The rise of AI-powered customer support in the SaaS industry.

“Your customer doesn't care how much you know until they know how much you care”. - Damon Richards

Welcome back to my newsletter. My name is Matt. Today, we’ll be discussing AI and customer service in the SaaS industry.

This is going to be a nice read, so kick back and enjoy this one. Let’s go!

Let’s see how AI, SaaS, and customer service come together.

What's SaaS? It stands for Software-as-a-Service. Essentially, it means providing software as if it were a service, with different pricing tiers and recurring payments.

?What’s AI? Artificial Intelligence. Machine Learning. Etc.

What’s customer service? How you deal with customers. How you respond to their queries. How you ‘serve’ them.

How does all of this come together? Well, when you’ve got a service you’re giving out to multiple people, and there are problems, you want to be able to deal with them effectively, whether it’s a software bug or a customer query. And in the case of SaaS, customer inquiries will be more than just a few.

If you’ve got potentially millions of people using your software, you’re going to have to provide customer service BEYOND your manpower. And that’s where AI comes in.

” AI? Helping with customer service? How?”

Well, customer service doesn’t just mean talking to customers over the phone. It means serving them in ways that can help them. from a chatbot, problem troubleshooting, or in-app guidance, it’s all about helping them. And it's here that AI gets to show its true colors.

Want to make your agent’s work easier? Integrate AI into their calls, so that it can pull up relevant material on their screen, making things more manageable for them.

Want to scale beyond your physical manpower? Bring on AI VAs onto your team. No need to buy the hardware. Just give them the tasks and they’re off.

There’s a lot you can do with AI in this space. And that is what we’re going to be exploring.

People nowadays have short attention spans and their loyalty to brands is quick to change. Retaining them means doing everything from resolving issues as quickly as possible to helping them get what they want and when they want it.

How? By doing a series of things. Although the use cases here are so many that we can go on and on…

I’ll be discussing three categories that I think are important.

1. Dealing with customers. Everything from helping them help themselves to accommodate them timely on customer support calls.
2. Retaining them and getting them to upgrade their services.
3. Internally. Whether it’s for marketing purposes or more efficient resource management.

So, customer service.

Suppose you’ve got an online note-taking app that allows integrating and embedding various things. From forms to search bars to full-blown websites, there’s so much you can do. It’s easy to use, has apps on the Play Store and the Apple App Store, and has various tiers, with the lowest one being free.??

If someone has an issue, there are various ways they can deal with them:

• They could email or message an agent, which could take time.
• They could communicate with an AI-powered chatbot, that, powered by machine learning and natural language processing, can communicate with them in real-time and help them solve their issues

Or they could simply access a “Help” section, and browse through a variety of material until they find a solution.

One other thing that can be done is to monitor their behavior. Upon detecting that they’re facing issues, or seem to be stuck somewhere, they can get an automatic pop-up, helping them solve their issue.

Might seem simple, but all of these simply go a step further and show your user that, regardless of if they’re a free user or they pay, they get to experience the level of customer service they deserve, simply because they use your service.

And using AI? Gives you extra access to resources to help, without significantly increasing your manpower.

Maybe you want to retain your customers and reduce churn, while also getting them to upgrade.

Again, AI can help here. Suppose some features can be used for a limited period every month on the free tier. Now, if some users regularly use up that quota, maybe it’s time to encourage them to upgrade to the next tier. Sell them on the benefits. The increased or unlimited quota they get for that feature.

And that’s not it. If you’re setting up and sending out emails, you can use AI to personalize those sequences. You can analyze all types of data to make everything from suggestions to promos ultra-relevant. Want to target people who don’t speak your language? Utilize? AI for accurate translations.

From trying to make your messaging personalized to trying to upsell various segments of your audience in various ways, you’re not restricted in how you try to use AI when it comes to making sure your customers keep growing.

And then there’s the internal, corporate use as well.

Want to run personalized marketing campaigns for a variety of segments? Train models using data you’ve collected and get it to power your decisions for running ads. Use it to streamline your resource utilization, focusing time and energy on things that need it. You can even use AI for security purposes. Analyzing potential cyber threats and taking action before something happens is another thing it can do.

“It sounds kind of vague Matt. AI. Models. Data. I’m kind of lost.”

Well, the thing is, you only really grasp how this works when you try to implement things for yourselves. When you experiment with various tools, and models and try to train and feed it various types of data and get different outputs, that’s when you figure out what to do.

Is it useful? Yes. Does it save resources? Yes. It can allow you to have support online 24/7, to provide as much convenience to your customers as possible. You can provide hyper-personalized experiences, whether it’s in-app or during the marketing process, as they travel through the funnel.

Is it advanced? Well, it can’t exactly replace humans totally, so not really. However, it can help you do an extensive number of tasks, whether it’s automating them, or making it easier for your team.

At the end of the day…

This is something that you’ve got to explore to understand. You’ve got to try your hand at various tools. At trying integrations. At trying to build a chatbot or two.?

There are lots of use cases here. From helping in sentiment analysis of reviews and giving insights accordingly to helping users solve their problems without having to face too much hassle, there’s a lot you can do.

And if you get confused…?

Remember this: your SaaS’s end goal should be to help businesses and individuals maintain productivity, while also thriving in a digital-first environment.

How? With the help of AI.

See you next time, and keep building,