Introduction
What is a simulation?
Simulations allow you to visualize price changes in Orb before you make them, without any of the billing risks associated with traditional price experimentation.
Because Orb sits at the unique intersection of your product usage and revenue data, Simulations have a number of powerful applications, including:
- Backtesting to de-risk price changes
- Forecasting for new product pricing
- Churn prediction and prevention
Input price change(s) you’re considering as scenarios, and a set of simulation parameters to kick off a simulation. Orb will output forecasted revenue, customer impact, and churn guidance by scenario using your real historical data, so you can make a more informed decision.
Orb Setup
To use Simulations, make sure you’re first up and running with Orb. Orb’s Quickstart guide can help you get started.
Specifically, you’ll need to:
- Ingest events: this gives Orb visibility into your product to power the simulation
- Define a billable metric: this models the specific change / new price(s) you’re introducing
- Have a plan with subscriptions: this is how you’ll define the cohort parameter for your simulation
Creating a simulation
Step 1: Define simulation parameters.
Name your simulation for easy reference, set a time frame, and select a plan to run your simulation over. This determines the actual historical data that will be used in your simulation.
Ensure you define parameters that provide sufficient, and representative data.
Step 2: Create one or more scenarios to simulate.
A scenario represents a hypothetical price change you’re considering.
- Usage-based prices are best used to model prices that scale with variable events like costs, product actions, and/or outcomes.
- Ex: tokens consumed, conversations started, resolutions achieved.
- Fixed fee prices best represent a platform fee or minimum spend, typically used for capturing upfront revenue.
A simulation can include one, or multiple scenarios to compare to your baseline historical data. We recommend up to 5 scenarios in a simulation.
Common scenario setups:
- Optimize the price point: create a scenario, then duplicate and assign different rates.
- Determine your value metric: create multiple scenarios for different value metric candidates - one per usage-based price to be considered.
- Choose a pricing strategy: create multiple scenarios to evaluate different strategies like standalone usage-based pricing vs. hybrid usage + fixed fee pricing.
- Choose a pricing model: create multiple scenarios to evaluate different price models like unit vs. tiered pricing.
Step 3: Run the simulation.
You’ll receive an email when your simulation is complete and insights are ready for review.
Actioning on insights
The results of your simulation are designed to help inform your decision on how / if to implement your price change. Key revenue and customer risk impacts associated with your changes are highlighted for consideration, replacing the tedious spreadsheet alternative and freeing up valuable Finance and Bizops resources.
Top-line insights
Use the summary of your simulation inputs (scenarios and parameters) to refresh on context for what went into your analysis.
The top-line revenue, and customer impact insight cards highlight the upside potential and downside risk associated with your price change for customers included in the simulation.
When considering a price change, you don’t want to only optimize for revenue uplift. You’ll want to weigh the risk of price hikes on your existing customers, especially your largest ones.
Orb highlights the scenario with the largest absolute increase in revenue, and the scenario with the lowest relative % change relative to what a customer currently pays in blue, to help you make a more balanced decision or iterate on your price change.
Deeper insights
Monitoring how incremental revenue changes over time across scenarios helps to diagnose unexpected variability, identify seasonality impacts, and illuminate foundational product usage patterns to consider.
Typically, you’ll want to aim for a smooth and consistent revenue curve over time. Inconsistent revenue spikes may suggest this price change is not in line with your optimal monetization strategy.
Understand where the impact of your price change is concentrated to balance absolute vs. relative % change. Said another way, a $5 increase is going to have a different effect on a customer currently paying you $1, vs. $100.
You’ll want to aim for scenario outcomes concentrated in the bottom right of the graph – these introduce the least risk (% change to baseline revenue), with the greatest upside (actual revenue change).
Use the customer impact table to proactively identify which customers will be affected by your change, and get ahead of notifying your customer teams.
Then, in partnership with GTM, leverage Orb to:
- Look at historical subscription(s) and invoices to understand customer LTV
- Create a new plan version or price override to accommodate exceptions
- Control migrations of affected customers to a plan version, while grandfathering marquee customers on existing plans if needed
Introduction
What is a simulation?
