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- TV Demand Prediction
TV Demand Prediction
Increasing the value of advertising
Advanced prediction of demand on advertising space allows identifying the best pricing strategy from a maximum profitability standpoint, as well as the best programming grid configuration, at each point in time.
Advanced prediction of demand on advertising space allows identifying the best pricing strategy from a maximum profitability standpoint, as well as the best programming grid configuration, at each point in time.
The solution
In a highly competitive regulated market with changing rules, the ability to answer certain questions in advance, on the basis of anticipated information, yields significant competitive advantage.
Depending on a network's position in the market, the strategy to be developed, and therefore the questions to be answered, can vary substantially. In this regard, two radically different contexts can be defined:
Leadership position: The TV network dominates the market and there is a strong demand on its advertising space. In this case one may ask the following question: How much would network revenues increase by optimizing the location of purchase orders in the programming grid? And being more demanding yet on the improvement: What should be the optimal location for revenue maximization?
Trailing position: There is no predominance and therefore demand is far from the saturation point of advertising space. In this framework, the important question is the following: How much would revenues increase if pricing rates were improved for the different segments on the grid, lowering prices where there is no demand and raising them where demand is higher? In sum: What are the optimal rates for maximum market share?
The possibility of answering all these questions automatically and the ability to simulate profitability for various competing commercial strategies with updated market information, prior to launching the best option, provides companies with a tool that yields competitive advantage with positive impact on their bottom lines from the outset.
Depending on a network's position in the market, the strategy to be developed, and therefore the questions to be answered, can vary substantially. In this regard, two radically different contexts can be defined:
Leadership position: The TV network dominates the market and there is a strong demand on its advertising space. In this case one may ask the following question: How much would network revenues increase by optimizing the location of purchase orders in the programming grid? And being more demanding yet on the improvement: What should be the optimal location for revenue maximization?
Trailing position: There is no predominance and therefore demand is far from the saturation point of advertising space. In this framework, the important question is the following: How much would revenues increase if pricing rates were improved for the different segments on the grid, lowering prices where there is no demand and raising them where demand is higher? In sum: What are the optimal rates for maximum market share?
The possibility of answering all these questions automatically and the ability to simulate profitability for various competing commercial strategies with updated market information, prior to launching the best option, provides companies with a tool that yields competitive advantage with positive impact on their bottom lines from the outset.
The elements of the solution
In order to be able to simulate the economic impact of the different commercial strategies, without need for testing on the market, it becomes necessary to combine advanced information of various different types:
all this in the short, medium and long run.
Although each of the elements described yields competitive advantage by itself, the integration of all elements allows building a solution capable of answering the questions posed above.
- Assessment the market will make of each programming grid
- Competitiors offering and pricing rates
- Demand that will hit the market concurrently
all this in the short, medium and long run.
Although each of the elements described yields competitive advantage by itself, the integration of all elements allows building a solution capable of answering the questions posed above.
Main benefits
Forecasting demand on advertising space.
Advanced determination of advertising ratings for each viewing target, short, medium and long-term, both for the TV station and its competitors.
Impact simulation for grid configuration and related program performance changes.
Anticipating impact on the ratings of the programming grids involved resulting from:
Estimation of bottom-line impact for all different commercial strategies.
Determination of optimal pricing and grid configuration at each point in time, from a perspective of economic contribution to the P&L account.
Advanced determination of advertising ratings for each viewing target, short, medium and long-term, both for the TV station and its competitors.
Impact simulation for grid configuration and related program performance changes.
Anticipating impact on the ratings of the programming grids involved resulting from:
- Changes in program scheduling
- Inclusion of new programs
- Relocation and/or changes in duration of advertising segments
- Changes in station's internal regulation
- Changes in audience composition or size for a broadcast or all broadcasts of a specific program
Estimation of bottom-line impact for all different commercial strategies.
Determination of optimal pricing and grid configuration at each point in time, from a perspective of economic contribution to the P&L account.