How buyer AIs see pricing pages
Steven Forth is CEO of Ibbaka. Connect on LinkedIn
AI is playing a growing role in the buying process. More and more companies use AI to define their requirements, identify vendors and then compare them. There are still humans in the loop, buying has not been taken over by agents, at least not yet, but the initial search and the comparison are increasingly shaped by AI.
See Will AI in the buying process lead to more pricing transparency?
One of the things that the AIs look at is pricing pages. There is a long tradition of pricing experts looking at pricing pages and commenting on the design of the page and the pricing model it contains. Marcos Rivera recently did this for Calendly. See his LinkedIn post.
A prompt for a buyer AI
How would a buyer AI see Calendly’s pricing page? Let’s craft a prompt and see.
<goal> Analyze the pricing page to understand how the solution is priced and its value proposition. </goal>
<role> You are a purchasing manager for a [specific industry/size] company, responsible for selecting and negotiating SaaS solutions that offer good value while meeting business needs. </role>
<context> Evaluate the pricing page for [pricing page URL] to assess pricing strategies and compare with competitors in the [specific SaaS category, e.g., CRM]. </context>
<tasks>
**Task 1**: Research best practices for buyers evaluating B2B software pricing.
**Task 2**: Analyze the pricing page:
***Task 2.1***: Describe the package or offer architecture. - ***Task 2.2***: Identify pricing metrics (e.g., per user, per feature). -
***Task 2.3***: Explain fences between packages or offers (e.g., feature limitations). -
***Task 2.4***: Detail how price changes with user count, scale, use, or outcomes. -
***Task 2.5***: Assess how the price-to-value ratio changes with user count, scale, use, or outcomes, using metrics like customer reviews or feature sets. -
**Task 3**: Identify up to three alternative solutions with similar features and market reputation. Find their pricing pages. -
**Task 4**: Compare the target company's pricing with each alternative: -
***Task 4.1***: Compare offer architectures. -
***Task 4.2***: Compare pricing metrics. -
***Task 4.3***: Compare how price changes with user count, scale, use, or outcomes. -
***Task 4.4***: Compare changes in the price-to-value ratio. - ***Task 4.5***: Consider additional costs (setup fees, support). - **Task 5**: Recommend a solution based solely on pricing page analysis, considering scalability, support, and unique features. </tasks>
<summary> As a purchasing manager, analyze the target company's pricing page, compare it with alternatives, and recommend a purchase based on pricing strategies and value propositions. </summary>
I wrote this by hand and then ran it through Perplexity Pro Search to improve it. It came back shorter with all those asterisks! Note that his prompt has been left generic. In the real world, the prompt would have two more sections:
A detailed description of the buyer
A set of requirements
The post might even ask for a price estimate and value estimate in dollars!
Pricing pages should provide the information needed to estimate price and value.
Otherwise, the AI is likely to hallucinate an answer that may not put you in a favorable light.
AI parsing of Calendly’s pricing page
Calendly is a popular calendar and scheduling application. Ibbaka includes a Calendly link in its situation summaries and proposals to remove friction from the sales process.
How does this prompt respond to Calendly’s pricing page?
Calendly’s pricing page accessed March 22, 2025
You can read the full response to the prompt here.
Calendly's pricing structure offers a tiered approach that balances feature accessibility with cost scalability, making it a strong contender in the scheduling software market. After analyzing their pricing page and comparing it with leading alternatives, I've identified key insights to guide purchasing decisions for organizations seeking scheduling solutions.
…
Recommendation
Based solely on the pricing page analysis, Calendly offers the best overall value for most organizations due to its:
Scalability: The clearly defined progression from Free to Enterprise accommodates growth without platform changes.
Comprehensive integrations: Strong connections to CRM, payment, and marketing systems provide better business value than competitors.
Predictable pricing: Per-seat model makes forecasting costs straightforward as teams grow.
Balanced feature distribution: Essential functions are available at lower tiers, with business-critical features at higher tiers.
For specific use cases:
Healthcare providers might prefer Acuity for its HIPAA compliance
Budget-conscious small teams might prefer ScheduleOnce's more generous free tier
Organizations requiring advanced polling might find Doodle more suitable
The final decision should consider your specific scheduling needs, growth projections, and required integrations with existing systems.
Table for Calendly generated by Perplexity AI in response to the above prompt. Generated March 22, 2025.
AI parsing of Algolia’s pricing page
Algolia was one of the companies featured in the recent PricingSaaS Pricing Metrics Report (released March 2025). It was used as an example of usage-based pricing. The usage metrics are the number of search requests and the number of records stored.
Algolia is a search, discovery, and recommendation platform used behind the scenes by many eCommerce and B2B websites.
Here is its pricing page.
You can see the full Perplexity thread here.
Recommendation
Based solely on pricing structure analysis, I recommend:
For startups and small projects:
Algolia's Build (free) tier offers the most generous free allocation (10,000 searches/month and 1 million records) with no credit card required, making it ideal for testing and small-scale deployment.
For growing mid-market companies:
Algolia's Grow tier provides the most cost-effective scaling with straightforward pay-as-you-go pricing at $0.50 per 1,000 searches. This is significantly more affordable than AddSearch's $1.80 per 1,000 queries while maintaining competitive features.
For large enterprises with advanced AI needs:
The choice between Algolia's Elevate tier and Azure AI Search depends on:
Existing technology stack (Azure users may benefit from Microsoft integration)
Required customization level (Azure offers more configuration options)
Implementation resources (Algolia may be simpler to deploy independently)
For e-commerce-specific requirements:
Luigi's Box warrants consideration for its e-commerce focus, one-minute integration promise, and strong support emphasis, which could translate to faster time-to-value despite potentially higher costs.
Final Assessment
Algolia's pricing strategy effectively balances simplicity and flexibility with its combination of a free tier, pay-as-you-go options, and enterprise plans with volume economics. The usage-based model aligns well with value delivery in search applications, ensuring organizations only pay for what they use.
As AI continues to disrupt traditional SaaS pricing models7, Algolia's approach appears well-positioned to adapt through its existing usage metrics and tiered AI capabilities, making it a future-proof choice for organizations investing in search technology.
The prompt also gives a comparison table.
Table for Algolia generated by Perplexity AI in response to the above prompt. Generated March 22, 2025.
Pricing and Buyer AI
Buyer AI is real and is here today. B2B SaaS marketing and pricing need to get ahead of this. What can you do?
Develop a set of buyer prompts and test your website and pricing page; compare to your competitors
Develop a set of buyer prompts and share them with potential buyers (this is the old provide an RFP template tactic updated)
Make sure that your website has a value model that can be accessed by buyer AIs and used to estimate the value you provide
Make sure that your pricing model and all the pricing metrics can be accessed by buyer AIs and used to estimate the price you will charge
Make it easy for the AI to connect price to value and estimate the value to price relationship
Do this for all your use cases (the value can differ significantly by use case)
