Sponsored by Bold360 by LogMeIn
An investment in customer service technology doesn’t guarantee a positive return. To be successful, your organization has to be ready. Join this VB Live webinar to learn about the five biggest mistakes companies make when they bring AI to their workflows, and how to achieve real results.
AI is helping companies build platforms, which is helping to better deliver customer outcomes, but there’s a lot of hype associated with AI, says Akhil Talwar, senior product lead for Bold360 by LogMeIn.
Whether it’s a business that’s trying to position itself as a leader in AI, or people in an organization trying to get buy-in for their initiatives, it’s convenient to throw any cutting edge technology under the banner of AI, which means then it gets a lot of attention.
And because of that, there’s a lot of confusion around what artificial intelligence really entails.
“From a business standpoint, it’s important to know what your goals really are before you think about AI or automation,” Talwar says. “If you’re looking to try to automate simple, repetitive tasks, maybe you only need automation. But if you’re trying to do something more complex like trying to conduct actual conversations with customers, or try to analyze patterns in customer data, that’s where you should be looking at AI.”
At its core, automation is all about manual rules: if this, then that. For example, programming your thermostat to turn on at six o’clock in the evening before you get home. AI, on the other hand is about approaches to problem solving that essentially mimic human thinking. Machine learning part of the broader context of AI, in which algorithms continue to learn as they’re exposed to more data over time, like the recommendation engine in Netflix or Spotify that learns your preferences over time by observing patterns.
Making the wrong choice can be a big setback for companies that were hoping that cutting-edge technology would be a leap forward instead, because if you choose the tool, you’ll either spend more time and money than you should have for your needs, or you’ll end up with a solution that doesn’t meet your needs at all.
For instance, chat bots, which come in a lot of different shapes and sizes. If you’re trying to automate an intake process like lead generation, collecting prospective contact information and scheduling a followup meeting with a sales representative, that would only require a simple automation process type of a bot. It can ask a predefined set of questions, capture the answers, and then automatically block out time on the prospect’s and representative’s calendars.
In other words, you wouldn’t necessarily need a sophisticated AI solution in that case.
If you want a chat bot that that can understand the intent of what a customer is asking, or be able to retain context from a conversation and handle multiple topics, that’s where you will need AI.
“The key thing is businesses have to be sure they’re not paying AI prices for something that’s basic automation, or might look like it’s more advanced than it actually is,” Talwar explains. “Those are some of the things that really make an impact from a business decision standpoint — making sure you have the right tools and technologies in place to deliver on what they’re looking for.”
Once you’ve gone through the whole process of determining that AI is the most appropriate type of approach you want to take for your problem, you need to then make sure expectations across your organization are very clear. The executives who are going to be signing off and funding some of these initiatives need to fully understand both the benefit that’s going to come out of it, as well as the cost and the time investment. It’s very important also that the employees that are going to be involved or impacted by the use of this technology–they need to clearly understand how that’s going to change their operations.
But the success of any of these projects is heavily dependent on the employees, Talwar says, so it’s important is to make sure the front line employees don’t feel that AI is coming in and going to take away their jobs or make their jobs less relevant. It’s important to be very clear about what that new technology is going to look like in their daily work life. Using AI to solve the more mundane, repetitive, low value types of engagements that don’t require human beings usually frees agents up to handle the more satisfying, interesting jobs.
You also have to be very clear on how you measure success against your goals, which is crucial in implementation and delivery. That means making sure that your organization is set up to take full advantage of AI. Companies should focus on how AI is going to help augment their human employees, and also their customer experiences, rather than thinking of them as silo’d initiatives.
“Thinking of AI as its own separate thing is a bad approach,” he says. “You really have to be thinking of this holistically, how it’s going to impact your employees and your customer experience, and augment it.”
Finally, a successful AI strategy must be connected to a solid data strategy. In customer experience, for example, it’s crucial that any AI approach you take will need to be able to share those data and insights across the customer journey. Your marketing, your sales, your care, your product, and all other cross-function teams will need to be able to access all of those systems and store that kind of customer data, because that’s only going to help deliver richer experiences with AI.
“Customer experience is more than just the sum of technology,” Talwar adds. “It requires the right people, the right processes, and you have to make sure all of this connects back to your business problem, when you’re going to make that bet on AI.”
To hear real-world B2B and B2C case studies, plus more about how AI and automation can impact a customer journey from pre-purchase to engagement and retention, how to deliver the best customer experiences and more, register now this VB Live event!
Don’t miss out!
You’ll learn about:
- What AI actually is (hint: it’s not automation)
- The importance of buy-in from executives and agents
- How to approach AI implementation and measure success
- The impact of AI across the customer journey
- Akhil Talwar, Senior Product Lead, Bold360 by LogMeIn
- Michael Butler, Head of Customer Success, Ople