STRATEGIC PREDICTION USING MARKETING INTELLIGENCE SYSTEMS: A COMPARATIVE STUDY BETWEEN AL-BAWADI AND AL-MARA’I COMPANIES WITHIN THE FOOD PRODUCTS SECTOR IN IRAQ - Assist Prof. Ahmed Sameer. N. Al-Thabit; Assist Prof. Ahmed Abbas Hammadi (Scholars Digest Publishing, 2025)
This study aims to explore how marketing intelligence systems can enhance strategic predictions within the food products sector in Iraq, focusing specifically on these two companies. By employing a quantitative approach, data collection is carried out by following the Stratified Sampling Method. This method can be defined as a probability sampling method applicable in quantitative research, where the population is divided into well-defined groups called strata such that within each stratum, individuals share some common characteristics, and then researchers take a random sample from each stratum. The sample size comprises 90 marketing managers and experienced employees from Al-Bawadi and Al-Mara’i Food Products Companies in Iraq (45 managers and employees from Al-Bawadi Company and 45 managers and employees from Al-Mara'i Company). For the sake of implementing this quantitative study, the researcher built a questionnaire of 11 items depending on this research question. It was judged by a group of assistants and associate professors who have the same major. The questionnaire items are filled in by the participants. Their responses are carefully studied and analyzed statistically. Likert's three-point scale frames their responses as: agree, neutral, or disagree. The results show that the use of the marketing intelligence system by Al-Mara’I Company adds a lot to the quality of strategic decisions. The system works effectively in Al-Mara’i to help it understand the likes of customers. The marketing strategies of Al-Mara’i Company are more data-oriented compared to Al-Bawadi Company. Workers at Al-Mara’i have received enough training to use the systems of marketing information effectively.
Keywords: Marketing strategies, marketing intelligence systems, food sector.