Artificial intelligence. What used to be a dream in science fiction novels is now an everyday reality.
Self-driving cars, text generation, fraud detection, and more – AI seems to suddenly be everywhere.
So, how can you take advantage of AI, especially in the SaaS industry?
This blog post features several AI SaaS use cases for various departments. We’ll also explore how these AI SaaS solutions can help you get ahead. Hopefully, these examples will inspire you to automate some of your tedious tasks.
Is AI new?
Before diving into examples, let’s briefly explore AI’s journey. How did we even get here?
Before ChatGPT from OpenAI blew up, AI was already prevalent in SaaS. It helped companies:
- Send automated emails
- Respond to frequently asked questions (chatbots)
- Personalize website content, offers, and recommendations
- Screen resumes
- Score leads
- Segment customers
- And much more
In 2022, AI reached a new level. Generative AI (like ChatGPT) appeared seemingly overnight. After that, many AI tools followed. Today, many AI tools are helping practically every SaaS company save time and work faster.
“AI serves as a catalyst for handling those mundane and repetitive tasks. Thanks to AI, I can focus on more strategic aspects of my work.”
Deborah Bittencourt, Product Manager and Product Designer, IBS Consulting
Now, let’s break down the seven ways AI can help you outperform your competition in SaaS.
1. Product development
AI streamlines various aspects of product development, such as:
- Analyzing users
- Generating ideas
- Prototyping
- Testing
- Writing and fixing code
- Detecting anomalies
- Surfacing vulnerabilities
- Managing projects
- Optimizing design and costs
Here are some sample prompts you can use for each of these points.
- Analyze user data to identify the most engaged customer segments over the last quarter.
- Generate a list of the top five feature requests from user reviews on our platform.
- Generate three prototypes for the new dashboard based on current user behavior analytics.
- Run automated tests focusing on newly deployed features and summarize the results
- Suggest optimizations for the current code base to improve performance.
- Scan the system logs for the last week and flag any unusual activity.
- Perform a vulnerability assessment for the latest build.
- Predict any potential delays in the current project timeline and suggest mitigating actions.
- Analyze the cost-efficiency of design alternatives for the new feature set.
There are many AI tools out there that can help. Let’s explore what’s out there (beyond ChatGPT).
TL;DR: it’s now easier to manage product development, thanks to AI.
Feature development
When you’re developing features, there are three main aspects where AI can assist:
- Predictive analysis: AI can analyze trends to help you understand what features are more likely to be successful.
- Natural Language Processing (NLP): For text-heavy applications, NLP can help in auto-categorizing user-generated content, summarization, and more.
- Coding: AI can suggest new lines of code, entire functions, tests, and even complex algorithms.
“GitHub Copilot is already writing 46% of code and helps developers code up to 55% faster. Our R&D team (GitHub Next) has been hard at work to bring GitHub Copilot beyond the editor. Auto-completion is just the starting point.”
Thomas Dohmke, CEO at GitHub
TL;DR: AI can help you develop products and features that your customers will love. It can also save lots of engineering time.
2. Product management
AI enables product managers to automate numerous daily tasks, including:
- Detecting trends in customer sentiments
- Analyzing user feedback
- Brainstorming and prioritizing ideas
- Writing support documentation
- Creating project plans
- Tailoring user experience
- Automating reporting
- Analyzing competition
- Detecting bias
“The integration of AI into product management has been nothing short of transformative. An advanced AI algorithm can sift through vast datasets, deciphering intricate customer behavior and preferences.”
Kamil Rejent, CEO at Survicate
Canny recently released Autopilot – a suite of AI features that save time. Autopilot automatically detects, extracts, and deduplicates feedback from support and sales conversations.
Smart Replies generate automatic replies that uncover more information. And Comment Summaries summarize busy threads and bring key insights to the surface.
All this will save product managers from manual work and will free up their time.
Roadmapping
To create an effective product roadmap, product managers need to:
- Prioritize features
- Evaluate market demand
- Forecast development timelines
- And so much more
AI can assist with these tasks and make the roadmapping process more data-driven and efficient.
ChatGPT is an undeniable leader that can also be very useful in product development.
“I continue to rely on ChatGPT for various tasks, from shaping our product roadmap to engaging with beta test users.”
