Category: Blog

AI-powered Email Management Automation

AI-powered Email Management Automation

Introduction

Despite email being the preferred customer service channel for many customers, businesses often struggle to manage email inquiries quickly and efficiently. The financial consequences of delayed responses and resolutions are becoming increasingly more significant, and this underscores the critical need for email automation solutions. Among the biggest pain points of managing emails are:

1. Having to manually categorize emails to determine which team to direct the queries to.

2. Delayed response times due to a large number of incoming emails and/or the lack of 24/7 availability.

3. Inconsistent responses due to varying levels of knowledge and training.

4. High costs of staffing a team to handle email support, especially as the volume of inquiries grows.

5. Handling complex or multi-intent emails can be challenging and time-consuming for agents.

Born Digital’s AI-powered email automation solution addresses these pain points by providing effective email-based support leading to an improved customer experience.

AI email automation for better efficiency

The solution leverages generative AI to autonomously handle 80% of incoming email queries, ensuring quick and accurate responses around the clock. Seamlessly supporting multiple languages, it integrates with Born Digital’s omni-channel customer service platform, delivering a comprehensive and personalized support experience.
Powered by Large Language Models (LLM), AI Email Automation is able to understand complex, unstructured emails and accurately identify multiple intents and infer the object and urgency of the email. Taking it a step further, it identifies the user and delivers a contextual response grounded in user insights, reducing ticket volumes by up to 80% and improving first contact resolution by up to 20%.

Streamline email handling

Born Digital’s email automation can self-serve up to 80% of incoming emails, significantly reducing operational costs by up to 60%, and cutting ticket volumes by 85%, leading to a 20% improvement in first contact resolution (FCR).

Advanced email understanding

Powered by Large Language Models (LLMs), Born Digital’s solution comprehends complex, unstructured emails, identifies multiple intents, and recognizes urgency and sentiment. This sophisticated understanding allows businesses to provide accurate and contextually relevant responses quickly.

Automated workflow triggering

This feature automates workflows by identifying the intents within emails, directing them to knowledge bases, escalating to the relevant teams, or transferring to agents for complex issues. Automating these processes ensures businesses can resolve queries promptly and efficiently.

Empathetic, personalized resolutions

Born Digital tailors responses by cross-referencing CRM data, detecting user sentiment, and following company guidelines. This approach ensures that each interaction is personalized and considerate, fostering stronger customer relationships.

Categorize and prioritize emails you receive

Seamless transition to human agents is ensured, with AI suggesting responses and triggering transfers when negative sentiments are detected, maintaining a human touch for complex queries. Agents are equipped with suggested responses, enabling quicker and more effective resolutions.

Easily integrate with existing systems

The solution integrates seamlessly with existing ticketing and CRM systems, ensuring contextual and efficient responses by leveraging customer insights from previous interactions. This integration helps in maintaining a coherent and comprehensive support system.

Get in touch with our experts to learn more about AI-powered email automation

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AI Outbound Dialing: Compliance Issues

AI Outbound Dialing: Compliance Issues

Introduction

Generative AI has rapidly advanced, offering new opportunities for contact centers. Voice bots can now engage in conversations that feel nearly human. Additionally, speech synthesis can produce voices that are almost indistinguishable from real ones, allowing for semi-realistic AI voice interactions.

For organizations aiming to enhance efficiency or handle large volumes of outbound contacts, the question arises: what compliance issues should be taken into consideration when considering bringing in AI to automate the initial conversations?

This article explores key compliance considerations for using AI voice to make outbound calls more efficiently.

Compliance Isssues

One of the biggest issues you will need to overcome when making automated outbound contact is how you’ll ensure compliance with the relevant legislation in the countries you are dialing into.

Automated dialing compliance

Most jurisdictions do not completely ban automated phone calls but have specific regulations that must be followed. For example:

In the US, the Telephone Consumer Protection Act (TCPA) requires telemarketers and debt collectors to obtain prior express written consent before making automated calls. For other calls, or when customers have agreed to automated contact, the FCC mandates that customers must be able to opt out of future calls at any time during the conversation, with this option clearly communicated at the beginning. Additionally, there is a three-call limit per residential phone number within a thirty-day period, alongside other TCPA restrictions.

In the UK, Ofcom requires that automated calls are made only to individuals who have given permission. If the AI connects the customer to a human agent, the transfer must occur without an unfairly long wait time.

