Tech Wizardry

Reaching a customer service department should be easy, but that’s not always the case, and it leaves customers feeling irritated before even connecting with the brand. When they do connect with a brand, it's not always productive. They might start off with a bot. When that bot can’t help, they’re transferred to a human who asks the same questions they just answered. Herein lies the problem. In our personal lives, we can send images while we text and talk, and even participate in multiperson video conversations from the same device. Why is customer service so different?

Customer experience (CX) is more important than ever. The Global State of Customer Experience report states that “three-quarters of consumers switch to a brand competitor after just one bad experience,” underscoring that the CX you deliver is critical to success. In short, if you’re complacent about CX, you’re going to struggle.

Many people say omnichannel when they really mean multichannel. I don’t want to be a nitpicker, but the difference matters.

Customers use multiple communication channels to interact with your brand. One report noted that 86% of consumers expect you to recognize them across channels. They may choose from an in-store service desk, email, phone calls, in-app chat, chatbots, text messages, social media, live chat or even a self-service knowledge base. Omnichannel customer support is offering seamless customer service across all touchpoints. 

This is why omnichannel matters. People want to experience brands the way they experience communicating with friends and family: easy, on any channel (or every channel) and as fast as they want it to be.

Unfortunately, much of the business world is still stuck in the multichannel phase; many companies are still utilizing cumbersome, inflexible, on-premises technology and lack the knowledge/trust of a cloud contact center. But it’s really not optional to offer just one or two communication mediums any longer The time for brands to figure this out is now — or never.

Our omnichannel support CURSOR incorporates AI and natural language processing, enabling chatbots to learn over time with each interaction and dramatically increasing your organization’s ability to solve complex issues through automation – in addition to the human interaction customers still expect. AI-powered agent assistance can even use chat histories and insights to help coach human sales agents and improve their close rates and overall performance.

As machines increasingly complement human labor in the workplace, we will all need to adjust to reap the benefits.

Automation and artificial intelligence (AI) are transforming businesses and will contribute to economic growth via contributions to productivity. They will also help address “moonshot” societal challenges in areas from health to climate change.

While we believe there will be enough work to go around (barring extreme scenarios), society will need to grapple with significant workforce transitions and dislocation. Workers will need to acquire new skills and adapt to the increasingly capable machines alongside them in the workplace. They may have to move from declining occupations to growing and, in some cases, new occupations.

Beyond traditional industrial automation and advanced robots, new generations of more capable autonomous systems are appearing in environments ranging from autonomous vehicles on roads to automated check-outs in grocery stores. Much of this progress has been driven by improvements in systems and components, including mechanics, sensors and software. AI has made especially large strides in recent years, as machine-learning algorithms have become more sophisticated and made use of huge increases in computing power and of the exponential growth in data available to train them.

These technologies are already generating value in various products and services, and companies across sectors use them in an array of processes to personalize product recommendations, find anomalies in production, identify fraudulent transactions, and more. The latest generation of AI advances, including techniques that address classification, estimation, and clustering problems, promises significantly more value still. An analysis we conducted of several hundred AI use cases found that the most advanced deep learning techniques deploying artificial neural networks could account for as much as $3.5 trillion to $5.8 trillion in annual value, or 40 percent of the value created by all analytics techniques.

Our research suggests that, around 3 percent of the global workforce will need to change occupational categories by 2030, though scenarios range from about 0 to 14 percent. Some of these shifts will happen within companies and sectors, but many will occur across sectors and even geographies.

As intelligent machines and software are integrated more deeply into the workplace, workflows and workspaces will continue to evolve to enable humans and machines to work together.

We built our own AI technology called Transcendence to help our clients extract the most value from their investments. Our in-house AI experts apply customizable algorithmic models that optimize programmatic campaigns and engineer stronger outcomes.

We've already migrated to CDP from CRM while the world around us is still waking up to it.

Our Customer Data Platform (CDP) is a piece of software that combines data from multiple tools to create a single centralized customer database containing data on all touch points and interactions with your product or service. That database can then be segmented in a nearly endless number of ways to create more personalized marketing campaigns.
CRMs are for improving the personal interactions you have with your customers. CDPs are for understanding your customers and their behavior. They consolidate and manage all customer data across all touchpoints to gain a single, unified view of the customer. In aggregate, these “unified views” of many customers will reveal the entire customer journey.

Data Fabric Architecture is Key to Modernizing Data Management and Integration.

Gartner defines data fabric as a design concept that serves as an integrated layer (fabric) of data and connecting processes. Our Data fabric leverages both human and machine capabilities to access data in place or support its consolidation where appropriate. It continuously identifies and connects data from disparate applications to discover unique, business-relevant relationships between the available data points. The insight supports re-engineered decision-making, providing more value through rapid access and comprehension than traditional data management practices.

For example, a supply chain leader using a data fabric can add newly encountered data assets to known relationships between supplier delays and production delays more rapidly, and improve decisions with the new data (or for new suppliers or new customers).

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We identified the need for universal connectivity, where everything can be connected anywhere, anytime, in a transparent, accessible, and economical manner. The first to provide a mobile core infrastructure as a cloud service, Boolean enables secure, reliable and scalable connectivity, in ways previously impossible.
The architecture of the Boolean infrastructure follows the concept of layered Cloud Computing - deploying Edge Computing as an additional layer of data distribution, storage and analysis.

Edge integrates centralized and distributed architectures. Cloud and the edge work hand in hand to enable new experiences. Data is generated or collected in many locations and then moved to the cloud, where computing is centralized, making it easier and cheaper to process data together in one place and at scale. Edge computing uses locally generated data to enable real-time responsiveness to create new experiences, while at the same time controlling sensitive data and reducing costs of data transmission to the cloud. Edge reduces latency, meaning it lowers response time by doing the work close to the source instead of sending it to the more distant cloud and then waiting for a response.

We deliver robust, secure IoT solutions that comply with all major industry standards. Our IoT team is in the loop about all types of communication and network protocols, hardware interfaces, and sensors. Powered with custom business intelligence algorithms, our tools help improve decision-making.

With our SaaS Integration System, software is delivered and ready-to-use over the internet. SaaS provides already developed software, through a monthly or annual subscription, without any responsibility to maintain the software. It involves the delivery of an application as a service that is ready-to-use and hosted in the cloud. Accessed through any internet browser, SaaS often increases overall ROI since it doesn’t require any maintenance or updates by the user. With its cost-effectiveness, it has become a vital tool in sales, communications, customer relationships, and project management.