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In the classic recency‐frequency‐monetary value (RFV or RFM) approach to market segmentation, customers are grouped together into an arbitrary number of segments according to data on their most recent day of purchase (R), the number of buying orders placed (F) and the total monetary value of their purchases (V). The purpose of this paper is to show how to select the order in which the RFV dimensions are applied to data and choose the number of segments and the time frame used in such a way as to maximize the results of direct marketing campaigns.

A “genetically” optimized RFV model is built from data collected from a real world direct marketing campaign. The results produced when it is used are compared with the results yielded without the use of any forecasting method at all and with the support of a widely used basic RFV model.

Not only does the new model provide better results, but it is also easy to build and allows for the introduction of new dimensions that may improve its performance even further.

The new model improves the cost‐effectiveness of direct marketing campaigns by permitting more accurate identification of a company's most valuable customers and improving the quality of communication with its customers. It can thereby help them to become more competitive and profitable. This has clear implications for the gathering of marketing intelligence and planning of marketing strategies.

Although genetic algorithms have been shown to be powerful tools for problem solving, their use in marketing has been little reported. This work is a step towards bridging that gap. The genetically optimized RFV model is a new contribution to direct and relationship marketing, generating a positive qualitative and quantitative impact on the way companies relate to their customers.

The purpose of this paper is to investigate the use of Pinus wood waste in lead adsorption as a remediation technique in aqueous medium and its subsequent use in obtaining synthesis gas.

The capacity of the timber in the lead adsorption was studied in aqueous medium at various pH, determining the amount adsorbed in equilibrium. Then, the same timber was added in a fixed bed, co-current flow of two stage gasifier type, working temperature of 900°C, for obtaining synthesis gas. The synthesis gas composition was evaluated by the spectrophotometry in the infrared region and the gas chromatography and lead content in the ash and gas was determined by the atomic absorption spectrophotometry.

In laboratory tests carried out, the optimal pH for lead removal was pH 4 with 96.15 percent removal rate, reaching equilibrium after 180 min. In pilot scale the lead removal after 72 hours was 96 percent. The average production of syngas was 11.09 m³h⁻¹. For tests with the motor-generator, the best condition occurred with charge of 2.0 kW, wherein gas consumption per kW produced reached 4.86 m³ kW⁻¹, resulting in a 14.81 percent efficiency rate. The gas analysis showed an average concentration of 14.85 percent H₂, 30.1 percent CO₂, and 50.49 percent of atmospheric air. The concentration of lead in the gas was below the limit established by law. Pinus elliottii waste proved to be an excellent adsorbent, with removing more than 96 percent of the Pb ion present in aqueous solution and a starting material in the gasifier to generate synthesis gas.

This paper describes the waste wood application in the treatment of contaminated environments and for obtaining syngas providing a sustainable process.

This paper shows a process that combines the remediation of contaminated environmental with power generation systems, allowing efficient management of contaminated environments.