The widespread availability of software solutions augmented by artificial intelligence (AI) have boosted their popularity and uptake within the enterprise space over the past five years.
An IBM survey revealed that 50% of enterprises are already taking action to deploy AI, using it to quickly access insights and automate processes.
The value of AI-powered customer experiences
Companies have been adopting digital systems to improve customer journeys since long before the pandemic, but the urgency to provide meaningful, personalized digital customer experiences has accelerated over the past couple of years.
The majority of executives surveyed (57%) say that responding to customer demands for more personalized experiences is their number one reason for adopting AI, and they plan on embedding it directly into new touchpoints with their customers.
The best way to do this? Optimizing the use of the customer data collected in the field.
AI can be used to track individual interactions throughout a customer's journey and identify areas of improvement. This helps support experts in creating memorable customer interactions, providing customized recommendations augmented by learnings from previous interactions.
AI is only as reliable as the data it is fed
Customer experience (CX) owners expect the adoption of AI solutions will trigger change in many aspects of their business, including new business models, improved brand loyalty and differentiation, and customer experience. However, 47% of executives are unsure if the customer data they are using to inform these strategies is reliable and sufficient.
This data is a field team's most valuable resource. In order to derive accurate insights from company data, it needs to be captured and labeled reliably and consistently from the start.
Accurately labeled data ensures reliable pattern recognition, forming the foundations of an effective data insights engine specific to a company's needs.
Supporting the strategic shift to AI-powered CX
These are three areas where companies can focus on building a jump-off foundation for their AI-powered customer experience strategy:
1. Reliably capturing customer data
Optimizing the use of customer data is becoming increasingly important for companies looking to create meaningful, personalized customer experiences and differentiate themselves from competitors.
This becomes difficult when data is not captured or organized in a central location for team members to contribute to and managers to access.
By using a secure virtual service platform to passively capture and store customer data, companies ensure their data is reliably collected and labeled in a centralized location to derive accurate insights and analytics from, both in real-time and over the years to come.
2. Creating a comprehensive roll-out strategy
Companies looking to augment their processes with artificial intelligence should be looking at the transformation as a strategic shift, not as another ‘tool’ or a technology upgrade.
By building a governance program to oversee the cross-functional data collection, and identify potential use cases and activities the data insights could be used to inform, companies are better prepared to roll out a comprehensive strategy that doesn’t silo the inputs from individual departments.
Customizable virtual service platforms are tailored to specific industry use cases and requirements, designed to capture and create actionable insights from data collected across the organization, taking stress off of field teams and providing a smooth road to implementation and organizational change.
3. Enabling the workforce
A common misconception about artificial intelligence is that it’s taking away existing jobs, creating fewer opportunities in the workforce. Gartner reveals that the opposite is true: the more organizations implement AI, the more jobs it creates.
These jobs will fall into two categories — jobs directly related to implementing AI within the organization and jobs created by the opportunities for scale that AI provides.
With a comprehensive change management program, companies can re-skill existing experts to provide data-powered service, and create more engaging job roles where an expert’s main focus is on creating meaningful customer experiences instead of manually resolving issues, or collecting and interpreting data.
Build a foundation first, and then scale
Balanced AI/CX experiences are key in creating scalable data-driven journeys for both customers and experts, ensuring that companies can stay agile and competitive as digital shifts occur in their industries.
Instead of casting a wide net and hoping for meaningful results, companies should hone in on finding the best solutions to real problems within their organization first. This way, they will gain impactful and actionable insights that they can build on as they scale.
For more information on how ICwhatUC's data insights can help companies gain a better understanding of their customers and processes, book a demo!