Simulations allow you to visualize price changes in Orb before you make them, without any of the billing risks associated with traditional price experimentation.
Because Orb sits at the unique intersection of your product usage and revenue data, Simulations have a number of powerful applications, including:
- Backtesting to de-risk price changes
- Forecasting for new product pricing
- Churn prediction and prevention
Input price change(s) you’re considering as scenarios, and a set of simulation parameters to kick off a simulation. Orb will output forecasted revenue, customer impact, and churn guidance by scenario using your real historical data, so you can make a more informed decision.
Orb Setup
To use Simulations, make sure you’re first up and running with Orb. Orb’s Quickstart guide can help you get started.
Specifically, you’ll need to:
- Ingest events: this gives Orb visibility into your product to power the simulation
- Define a billable metric: this models the specific change / new price(s) you’re introducing
- Have a plan with subscriptions: this is how you’ll define the cohort parameter for your simulation
Creating a simulation
Step 1: Define simulation parameters.
Name your simulation for easy reference, set a time frame, and select a plan to run your simulation over. This determines the actual historical data that will be used in your simulation.
Ensure you define parameters that provide sufficient, and representative data.
Step 2: Create one or more scenarios to simulate.
A scenario represents a hypothetical price change you’re considering.
- Usage-based prices are best used to model prices that scale with variable events like costs, product actions, and/or outcomes.
- Ex: tokens consumed, conversations started, resolutions achieved.
- Fixed fee prices best represent a platform fee or minimum spend, typically used for capturing upfront revenue.
A simulation can include one, or multiple scenarios to compare to your baseline historical data. We recommend up to 5 scenarios in a simulation.
Common scenario setups:
- Optimize the price point: create a scenario, then duplicate and assign different rates.
- Determine your value metric: create multiple scenarios for different value metric candidates - one per usage-based price to be considered.
- Choose a pricing strategy: create multiple scenarios to evaluate different strategies like standalone usage-based pricing vs. hybrid usage + fixed fee pricing.
- Choose a pricing model: create multiple scenarios to evaluate different price models like unit vs. tiered pricing.
Step 3: Run the simulation.
You’ll receive an email when your simulation is complete and insights are ready for review.
Actioning on insights
The results of your simulation are designed to help inform your decision on how / if to implement your price change. Key revenue and customer risk impacts associated with your changes are highlighted for consideration, replacing the tedious spreadsheet alternative and freeing up valuable Finance and Bizops resources.
Top-line insights
Use the summary of your simulation inputs (scenarios and parameters) to refresh on context for what went into your analysis.
The top-line revenue, and customer impact insight cards highlight the upside potential and downside risk associated with your price change for customers included in the simulation.
When considering a price change, you don’t want to only optimize for revenue uplift. You’ll want to weigh the risk of price hikes on your existing customers, especially your largest ones.
Orb highlights the scenario with the largest absolute increase in revenue, and the scenario with the lowest relative % change relative to what a customer currently pays in blue, to help you make a more balanced decision or iterate on your price change.
Deeper insights
Monitoring how incremental revenue changes over time across scenarios helps to diagnose unexpected variability, identify seasonality impacts, and illuminate foundational product usage patterns to consider.
Typically, you’ll want to aim for a smooth and consistent revenue curve over time. Inconsistent revenue spikes may suggest this price change is not in line with your optimal monetization strategy.
Understand where the impact of your price change is concentrated to balance absolute vs. relative % change. Said another way, a $5 increase is going to have a different effect on a customer currently paying you $1, vs. $100.
You’ll want to aim for scenario outcomes concentrated in the bottom right of the graph – these introduce the least risk (% change to baseline revenue), with the greatest upside (actual revenue change).
Use the customer impact table to proactively identify which customers will be affected by your change, and get ahead of notifying your customer teams.
Then, in partnership with GTM, leverage Orb to:
- Look at historical subscription(s) and invoices to understand customer LTV
- Create a new plan version or price override to accommodate exceptions
- Control migrations of affected customers to a plan version, while grandfathering marquee customers on existing plans if needed