In Australia, while there are no specific restrictions on automated calls, they must comply with ACMA rules, such as identifying the caller and the call’s purpose at the start. The Spam Act also requires providing an easy way to unsubscribe from future calls.

Before implementing an AI-driven outbound calling system, it’s crucial to consider compliance with these regulations. While countries like Australia have relatively straightforward rules, the US has more detailed requirements enforced by the FCC.

Privacy laws and customer data

Beyond compliance issues with automated outbound contact, broader privacy legislation must also be considered.

Training AI with customer conversations is essential for optimal performance. Without this training, the AI might struggle with the nuances of your customer interactions.

Some compliance requirements might be met by informing customers that calls will be recorded for quality and training purposes. However, other considerations include:

In GDPR-covered jurisdictions, customers have the right to be forgotten. This involves more than just deleting CRM records and call recordings if the AI has already processed this information.

Do you have the legal right to use customer data for AI training? While using call recordings with a disclaimer might be permissible, using additional customer data to enhance AI conversation quality could pose compliance risks.

Some jurisdictions limit the retention period for customer data. If the AI retains processed data indefinitely, this might introduce compliance risks.

Given these concerns, AI might be better suited for handling inbound calls. When customers initiate contact with a clear purpose, it minimizes compliance risks and leverages AI’s strengths in tasks like processing payments or retrieving information.

Technological and feasibility issues

Beyond compliance issues, several technological and feasibility concerns must be addressed before using an AI agent for outbound dialing.

Latency: How quickly can the AI respond to a customer? This is crucial for international calls, where delays of three seconds or more could negatively impact the customer experience.

Transcription issues: Can the AI accurately understand customer speech, considering call audio quality? Customers may become frustrated if they have to speak unusually clearly for the AI. 

Controlling the AI: What if the AI deviates from the prescribed messaging? There have been cases where AI chatbots behaved inappropriately despite controls, such as expressing romantic interest in users.

Utilizing customer data: With traditional dialing, agents can learn about the customer before the call and tailor their messaging. How will you leverage customer data with AI? If valuable information is available about the customer, it’s essential to use it effectively; otherwise, your calling performance may decline.

Handoff to real agents: How will you transition conversations to real agents, especially if the AI malfunctions? If the handoff occurs deep into the conversation, how will the human agent be briefed on the call’s context?

Get your free consultation with Born Digital

AI can significantly improve the efficiency of large-scale outbound dialing for specific use cases, as demonstrated by our clients at Born Digital. However, it’s crucial to understand and adhere to relevant regulations to ensure compliance.

We at Born Digital are experts in outbound AI voice bot solutions, having successfully assisted numerous clients in building and deploying their own bots. Our team of specialists ensures compliance with all relevant regulations, delivering efficient and effective AI-driven communication strategies. To learn more and get started, schedule a free, non-binding consultation with our team of experts.

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Martin the Digital Policeman 

Meet Our Digital Humans: Martin the Digital Policeman

Meet our Digital Humans: Martin the Digital Policeman

Introduction

 

Crime never sleeps, and Martin doesn’t either, so having him onboard as a digital human policeman might be what your city needs to rest peacefully at night. Using AI technologies has allowed for unforeseen improvements in the policing industry. Martin can standardize and improve many of the monotonous tasks that slow down investigations. Police officers are an essential part of society that tend to be overworked and overlooked, with the assistance of AI (in human form of course) they can focus on what really matters, all of us.

Defining Digital Humans

The technology of Digital Humans merges the authenticity of human interaction with the power of AI to deliver a more personal and engaging experience. Thanks to Generative and Conversational AI, they’re able to interact with users in emotionally intelligent ways. 

They excel in natural language processing, emotion recognition, and machine learning, allowing them to perform complex tasks and make informed decisions.  

Meet Martin

We at Born Digital believes that everyone has a right to safety, and if advancements in technology can be put towards that then they should. In comes Martin who can help the policing industry in a variety of different ways by doing work that is normally done by humans, not to replace police officers but rather to allow them to prioritize the community over paperwork and transcripts. 

Martin, a police front-office assistant, employs a range of AI technologies including generative AI, analytics, and both conversational and visual AI. His capabilities are extensive: he can automatically analyze data from police cases, facilitate communication with various institutions to gather necessary documents, and expedite the seizure of stolen funds in offenders’ accounts. Furthermore, Martin can create real-time transcripts of phone calls and conversations for detailed analysis.  

