When people ask what you do for a living, your response is probably met with blank stares. And rightfully so. Your job is more nuanced than wearing a fancy suit and “analyzing business”.
If you were to say, “I’m the bridge between business stakeholders and their teams,” they would be more inclined to show more interest. Essentially, you analyze data and processes and drive strategic decision-making.
When it comes to SaaS billing platforms, business analysts (BAs) should have an intimate understanding of monetization models. After all, pricing directly influences company profitability, customer retention, and growth metrics.
Most SaaS startups are betting big on AI technology. McKinsey says companies are investing in agentic use cases and embedding AI into their workflows.
McKinsey’s research estimates that AI-powered productivity could unlock up to $4.4 trillion in additional economic value. Combining AI with the scalability and accessibility of cloud-based software has its challenges. One of them is monetization.
As a BA, it’s important to know why AI software is experiencing slower-than-anticipated growth.
AI was sold to us as an efficient solution to increased overhead costs. In some ways, it did. In others, it didn’t.
While many companies have explored AI use cases, McKinsey claims that only 30% have quantifiable ROI in dollar terms from real customer deployments. The bottleneck pointed to AI-agent-led customer service.
Compared with their human counterparts, AI agents struggled to close a deal due to their limited capabilities. Consumer preference also plays a huge part.
A recent survey published by CX Dive reveals that two-thirds of consumers are not optimistic about how companies use generative AI to interact with customers.
Rising IT costs have put a damper on labor spend. Enabling AI across the full customer service tech stack could result in a 60-80% increase in prices. That increase is eventually passed on to the consumer.
Considering the above issues, BAs must establish a logical pricing model from the start. Below are some of the most effective monetization models that work for SaaS companies.
A popular choice for software companies, the subscription-based model is reliable.
Software Developer Lena Tyson says that startups offering AI development tend to favor this approach. Customers pay a recurring fee (monthly or annually) to use your product. Steady and predictable revenue streams.
PayPro Global advises partnering with a payment processor for digital products with built-in flexible subscription management tools. It takes the pain out of managing global payments and tax compliance.
Clients pay a once-off fee. Also called hybrid billing, one-time payments can increase cash flow.
The model provides immediate, high-volume revenue. Ideal for early-stage startups needing capital for growth.
Ensure your global payment solution for software acts as your merchant of record (MoR) and accepts one-time payments without local entities.
Users get access to basic features for free. They pay only for the more advanced tools.
Freemium pricing is used for products where users need to see the value in the full package. You can guide free users toward a paid plan by prompting upgrades within the platform.
The model works. Forbes reports that consumers prefer goods or services that are priced at zero. Referred to as the “zero price effect,” technical SaaS companies often incorporate it into pricing strategies.
Customers pay according to how much of a product or service they actually use. Unlike a fixed subscription fee, usage-based billing is more flexible and better aligned with the delivered value.
The model is used by storage businesses and for processing transactions. Usage models enable faster deal entry and natural expansion opportunities.
Customer needs are unpredictable. Their usage can surge or decline. Once they see the value in your product, they’ll naturally use it more. By linking price to usage, usage-based billing justifies the expense.
Using a combination of models could be best for the business. Like one-time payments, it encourages customers to try new features or products without paying upfront.
An example of this is offering a base subscription with core features and then charging extra for advanced tools. This method works well because it doesn’t fit everyone into the same box.
On the practical side, companies that use AI integration benefit most from this pricing model. AI tools consume a lot of data, and a usage-based fee shows transparency on your behalf.
Helping the business grow is your main objective. And monetizing is part of that growth strategy.
Always keep customer behavior and expectations at the forefront of every decision. Observe how they interact with the product. This will help you design pricing that makes sense to them.
Lastly, software companies are always adding to or improving their offerings. Your pricing structure should accommodate that.