AI for Customer Support Can Help Build Trust

For many businesses, AI is becoming a familiar part of everyday work. Whether using it for brainstorming, research, catching up on customer messages or a range of other tasks, AI can be a catalyst for both creativity and efficiency.  

However, as AI becomes more commonplace, we’re also seeing what happens when it’s misused. Corners are cut, customers are frustrated and, in one infamous example, children and parents are left disappointed in a bizarre event that falls far below the expectations set by AI-generated marketing materials. 

Despite these cautionary tales, it is important not to overlook AI’s potential, because with the right approach, it can delight, rather than frustrate. Particularly for teams like customer support, customer service and sales – who have to deal with vast amounts of data and interactions – AI can help teams make better use of their data, nurture closer relationships with customers and ultimately unlock better decisions and smarter ways of working. 

Striking the balance is all about identifying a trusted role for AI that harnesses the organization’s own data to make work simpler and more productive while keeping humans at the helm.

Keeping Employees Front and Center

Before implementing AI into any customer-oriented area like support, service or sales, it’s important to remember that customers want to keep the human touch. Salesforce research shows that 83% of consumers expect to speak to a person immediately when they contact a company. 

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With that in mind, businesses need to think about how they can use AI to augment those interactions, rather than replace them. Often, this will mean AI serves a back-office function.

Acting behind the scenes, AI can help customer-facing teams catch up on an individual’s sales history, analyze data to identify trends or quickly provide a summary of previous interactions a customer has had with the business. In other words, it can act as an assistant, handing a team what it needs to work its magic faster and more effectively. 

This is the approach the team at financial services platform, Stripe, has taken. By using it as a writing partner for Q&A, message summaries and more, Stripe is deploying AI to make significant time savings as part of a strategy built around integrating Salesforce’s Sales Cloud with Slack. This enables teams to easily update customer records in the same place they are discussing work.

The result of this AI and technology strategy is that sales reps and others can reinvest time that would have been spent on tasks like searching for information or updating records back into delighting their customers. 

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Stripe’s strategy epitomizes successful, customer-centric, AI implementation that keeps human interactions in the spotlight while offloading the unengaging work to AI helpers.  

AI Needs the Right Foundation to Flourish 

While AI can do wonders for workers, its implementation requires some thought. Think of AI technology in today’s workplaces as a seed, packed with potential, but in need of the right environment to grow and realize its true potential. 

This is demonstrated by the large-scale models launched by the likes of OpenAI. These draw on vast amounts of information created by humans to train them. In the same way, AI in the workplace needs a foundation to build upon. The good news is that without knowing it workplaces have been doing the groundwork for years and that data is the most relevant. 

The workplace foundation AI needs is made up of structured data and unstructured data. Structured data is already organized. For example, sales history logged in a CRM showing items purchased, dates and other information. Most businesses will already be using this data to help inform decision-making manually, though it can be a time-consuming process.

Unstructured data, on the other hand, has historically been less easy to track. It’s the institutional knowledge that exists for every company and is made up of all the information that is created and shared around work, for example, internal conversations and communication.  

With the emergence of AI, structured and unstructured data both have a key role to play. By applying AI to structured data, teams can rapidly analyze sales histories, find insights or detect anomalies. Meanwhile, AI can use unstructured data to reveal context. It is when these are combined, though, that the magic really happens.

Think of a tricky customer support interaction – a customer calls up, unhappy with a previous product. With AI drawing on both structured and unstructured data, teams can rapidly pull insights from the sales data, identify which members of the team are product experts, quickly find key messages relating to customer challenges and gain a summary of other similar challenges and how they were overcome. 

With all of this at their fingertips, they’re able to rapidly help problem solve, while avoiding hours of delays. It’s just one example of how smart use of AI can result in a happier customer and a more efficient team. 

Customer Happiness in the AI Age 

With any new technology, there is a learning curve, and it’s unlikely that we’ve seen the last AI-generated controversy. Responsible, future-facing businesses, however, can lead the way in implementing AI in a customer-friendly way. To do so, they need to focus on augmenting employees and accelerating processes, rather than cutting corners. 

The good news is that since the dawn of the digital age, businesses have been preparing for this moment. Every sale that’s been logged or internal memo shared can help these tools learn. In turn, teams can use AI to move faster and invest more time in the human experiences that – no matter the technology being used – will always underpin the magic of working with customers.