Using Cognitive & Open AI services, Martin produces automated police reports based on citizen-reported crimes, adhering to templates specified by the police department that detail the name, crime, location, and date. 

Currently active with the Czech Police department, Martin significantly boosts their operational efficiency. His ability to track and trace additional information about offenders aids law enforcement in processing data on a larger scale, enhancing their capability to identify behavioral patterns and combat organized crime.  

Hire Martin or create your own Digital Human today!

Although Martin was specifically created to tailor to the needs of police and detective agencies, you can create a Digital Human to meet your companies’ specific needs! Digital Humans are very easy to onboard onto projects and have already proven capable of helping streamline repetitive tasks, saving time and money.  

The best part of Digital Humans is their human aspect. They can be created to have their quirks, make jokes, and have human-like interactions. This is essential in all different industries since it emphasizes the most important part of every and any job: humanity. 

Stay tuned as we introduce our other Digital Humans! 

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How to Qualify Sales Leads with AI

How to Qualify Sales Leads with AI

What is Lead Qualification?

A lead qualification process is a set of sales activities designed to identify leads that are well-suited for your product or service. For instance, during a discovery call, asking the right qualification questions helps in deciding which leads are ready for further engagement, such as a product demo.

Implementing a robust lead qualification process can significantly increase your close rates—potentially by 20, 30, or even 40%.

Without such a process, your Business Development Representatives might indiscriminately pursue every lead, resulting in a low number of successful deals and a considerable waste of time each week.

How can AI voice bots help you automate Lead Qualification?

When your leads are in the hundreds, they can be managed by your sales team. But when they get into the thousands, it’s a whole different game. 

The solution — conversational AI. 

Conversational AI combines generative AI, speech recognition, natural language processing, and machine learning, enhancing virtual agents’ ability to engage effectively with a wide audience. Consequently, virtual agents are moving from simple voice bots to sophisticated conversational platforms that boost their lead generation capabilities.

Deploying AI agents can speed up the process of qualifying leads, reducing or completely removing the need for human input. They can be designed to pre-screen leads with a set of predefined questions before they are introduced into the sales funnel.

Main features of Borndigital.ai's no-code bot builder studio

Using Borndigital.ai’s no-code platform, you can build an advance voice bot for your organization to qualify leads for you by asking a set of pre-defined questions. Our drag-and-drop builder allows you to easily build and customize bot conversations without requiring coding expertise. Key features for lead qualification bots include:

How to create an AI sales agent in 5 simple steps:

1. Create your agent

Using Borndigital.ai’s no-code bot builder, you can begin creating the voice bot which will qualify your leads. Here you will define the type of bot (chatbot or voice bot), its name, gender, language and accent, goals, and personality. You can also adjust its speed and pitch settings.

2. Build the conversation flow

The conversation flow is a structure that defines the sequence of a voice bot conversation with users. 

Here you can define the set of qualifying questions and other aspects of the flow. You will start with the introductory message (the first message the user will hear when the conversation starts) and the subsequent questions you would like to ask. Other interactions, for example the lead asking about your products or services, can be redirected to the generative AI node to enable the bot to provide a natural human-like response.

3. Train your agent on your knowledge base

The Knowledge Base is a repository of information that the voice bot can access to provide accurate and relevant responses to queries. You can enrich the knowledge base by adding website URLs or uploading documents. Having a knowledge base is important order to enable the bot to become an expert on your products or services. 

4. Integrate with your existing systems

To create an AI voice bot that qualifies sales leads, you can integrate it with various systems. It can connect with your existing customer data systems like CRM or use a manually uploaded list of leads. The bot can also link with your calendar to schedule calls between leads and your sales team, automatically handling meeting details. Additionally, the bot can initiate calls based on specific events, such as changes in a lead’s lifecycle stage within the CRM. Beyond these integrations, Borndigital.ai supports seamless connection with any third-party APIs.

5. Deploy and analyze

Borndigital.ai not only automates outbound campaigns but also analyzes interaction data to provide valuable insights. The Statistics section offers critical data on the performance of your lead validation voice bot, helping you refine your sales strategies. In the recordings section, you can listen to and analyze interactions, including transcriptions, for quality control and training.

Summary

In conclusion, creating a lead qualification voice bot using Borndigital.ai can transform your lead management process. Using the instructions above, you can set up a voice bot that not only automates the initial stages of lead qualification but also leverages advanced analytics to refine your sales strategies and improve engagement. The integration capabilities, along with the insights gained from detailed statistics and sentiment analysis, empower your business to effectively screen and nurture leads.

