Simulation Module

Simulation Module

Overview 

The Simulation module allows users to run different "what-if" scenarios or algorithm-driven budget optimizations to understand the best way to allocate the available marketing budget across different marketing channels.
 
By analyzing historical spending and the impact on key metrics like revenue and profitability, the module helps users explore how different marketing strategies might affect outcomes. While the Marketing Mix model considers both marketing and non-marketing factors, the Simulation module focuses only on marketing factors, assuming that other base conditions remain the same.

Getting Started

Publish a report/model to Simulation

To access simulation dashboard, user must publish a report to simulation. This is done by selecting the checkbox ‘Simulation’ in report module.


Default Dashboard 

By default, the dashboard is generated with certain pre-requisites like,


1.      It is generated for the latest 1 year from the first report that is published to simulation

2.      Response curves are generated at aggregated or highest dimension level

 

The dashboard includes four main options:

       1. Simulate Tab:

In the Simulate tab, users can run scenarios by entering the desired spend % or absolute value or use the slider. The default is 100% reflecting the total spend, revenue, profit and ROI for latest 1 year of the model duration. User has an option to simulate between 0- 3 times (0-300%) the base spends.

                                          

       2. Optimize Tab:

In the Optimize tab, users can optimize the marketing budget using the inbuilt algorithm. By defining their objective and setting constraints on variables and the total budget, the system simulates different scenarios to determine the ideal marketing mix that meets the specified constraints and goals.

                                               

To use this algorithm-driven optimization feature, click the Optimize tab and then specify:

            ·         Optimization Objective: Choose the objective between maximizing revenue or profit.

·         Budget Constraints: Set min and max constraints for the total marketing budget. To lock the total marketing budget at 100%, set both min and max to 100%.

·         Tactic Constraints: Set min and max spend constraints for individual tactics or groups, or both (default Min at 0% and Max at 300%). To lock the constraints by setting min and max to the same value.

·         Apply to All (optional) - Use this functionality to apply the same constraints for all the drivers (except the Total Budget).

·         Run the optimization.

·         The system will automatically adjust the variables to optimize spend allocation based on your criteria and see the optimized media plan with the highest performance within your defined constraints. To view the optimized plan, user must click on simulate tab.

Note: For multi-dimensional datasets, the user can provide constraints at the dimension at which the response curves were generated in both simulate and optimize tab.

     3. Key Indicators:
    • The dashboard displays four key indicators:
      • Spend
      • KPI
      • Revenue
      • Profit
      • ROI
     4. Filter Options:
    • The values in the filters are based on data classification. If the dataclassification has the following groups, Incremental, Base, Media and Non-media then the filter options will be:
      • Incremental
      • Total
      • Media
      • Non-media
    • "Total" includes both base and incremental values.

                Note: By default, key indicator values are displayed at the incremental level.


Additionally, the View Details feature, located next to the Optimize tab, expands to show a detailed table of base, forecast values for spend, contribution, revenue, profit, and ROI, along with the differences between forecast and base/default metrics.

Dashboard Charts

Each chart in the dashboard includes a default scenario and an optimized scenario.

Default Scenario – This represents the chart based on the created session, which serves as a comparison for the forecast scenario.

Forecast Scenario – This reflects the results obtained by the user after applying specific constraints.

In the dashboard view, the users can find the following charts in order,

1. Budget Allocator-

Budget allocator allows user to see how the simulation output (Simulate or Optimize) has changed the budget across channels in comparison to the initial allocation.

To depict this, the budget allocator chart shows comparison between default scenario and forecast scenario.

                   

Snippet of drilldown view,

               

 The default scenario displays the original media allocation amounts before any optimization, based on session duration and its settings. The forecast scenario shows the optimized values after applying the simulation with defined constraints.

2. Revenue-

The revenue chart helps in analyzing the revenue uplift from optimization, depicting the financial benefit gained by comparing Default vs. Forecast revenue.

              

Snippet of drilldown view,

             
             Default Scenario – Represents the revenue achieved with the original marketing budget and settings

Forecast Scenario – Represents the revenue achieved after optimizing variables within the constraints and the budget provided by the user.

3. ROI-

This chart features two ROI bars: one for the Default Scenario and one for the Forecast Scenario. Initially, both bars are at the same level, reflecting no simulation or optimization. After running a simulation or optimization, the Default Scenario bar shows the ROI for 100% budget allocation, while the Forecast Scenario bar displays the ROI based on the results of the simulation or optimization.

               

 Snippet of drilldown view,

         

4. Response Curve-

This chart shows the average returns curve for all media tactics in the model. The y-axis represents average return, while the x-axis shows spending as a percentage from 0% to 300% in 1% increments. The dotted vertical blue line marks the 100% spend level, representing the historical spend for each media tactic.