Deborah Bittencourt, Product Manager and Product Designer, IBS Consulting
Here’s how AI helps Deborah create and manage product roadmaps:
- Market research and insights
AI can identify emerging trends, competitor strategies, and customer pain points, which can help determine our product development priorities. I still fact-check everything and bring more data from 2022 on. - User feedback analysis
Depending on the amount and form of feedback I have, I experimented with feeding ChatGPT customer feedback, surveys, or product reviews to analyze and provide more insights. It can summarize common issues, feature requests, and sentiment analysis, doing some bulk work for me. - Prioritization (⭐️ my personal favorite)
AI helps me create scoring models or frameworks to objectively assess and rank potential roadmap items. I like to ask ChatGPT to consider user impact, technical feasibility, and business value. - Roadmap documentation
I use it to draft and refine my product roadmap documents, ensuring they are clear, comprehensive, and well-structured for communication within the team.
TL;DR: AI can help get started with roadmapping: research the market, analyze and prioritize feedback, and draft documentation.
3. Data analysis
There are also AI tools that dive a lot deeper. They can help:
- Analyze data
- Uncover customer insights
- Predict trends and project outcomes
- Make more informed product decisions
“Leading SaaS companies utilize various AI tools such as natural language processing (NLP), computer vision, and predictive analytics. Examples include:
Dennis Brown, lead software engineer, Ling Ltd.
- Machine learning
- Computer vision
The key is to feed AI your own unique data.
“It isn’t enough for AI to be trained on publicly available data. It must marry that data with internal enterprise data. This includes established product and service data as well as contextual customer interaction data.”
Umesh Sachdev, CEO & co-Founder of Uniphore
TL;DR: AI can assist with data analysis, but it needs unique data to be truly effective.
Looking at AI from this angle, you can’t help but get excited. Let’s explore how other teams can benefit from AI, too.
4. Customer support & success
It’s not just product managers who can benefit from AI.
AI-powered chatbots are probably already on your radar. Zendesk, HelpScout, Intercom, Lyro AI Chatbot, and others have been using AI to answer customer questions faster.
“Intercom has an AI tool that will summarize a thread in the notes. It is very helpful for longer threads. We also use Fin – their new AI chatbot that can answer complex questions and save us a lot of time.”
Jacques Reulet, head of customer support, Canny
Now, AI’s providing more accurate answers and imitates human conversations much better.
After the conversation is done, AI can process it and uncover insights.
It doesn’t end with chatbots, though. Customer service, customer support, and customer success managers can personalize their user experience through AI. For example, AI now makes individual product recommendations, tailored offers, and useful prompts possible.
TL;DR: AI chatbots have evolved to understand customer sentiment and can escalate issues to human agents when necessary.
ALSO — check out how Canny’s AI can support your customer feedback management system.
5. Marketing
While marketing remains a creative field, AI can enhance certain aspects. For example, product marketers rely on AI to help them with copywriting and design.
“I use AI as a starting point for some tasks. It’s helpful for tasks requiring data analysis, automation, and content generation.”
Deborah Bittencourt, Product Manager and Product Designer, IBS Consulting
Many marketers are using AI to help specifically with copywriting and editing. While this is a great time saver, try to be a little critical of AI’s outputs.
Note: instead of copying and pasting what AI gives you, use it as guidance and a starting point. AI isn’t always accurate, and its writing rarely fits your style guide perfectly. But, with some human touch, you can produce valuable content.
You can also create and read through complex documentation faster with AI.
“We’ve started transitioning some of our documentation to Notion. Their AI-powered tools have helped streamline the documentation process and save me time and effort. For design and creative inspiration tasks, I’ve experimented with Firefly by Adobe.”
Deborah Bittencourt, Product Manager and Product Designer, IBS Consulting
Beyond content, AI can help marketers:
- Research audience & competition
- Generate personas
- Evaluate and edit copy
- Create charts and graphs
- Personalize experience for your users
Andy Crestodina from Orbit Media shares some useful ChatGPT and Bing prompts for marketers here. He recommends to:
“Try everything. Never trust it completely. Once you find insights, focus on execution.”
Andy Crestodina, co-founder & CMO, Orbit Media
Similarly, Ross Simmonds from Foundation Inc is using AI to:
- Research the market
- Analyze reports and data
- Create content (written and visual)
- Save money!
TL;DR: AI can help marketers get started with creative ideas, analyze the market, and personalize user experience.
6. Sales
Sales is another area that requires a human touch to be effective. Still, sales reps can use AI to:
- Transcribe and summarize sales recordings: tl;dv, Otter.ai, rev.com
- Find common pain points: H2O.ai, Gong.io
- Uncover feature requests: Canny
- Score leads: Hubspot
- Assess their own effectiveness: People.ai
- Write or critique email copy: ChatGPT, Collato
Technological progress has been accelerating and bringing us more and more data. More data is useful, but processing it gets complex. That’s why AI is so timely – it can help make sense of that data.