If you’re ready to integrate AI into your lead qualification process to, or if you have any questions about implementing your own sales lead validation voice bot, please don’t hesitate to reach out to our team of experts.

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How to measure call quality: practical tips​

How to measure call quality: practical tips

Table of contents

Nowadays, managing contact centers involves a more data-driven approach to refining call strategies than relying solely on personal experience. Modern cloud-based contact center technologies simplify the process of gathering and analyzing data from customer-agent interactions. Managers can use recorded calls and performance metrics to consistently pinpoint and address issues in call quality. They can then tailor training and modify processes and scripts to improve performance. This article will cover the importance of monitoring call quality, its definition, and how technology enables managers to do this effectively and smartly.

What is call quality?

Call quality evaluates how well contact center agents communicate with customers over the phone. Different contact centers have specific criteria for what constitutes good call quality; typically, it involves agents being courteous and effective, ensuring customer satisfaction with clear resolutions to their issues.

Meanwhile, call quality monitoring is the continuous practice of collecting and analyzing data from customer service calls to enhance the performance of a contact center.

What's the importance of monitoring call quality?

Given the significant impact of customer service on customer experience, sales, and retention, it is crucial for contact center managers to optimize phone performance, and monitoring call quality is key to achieving this. This can be likened to a top sports coach who tailors training based on observed player weaknesses rather than wasting time on already mastered skills.

Similarly, a contact center manager must adopt this coaching approach to consistently enhance agent performance by pinpointing individual and team weaknesses through effective call quality monitoring. This allows them to provide tailored training or resources, like specific technical papers or scripts for handling objections.

Additionally, managers can modify contact center processes to address these weaknesses broadly. For instance, if analytics reveal frequent call failures when customers inquire about a specific technical issue, managers might update training on this topic and adjust call scripts to include helpful language agents can refer to during calls.

How can you monitor call quality?

The primary goal of call quality monitoring is to enhance agent performance by identifying and correcting deficiencies in how calls are handled. To achieve this, contact center managers implement systems to gather and analyze data from customer interactions, seeking insights to improve service. This data might include:

• Call recordings

• Customer surveys

• Mentions on social media

• Information from other communication channels like live chat and email

For a practical example, consider a scenario where all agent phone calls are recorded and customer survey feedback is collected on a platform. When a customer leaves a negative review, the manager listens to the related call, identifies why it was unsuccessful, and coaches the agent on improvements for future interactions.

If a particular issue recurs frequently, managers might update the team’s standard operating procedures or scripts to prevent future occurrences. They could also disseminate the guidance provided to one agent across the entire team during meetings.

However, monitoring call quality can be challenging with a high volume of calls, as it’s not feasible to review each one and difficult to pinpoint the most common call handling errors. Here are some best practices for efficient call quality monitoring:

Automate the collection and analysis of call data

Call data includes elements like call recordings, live metrics, historical reports, and other metrics such as average handle time (AHT). 

Many companies leverage AI-powered contact center analytics solutions to automatically capture this data during conversations. This software also aids in analyzing the data, facilitating the identification of unsuccessful calls and the reasons behind their failure. Ultimately, using the right software to automate data collection and analysis is crucial for establishing a systematic approach to monitoring call quality.

Listen to the recordings critically

Simply collecting metrics through automation doesn’t provide a complete understanding of where an agent or process might be underperforming. A deeper analysis is necessary to grasp the issues fully. This involves listening to call recordings and considering specific questions:

• Is the agent adhering to the script?

• What triggers customer friction? Are there specific talking points that precede it?

• What types of questions does the agent ask?

• At what point does the call start to deteriorate?

• Were there missed opportunities to clarify information?

• Does it appear that the agent lacks essential knowledge about the product?

A detailed and critical review of an agent’s conversations can reveal nuanced problems with their approach, enabling targeted coaching to enhance their performance significantly.

Track the impact of impact of any new processes

Whenever you implement a new call handling process or update your script, it’s essential to monitor the effects of these changes to determine their effectiveness. By tracking and comparing key team-wide metrics such as average handle time or customer satisfaction scores (CSAT) before and after these changes, you can assess whether there has been a notable improvement. If you see a positive shift in these metrics, your adjustments are working well. However, if there isn’t a significant improvement, it might indicate a misjudgment in identifying the initial problem, suggesting a need to revisit your strategy.

