Solving Customer Pain Points: Leveraging AI/ML for Effective Product Solutions

If you play several instruments at once, people look at you like you're crazy. 

If you tell them you're a product manager or CEO in a SaaS company, they'll nod their heads in admiration. This is a strikingly different reaction to such similar things, right?

You know exactly how much it takes to be a successful product manager. Your team has to process a ton of data, collect customer feedback, and come up with awesome solutions to tackle customer pain points. And that's just to keep things running smoothly!

But, this chaos has led to innovations. More than 70% of US companies have adopted AI/ML in some form to level up different areas of their businesses. And you, as SaaS specialists, have pulled up a lucky card in this game.

Why? Because existing AI solutions can solve a whole range of tasks you deal with every day. 

Leveraging AI/ML for Customer Pain Point Solutions

AI-based solutions open up a whole new level of customer data analysis. On top of collecting and sorting through customer feedback, these advanced tools identify trends and patterns in customer behavior. Most importantly, they synthesize them into actionable customer insights. 

Let's take a closer look at the ways AI tools can help you in solving customer pain points.

Predictive Analytics

AI models use statistical techniques and machine learning algorithms to analyze historical data. Once they identify a particular trend in your consumer's behavior, it gets a score. If the score is high, then this behavior will likely happen in the future.

These insights could help you determine which features your users love the most, how they navigate your app, what issues they encounter, etc.

Let's take Grammarly, a language-checking solution, as an example. It uses AI to pinpoint the most common mistakes users make. These insights help the product team prioritize new features that will address customer pain points.

AI has also become a valuable tool for proactive issue resolution. One such solution is Zeda.io, an advanced AI product management software used by SaaS professionals. 

It analyzes data sources like product feedback and support tickets to inform you of potential issues. This way, you can swiftly resolve frictions in customer experience and build a more user-friendly app.

Personalization through Machine Learning

Personalization gives your product a competitive edge. You probably know that a highly personalized solution addresses customer pain points with laser-focus accuracy and speed. But it takes a lot of work to build it in the right way.

The volume of data is enormous. It's easy to overlook important details, even if you have a basic analytical tool at hand. This is because the reports generated with these tools are often difficult to read.

Advanced AI-based tools are better at this task. They create reports that are easier to read and group users by their preferences, behavior patterns, and unique needs. As a result, you can offer them a personalized user journey that will help them get things done faster.

Simple example: Your product is a time-tracking app. If AI notices that a specific group of users prefers the Pomodoro timer over other features, you can make it a part of their default layout.

Chatbots and Virtual Assistants

Have you heard that users prefer to interact with real people? Recent stats debunk that common myth.

69% of consumers prefer chatbots for quick communication with brands. This is not a coincidence— 90% of businesses have reported faster complaint resolution with bots.

SaaS professionals can use AI bots to:

• Identify pain points. Whenever your customers experience issues, they go to your website and chat with an AI assistant. The feedback it collects will help you find common pain points faster.
• Fix pain points. This one is about direct human-robot interaction. You can feed AI with data on known issues so it can suggest solutions without human intervention. Your customers get the fast answers they need in seconds, 24/7!

Data-Driven Decision-Making

We’ve talked a lot about data processing. But it's not enough to just collect, analyze, and interpret it. You have to make use of these data.

So, how can you leverage these AI-Powered Customer Insights? The potential is limitless. Using an AI tool helps you inform your product decisions, marketing efforts, and customer support strategies.

What’s more, some advanced AI-based tools, like Zeda.io, can help you predict the outcomes of any product decisions you make. The tool also provides actionable suggestions based on the analysis's results in a simple format. 

Challenges and Considerations 

Nobody likes to talk about the potential problems that new technology can bring, especially when it's extremely helpful. But you need to know about the main concerns surrounding AI in SaaS:

• Ethical and Privacy Concerns. The people behind tools like ChatGPT use public data to train AI algorithms. This is not illegal because users provide consent when sharing their data online. However, when it comes to industries that collect sensitive data, the risk of privacy violation increases.
• Integration Challenges. Even though AI tools can process unstructured data, the quality of their output still depends on the quality of the data they receive. If you feed AI applications with unstructured data, it will take more time for them to provide accurate insights.
• Balancing Automation with Human Touch. People come to you because they seek empathy and support, something AI that solutions can't provide yet. Once again, AI is not perfect. It makes mistakes you have to find and correct.

Case Studies: How do B2B SaaS companies leverage AI and ML to address customer pain points?

Collaborations between tech leaders always yield inspiring results. Let’s look at how famous B2B companies successfully leveraged artificial intelligence to address customer pain points:

ServiceMax

Service Max, a service execution management company, was looking for opportunities to attract and retain customers by providing more relevant content on their landing page. One of the key issues they faced was the difference between customer segments.

Solutions:

• ServiceMax used an AI-based solution from Demandbase to track customer interaction on a website.
• AI-tool determines which segment the customer belongs to.
• The web interface automatically adapts and displays content relevant to users' needs in real-time.

Results:

• Bounce rates have decreased by 70%.
• Time-on-site and pages-per-session have increased by more than 100%.

Artesian 

Artesian Solutions, a UK sales insights company, had already been using AI for data analysis when a new generation of conversational AI platforms (CAPs) entered the market. Artesian just couldn’t miss the opportunity to improve their customer experience through CAPs. 

Solutions:

• The tech company Volume specifically designed a CAP named “Arti.” It was trained on historical data provided by Artesian as well as on external data.

Results:

• The monthly website traffic has increased by 11%.
• Arti answered over 5000 questions with 99.1%. This led to higher customer satisfaction and retention rates.
• Arti has increased Artesian’s prospect pool by a factor of four.

Future Trends

Here’s a big truth: we’re just at dawn in the age of the “AI revolution”. The next five years will be breakthroughs for AI-based software and services. 

Advancements in AI/ML Technologies

• Privacy Matters. Experts anticipate that new-generation AI tools won’t use personal data sent to external servers. Instead, the AI itself will “migrate” from the user device to the server. This technology is called federative learning.
• No Brainer. Small companies will benefit from no-code or low-code AI platforms for app development. This will save time and costs needed for traditional coding.

Emerging Applications for Customer Pain Point Solutions

• Adaptive UI/UX AI. These apps will track individual user behavior and preference to adapt their interface and user experience in real-time.

• Virtual Assistants. Most SaaS companies will integrate conversational bots within their solutions to solve customer pain points “on the spot.”

Bottom Line

I believe that there are no customer points your product team can’t solve. However, the synergy between the human mind and artificial intelligence can deliver mind-blowing results. You’ll be able to deliver faster, more personalized solutions that truly cater to your customers' needs. Merge your efforts with AI and welcome the new era of SaaS product management today! And thank me later!

Author: Luca Castelli

Luca Castelli is the CEO of Detectico. He has over 15 years of experience in the SaaS industry and is passionate about Marketing and Technology.