Pricing Shastra

AI is accelerating innovation across the Tech industry and for us, at Pricing Shastra, many of our conversations with leaders of fast-growing tech companies focus around the best ways to monetize AI driven innovation. While the spotlight so far has been on the Foundational Models, AI is also powering the applications that are building on top of the Foundational Models and requires a revaluation on everything from how AI delivers value, how it fits in with pricing structure, most effective way to monetize etc. 𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 → Many Gen AI products seem to be choosing the consumption based pricing models because LLMs are priced on token-based models. You do not always have to choose a consumption based pricing model for your product just because LLMs are priced that way. It depends a lot on the value of your product. → We also see many providers who believe including AI in their highest priced plans is a good way to monetize. That in our view is also an extremely simplistic way to approach AI monetization. → Here are our thoughts on when a rethink of the existing monetization model may be needed vs. when a simpler approach is more appropriate. 𝗥𝗲𝘁𝗵𝗶𝗻𝗸 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝗼𝗿 𝗠𝗼𝗻𝗲𝘁𝗶𝘇𝗲 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹𝗹𝘆? → AI can significantly influence product usage patterns - mostly because of elimination/automation of activities. From a pricing perspective, a key question you need to ask is “How does it impact monetization based on my current model?”. Let’s look at it for the two broad monetization models in use - User based and Usage based. → 𝗨𝘀𝗲𝗿 𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹: →→ In user based pricing models, user count can go down with the introduction of AI. Gen AI products generally result in increased productivity, which could result in workforce reduction and fewer addressable users. In this case, you need to rethink your pricing model and meters. Example: Agent based subscriptions for Service Management software such as Zendesk, Salesforce, ServiceNow etc. →→ If however, there isn’t any significant impact to User counts because of AI, you can continue the existing model and monetize AI incrementally. Example: Office 365 subscriptions and the introduction of Office CoPilot (priced as an add-on but not changing base model). → 𝗨𝘀𝗮𝗴𝗲 𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹: →→ If you currently have a usage based pricing model, u͟s͟a͟g͟e͟ ͟m͟a͟y͟ ͟g͟o͟ ͟d͟o͟w͟n͟ ͟w͟i͟t͟h͟ ͟i͟n͟t͟r͟o͟d͟u͟c͟t͟i͟o͟n͟ ͟o͟f͟ ͟A͟I͟. Example: For case based pricing for Service Management, AI can deflect case creation and reduce the number of cases. In this case, you need to rethink if the usage meter is still the right one or if additional meters need to be introduced. →→ If usage is not expected to change drastically, you can introduce AI as an additional charge or might just monetize because of additional volume generated. Facing this challenge? Connect with us to discuss more.

AI is accelerating innovation across the Tech industry and for us, at Pricing Shastra, many of our conversations with leaders of fast-growing tech companies focus around the best ways to monetize AI driven innovation. While the spotlight so far has been on the Foundational Models, AI is also powering the applications that are building on top of the Foundational Models and requires a revaluation on everything from how AI delivers value, how it fits in with pricing structure, most effective way to monetize etc. 𝗖𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 → Many Gen AI products seem to be choosing the consumption based pricing models because LLMs are priced on token-based models. You do not always have to choose a consumption based pricing model for your product just because LLMs are priced that way. It depends a lot on the value of your product. → We also see many providers who believe including AI in their highest priced plans is a good way to monetize. That in our view is also an extremely simplistic way to approach AI monetization. → Here are our thoughts on when a rethink of the existing monetization model may be needed vs. when a simpler approach is more appropriate. 𝗥𝗲𝘁𝗵𝗶𝗻𝗸 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝗼𝗿 𝗠𝗼𝗻𝗲𝘁𝗶𝘇𝗲 𝗶𝗻𝗰𝗿𝗲𝗺𝗲𝗻𝘁𝗮𝗹𝗹𝘆? → AI can significantly influence product usage patterns - mostly because of elimination/automation of activities. From a pricing perspective, a key question you need to ask is “How does it impact monetization based on my current model?”. Let’s look at it for the two broad monetization models in use - User based and Usage based. → 𝗨𝘀𝗲𝗿 𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹: →→ In user based pricing models, user count can go down with the introduction of AI. Gen AI products generally result in increased productivity, which could result in workforce reduction and fewer addressable users. In this case, you need to rethink your pricing model and meters. Example: Agent based subscriptions for Service Management software such as Zendesk, Salesforce, ServiceNow etc. →→ If however, there isn’t any significant impact to User counts because of AI, you can continue the existing model and monetize AI incrementally. Example: Office 365 subscriptions and the introduction of Office CoPilot (priced as an add-on but not changing base model). → 𝗨𝘀𝗮𝗴𝗲 𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝗶𝗰𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹: →→ If you currently have a usage based pricing model, u͟s͟a͟g͟e͟ ͟m͟a͟y͟ ͟g͟o͟ ͟d͟o͟w͟n͟ ͟w͟i͟t͟h͟ ͟i͟n͟t͟r͟o͟d͟u͟c͟t͟i͟o͟n͟ ͟o͟f͟ ͟A͟I͟. Example: For case based pricing for Service Management, AI can deflect case creation and reduce the number of cases. In this case, you need to rethink if the usage meter is still the right one or if additional meters need to be introduced. →→ If usage is not expected to change drastically, you can introduce AI as an additional charge or might just monetize because of additional volume generated. Facing this challenge? Connect with us to discuss more.

