Optimizing Team Integration in M&A: A Classification Approach Based on Target Market Buying Behavior

This study presents a quantitative framework for classifying commercial organizations based on target customers’ purchasing patterns to optimize post-merger team integration. This data-driven approach offers a quantitative tool for anticipating and mitigating integration challenges in heterogeneous markets. Using a mixed-methods approach, we analyzed transaction data from a range of companies. Hierarchical clustering algorithms identified distinct buying behavior profiles, while logistic regression correlated these with integration success metrics. Results indicate that post-merger integration efficacy inversely correlates with the heterogeneity of buying behaviors across merged entities’ target markets.