Never in history have we had more access to affordable technology to change the way we live, work, and play. Yet despite this abundance of technology, many of an individual's experiences remain generic and unsatisfactory. Employees struggle to deliver meaningful customer experiences because they lack access to the right information, and even accurate data isn’t readily available in real-time.
Market leaders are changing this by building what Lopez Research defines as “Right-Time Experiences.” RTEs are enhanced business processes or services that deliver the right information or service experience, at the precise moment of need, to an individual's device of choice.
But RTEs aren't just for business to consumer engagement. Industry leaders are improving their business outcomes by creating new workflows for its employees and business partners. While there could be many types of RTEs, the three main categories include improving communications, care, and commerce. Enhanced communications experiences provide the foundation that fuels better customer care, and enables employees to work more effectively. Communications-focused RTEs also extend beyond person-to-person engagement to include person-to-machine and machine-to-machine interactions.
Defining the principles of RTEs
RTEs differ from many of today's experiences by delivering interactions that are contextual, adaptive, and connected across a company's data sources. The best RTEs use AI technology like natural language processing (NLU) and neural networks to provide predictive experiences, based on machine learning.
Many of a company's existing applications lack embedded communications. But it's not enough to add notifications, SMS, and calling into your applications and services. The best communication experiences will use more than one source of contextual information, such as location, time, sensor information, and data, to create personalized communications experiences.
Communications RTEs combine data from previous transactions with current contextual data points to understand what a user is doing and what would be useful. These communications experiences are persistent and consistent across physical and digital channels, allowing the organization to engage with people in their channel of choice. Persistence means the communication RTE will have knowledge of prior and current interactions, and that this data will seamlessly follow the user as they move between various communications channels.
Right-time experiences blend human and digital interactions, enabling 24/7 global engagement that leverages both humans and bots. RTEs benefit from real-time data, but a dialogue can also happen over a protracted period, based on a person's desired engagement channels.
For example, a customer on a smartphone might ask a bank's chatbot to explain a certain fee in the evening but request a callback at a specific time in the morning to discuss removing an erroneous charge. When the agent calls back in the morning, the context of the previous communications would be available to the agent. The bank may even choose to resolve the issue by removing the fee and sending a notification that a callback is unnecessary.
Contextual communications also apply to connected devices communicating with both people and systems. For example, if the humidity rises above a certain level in the paint section of an automotive manufacturing line, the environmental control software could contact the plant manager with a critical alert and automatically log a service request with the maintenance company.
Adaptive and connected across internal and external data sources
Most custom applications built for corporations are designed to work on a specific device, such as a PC, and lack personalization. Leading communication RTEs will operate across anything from tractors, to smartphones, to a TV. RTEs are sensing systems that understand device capabilities and use multiple types of communications functions such as messaging, SMS, conversational interfaces and bots. Ensuring they operate at full efficiency, though, requires some legwork.
Communications RTEs require companies to minimize data silos by connecting information across systems and integrating new functionality to create a new workflow. They also require companies to connect to data, functions, and services that reside outside of the company. They need application programming interfaces (APIs) that allow it to connect to applications, data, and services –– like reviews, product comparisons, transaction clearinghouses, authentication services, and click-to-call services.
However, it's not just consumer-oriented data up for grabs. Businesses are also providing API-accessible data to their partners, and IT will use this data to create RTEs that optimize workflow. For example, a manufacturer could make its inventory data accessible to its distributors’ dispatch systems with APIs.
Real-time experiences must be learning and predictive
An RTE learns and adjusts to a user's behaviors over time. If the user's context changes, the RTE should self-adapt. The best RTEs will make the technology seemingly disappear, leaving people free to do their job or perform a task without learning how to use an app, system, or process. A predictive RTE prevents issues and presents opportunities to the user. How could this work in real life? If an airline knows you're going to miss your connection, it can send a message to your mobile phone with rebooking options and methods of contacting customer care.
While we've had big data and analytics in the past, the declining cost of cloud computing, the availability of GPUs for training, and the emergence of machine learning software and services allows companies to take analytics to the next level.
Building the technical foundation
Yet, cloud-native platforms are what allow companies to improve customer and employee experiences by offering a wide range of functionality such as communications, authentication, and AI utilities.
Cloud-native platforms continuously deliver new features and functions while eliminating the need for IT to update hardware and software. Cloud-native platforms can rapidly and seamlessly scale to support peak workloads to improve customer experience. To successfully deliver RTEs, a company should embrace a cloud-native communications platform (CP). This CP should:
- Enable omnichannel communication for seamless support. Rich communications experiences require a company to support email, chat, voice, and SMS. SMS was the primary messaging app that companies had to support through the mid-2010s. To meet customers where they are today, companies must support globally adopted messaging apps such as Facebook Messenger, WhatsApp, and WeChat. While there may be several different solutions a company can purchase to support various communications modes, it's easier for IT to procure and monitor multiple communications modes with one platform.
- Deliver global, scalable connectivity. Companies should look for a communications platform that supports connectivity in multiple countries and offers multiple language support for voice and messaging. Selecting a global platform eliminates the hassle of managing multiple contracts in various currencies. It also provides one point of contact for technical support issues. CPs should provide detailed monitoring and visibility into call quality, performance data, and API operations.
- Support communications for the Internet of Things (IoT). We're in a world where things will communicate with people and other connected devices. Part of your communications strategy should be to add SMS capabilities in addition to cellular data to your IoT devices. Enabling machine-to-machine and machine-to-people communications requires APIs to link data into applications and the ability to messages to a person's phone. A CP can provide management for SIMs, APIs and tools for integration and communications.
- Integrate with your systems of engagement and record. A communications platform should provide tools that allow a company to integrate with its CRM system, marketing automation systems, and service desk.
- Help you embrace bots and conversational interfaces. In a world where everyone is talking to Alexa, Siri, and Google, a company must offer bots and conversational interfaces, or it will be left behind. A modern CP will help companies build conversational IVRs and bots that work across web and mobile chat, SMS, WhatsApp, and your contact center. Companies need the ability to design, build, and train bots using machine learning and natural language understanding. To do this, a company can purchase cognitive services from its cloud computing provider, use services that are part of a CP, or use APIs to connect its CP to its chosen AI platform. A platform should provide tools that help you streamline the process of creating bots such as baseline templates for bot actions, analytics, and contextual handoffs.
- Improve support for regulatory compliance and privacy. Selecting a cloud resident platform that offers a choice of data centers will allow a company to keep customer data within a specific geography. However, privacy doesn't stop there. The CP must provide a platform that will enable companies to support communications without sharing a person's number.
Cloud-native services, connected data, and analytics enable agility by making a company's systems and processes more intelligent, scalable, and interconnected. Right-time experiences are contextual services that leverage data, analytics, and artificial intelligence to change how a company communicates. RTEs can reshape a company's business models, increase collaboration, and improve customer relationships by leveraging cloud-native communications platforms that enable you to add multiple types of communications into your apps, services, and web sites.