Don’t cheat on data for better CX

Interconnected people icons depict the complexity of customer data needed for the best CX

This exciting chapter contributes to the release of our recent CX Trends 2020 whitepaper.  Here we focus on facts over assumptions and how insight and client feedback have re-shaped our approach to delivering Customer Experience as a Service (CXaaS). For example, customers continue to share their common frustrations with today’s consultants: “Clients no longer just want to hire legions of people, however brainy they are. They want consultants to provide and install products, including new technologies, that transform them from top to bottom and keep disrupters at bay.” This sentiment was reinforced recently by The Economist.

We understand that today’s market needs partners who can advise and more importantly, integrate. At HGS, we’re owning the technology interactions and automation across voice, chat, social, email—and the analyzed insight of all these touchpoints—to deliver customer predictability. When assisting clients with their digital maturity roadmap, we focus on staying true to the data science and analytics. From an automation perspective, our value as an organization is delivering a frictionless experience, and we achieve this goal with data. This is why we’re passionate about our clients having a clear understanding of the real meaning behind cognitive automation and what it entails.

Cognitive automation starts with data

By definition, cognitive automation is completely data-reliant and includes the combination of machine learning, deep learning, neural networks, natural-language-processing, and sentiment analysis. This combination of data tools, models, and techniques do their best to mimic human thought.  If we break down those attributes a little further, it becomes clear that each of these processes are completely data-dependent. For example:

  • AI is a subset of data science
  • Machine learning is a subset of AI & data science
  • Deep learning is a subset of machine learning, AI & data science
  • Neural network is a subset of deep learning, machine learning, AI & data science

The flow above represents the automation journey where machine learning becomes a relatively predictable model and starts to connect data patterns toward a known or desired outcome for the user(s). We then progress to a more self-driven model where machine learning shifts to deep learning and the input sees the machine making up its own classifications with unpredictable data patterns; this delivers several outcomes. In the neural networks phase, the model is similar to deep learning, but further classifications and unpredictable patterns attach themselves to new and deeper connections; this is closer to the neural workings of the human brain for real-time decision making. With no human intervention, neural networks also deliver several outputs. Keep in mind that these innovations all rely on data inputs to start the process. It’s the accuracy of that information that determines the quality of the outputs. A fantastic article that speaks to the importance of breaking down these terms for a more methodical approach to automation in 2020 is by Tom Foremski at zdnet.     

Our expanded collaboration for CX innovations across analytics, cloud, omnichannel and automation has led to the new consulting arm for HGS Digital—our response to the market need for a tech partner who owns the vendor stacks connecting martech with customer touchpoints to deliver Customer Experience as-a-Service (CXaaS). Decades of customer interactions have fine-tuned technology and human interactions for the HGS-coined term “BOTS & BRAINS”.  This success sees scale from the HGS Digital expansion to include 360-degree customer profiling that allows for predictable insight, which translates into quick and accurate service. To define who we are—and our value to you in this over-crowded technology market—we need you, our clients, to correctly understand the term “cognitive automation” and the importance data analytics plays in that process.

The meaning of "cognitive" in cognitive automation

When we mention “cognitive” in automation, we are referring to the connection with Artificial Intelligence (AI), a huge over-arching umbrella term with several automation categories. We need to be clear that AI and all these connected categories are sub-sets of data science. This is incredibly important because data, combined with the HGS Digital strategy, forms the backbone of all our successful innovations. This explanation is supported by , Director of Data Science HGS Digital who speaks to the importance of cognitive automation from an integration perspective. Yas stresses that keeping data in siloed technology stacks negatively impacts  omnichannel insight within the “Cognitive” Contact Center.

When starting discussions on automation, conversations rarely see clients reference the access, security, or quality of data.  This raises the question of whether today’s clients truly understand that cognitive automation is a data-oriented conversation. When discussing how to leverage bot technology for customer experience that moves the needle, several clients and analyst firms (Ryan Strategic Advisory and NelsonHall) all confirm that the "devil-is-in-the-design", and there is value in acknowledging the daily human discussions and interactions that are working for their customers now. Therefore, it’s important to start with a baseline for what’s working, and this all starts with the data and analytics. Follow that analysis with a data-based, elegant execution of front and back-office automation—along with intelligent escalation—and your team can focus on the important and complex tasks as experience ambassadors.

Today’s automation can be purely binary for standard information about deliveries, opening times, etc. All of this has value when you're replicating on-demand information, but the market expectation has shifted to something more enjoyable, more intelligent, and more data-based. The data available today for customers includes historic information streams, and when combined with machine learning, we now have a starting block for:

  • Customer name by data-dip to Customer Relationship Management (CRM) platform
  • Purchase history by data-dip to account data
  • Trend of topic conversations by product and market segmentation with Customer Data Platform (CDP) 

This is a start to personalization; escalating the conversation with the appropriate human-based counterpart would be one value example.

Why HGS Digital's CXaaS?

A group of electric bulbs with the 'Settings' icon inside all of them and only one of these electric bulbs is lit up

At HGS Digital, we believe there’s more value in the bot, now more commonly known as an IVA (intelligent virtual assistant). We are starting to see the real building blocks that can connect among technology stacks, data, and natural language conversations for a more accurate 360-degree customer profile. If we take the current customer conversation together with historic data and run models for the available and likely outcomes based on that customer profile, we have a true value add over a 24x7 binary response. The IVA running several data models maintains the active discussion, but this only meets what the customer was expecting.  Decisions for the best-matched response by calculating several conversational models changes the game entirely. This would be roughly equivalent to your customer services team having a natural conversation that keeps the customer engaged while simultaneously absorbing every piece of historic data on every platform.  They would then be cross-checking that with the current conversation, and the consolidated data would then be further cross-examined to market segmentation and the customer profile to predict what that customer most probably wants to hear next.

All HGS digital practice leads innovate with data in mind and our slickest cloud-enabled experience still relies on raw data for determining what we understand about the customer’s profile, their past interactions, habits and expected interactions for a predicted desired outcome. 

To understand what this all looks like as a real solution, proof of credibility is in the pudding and I am delighted to share real cognitive automation for HGS Digital CXaaS.

To help us assist you with the nest stage in your digital maturity roadmap, please arrange a discovery session with  and let us workshop the data behind your customers' experience.


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HGS Digital provides intelligent automation, AI, analytics, cloud services, and DigiCX® services to leading enterprises. Specializing in a technology-agnostic approach, our solutions help to improve customer engagement, optimize operations, reduce cost and increase revenue.