vCons or Virtual Conversations will be a new term for most people. A vCon is a standard document format (like a PDF) for recording conversational data with customers.

It represents a movement by the Internet Engineering Task Force (IETF) to create an interoperable standard for recording conversational data.

It is being developed in response to the need for a more robust conversational data platform in the wake of mass-market artificial intelligence (AI) and advanced analytics.

It has not yet seen broad adoption, but the standard promises significant potential benefits that could see more companies adopting the vCon standard.

With Cavell’s latest Enterprise CX research showing that 65% of businesses still use phone calls to communicate with their customers, 40% using website chat, and 44% using social media messaging, what is clear is that conversations still form the part of a successful CX/CCaaS strategy

A vCon is a new approach to storing conversational data in an open-source standardised way.

It will be a standard output that contains data in the same format in every record, meaning that any software designed to read one should be able to read any.

Not every call recording or customer data record is a vCon. Instead it is a specific standard that exists within certain parameters. The goal is for all of them to match the same standard, rather than every record to call itself a vCon.

vCons serve as a standard format to document, store and analyse conversations. They aim to be a broadly useable data format similar to a PDF or a Word document.

vCons are records containing information on who is involved in the conversation (chat/call/voice assistant, etc.), what was discussed, and any other analytics or documents used.

Multiple systems can interact, open, and process a vCon, as all of them will be designed within the same parameters.

Conversational data is a broad term that includes all the data generated from conversations over digital platforms.

For example, if two colleagues have a call and record it, the conversational data would be the record of the call, who called, who, and how long the call lasted, as well as any post-call analytics (e.g., sentiment tracking).

Conversational analytics is a broad term for all the analytics that can be done on conversational data.

This includes traditional approaches to reviewing recorded calls, manual summarisation and call categorisation.

It also includes the newer approaches powered by machine learning and AI, like sentiment and intent analysis and other forms of automated analysis.

vCons aims to include all forms of data relevant to a conversation that involves a person. This currently includes:

1. Who is on the call
2. Any recordings, transcripts or records of what was said
3. Any analysis that was done on the call
4. Any supporting attachments
5. Other forms of communication e.g. post-call emails, SMS

However, it is also worth noting that this is still an early-stage idea, so as the industry grows, the data included can also change.

vCons are designed as an open-source standard by the Internet Engineering TaskForce (IETF); this means that rather than being made by one company, anyone can make one.

They are intended to be used by as many companies as possible to create a record that enterprises can use to interact with many systems.

vCons will be used by businesses to store their customer data in a secure and standardised format. This will aim to create a database of customer data that is not siloed in one individual place or business unit but can be understood and shared across the company.

There are also broader-reaching implications. If data is stored in vCons and the company wishes to change CX provider, if the new provider also works with the technology as well, the customer database will not need to change even if the end CX technology does.

In addition, vCons allow companies to be prescriptive in the types of data they share, meaning that competitors could share data on calls between different companies without sharing any unwanted data. For example, a number repeatedly making fraudulent calls could be shared with a cross-industry task force or a fraud prevention company without exposing any other customer data.

The benefits of vCons are varied, but include:

1. De-siloing data
   • By ensuring conversational data is stored in the same format, you remove the barriers between different parts of your business. While previously they might have used different technologies, now they share a singular cross-platform data record.
2. Fraud prevention
   • By allowing the sharing of specific data across the company or the industry, you increase the capabilities for fraud detection and prevention.
3. Industry-wide analytics
   • vCons allow for anonymised data sharing across industries by only exposing specific information, meaning competing companies can share data on fraud or best practices without exposing critical information.
4. Consumer protection
   • By having a single record that contains all the conversational data about a customer, you also have far more control over that data. This means that if data deletion is requested, it is easier to execute, and customer requests for information can be handled more efficiently.

As vCons are primarily a storage format for information they suffer from similar challenges/drawbacks as other similar formats, for example:

1. Data security
   • VCons provide a powerful tool for creating, formatting and storing that data, but this also means the data might be easier to access and more prone to being leaked. As such it’s important that the database is still given adequate protections to mitigate these risks.
2. Storage and Processing
   • While vCons present an interesting approach to storing and categorising conversation data, there are also challenges with storing all of this new information, managing updates and changes to the records, and building a database to handle them.

Yes, vCons are an open standard proposed by the Internet Engineering Task Force (IETF). The code for designing them is open-source and can be accessed and created by anyone.

vCons being an open standard is vital as it allows anyone to create their own. This facilitates their use by ensuring that they are the same across all platforms that use and create them.

Being open source is vital to ensure the interoperability of the technology and is essential to the idea of this new standard, as many non-standardised conversational data databases already exist.

vCons are not yet broadly used or adopted by the CX/CCaaS industry. They are a relatively new concept that has only recently been proposed.

