Modern SaaS businesses continuously iterate on their pricing to gain a competitive edge in their market. This is especially true for new AI startups that frequently launch new products and models. This creates significant challenges for developers as they must translate changes on the marketing page to changes in infrastructure and products. This involves synchronizing data between multiple sources, integrating product catalogs, and enforcing entitlements. Businesses where engineering organizations cannot keep up with pricing iterations lose their competitive edge.
Complexity of Modern Pricing Models
Modern pricing models have evolved beyond traditional subscription-based approaches. They now include usage-based, value-based, and hybrid models. For example, AI products often require sophisticated unit-based pricing systems that align costs with actual usage, offering more flexibility and value to customers.
Challenges in Implementing Pricing Changes
Changing your pricing is always complex, and implementing it in your infrastructure and product is equally challenging. This responsibility relies on engineering organizations to keep up with pricing changes and enable quick iterations. Let's discuss the most common challenges developers face when adopting pricing changes.
1. Integrating Product Catalog
The product catalog is at the root of billing, as it holds the metadata about available packaging and prices over time.
Multiple Datasources
Product catalogs and entitlements can have multiple sources, including databases, data warehouses, and external services like Stripe and Salesforce. In many cases, especially in the early days, the self-service product catalog lives in the code base or the database, while sales teams often leverage the CRM for CPQ (Configure Price Quote) to handle custom pricing agreements. In all cases, changes must tickle down to the infrastructure.
Real-Time Synchronization
Synchronizing product catalogs from multiple sources to your product and infrastructure creates challenges around integration and consistency. Synchronization can happen in a pull or push model; with an extensive catalog, the push model works better, as polling every resource to detect changes can be expensive. For example, Salesforce has strict API and rate limits, making it challenging to keep CPQ up-to-date with your infrastructure.
Multiple Versions Over Time
As pricing evolves, maintaining multiple versions of product catalogs becomes challenging. For example, a plan's name might remain the same while its entitlements change frequently. Hardcoding plans in your codebase don't work as the entitlements behind the key evolve, and customers may need to remain on older plans for extended periods.
Multi-Currency and Multi-Region Support
Supporting multiple currencies and regional pricing models adds complexity to monetization. Backend apps must handle regional overrides, often involving integrating local payment providers or using different legal entities to handle transactions. Client apps must present information to customers based on location and show prices in the appropriate currency and language.
Legacy Billing Systems and Technical Debt
Many first-generation billing systems either don't support usage-based billing or entitlements or have strict limits on how many usage data points you can report over a customer's lifecycle. Integrating new pricing structures with these outdated systems can be difficult and necessitate developing custom integrations that bridge the gap between old and new systems. Migrating customers from old plans to new ones further complicates the process.
2. Implementing Entitlements
Entitlements describe what features specific customers can access as part of their subscription, such as which features are enabled and how much the customer can consume over the billing period.
Metering Usage-Based Entitlements
Usage-based pricing models allow customers to pay based on consumption, offering greater flexibility and tighter control over costs. However, implementing accurate usage metering on a large scale can be challenging for engineering teams.
In our previous blog post, you can read more about metering challenges.
Enforcing Usage Limits
Enforcing usage limits is technically challenging. Real-time metering and credit balance tracking are essential to determine customer eligibility for further product usage, especially in online traffic scenarios. This requires robust, low-latency systems capable of quick response times across various global regions. Without real-time usage monitoring and enforcement, we can't protect margins from abusive overages.
Challenges of Credit Systems
Credit systems must be instant, accurate, and accountable. Credit changes must be auditable on the ledger and synchronized with the billing system. As the billing period changes, the credit system needs to be able to re-issue grants and trigger top-up payment flows.
You can read more about credit system challenges in our previous article.
3. Analytics and Third-Party Integrations
Finally, we must surface billing data to third-party and analytics tools to provide a unified view of customer usage and billing information.
Integration with Third-Party Systems
Companies often rely on various third-party systems for CRM, analytics, customer engagement, and other services. For example, usage data and entitlement insights help sales teams identify revenue opportunities. These systems require consistent real-time data to operate correctly. This requires robust ETL pipelines to synchronize data with third-party tools.
Financial Reporting
Accurate financial reporting is essential for decision-making and regulatory compliance. Integrating billing systems with financial reporting tools ensures transparency and accountability. Developers must create robust ETL pipelines to consolidate billing data from multiple sources. This can be challenging when accepting numerous payment types or using local providers.
Billing After Complex Pricing Models
The rise of new billing models creates new challenges for the monetization stack and the engineering teams behind it.
Hybrid and Tiered Pricing Models
Implementing hybrid models that combine recurring subscription fees with usage-based components requires dynamic calculations and real-time data processing. Tiered pricing adds another layer of complexity, as it dynamically adjusts prices based on usage thresholds.
AI and Usage-Based Pricing
AI increased the adoption of usage and unit-based pricing models. UBP requires metering multiple resources, such as the number of tokens consumed, API calls made, or compute time, and converting them into billable units. This requires robust metering and billing mechanisms that can handle high volumes of data in real-time.
Prepaid Billing
Prepaid billing combines credits, wallets, and tokens. Customers can buy tokens upfront and top up their balance as they use more. This requires close tracking of entitlements and adopting credit systems, further complicating the monetization infrastructure.
Read more about pricing AI products.
Impact on Go-to-Market Strategy
SaaS businesses continuously iterate on their pricing to gain a competitive edge in their market. When this iteration slows down, it directly impacts the business's success. This is why it is so essential for engineering teams to enable quick pricing iterations.
Time-to-Market Delays
Implementing complex pricing changes can significantly delay product launches. The time required to develop, test, and deploy new billing systems can slow down the go-to-market strategy, giving competitors an advantage. This is critical in the early days when products are more likely to undergo more extensive pricing changes.
Flexibility and Adaptability
Fast-growing businesses need flexible billing systems that quickly adapt to changing market conditions and customer needs. A good monetization stack helps introduce new pricing models and enables revenue teams to sell custom agreements and win deals over competitors.
Competitive Disadvantages
Companies that struggle to implement pricing changes or offer custom deals risk falling behind more agile competitors. Slow adaptation to market demands can lead to lost opportunities and diminished market share. AI is a good test for enterprises to see if they can adopt usage-based and value-based pricing for new LLM-based features.
Conclusion
Rapidly adopting pricing changes is a complex challenge that directly impacts go-to-market strategies. When the backend and frontend systems can't effectively follow pricing changes, the company loses the ability to iterate on pricing quickly and gives up its competitiveness. Monetization is as much a developer challenge as a business one. Investing in modern billing solutions, seamlessly integrating product catalogs, managing entitlements accurately, and ensuring compliance are essential to meeting customers' evolving needs and staying competitive in today's dynamic market.