Simulation of Telecom Market in Argentina

Problem Definition

In 2008 there were three huge companies in the telecommunications market in Argentina. Each company sold some of the four products (known as “quadruple play” when combined), including high speed Internet, cable TV, telephone, and cell phone services. Many households purchased individual services from the different companies. The aggressiveness of the players made “product bundling” a key marketing strategy, but there was not a clear understanding of how to use this strategy, or the impact it might have on the market.

Each company wanted to enter the markets that they hadn’t covered yet, but each one knew that penetrating the competitor’s niche would force them to reply in the same manner. The consequences of such actions had to be estimated. That’s why Telefónica (one of the competitors) decided to employ Continente Siete, a consulting company, to build a model of the market using AnyLogic multimethod simulation software.

The challenge was to build a model that would allow the client to analyze several scenarios, taking into account the whole telecom market (with its 3 major players) and the “product bundling” effect. Scenarios had to cover the telecom market evolution for 24 months and issue an integrated set of metrics (market share for each product, revenue, brand effect, etc.). The model had to consider all 100+ products potentially available in the market. It also had to work with a previous conjoint analysis made specifically for this purpose, as well as include historical information on complementary products and macroeconomic variables.


The core of the model was consumer choice. Households were modeled as agents (1 agent simulates 1000 people). The whole consumer decision process (Know-Evaluate-Decide-Implement) was embedded into each consumer agent, based on the results of the conjoint analysis. Many factors influenced consumers in their decisions. For example, the conjoint analysis allowed the estimation of each product’s attribute value (including both price and brand) for each consumer. Besides those preferences, the consumer had to be familiar with each new product and keep it in mind before buying. Also, wallet restrictions were added, as all of the agents were divided into three groups by their income level. Other barriers, such as needing to buy a PC to have Internet, going through the hassle of changing the service provider, and even the service provider’s retention strategies (making a better offer to a customer who wants to quit the service), were also taken into account.

The companies were modeled as agents too. They dealt with different levels of the four basic products (for example, low-speed Internet vs. high-speed, etc.), bundles, promotions, and retention offers. Prices, promotion lengths, retention policies, and even the launching of new products were all controlled by the companies. 

Market Model Structure and Consumer Behaviour Simulation

The whole model reflected the current state of the market, including the companies, their income, their number of customers (structured by geographical and socio-economic properties), technologies sold by the companies, government regulations implied, and PC market evolution over time. All macroeconomic variables were simulated with the System Dynamics approach. An adapted innovation diffusion Bass model was used to model PC evolution over time.

Scenarios were built to understand possible outcomes of launching the new basic products for each company. A particular emphasis was placed on possible delays between the competitors’ product releases. Price escalation and promotion removal scenarios were also tested. Another key question was the subsidization of buying PCs for low income consumers. Scenarios were built to understand the impact of this policy.


It was the high flexibility of AnyLogic simulation software that allowed the consultants to grasp the system in its complexity. It allowed them to build a truly multimethod model using System Dynamics for reflecting the market as a system and Agent Based Modeling for simulation of the behavior of each household and of the companies.

The use of the validated model for scenario generation allowed Telefónica to build up their strategic plan for 2009 to optimize their performance in the market. 

Watch the video of J. Pablo Rodríguez Varela, the co-founder of Continente Siete , presenting this case study at The AnyLogic Conference, or download his presentation.

More Case Studies

  • Major US Airline Decides NOT to Charge Additional Fees
    A major US airline wanted to explore several options to generate new profits through ancillary products or changes to existing policies. Although the revenue generation through charging additional fees was apparent in the short term, prior to implementing a policy change, the airline opted to evaluate the long term perceived impact on brand equity, market share and customer loyalty.
  • American Motor Vehicle Market Simulation
    One of the world’s leading motor vehicle producers needed a strategic forecast of their performance in the US market for the next five years. The company wanted to estimate the dynamics of demand on their product and the expected revenue, taking into account current clients, dealers, competitors, and the used vehicle market. Their main objective was to determine how much product the company would need to produce in the following years.
  • Modeling of a Pharmaceutical Product Launch
    One of the huge pharmaceutical companies employed Bayser Consulting for development of product launch strategy. Simulation modeling was applied for reconstruction of interactions between the company, doctors and patients.
  • AnyLogic Simulates Consumer Choice in Telecommunication Market
    Evans & Peck and Alcatel Australia jointly developed an agent based model of consumer choice of Internet services which allowed market scenario analysis for the following 10 years.
  • A Pharmaceutical Company Decides on a Marketing Strategy Using Agent-Based Modeling
    Sterling Simulation consulting company was chosen to provide an agent-based marketing model for a pharmaceutical firm. The company owned two competing non-generic drugs on the same market. One drug was well established and tended to be the industry leader, and the other one was recently introduced. There were several concerns about how to obtain a useful market share for the newer drug, while maintaining or increasing the market share for the company’s drugs as a whole.