5 New Advances In AI For Customer Service You Can Expect To See In 2020
Compared to other technology used in customer service, AI is still in the early stages. It’s developing at a fast pace though. In 2020 we’ll see important advances, as thousands of researchers work to push it forward into the mainstream.
As AI becomes more ubiquitous, we’ll see more practical uses of this technology across industries, especially in the field of customer service.
One reason customer service is a fantastic experiment lab for AI is that people are continuously demanding better service and faster answers from businesses. People don’t want to wait longer than necessary to get the help they need. They want their answers fast. According to McKinsey, three-quarters of online customers expect help within five minutes. That’s a lot to ask from a human agent! With the help of AI, this and other challenging goals, like automating end-to-end requests, will become more common.
Here are five ways AI will play a bigger role in customer service in 2020.
1. Deeper integrations between AI and business systems
Customer support centres are one of the main functions that will feel the impact of AI advancements, which can completely transform the way they work. It helps that customer service is an area with a huge amount of data. With all that customer history, service logs and repetitive questions, it’s the perfect candidate for using AI. With machine learning, AI can learn from all the data, improving the quality of its predictive power.
But none of that is new. What will change in 2020 is the level of integration between AI and various business systems. Rather than being a standalone platform or an add-on, AI will become the thread that pulls organizational data together.
Because more software is being developed as API-first, tools can integrate more deeply. AI software can access processes and data with read/write privileges. This means processes can be automated across multiple tools; including help desks, CRMs, system logs, internal tools, billing software and more.
With the AI no longer being restricted to just learning from conversational data, customer service teams can offer an end-to-end experience to their customers.
2.Real end-to-end process automation
There’s probably only one thing worse than arriving at the airport and finding out your flight has been cancelled: being unable to reach your airline to rebook your flight because their customer support is swamped.
The year 2020 will see the use of AI that doesn’t stop at responding to simple queries but fully resolves cases, even when they involve digging with your own backend systems. Combined with deep learning, AI will drive entirely automated actions through APIs integrating with your CRM. That’ll allow for fast, effective end-to-end resolution of customer inquiries.
Here are some examples of actions where AI will be able to provide a solution without the interaction of a human agent:
-Returns and refunds
More than 75% of consumers expect customer service agents to have some information about their previous interactions and purchases, yet nearly half of customers say agents almost never or only occasionally have the context they need to solve their issue.
That’s not only a missed opportunity to serve your customers better, but it can also cost you money. Brands that excel at personalization boost their sales by more than 10% over companies that don’t personalize.
Unfortunately, when agents spend time digging for the information they need also risk increasing the response time, which can affect customer satisfaction negatively. What if you didn’t need to choose between the two? Personalization is one of the areas where AI can have a greater impact, as artificial intelligence will always be better at processing data and looking for information.
StitchFix has designed a framework that determines the most effective strategy for engaging customers based on their previous interactions. “This allows us to personalize the action taken on each individual client, rather than simply applying the overall best tactic,” explains Divya Prabhakar, Data Platform UI Engineer at Stitch Fix on the TOPBOTS blog. “For example, while Tactic B might perform the best if applied to all clients, there are certainly some clients who would respond better to Tactic C.”
While StitchFix primarily uses this algorithm to maximize outreach engagement, the same approach can be used to anticipate the best response to a customer’s service inquiry. Will this particular customer respond best to a refund or do they simply want a discount on their next purchase? Previous interaction history can help agents make the best decision resulting in the best outcomes.
4.The beginning of Cognitive Document Automation (CDA)
Cognitive Document Automation, or CDA, is something we’ll hear more of in 2020. CDA refers to the transformation of data found in documents to deliver information. In practice, CDA allows you to know what the document is about, what information it’s found in it and what to do with it.
Organizations that use a lot of documentation, like hospitals or insurance companies, will be the first to benefit from advances in CDA. Document-based processes like intake forms and scans will be made more efficient by automating the acquisition and understanding of the documents and information contained in them.
For example, CDA will make it really straightforward to read invoices. This frees human agents from the repetitive data entry task. The key is that CDA doesn’t require rules or templates to “read” documents. With the help of only a few samples, AI uses machine learning to automatically recognize the invoice’s fields. Then, the system is able to extract data like the currency of the invoice. The technology used by CDA is not new but 2020 will see a major push in how AI algorithms use machine learning to process documents.
5.Steady growth for VR and AR technologies
With the arrival of 2020, VR (Virtual Reality) and AR (Augmented reality) will sound less like catchy buzzwords and more of a reality. Market research firm Statista found that the growth rate of AR and VR spending in retail is forecasted to be 103% worldwide between 2018 to 2023.
While not always directly linked to customer support, VR and AR will play an important role in how technology can help businesses improve the overall satisfaction of their customers. For example, some companies are using VR and AR to complement and improve customer experiences online or at events.
With AR you can, for example, point your phone’s camera in an empty room and it’ll show you a sofa so real that you’ll think it’s there. That’s what IKEA has done with its Place app.
Furniture retailer Ikea Place’s app lets you put virtual objects in real scenes to preview how new furniture might look in a room.
Tools like ZapWorks make AR more accessible to the average company. Developers can build their own AR-based apps on the ZapWorks platform, or hire their consulting team to design and deploy a custom-built tool. Customer service teams can use this opportunity to improve the customer experience in a variety of ways:
-AR-based troubleshooting apps for routers, POS systems, and game consoles
-“Try before you buy” AR catalogues
-Onboarding manuals that use AR for clearer guidance.
2020 will be the year where VR and AR transition from being still relatively underused to being widely adopted. That means that the technology will really develop this year just before reaching the masses next year!
There are plenty of areas where AI will make an impact in 2020, but you can expect dramatic changes in customer service.
The use of AI in support won’t be just about chatbots redirecting issues to agents but about full end-to-end interactions. Combined with the use of deep learning and internal APIs, you’ll be able to use AI to completely automate requests which until recently needed some sort of human interaction. Changing your seat? Process a refund? All that will be done by AI from start to finish.
In 2020, AI will help companies deliver better, faster customer support and save money. Ultimately, that’ll free human agents to focus on designing a great customer service strategy that works best for their customers and business – instead of replying to questions they’ve already responded to a hundred times before.