Conclusion

Monitoring call quality to enhance agent performance is a crucial task for leaders in contact centers. True progress in this area can only be achieved through continuous measurement and analysis of call quality.

If you are searching for a tool that supports call quality monitoring and improves agent performance through features such as agent dashboards and sentiment analysis, consider exploring what Born Digital offers.

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Meet our Digital Humans: Sarah in Sales & Marketing​

Meet our Digital Humans: Sarah in Sales & Marketing​

Introduction

We’ve all experienced the frustration of dealing with bots that struggle to understand simple responses, requiring us to repeat “yes” multiple times. Fortunately, thanks to improvements in AI, those days are behind us. 

The future of customer interaction is Digital Humans and in this article, we’ll introduce you to Sarah, a Digital Human who specializes in sales and marketing. Sarah is designed to not only understand and respond to queries but to also ask targeted questions and provide personalized solutions, creating a lasting impression and pleasant buying journey. 

Defining Digital Humans

The technology of Digital Humans merges the authenticity of human interaction with the power of AI to deliver a more personal and engaging experience. Thanks to Generative and Conversational AI, they’re able to interact with users in emotionally intelligent ways. 

They excel in natural language processing, emotion recognition, and machine learning, allowing them to perform complex tasks and make informed decisions.  

Meet Sarah

As a sales and marketing expert, Sarah can listen to a multitude of tastes, interests, or issues and make calculated product recommendations that will satisfy customers, thereby engaging in dialogue rather than monolog. For larger purchases that require more thought and discussion, Sarah’s infinite patience allows her to guide customers through every step of the purchasing journey, ensuring they are fully comfortable and confident in their choices.  

Her emotional recognition features and machine learning capabilities enable her to respond in ways that personally appeal to each customer, building a connection that fosters trust in your brand. 

Sarah doesn’t need sleep or rest, so she is available 24/7 to assist customers. Additionally, she can be programmed to speak multiple languages, allowing her to communicate globally and eliminate language barriers. All these features create a marketing experience that helps each customer feel valued and invested in something deeper than the product. 

She can be made available to consumers via kiosks, tablets, apps, websites, and more. By integrating Sarah into your website, you can offer a customized user experience that helps customers find the perfect product. 

Hire Sarah or create your own Digital Human today!

The amount of time it takes to onboard Sarah is relatively short compared to traditional employees since she teaches herself and is built to serve your company. Overall, she stands apart from other Digital Humans and employees since she is meant to become a specialist in exactly what you want her to be.  

You can also create your very own Digital Human that can act as your sales expert. Using our platform, you can upload or connect to your knowledge base, and personalize her or his personality and overall appearance. You can adjust the tone of voice, quirks, and much more to match your brand. 

Stay tuned as we introduce our other Digital Humans! 

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What’s new in the Digital Studio: June 2024 release

What's new in the Digital Studio: June 2024 release

Index Parsing Methods Improvements to provide more accurate bot reponses

We have introduced new capabilities to enhance the parsing of documents into multiple chunks within the Index:

Simple Parsing Method – Delimiters: You can now split documents by setting a delimiter (ENTER or double ENTER). The document will be divided into snippets based on the chosen delimiter. Default delimeter means snippets will be parsed with the same approach as before.

Custom Parsing Method: Select specific areas to split into snippets using the SHIFT + ENTER command, allowing for more control over how the snippets are creating. For now, upload just one document at a time if you want to use this method.

Easily export and manage indexes from your knowledge base

We have enhanced our Knowledge Base tab to allow you to easily export and manage indexes. You can now export one or multiple indexes with a simple click. Additionally, we’ve updated the functionality to ensure that the exported indexes can be seamlessly re-imported.

Copy indexes functionality can be also used if you just want to copy the index (either to the same, or other project).

This will help you to move your fine tuned index from Test to Prod for example. All content of your index is exported (incl. snippets) and are uploaded to the new environment in the same way. You can also export and import whole project configuration, which includes also indexes now.

Share specific nodes or project paths

We redefined how the URLs are structured when using our product. The unique Project ID is now integrated directly into the URL structure, as well as information on which tab are you located and which element you have opened.

With this update, you can now share exact node paths or project paths within the conversation flow with your colleagues. When they access the shared URL, the connected project with the specified node will appear, streamlining teamwork and facilitating more frequent project sharing.