PLG vs. SLG debate is a topic on the minds of many executives today. Choice of PLG or SLG has huge implications across the organization - GTM, Product strategy, Systems and Processes and of course Pricing and Packaging to name a few. Transitioning from one model to another is not easy (ask those who have done this!!). In this latest blog, published through Sapphire Ventures, our Founding Partner Mohan Kasibhatla shares how to best navigate PLG vs. SLG models - with a specific focus on Pricing and Packaging.   Read this blog post to understand which approach is best for your organization. #plg #slg #productledgrowth #gotomarket #gtm #pricing #pricingstrategy #saasgrowth #saasmarketing #pricingforgrowth

Pricing Shastra is a management consulting firm specializing in pricing strategy for technology companies. We set up Pricing Shastra in 2023 with a goal to enable transformative growth 🚀 for growth stage tech companies through pricing and packaging initiatives. We have been fortunate that clients have reposed their faith in us and we have been able to respond by delivering impactful changes. Our recent work has featured: ⚡ Expanding market opportunity for a Generative AI copilot platform 👨💻 Unlocking growth for a leading composable web platform across PLG & SLG 🛍️ Increasing growth for a leading POS provider by optimizing pricing and packaging In the coming weeks and months, we will continue to share updates about our work through our “𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁” series of posts. We have observed that scaling tech companies often see ⚡ 𝘴𝘪𝘨𝘯𝘪𝘧𝘪𝘤𝘢𝘯𝘵 𝘨𝘳𝘰𝘸𝘵𝘩 𝘰𝘱𝘱𝘰𝘳𝘵𝘶𝘯𝘪𝘵𝘪𝘦𝘴 𝘧𝘳𝘰𝘮 𝘱𝘳𝘪𝘤𝘪𝘯𝘨 𝘢𝘯𝘥 𝘱𝘢𝘤𝘬𝘢𝘨𝘪𝘯𝘨 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯 ⚡ but are not always able to realize those opportunities - lack of access to Pricing expertise being a significant factor. Developing in-house pricing teams is not always a viable option for these scaling organizations. We combine our Pricing expertise ⭐, extensive experience in Tech ☁ industry and our relentless focus on delivering impact 📈 (rather than slideware) to enable our clients to realize the transformational opportunities from Pricing initiatives. Cornerstone of our consulting approach is to use our 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗳𝗼𝗿 𝗚𝗿𝗼𝘄𝘁𝗵 (𝗣𝗙𝗚) framework which enables us to shape pricing and packaging by holistically aligning with Product and GTM strategy. Staying true to our philosophy, we have been codifying our pricing knowledge in our Insights. We will post insights over the coming weeks on many topics through our “𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀” series of posts. We have seen many companies express interest in engaging with us and would request you to 🔁 𝕤𝕙𝕒𝕣𝕖 𝕥𝕙𝕚𝕤 𝕡𝕠𝕤𝕥 𝕓𝕣𝕠𝕒𝕕𝕝𝕪 𝕚𝕟 𝕪𝕠𝕦𝕣 𝕟𝕖𝕥𝕨𝕠𝕣𝕜 💬 to help connect us with more companies we can help.