“As selling complexity grows, so does the need for documentation, approvals, and compliance reporting. Generative AI can reverse administrative creep by helping salespeople write emails, respond to proposal requests, organize notes, and automatically update CRM data.”
Prabhakant Sinha, co-founder of ZS
“The future? AI AND Humans working together for a more potent sales force.”
Collin Stewart, CEO, Predictable Revenue
TL;DR: AI can improve sales strategies through lead scoring, call recordings, and data management.
7. Growth
Most businesses need to grow and do it faster than the competition. While others are still figuring out AI, you can start using it to get ahead. For example, you can:
- Understand how your customers use your product: Mixpanel, Amplitude
- Find usage gaps: Looker (from Google), Tableau
- Tie them to churn: Salesforce, Hubspot, Gainsight
- Fill those gaps and improve retention: Marketo, Dynamic Yield
You can also analyze your own usage patterns. Maybe there are some processes you can optimize?
Growing involves using resources wisely. AI can help with smart resource optimization as well.
Some of these tools (Salesforce, Hubspot) combine a few of these features. Check them out to see if one tool can check more than one box for your teams.
All of those efforts can help your SaaS company grow faster.
“Top SaaS companies are leveraging AI to gain a competitive edge. They implement machine learning algorithms to automate tasks, improve customer experiences, and drive business growth.”
Dennis Brown, lead software engineer, Ling Ltd.
TL;DR: use AI to understand how your customers use your product.
8. Operations
Good operations = efficiency. Especially in startups, the operations department has to do a lot: legal, HR, finance, and more.
AI can automate a lot of that, for example:
- Repetitive workflows
- Insights gathering
- Scenario planning
- Resume scanning
- Budget optimization
- Fraud detection
- Risk assessment
- Compliance monitoring
- Forecasting
- Resource allocation
- Feedback loops
It’s hard to find an AI tool that can do all of that at once. Depending on your organization’s priorities, some of these may work well:
“Artificial intelligence is more than a buzzword. AI is rapidly reshaping the fabric of business operations.”
Whitney Vige, SEO Content Writer, Asana
TL;DR: AI tools can help you boost operational efficiency by eliminating repetitive tasks.
Limitations
No tool is perfect. And most AI tools are still fairly new, so they come with some limitations you should be aware of.
Many experts agree that AI raises concerns around:
- Privacy – where is the data going?
- Accuracy – can we trust this information?
- Originality – is this plagiarism?
- Humanity – will our customers get annoyed by AI and miss human interactions?
“My primary concern with AI is how personalized product insights can be. Most AI data is broad and generic information. It doesn’t always perfectly align with specific user needs. As a product manager, it’s my job to go after user research and testing. I need to ensure that AI-driven solutions are aligned with our users’ unique requirements and expectations.”
Deborah Bittencourt, Product Manager and Product Designer, IBS Consulting
Does this mean we should disregard AI and stick to what’s worked in the past? Definitely not.
Instead, we must critically assess all the information AI provides us. We must still use our critical thinking, seek a deeper understanding of our users, and improve what AI gives us.
Because these concerns are common, most AI creators are actively improving their tools.
What’s next in AI?
More and more AI trends and use cases surface every day. Generative AI tools like ChatGPT are only the beginning.
Here’s an example of a conversational AI voice assistant that goes beyond services like Google Home and Amazon Alexa you might be used to.
In our recent blog post, we also highlighted top AI tools for product managers – check it out.
Experts predict AI will get more accurate, process larger amounts of data, and do it all faster.
“In essence, the marriage of AI and SaaS is not just a fleeting trend; it’s the wind beneath the wings of any SaaS firm.”
Kamil Rejent, CEO at Survicate
TL;DR: stay on top of AI trends to work faster and smarter.
AI – the future of SaaS
AI is changing our lives, especially in the SaaS industry. Every part of your organization can benefit from AI.
So, start implementing AI into your daily processes today. You can save time, get ahead of the competition, and enjoy your job more. After all, AI will handle your mundane tasks, and you’ll have more time for deep and creative work.
AI can help you boost customer satisfaction, too. When your users get help and answers faster, they’ll appreciate it.
Introducing AI into your workflow doesn’t necessarily mean spending more money. Check out your existing SaaS tools. Chances are, they’ve added AI components.
“SaaS companies today elevate customer journeys, predict market shifts, and automate tasks seamlessly through AI. We use Salesforce Einstein, Zendesk AI, and HubSpot’s AI functionalities.”
Ranee Zhang, VP at Airgram
Did we miss any cool companies or use cases? Let us know, and we’ll add them!
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