                     

To view details for a specific tactic, click the curve specific to the variable/tactic. And on clicking the curve the second time, it will display the optimal zone highlighted in green on the curve and clicking or drilling down third time will displaying the KPI curve from 0% to 300% of base spend, including Average Returns (AR) and Marginal Returns (MR) curves. The optimal spend range is between the peaks of the MR and AR curves.

Snippet depicting optimal zone (a) -

              

Snippet of KPI curve along with AR and MR (b),

         

For example, with google_shopping, the optimal range is 22% to 39% of base spend as shown in the screenshot (a) above. The data grid below the chart shows the average spend and revenue for the tactic.

          

While the response curves suggest an optimal spend range, consider relative ROIs and base spend levels for a comprehensive budget allocation decision.

5. Spend vs Contribution with ROI-

This chart helps the user to eyeball the difference between the ROI, spend and contribution share between the default and forecast scenario. For example, in the image below, the marketing budget is set at 100%, and when optimization is applied with constraints of 50% and 150%, the simulator can recommend spending between 50% and 150% of the current budget. After optimization, a shift in spend from offline to digital is observed due to the reallocation, leading to an increase in overall ROI while maintaining the same total marketing budget.

                       

There are additional features to this chart for optics, the Horizontal view and Switch view.

Horizontal view- user can view the bar chart in horizontal view.

                    

Switch view – In both the initial and horizontal views, the chart shows Spend, Contribution, and ROI for the Default and Forecast scenarios, using these metrics as legends. When the user selects Switch View, the chart updates to display Spend and Contribution as separate charts, while the Default and Forecast scenarios are represented as legends in the same chart for both spend and contribution.

                        

6.  Strategic Quadrants -

This chart illustrates four quadrants—Shift, Optimize, Expand, and Sustain—providing high-level investment strategy guidelines for each media and non-media tactic. The bubble size represents the spend level for each tactic, with Contribution plotted on the y-axis and ROI on the x-axis. The Default Scenario is shown in a lighter shade, while the Forecast Scenario is represented in a darker shade of the color assigned to the respective variable.
                  

This visualization helps in determining the strategic focus for each tactic based on its contribution and ROI. 

7.   Marketing Spend -

This chart is similar to budget allocator, but it is represented as a pie chart. This chart represents the spend share across the different media and non-media tactics for the default and forecast scenarios.
                                

8.  Marketing Contribution-

This pie chart represents the contribution share across the different media and non-media tactics for the default and forecast scenarios.
                            

Additional Features

  • Absolute Value Entry: Users can switch from percentage to absolute values in the constraints tab.
  • Drilldown Feature: Users can click on bars or pie segments to access more detailed levels. For instance, the budget allocator chart initially shows data for the Media group. Clicking on the Media bars will expand the view to reveal the next level, which includes Digital and Traditional categories in both dashboard and expanded view.
  • Dimension Filtering: For multi-dimensional datasets, users can filter results by specific dimensions using the 'Select Dimension' option.
  • Compare Scenarios: This feature is available at the top right corner of the scenario dashboard, and it allows user to compare saved scenarios and historical period with base scenario within the same session. At max, they can compare 4 scenarios. Note: All the scenarios can be compared within a session, comparisons across different sessions are not possible.

If user doesn’t want to go with default scenario, they can create new session by clicking on ‘Create New Session’ at top of the default dashboard.

Create New Session

A session acts as a workspace where users configure properties that apply to every scenario within that session. Sessions are used to create base/default scenarios for comparison against forecasted or optimized scenarios based on the user-provided constraints.

To create a new session, users need to configure the following:

1.      Simulation Scope:

Define the simulation scope by specifying the time-period (either historical or future), selecting the relevant dimension, and choosing the model to be used for

To set up a simulation session, follow these steps:

a.      Scenario Group Name: Enter a name for the session, avoiding special characters.

b.      Description: Provide a description for reference and this step is optional.

c.      Select Report: Choose the report you wish to use which are published from report module from the dropdown menu.

d.      Date Range: Define the simulation timeframe, whether it’s a historical period or a future-looking period.

e.      Dimension Filter: For single-dimension projects, the dimension will automatically default to the classified dimension, and the response curve aggregation will be generated at this level. For multi-dimension projects, all dimensions will be selected by default. The user must then choose the specific dimension at which they wish to generate the response curves.

f.        Import Marketing Plan: This feature allows for simulating data over a future period. Here’s a step-by-step guide to using this feature:

1.      Select the Report and Plan Period:

o    After selecting the relevant report, the user must define the plan period using the ‘Date Range’ option. 

