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Stratforge CX 

CX THROUGH AI


CX and AI – what is the deal?

“Among the many technology trends shaping 2019 and beyond, the adoption of AI when it comes to CX is one of the most exciting. The use of AI technologies such as machine learning, natural-language understanding and natural-language processing can help analyse customer sentiment and customer feedback at scale, precision and speed not achievable through humans.”
Gartner, 2019.

Why AI for CX?

The customers expect to have personalized, frictionless, on-demand and data-driven experience to help them make better decisions. However, to live upto the expectations of ‘always connected’ customer, the business must embrace the technology. Poor customer experience can lead to higher churn, diminished reputation, reduced recommendation and potential revenue leakage. Try Artificial Intelligence to deliver compelling experience on customer’s expectation significantly.

How?

Using Artificial Intelligence to deliver superior customer experience (CX) provides a competitive advantage to the organization alongside increased customer satisfaction, loyalty, and advocacy. Artificial Intelligence is a technology that imitates human psychology and intelligence. It can automate potentially any repetitive tasks and routines. The machine learns with data. It marks the pattern and improves the accuracy as it gets seasoned – yeah, just like how humans learn from experience and gets better to handle situations. However, the transformation/impact comes from the way it is used to engage and assist customers and employees. The factors driving today’s customer experience are the evolution of the digital economy, the growth of subscription services, multi-channel experience, knowing customer DNA, and trust for data privacy.

The business needs to have a well-defined approach embedding the following points to leverage AI effectively and implement a successful project.

Defined use-cases

The success of using artificial intelligence for customer experience requires clear use-case that provides the starting point to collect relevant data for AI engine. What are the customer touch points? What are the critical data that would impact the CX index? What auto triggers can be set? How can we device the potential AI powered next actions?

CX cannot be a driven in silo, bring ‘em together

CX is not a role or a process, it is a philosophy. Blaming ‘customer support’ division as a single point of failure for low CX scores does not make sense. Like how engine, tyres, gearbox + about 30,000 parts make a complete car, a business is a combination of all divisions, people, process. The business should have common goals across functional units. The departments should break silos and have common goals to get the best out of AI program.

Data integration and harmonization

The more you talk to the data, the more the data talks to you. A well-designed system architecture is essential for successful implementation of AI-based applications that connect and integrate with other systems to collect relevant data points and harmonize them. The blended data set fuel AI engines for learning, testing and thereby improving itself.

Ensure it seamlessly integrates with your tools and technology

Ensure that the ecosystem is matured to handle the AI technology. Choose a product/vendor who can seamlessly wrap on each-and-every component of the ecosystem. What is the point of buying a Ferrari when you don’t have proper roads to drive? The system should be well equipped to reap the rewards of AI. If you are building an AI solution that connects with the knowledge-base, ensure the knowledge-base is content rich, well organized and easily retrievable.

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