Additional changes

Global Fallback Counter in Answer Node: You can now create a global fallback counter for ANSWER nodes, instead of having individual counters for each node. This means, where applied, that fallbacks count in the whole conversation is considered.

Digital Email Processing tile has been removed from the main page, since email bot is now part/combination of both main products.

Technical Logs Removed from Sidebar: As part of our UI improvements, access to Technical Logs has been removed from the sidebar, resulting in a cleaner and more user-friendly interface

Application Performance: We have enhanced the performance and logic of the Digital Studio, ensuring greater efficiency and a smoother user experience.

Bug Fixes and Improvements: Model queries have been optimized for increased speed and efficiency, contributing to overall system reliability and performance.

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Digital Humans Predictions for 2024

Digital Humans Predictions for 2024

Table of contents

In 2024, the boundaries between human and digital interactions continue to blur, with digital humans poised to take a central role in this transformative era. From enhancing customer service to revolutionizing marketing strategies, these virtual beings are not just figments of sci-fi imagination but are becoming integral to our daily digital experiences. This article delves into the top five predictions for digital humans in the forthcoming year, highlighting their potential impacts and the technological advancements propelling them.

Our Top 5 Predictions

1. Commercial Success and Brand Partnerships

Digital humans are expected to achieve unprecedented commercial success in 2024. Figures like Lil Miquela have already demonstrated the potential of digital influencers, having collaborated with high-profile brands and amassed millions of followers. This trend is anticipated to expand as more companies harness digital humans for marketing, customer engagement, and brand representation, driving substantial sales and fostering deeper customer relationships.

2. Integration with AI and Machine Learning

Digital humans are likely to become a key interface for interacting with sophisticated AI platforms, including large language models like ChatGPT. As AI becomes more advanced, these digital personas will provide a more natural and engaging way for users to interact with AI systems, enhancing user experience and efficiency across various applications.

3. Enhanced Role in AR and VR

Augmented and Virtual Reality technologies are set to become more embedded in our daily lives, with digital humans at the forefront of this evolution. These technologies will increasingly utilize AI-powered digital humans to create compelling, immersive experiences in sectors ranging from entertainment to education, thus broadening the scope and appeal of AR and VR applications.

4. Significant Roles in Metaverse and Web3

The metaverse and Web3 are set to offer fertile ground for the growth of digital humans. As these decentralized platforms develop, digital humans will likely be employed to offer more personalized and interactive experiences, contributing significantly to the metaverse’s evolution into a mainstream technology.

5. Multilingual Communication

Addressing the need for global communication, digital humans capable of speaking multiple languages will become more prevalent. For instance, a digital human in Amarillo, Texas, is set to support over 100 languages, vastly improving accessibility and inclusiveness in public services and beyond. This leap in multilingual capabilities could redefine global customer service standards.

Summary

In summary, 2024 looks to be a landmark year for digital humans, with significant advancements across various domains. These AI-powered entities are expected to not only enhance how we interact with digital content but also revolutionize customer service, marketing, and the burgeoning fields of AR, VR, and the metaverse. As technology progresses, digital humans will increasingly become embedded in our digital interactions, making them an indispensable part of the future landscape. Their evolution will likely continue to offer new opportunities for innovation and engagement in an increasingly digital world.

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What’s new in the Digital Studio: May 2024 release​

What's new in the Digital Studio: May 2024 release

You can now create new nodes within intents!

We have introduced the ability to create new nodes directly in the ‘Answer’ node of intents, enhancing the user experience by providing a more straightforward workflow.

We've enhanced our Knowledge Base!

We’ve upgraded our knowledge base!  You can now edit, delete, or add new chunks in one dialog. 

Project Deletion and Associated Asset Removal

Deleting a project will also remove all connected assets. A new dialog box will confirm that the following related assets will be deleted:

• Knowledge base indexes

• Campaign data

• Announcement settings

Additional enhancements

Application Performance: Enhancements to the performance and logic of the Digital Studio now deliver greater efficiency.

Bug Fixes and Improvements: Model queries have been optimized for increased speed and efficiency.

Knowledge Base Indexer: Document descriptions are now limited to 1024 characters.

Campaign Reports in XLSX: You can now export campaign data directly to XLSX format from the campaign page.

