not. Sales teams can use this insight to improve training and boost revenues.AI FOR CONVERSATIONAL COMPLIANCE:
How can AI help me meet all compliance standards?
In addition to company standards of communication with customers and partners, there are many government- and industry-driven compliance standards that need to be met, especially for companies in highly regulated industries, such as banking, finance, and healthcare. Consistently monitoring conversations for compliance can be challenging for any organization. Leverage AI to meet all compliance standards by using conversational intelligence and interaction analytics to find where problems are and correct them. Learnings can be applied to future employee training to ensure compliance risks are minimized in the future.
For Instance…
AI can quickly identify prohibited language when analyzing the calls and written communications between agents and customers, to meet all stringent guidelines—whether company, industry, or government. AI screens calls and emails for both positive and objectionable words and phrases within an industry. Spot red flag keywords that could indicate fraud or other criminal activity, for example in an insurance claim first notice of loss call. Use AI to ensure that all legal contracts have the necessary information within sections and headings. This would include key names, locations, dates, and amounts that are clear and legible, so that all compliance regulations are met completely.
Why an operating system for AI?
Where to begin to harness the power of AI to solve these conversational intelligence challenges? Organizations could build and deploy AI models themselves, solving each problem individually. But without a standard enterprise AI platform, each effort is ad-hoc, time- consuming, and costly, as point solutions are developed and scattered across the company with no clear AI strategy underpinning them all. An AI operating system is needed, providing all the AI models needed for conversational intelligence across all departments and communications channels of the enterprise. Veritone aiWARE is that operating system for AI, providing Interaction Analytics to enterprises for greater conversational insight. The cognitive operating system for artificial intelligence, Veritone aiWARE orchestrates a diverse ecosystem of hundreds of best-of breed AI models to transform audio, video, text, and other data sources into actionable intelligence. AI model categories include:- Speech (transcription, speaker recognition, and speaker detection)
- Data (geolocation and correlation)
- Biometric (face detection and face recognition)
- Audio (audio fingerprinting)
- Vision (object detection, logo detection, license plate recognition, and text recognition)
- Text (language identification, entity extraction, keyword extraction, text extraction, anomaly detection, translation, content classification, summarization, and sentiment analysis)
Veritone Interaction Analytics specifically focuses on speech, text and vision AI models to analyze customer communications from any channel and produce insightful data about customer interactions, leading to greater customer satisfaction, reduced operating costs, stronger compliance, and more business agility. 
Veritone’s AI ingests text, transcribes voice calls, and reviews video and images, and applies aiWARE-based models that analyze and extract value from that content, for communication to key stakeholders across the enterprise.