30 Aug How to maximize your contact center AI ROI?

Contact centers are at a crossroads. The pandemic has forced them to relook at their overall resourcing strategy. Besides the forced remote working and constrained access to talent, contact centers face external competition. Different industries in the US are competing for the same contact center labor pool, and that is likely to continue upward pressure on resource availability and wages in both the short and medium-term. Many contact centers are therefore deploying technology that reduces overall need for human resources, especially for customer facing roles. All this has accelerated focus and adoption of contact center AI solutions.

Robust contact center AI strategy is a big challenge

89% of CX professional believe in the importance of using AI in contact centers and acknowledge its role in improving CX. Yet, most organizations lack a coherent and exhaustive contact center AI solution. There are multiple reasons for the lack of success that plagues AI deployment in contact centers.

1. Limited clarity on objectives – Most organizations approach AI deployment without clarity on the objectives and what AI is meant to achieve for their contact centers. Hence the solution development and its integration with the existing workflows are impacted. Moreover, they aren’t sure how to measure success of their program and which metrics to use – AHT, ASA (or wait time), FCR, deflection rate or any other metrics.

2. Creation of channel siloes – While chat has been the primary channel using self-service, for rest of the contact center, voice continues to be the preferred channel. By applying A automation in pockets, the contact center AI journey creates channel siloes, with each channel competing against others and delivering different levels of experience

3. Lack of domain understanding – Customers expect AI to be domain-aware and provide contextual, intelligent answers. The days of dumb chatbot are gone but majority of contact center AI solutions operate rely solely on speech recognition and natural language understanding which are useful when it comes to generic intents, but fall short when complexity and domain intensity goes up.

Along with these tactical issues, a lot of organizations feel overwhelmed about AI deployment. The usual challenges highlighted include access to a team of data scientists, availability to large pool of training data sets, long implementation cycle periods for AI, and lack of post-implementation vendor support.

AI delivers quick response, omni-channel experience, and domain expertise

Avaamo launched the Contact Center AI State of Market 2021 to identify how customer expectations have changed in a post pandemic world, and how to leverage Contact Center AI automation to improve CX. Instead of relying on traditional survey-based research and the endemic issues of survey design, selective participation and extreme response bias, this report analyzed “actual” interactions, this report studied over 2 billion customer interactions across 18 countries and 9 industries, diving deep into the customer behavioral data and real time interaction preferences to understand the ongoing CX transformation. The insights coming out of the analysis outline the key aspects of customer service that matters to the customers and are therefore critical to the success of contact center AI implementation.

Zero Call Waiting (ZCW) matters, AHT does not:
The pandemic has forced us to confront the ultimate reality of contact center metrics. 90% of the customers rate immediate response as important. Customer wait has become the defining factor for CSAT. Wait time of 4 mins results in abandonment rate increasing by 25%.

It’s not the Channel, but the Experience that counts:
Customers’ acceptance of self-service and automation has increased. Customers’ comfort with voice self-service has increased over time, with voice experience matching chat self-service. By breaking channel silos, AI automation drives consistency across channels, delivering true omnichannel experience.

Customers are embracing AI-in-the-Loop, if it reduces wait time:
67% of customers prefer self-service than speaking to a human agent. The research revealed that Contact Center AI automation reduces agent and customer effort by reducing AHT by 22% and improving FCR to 83%.

Domain creates Differentiation.
The data reveals that Contact Center AI technology that offer domain-ready AI models and workflows accelerate time-to value. Whether its claims processing, vaccine scheduling or HR onboarding, domain-based Contact Center AI technology delivers 60% reduction in go-live time for automation projects and 23% reduction in live agent transfer.

It doesn’t take a Village to deploy AI.
The study analyzed successful Contact Center AI deployments, from pre-implementation to go live and identified key factors that accelerate time to value. Deploying pre-built AI models reduces implementation time to 6-8 weeks. Pre-built integration to existing contact center infrastructure reduces implementation cost by 20%.

Contact centers are increasingly using automation – not only to improve efficiency, but customer experience. The Contact Center AI State of Market 2021 uncovers key strategic factors that have significant impact on the success of AI-led contact center automation. You can read the full report at: https://avaamo.ai/contact-center-ai-state-of-the-market-2021/.