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How to empower digital email processing with Generative AI: 5 practicle examples

How to empower digital email processing with Generative AI: 5 practicle examples

Digital Email Processing for customer service

Table of contents

Omnichannel customer service is becoming increasingly important. McKinsey reports that about three-quarters of customers use multiple channels to interact with a brand. Depending on the situation and their needs, customers prefer different channels. Among these, email stands out as one of the most important. According to Ultimate’s Trend Survey for 2024, email is experiencing the fastest growth among channels reported by CX leaders, indicating that the volume of email requests will only continue to rise.

For customer service teams handling hundreds, thousands, or even tens of thousands of emails every day, the challenges are familiar. Ensuring that emails reach the right person and that customers receive a timely response without efficiency or revenue losses can be daunting. 

Fortunately, with Generative AI, managing customer emails has never been easier. Whether it’s routing emails or automating responses, the latest advances offer significant business opportunities. Let’s explore a few specific examples. 

Email classification and routing trends

Previously, the widely used NLP approach primarily relied on keyword extraction to classify emails based on keywords in the body or subject. However, it’s often challenging to determine whether an email mentioning payments multiple times should be addressed by someone handling transaction issues, returns, or coupon inquiries. Consequently, such emails often end up being manually routed. Combining this NLP approach with Generative AI can sometimes enhance efficiency and is advisable. However, the Generative AI alone offers a wide range of additional benefits that can significantly transform your customer service operations.

1) The knowledge base approach

Utilizing both large and small language models enables the classification and routing of requests based on context. This means that an email about payments isn’t simply routed based on keywords but rather on the knowledge base available within your company. The AI leverages this information, contextualizes it to resolve the issue, and routes the email based on the necessary next steps, such as complaint processing. With an astonishing 98% accuracy rate, the email is then directed to the inbox of the person responsible for that area, complete with a label indicating the required action. Additionally, the AI can prioritize responses based on the urgency sentiment conveyed in the message. 

2) Preprocessing and response automation

By making efficient use of the available knowledge base, Generative AI can help prepare or fully automate human-like responses, saving your teams significant time. In some scenarios, the prepared response may be sufficient for your agent and only require additional human oversight, such as insurance claims. Over time, however, you can identify processes that are ripe for full automation. This means that the Generative AI-powered email processing tool will accurately classify the request and then send a relevant response without any human intervention.

3) API hooks

In addition, when customers authenticate themselves within the incoming email, for example, based on order numbers, booking numbers, phone numbers, or IDs, additional information can be automatically retrieved from the system via connected APIs. 

With such authentication, the Generative AI-powered system can also deliver more personalized and relevant responses, including specific details such as delivery delays or claim status.

Born Digital’s Digital Email Processing tool also automatically prompts for additional authentication if it wasn’t completed correctly the first time. This approach results in significant time savings for agents and a noticeable increase in productivity and response time, as the majority of these requests can be fully automated. In our experience, more than 60% of automated requests can be successfully achieved.

4) Customer insight analytics

In addition to the perks mentioned above, Generative AI also offers significant advantages for uncovering customer insights. Beyond digital email processing, it allows you to analyze the sentiment of emails and prioritize responses accordingly. Furthermore, you gain insights into which topics are most frequently addressed, enabling you to understand what your teams need to deal with and which agents are most overwhelmed. The GenAI-powered analytics also reveal new topics that you weren’t aware of before, enabling you to allocate team resources efficiently. By optimizing team performances, redistributing responsibilities, and enhancing your digital email processing and routing, you can power up your customer service operations.

5) Data extraction from email attachments

Emails often come with attachments like invoices, insurance claims, or ID pictures. Born Digital Email Processing efficiently extracts data from these attachments in various formats. This functionality enables automation tools to seamlessly incorporate attachment information into tasks such as updating internal accounting systems. Moreover, it supports preprocessing email responses for human agents. Additionally, the system can also analyze attachment content for suspicious patterns or inconsistencies, aiding in fraud detection efforts within customer service operations. This multifaceted capability not only streamlines workflows but also enhances security measures, ensuring a more efficient and secure customer service experience.

Business results

In summary, integrating Generative AI into customer service operations presents numerous advantages. Businesses can anticipate cost savings through automation, quicker response times to customer inquiries, and seamless provision of multilingual support. Born Digital’s Digital Email Processing tool encompasses all these features, simplifying email classification, routing, preprocessing, and attachment data extraction. By harnessing Generative AI, companies can optimize team performance, gain deeper customer insights, and bolster fraud detection efforts. We’re thrilled to assist you in navigating the implementation process and addressing any questions you may have, ensuring a smooth transition towards a more efficient and effective customer service experience.

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