However, initial feedback from the vendors and service providers favours the idea, with many embracing the use case ideas that can be created from them.

vCons helps machine learning by creating a standardised information template that allows systems to take data from them regardless of where they were created. This means that systems will find it easier to share, extract, and utilise data from vCons rather than customising how they take data from each system.

vCons also helps with control over data, as having a central record for conversational data gives you more control over where that data is used or if you need to remove that data from the machine learning model.

vCon success is not guaranteed. Whether they are successful depends on how readily vendors or businesses adopt them.

1. Vendor adoption — Vendors will need to decide to build their platforms to create and interact with vCons. Some vendors are already discussing this, and others may be forced to adapt if their customers start requesting the format.
2. Business adoption — If businesses start requesting or demanding vCons from their platform vendors, vendors will be forced to implement them. Some companies may also wish to adopt them directly, giving them more control over their data and more ability to comply with customer protection regulations.

Vendors should consider using vCons as customers will appreciate the standardised approach to conversational data. Vendors can offer a future-proofed system with many cross-platform benefits and new use cases.

These factors mean that vCons could be a competitive differentiator as they will allow vendors to offer capabilities and integrations not provided by their competition or at a lower price.

Companies should consider using vCons as they provide a standardised repository of conversational data, which can be used in many different ways.

It creates a broadly interoperable database that is entirely under their control and can be used with multiple platforms even if the provider changes.

One strong vCon use case is in a distributed company with many branch/franchise offices. The company might not wish branch offices to share customer data and fully embrace the risks, but they may want the gains that can be achieved by sharing some data.

For example, using vCons, each branch/franchise could build its customer database, but access to specific data could be made available in an anonymised format across all the sites.

Examples of data that could be shared:

1. Fraud data – which phone numbers make fraudulent and scam/phishing calls.
2. Sales trends data – which products are selling the most efficiently via sales calls and why, what conversational marketing campaigns are working, and what are the hallmarks of the most successful conversations.
3. Customer data – the ability to identify customers across different branches without sharing all their information unprompted. For example, a representative at the new branch could recognise that they are a customer and request access to the previous records with the customer’s consent.
4. Customer intent mapping—Mapping customer intents requires a large amount of specialised company and vertical data. For example, data about how different conversational data indicates intent in healthcare could be shared across multiple companies to improve vertical-wide efficiencies.

vCons should enhance privacy and security by creating a more structured way of storing customer data. Rather than spreading data across multiple, hard-to-update and maintain systems, conversational data can be placed into a specific record. This means that if a customer record needs to be deleted, the associated vCons can be deleted .

vCons will secure customer data by making a much more precise record of what customer conversational data has been stored and providing a straightforward route to delete that data.

It also provides a pathway to enable the ‘right-to-be-forgotten’ for all customers, even when using customer data to train AI and Machine Learning models. By tying the vCon to the customer and feeding his record into your machine learning platform, you can create a pathway for ‘right-to-be-forgotten’ by deleting the vCon, which will also remove data associated with it from the model.

With the top concern of organisations in Cavell’s latest Enterprise CX Research for their contact centres being the security of customer data, organisations are highly motivated to build solutions like vCons to protect and secure customer data.

vCons help with compliance as they can provide a demonstratable process for deleting data on a specific customer.

Since the vCon will contain all the data from a conversation with a customer, so by deleting that record, you delete that conversational data. Creating a system that allows the deletion of vCons on customer requests ensures that your company will always comply with customer privacy regulations.

vCons helps with data protection, providing a centralised approach to storing and protecting customer data. Rather than securing multiple customer data platforms or systems, you can build security into the platforms that interact with and manage them, ensuring a central source of security for all your customer data.

vCons presents a solution to a growing challenge in the CX/CCaaS industry. The amount of data being generated on conversations is growing more prominent, as is the amount of analytics that data is expected to provide and the amount of systems that data is expected to be used for.

A new data format that comprehensively stores conversational data in a clear, cross-platform format that can handle the needs of developing CX/CCaaS technologies is needed.

There is also growing demand from enterprises to better store, manage, and use this data, making it available across silos without creating more risk.

Furthermore, enterprises are more interested in changing providers, updating their technology capabilities, and having a customer database that can provide the data needed to do all these things.

vCons presents a solution to the industry’s challenges: a standardised format that will work with multiple systems, a way for different companies in the same vertical to speak the same language and collaborate, and the building blocks for providing customer data to machine learning and AI systems without losing the customer’s power to control their data regardless of what company collects it.

Cavell is constantly researching the latest trends in the CX/CCaaS space. For access to Cavell’s latest market forecasts, enterprise insights or industry insights, please get in touch.

Cavell is always keen to get insights from the industry. Is your company working to adopt vCons? Do you think the industry needs this?

Contact finbarr.begley@cavell.com to discuss the idea further or reach out on LinkedIn.