With the General Data Protection Regulation (GDPR) coming into force in May 2018, organisations are currently navigating requirements and putting in place strategies to ensure customer data is protected. Those operating significant customer service and communication centres need to also consider how they will ensure that voice and call recordings are classified accurately and what security controls need to be put in place. But what if, rather than an additional burden, this process could also release significant value to the business.
Essentially GDPR gives more control to citizens and will allow them to understand what companies do with their data in order to safeguard their privacy. Under the new regulations, call or voice recording will be subject to the same strict rules that apply to other personal customer data. This means that businesses will be expected to protect customer privacy, notify them about any voice recording that takes place and gain their prior consent. It also means that, in order for the most appropriate security controls to be used and security policy to be enforced, any kept data will need to be properly classified, enabling the right security controls to be used to safeguard it, as well as enabling the enforcement of appropriate data retention policies. Businesses wishing to record calls, for example for staff training in a call centre, or to improve customer service experiences, must be able to demonstrate they have received explicit consent to do so from each customer. Under GDPR, businesses will be accountable and so must demonstrate the protocols and policies they have to put in place to gain consent and protect information in order to comply.
While data classification may seem difficult to address, doing it right could result in new opportunities for business value to be created, outside of pure regulatory compliance. Contextual discovery and storage really help with this. Using technology to automatically capture, classify and tag voice recordings will allow organisations to put the recording squarely within the context of other pertinent customer data and other customer communications that they already have. This will simplify GDPR compliance, because they can apply similar controls that are in place for other types of data of similar sensitivity. This presents a mechanism that will not only allow GDPR security policy to be more simply implemented, but that could also significantly improve customer engagement by providing the data required for contextual communication to take place.
What is Contextual Communication?
Rather than storing voice recordings in a silo of their own, combining them with other logged data about a specific transaction will help company marketers or sales people, for example, by understanding much more quickly why a communication was successful, what the markers were for the most productive conversations, and what a failing one looks like. These all help to build up a valuable deeper insight that can enable the business to make significant improvements to customer experiences.
This data can further be used to add context to business communications, so businesses can more effectively offer different ways for customers to get in touch with them in the context of the task they are doing. For example ‘app-less’ voice and video or text communication from within the shopping mechanism of a website, allows a customer to find information and then interact with the business via that website - importantly, from the environment, or context, that they’re already operating within. This gives every party more effective engagement, as well as aligning with the way today’s consumers want to communicate: it’s simple, accessible and instant. For businesses, it provides even more insightful data about how customers interact with businesses, including about their behaviours, attitudes, choices and so on, providing useful information upon which to base future systems, services and products.
Contextual Comms Leads to Better Machine Learning and AI
his base of classified, tagged customer data, placed in the context of the communications it pertains to, provides a solid foundation for future machine learning and AI projects that customer centric businesses are looking to implement.
Without that context, machine learning and AI are limited. Context helps limit the possible scenarios and outcomes meaning that a machine’s ability to give good or accurate answers and follow the right process flow is hugely improved. Using context helps because it is an intensive process to develop an AI or machine learning system to do learning for any arbitrary piece of knowledge; machine resources simply don’t exist to do that. Layering machine learning onto contextual communications reveals why a customer is there, what that customer’s journey was to reach that point, records the outcome combined and works out if the communication was effective or not, and finally provides ways to make it more effective if needed. By linking just the appropriate databases with CRM systems across the business – sales, marketing, contact centre – businesses can provide a really effective way to improve the workflows and processes that underpin customer engagements and experience, and feed that into machine learning databases. That contextual data about a customer, a transaction or big data trends allow better decisions to be made at the point of communication and enable a much more intelligent system that can deal with more requests.
Ultimately, businesses are keen to drive data-driven, personalised user experiences and the technology exists to deliver this. But context is the most important part in getting this right - without it, automation will fail, cause confusion and lead to frustration. At the same time GDPR regulations mean that many organisations are going through a process today of classifying their voice recording data. What a timely opportunity!
The convergence of contextual comms and AI has the potential to be really exciting, freeing up human to human interaction time to the areas where greatest value can be added. This is where we’ll see fundamental transformations in how the real-time enterprise of the future will communicate - via human or machine, or a mixture of the two - with its employees and customers in context: at the right time, with the right information at their fingertips, and in the right application.
This article was originally published by IT Pro Portal.