Customer Service Outsourcing in the Age of AI: 3 Areas Where BPOs Can Turn a Threat into an Advantage

In this post, Proxii's COO Diego Sanz highlights 3 ways BPOs can use AI to get ahead of the competition.

It’s no secret among BPO industry veterans that the proliferation of artificial intelligence (AI) and automation technology poses a challenge for the industry. According to one 2019 market report, BPO operators overwhelmingly said that “AI and Robotics” present the greatest threat to their businesses. The reason for this is that over the past decade or so, technologies such as robotic process automation (RPA) and Chatbots have displaced upwards of 10% of tasks traditionally performed by outsourced human agents. Perhaps the most visible example of this trend is in eCommerce customer support, where the most basic customer inquiries formerly handled by outsourced human agents are being replaced by the likes of Chatbots built into the eCommerce platforms themselves. But while these technological trends do mean that BPOs will have to adapt to a changing market, they also present an opportunity for BPOs to grow and differentiate.

There are many ways new AI technology can help BPOs evolve their business, yet all can be sorted into two categories – technology that improves operational efficiency, allowing BPOs to grow their margins, and technology that BPOs can sell as a value-added service, helping to fuel top-line growth. In this article I will focus on products that BPOs can utilize to improve their efficiency and lower their operating costs. A future post will address AI-powered value-added services that BPOs could, and should provide to their clients.

Area 1: Quality Assurance

BPOs have long performed QA by auditing a sample of call recordings or written communications and then making an evaluation. It’s an outdated process that is subject to sampling issues and reviewer biases, and is also a huge time-suck. An excellent example of a company using AI to dramatically improve performance in this space is Observe.ai. Focused on improving the performance of call centers agents, Observe uses AI to transcribe and evaluate every call and interaction conducted by an agent. It then uses these insights to provide coaching tips and actions for training and improving the performance of individual agents.

For BPOs providing chat and email support to their clients, MaestroQA is another strong option for providing comprehensive QA of agent performance when responding to customer support tickets. While MaestroQA doesn’t leverage AI to perform ticket audit independently, it does help automate the collection of high-quality ticket samples for grading and provide actionable analytics based on the audits. They also have a screen capture feature that allows managers to view recordings of agent’s screens while they answer tickets, which can help identify process improvements. For BPOs looking to leverage AI and automation technology to provide superior client services, both are a great options.

Area 2: Written Communications

My experience as a technology consultant managing offshore teams reinforced to me that written communications can easily be affected by educational or cultural differences. Whether it’s grammar, sentence structure, tone, or word choice, BPOs know the importance of their employees writing well. Grammarly is a company you may know from their omnipresent digital advertising campaigns, but they’ve built a powerful tool that assists their users in composing clear, grammatically correct writing. In their words, Grammarly is powered by a “sophisticated artificial intelligence system built to analyze sentences written in English”. In our experience it works quite well, and is certainly a solution customer support BPOs should consider implementing for their omnichannel customer support teams.

Area 3: Agent-Assist

AI powered agent-assist technology aims to provide important context and job aids to agents that enable shorter ticket resolution times, shorter ticket handling times, and faster agent training and ramp-up. It’s also an area we are focused on at Proxii. Proxii integrates with help desk systems and trains machine learning models on a clients’ historical ticket data. Once trained, each time an agent opens a new ticket, Proxii surfaces the best, most relevant ticket thread where the same issue occurred in the past, allowing agents to immediately copy over the correct answer and anticipate follow-up questions. It also uses AI to suggest relevant knowledgebase articles and ticket tags to improve both resolution efficiency and “ticket hygiene”. The magic is that Proxii creates unique models for each client and needs much less training data to be effective, meaning that clients start realizing benefits almost immediately, and sleep soundly knowing their data is separately and securely stored in an encrypted data warehouse.

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