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Rapid advances in speech recognition and processing technologies, coupled with the advent of many new intelligent sensors and interfaces have helped voice interfaces gain acceptance in hundreds of millions of households worldwide.
With a Community of Practice, Reply is building a conduit to gather, concentrate and channel its UX and technical know-how, providing enterprise voice solutions to customers from various sectors.
There is a huge gap between the human ability to speak, type, read and listen. While Anglophones can read an average of 238 words per minute (wpm), they are only about half as fast when listening. Therefore, caution is needed when writing speech dialogues.
Voice-driven applications are only successful if:
they have been designed according to best practices which are often radically different than those used in classical UX-Architecture;
the use case for the application is relevant and adds value;
they are properly placed within the customers‘ digital ecosystems, to enhance the entire spectrum of available touchpoints.
The transition from "screen design" to "voice design" holds several challenges. Reply supports you in overcoming them by designing interfaces that are not only functional, but also attractive.
With the right strategy, frameworks for seamless integration of all CRM touchpoints can be implemented in a way that allows a customer journey to be paused and resumed without loss of progress or information.
A HOLISTIC APPROACH TO CRM SOLUTIONS
CRM analysis and consultation for creating seamless UX across all touchpoints.
Finding the gaps
Naming the KPIs
Finding the best technical soultions
VOICE SOLUTION PROGRAMMING FOR ENTERPRISE CRM UX
Create and implement the entire UX and CRM environment
Designing, programming and publishing of voice solutions
Integration into existing systems
MAINTAINING THE EFFECTIVENESS OF A SPECIFIC CRM LANDSCAPE
Measuring success by revisiting and re-analyzing
Identification of new possibilities and touchpoints
Maintaining the infrastructure
Continuous UX and brand analysis
How can the Reply Voice-First Strategy help your company take full advantage of the voice revolution?
Whereas a “simple” digital assistant in the form of a chatbot or skill is an offering which is necessarily limited in scope and vision, the voice-first approach would allow for a holistic, top-down perspective of a customer’s entire digital landscape, embracing the next digital revolution, enhancing brand safety and dramatically boosting efficiency and customer satisfaction.
In an intensive workshop with a customer, Reply experts identify all possible enterprise touchpoints, applications, data pools and devices which play a role in their business processes. Then, coupled with the corporate tonality, we collaboratively visualize the entire voice-driven digital landscape.
In the future, many more business processes will be controlled with voice interfaces. Corporations which embrace this trend by implementing a global strategy – rather than a collection of single, unrelated solutions – will best profit from voice technologies.
No, a Voice-First Strategy involves input from brand-driven design, marketing experts, conversational designers and programmers alike. To create an engaging voice experience, tonality is as important as sentiment analysis, for instance.
Smart Assistants, particularly VUIs and NLP, will be most relevant technologies for the next interface revolution as Voice Interface Recognition accuracy gets closer to Human levels.
Therefore, Reply leverages various technical approaches and methodologies to create comprehensive conversational experiences.
Automatic Speech Recognition
Natural Language Processing
Natural Language Understanding
Automatic Speech Recognition is the interdisciplinary field of computational linguistics to develop methods for translating speech into machine language – in other words, breaking down the sound of our voices into binary language which can be digitally processed.
Natural Language Processing is a field of computer science concerned with the interactions between computers and human languages, in particular how to program computers to process and analyze natural language data. NLP can refer to a range of tools, such as speech recognition, natural language recognition, and natural language generation.
Natural Language Understanding is a subtopic of NLP that deals with comprehension. Furthermore, artificial intelligence and machine learning pattern recognition can be used for sentiment analysis to attempt to determine the tonality and meaning of spoken or written input. Natural language understanding can be applied to a lot of processes, such as categorizing text, gathering news, archiving individual pieces of text, and, on a larger scale, analyzing content.
Voice experiences are radically changing the way we interact with technology. Connect Reply joins the physical and digital world, crafting amazing IoT technology. Connect Reply is experiencing the true beginning of the Internet of Things era, in which the physical and digital world talk to each other and empower people and businesses.
The quest for increasingly “humanized technology” is more than a major key to finally integrating
chatbots as natural companions in our everyday lives, it also represents an opportunity to enter a
whole new world of human-machine communication. Elbkind Reply introduces the
new age of creative tech and social media with the potential to bring machines and people closer together than ever before.
The goal of Reply Digital Experience is to create sustainable customer journeys. From end-to-end customer engagement to commerce solutions, the offer includes innovative technologies, data-driven insights and active creativity. Transformation consulting, CRM and service design are additional key areas.
Reply supported a big German automaker with millions of enquiries about their products.
Data Reply developed a multi-threaded text analytics service that takes the stream of text documents, applies NLP methods to retrieve significant entities and keywords, clusters the documents hierarchically and generates intuitive labels.