The SaberyanModel for Adaptive Grid-Based Dynamic Bundle Optimization: Evidence from Factor-Based Simulated Data and Completely Randomized Design (CRD) Analysis

In today’s competitive environment, organizations are compelled to design their offerings in a manner that enhances perceived customer value while simultaneously improving sales performance and achieving a more efficient allocation of marketing resources. One of the key strategies in this domain is product and service bundling. However, a significant portion of the bundles utilized in the market remains static, failing to pay sufficient attention to customers’ behavioral, value-oriented, and preferential differences. The present study was conducted to propose and evaluate the “Saberyan Method” for dynamic bundle optimization based on adaptive customer grid-mapping. The primary data were extracted from the sales invoice file, which contained sales information for five product items. Since the initial data were recorded in the format of a single sales invoice and lacked the independent replicates required for inferential analysis, simulated data generation was performed based on the sales volume of each item to establish a proper statistical structure. Subsequently, the data were analyzed using a Completely Randomized Design (CRD) with five treatments and five replicates. Hypotheses were tested using one-way Analysis of Variance (ANOVA) and Duncan’s post hoc test at significance levels of ۵% and ۱%. The results indicated that the effect of treatments on the bundle performance index is statistically significant, and the treatment means are classified into distinct statistical groups. These findings confirm that dynamic bundling, when integrated with adaptive customer grid mapping, can serve as an effective decision making tool in marketing and the development of emerging businesses.

کلیدواژه ها:

Dynamic bundling ، Customer grid mapping ، Customer centricity ، Sales optimization ، Analysis of Variance (ANOVA) ، Duncan’s test ، Saberyan method