The Art and Science of Discovering What Your Customers Really Need
Tap into engagement and abandonment signals to understand customer intent in real-time
Jacada is focused on enabling automation and optimization of processes across the customer service value chain. Its ability to combine RPA and conversational AI capabilities to deliver an integrated customer service automation solution is one of its key strengths.
What is Real-time Intent?
Real-time intent is the process of discovering a customer’s needs, both hidden and those explicitly expressed, using conversational AI, data integration and user experience analysis during a live interaction between a customer and one your digital associates (intelligent virtual agent) or human associates (contact center agents) regardless of the modalities (voice, messaging, rich user interfaces) used by the customer and the agent.
Why Real-time Intent Matters Now?
#1 Easily Resolving Issues
#2 Anticipating Needs and Personalizing CX
#3 Knowledgeable Agents
Top 3 Factors Impacting CX – NTT 2020 Global Customer Experience Benchmarking
Customers get frustrated when their data isn’t used effectively to anticipate their needs and personalize the experience.
While there are many ways to prepare historical insights and generate next best offers, only 7% of organizations have figured out how to harness all that insight in real-time. This might explain why 81.6% of organizations believe that CX offers a competitive edge, while only 12.1% receive advocate level, and 42.9% receive detractor level net promoter scores from their customers. What’s aggravating is that these numbers have gotten worse in 2020.
One thing that’s clear: the ability to tap into insights in real-time and personalize the customer experience and the agent experience will separate leaders from laggards.
How to Discover Customer Intent in Real-time?
Your customer data is distributed across a growing variety of data sources. Customer intent is also hidden in everyday customer interactions. Rather than building a deeper data lake or solely relying on conversational AI, we believe that the better way to tap into your customer insights in real-time is in using what we refer to as intent flows.
Get to know the Intent Flow – an intent flow is a software component that processes data from a variety of data sources, evaluates business rules and personalizes the customer experience and the agent experience in the context of the customer’s chosen touchpoint and supported modalities. You can invoke an intent flow based on events generated by systems as well as by humans, creating infinite opportunities for intent discovery and personalization.
#1 Intent Powered by Conversational AI
Understand your customers in over 100 languages as they text or talk. Assist your customers and agents in real-time with intelligent virtual agents built in our no-code designer. Industry-leading conversational AI from the likes of Google, IBM, Microsoft, AWS, and Facebook. Pick your favorite services for intent recognition, sentiment analysis, speech synthesis, cognitive search and more. Blended to suit your unique needs and budgets.
#2 Intent Powered by Cross-Channel Journey Insights
Enable customers to switch channels easily, with an ability to pause and resume interactions regardless of whether they are in self-service mode or being assisted by your contact center agents.
Fire up an intent flow, share the customer’s journey insights so that the contact center is clued in should the customer seek live support. Offer effortless omnichannel experiences without having to upgrade to your next cloud contact center platform or CRM – that’s the power of contact center automation.
If the customer intent is recognized in self-service...
The agent assistant can leverage information about the customer’s intent to recommend the next best action and offer targeted guidance for the agent. While this saves AHT, it also offers a great customer experience where the customer is not required to repeat themselves.
If the customer intent is not recognized in self-service...
There are times when the self-service channel has been unable to recognize the customer intent accurately. In such cases, we recommend asking the customer to express their needs in their own words. The agent assistant can then process the natural language input to detect intent at the beginning of the live interaction between the customer and agent. This improves the quality of intent recognition and an organization’s ability to boost self-service automation without adversely affecting the customer or agent experience.
#3 Intent Powered by Agent Desktop Analytics
Discover opportunities to guide the agent to next best actions and automations by tracking what the agent is doing on the agent desktop. Attended RPA bots track agent desktop activities including the app that is in focus, data entered by an agent, and so on. The desktop automation bot can flag critical events and intervene with event driven automation and guidance so that the agent can stay focused on the customer experience.
RPA powered desktop intelligence complements conversational AI to develop a better picture of the real-time needs that surface in complex customer interactions. The capability comes in handy to prevent errors and fraudulent activities, as well as to guide the agents to next best action and next issue avoidance.
#4 Intent Powered by Customer Data Analytics
CRM systems and commerce platforms have been great at recommending next best actions to boost customer lifetime value. Real-time assistants should synthesize such recommendations typically at targeted points within a live interaction with a customer to maximize chances of customer buy-in or sales conversion. Furthermore, the best virtual agents and agent assistants not only present such offers but also help agents with the block and tackle needed to execute on those next best offers and drive the desired outcomes.