2.      Export the Data:

o    Upon selecting the period, the user clicks on the Export button, the generated Excel file containing two sheets:

a)       Spend Sheet: This sheet includes data for the base model period or report period, with spend details for all variables eligible for simulation. It also includes the plan period and its corresponding data. 

For example, for a monthly dataset spanning from January 2023 to July 2024 as the base model/report period, and a planned period from August to December 2024 (5 months of future-looking period), the file will have spend data for all variables during the base model period and the plan period. 

Note: By default, the system populates the plan period with the latest 5 months of spend data from the base model, which can be edited according to business requirements.

b)       CPP Sheet: This sheet contains CPP information for both the base model and the plan period. The last data point's CPP from the base model is used as the CPP for the planned period, assuming a similar trend will continue.

Note: For multi-dimensional datasets, the export may contain multiple sheets for spend and CPP, depending on the supporting data specified in the variable properties within the Input module.

3.      Usage Scenarios:

                  This feature can be used in two keyways:

a)       Validation for Existing Period: To determine the potential contribution if additional investment had been made during the existing period. 

b)       Forecasting: To simulate scenarios for a future period.

                Note:  The user cannot select a period that combines historical and future data.

4.      Importing and Simulation Setup:

After the spend and CPP data for the plan period have been provided, the user must import the data. The user will then go through the data validation process, select groups, and configure steps from the response curve and financial inputs using the advanced settings if needed. This process prepares the user to create a simulation session.

Once all the steps are completed, the user is ready to simulate for the selected plan period. 

   2.      Data Validation:

The Data Validation module allows you to verify and adjust the data for your configured simulation scope period. Below are the features that can be used to review and modify the data,

         

a.      Key Parameters: Check essential parameters for each variable, including:

·         Period of execution (non-zero executions)

·         Spend amounts

·         Support values

·         Units

·         Unit Cost

·         Base period (defaulted to the simulation scope period)

b.      Zero Executions: Variables with zero executions are highlighted. You can either select a different base period or remove the variable. 

c.      Base Period Adjustment: To change the base period for any variable, enable the time period in the Advanced Settings and adjust the period.

Note: this new period must be of the same duration length as simulation scope period.

d.      Variable Removal: In Advanced Settings, you can also activate the ‘Remove Variables’ option to delete variables that are not required for simulation. 

     e.    Pick period using ‘View Chart’: Select a variable and click 'View Chart' to visualize the data graphically and it highlights the spend pattern of its base period selected. This helps in selecting a comparable period from the full report timeline that aligns with the simulation scope period. By clicking on the datapoint on the chart at which the period must start, the base period start date changes automatically. This period will be same duration length as simulation scope period.

1.      Select Groups:

o Select the data classification level at which user must simulate.

For example, the below table is structure of data classification displayed in Select Groups,  

Users can select different levels to simulate. For instance, they might choose to simulate Digital at group 3 or variable group that is at “Google_Shopping”, “Meta_Conversions”, “Performance_Max”, “TikTok” and “X” and simulate "OOH_H1" and ”OOH_H2” at Group 2, that is at Traditional without including its group 3 components.

To simulate at the "Traditional", users should activate the toggle for group 2 as shown in the example screenshot above.

2.      Advanced Configuration Settings: Below are the features available in advanced settings,

o    Edit Time Period: Override the base period for individual variables.

o    Remove Variables: Delete variables that are not required for simulation.

o    Response Curves: Examine response curves based on the chosen aggregation and select groups.

o    Financial Inputs: By default, it displays the financial inputs set in input module but for the simulation, if It has be changed then user can use this feature to enter financial input (Coverage factor, gross margin, ROI Parameters) specific to this session.

3.      Session Summary:

o    Review the session summary and click ‘Create Session’ to proceed. 

Viewing and create new Session

1.      After session is created user will be navigated to the scenario list page for the specific session. If user wants to view other sessions, they can use the session dropdown and select if there are any existing sessions or click back button and it will take the user to session list page.

2.      User can click on ‘New Session’ button from bottom of the page to create a new session.

Viewing and create new Scenarios

After creating a session, users are directed to the scenario list page for the session that was created, where they can view and create scenarios.

1.      View Scenario:

a)      To view the scenario from session list page, user must click on ‘View Scenario’ which will navigate to scenario list page for the particular session.

b)      When user is in scenario list page, default scenario name, spends, KPI values, revenue, profit, ROI and when the default scenario was created are displayed. These values are generated based on the session configurations.

2.      New Scenario:

Within a session, users can create multiple scenarios by clicking ‘New Session’ to run simulations and save the outputs.

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