Rob Pickering, CEO at IPCortex, explains how UC resellers can differentiate themselves through context, AI and machine learning
Unified communications (UC) is increasingly positioned as an opportunity for resellers to reduce their overheads, rather than to differentiate their offering.
Demand for traditional telephony is declining. Yet, at the same time, end users and resellers alike are becoming frustrated with a major ?aw in the way many UC tools are built: instead of ‘unifying communications’, they’re actually fragmenting and complicating it because they’re built and operate in silos.
These problems are significant for the IT reseller community, which is under increasing pressure to differentiate services to remain competitive and relevant lest they simply join the ‘race to the bottom’ in terms of pricing for UC.
So what is the answer? One solution is contextual communications, where rich media communications, like voice, text and video, are embedded inside an application, website or device and are an integrated part of the workflow and processes that it facilitates, rather than merely being an adjunct.
By turning a standard web browser into an endpoint with no need for apps or plugins, open (and now pervasive) WebRTC technology puts an end to silos and makes UC easily accessible. It is a great enabler for efficient communication because it allows instant person-to-person (and person-to-application) interactions centered around a specific task.
A typical example is voice and video communications from within the shopping mechanism of a website so that a customer can find information on a product and then interact with the retailer via its website – i.e. the environment, or context, they’re already operating within – with no disruption to what they were already doing.
A great opportunity
Contextual communication makes it easier for the channel to offer open, joined-up solutions that allow people to interact with businesses, customers and the real world using all, and any, available media. It presents a huge opportunity for resellers to add value to their customers’ businesses by building out value-added services or applications for a vast array of scenarios.
In customer-focused businesses, for example, service agents can much more quickly and easily identify the reason a customer is contacting them. They can see instantly which web page the customer was on when they hit the ‘click to call’ button, how they got there and what other services they use. Additional context, such as that customer’s previous contact history or CRM record, sets the stage for more meaningful interactions.
Adding context to communication can also form the foundation for entirely new services. Housing associations and other organisations that provide accommodation for vulnerable people are already improving daily contact for thousands of people in real time. By analysing patterns of communication, they can identify when the cognitive state of an individual is changing and give a predictive assessment about the needs of every resident calling in to them before they answer the call.
Paving the way for AI
Contextual communication also paves the way for automated communication. By adding context to communications now, organisations can build up a database of learning that they can draw upon when AI becomes more widely available.
In its simplest form, machine learning is pattern recognition, and the more patterns it can draw upon (i.e. the bigger the database of conversations and real-life data), the more successful it will be at understanding intonation and sentiment and providing an intelligent response. Logging why a communication is successful and creating markers for the most productive conversations – and the least successful – will help create a valuable database. By beginning to capture, classify and tag business communications, including call recordings and automatic transcriptions, businesses can get a head start in preparing for machine learning and AI automation.
Without context, machine learning and AI are severely limited in their ability to give good or accurate answers and follow the right process ?ow. Layering machine learning onto contextual communications reveals why a customer is there and what their journey was to reach that point, it records the outcome and it works out if the communication was effective or not.
By linking appropriate databases with CRM systems across the business (e.g. sales, marketing, contact centre), businesses gain a really effective way to improve the workflows and processes that underpin customer engagement and experience, which they can feed into machine learning databases. The contextual data about a customer, a transaction or big data trends allows better decisions to be made at the point of communication and enables an intelligent system to deal with more requests.
UC has long provided opportunities for resellers, but the game is shifting thanks to digital transformation and changing customer behaviour. Today there is far less value and opportunity in simple telephony solutions and frustrating rich media tools built to operate within strict walled gardens.
In order to differentiate and add value, the channel needs to start building new value propositions that map onto this change and embrace the flexibility needed to meet different customer requirements. Contextual communication is the open, pervasive and simple response needed to do this.
If a reseller can build compelling propositions around contextual communications, they can lay long term foundations for lasting profitable relationships that will also see them adopt the latest AI and machine learning automation technologies. It’s a win resellers and their customers.