In　marketing,　customer　segmentation　is　a　very　critical　element.　This　paper　focuses　on　clustering　algorithms.　First,　the　commonly　used　K-means　algorithm　was　introduced,　and　then,　it　was　optimized　using　the　improved　Lion　Swarm　Optimization　(ILSO)　algorithm　and　the　Calinski-Harabasz　(CH)　index.　The　results　of　the　experiment　for　the　UCI　dataset　showed　that　the　CH　indicator　obtained　an　accurate　number　of　clusters,　and　the　clustering　accuracy　of　the　ILSO-K-means　algorithm　was　higher,　both　above　90%.　Then,　in　customer　segmentation,　the　customers　of　an　enterprise　were　divided　into　four　groups　using　the　ILSO-K-means　algorithm,　and　different　marketing　suggestions　were　given.　The　experimental　analysis　proves　the　usability　of　the　ILSO-K-means　algorithm　in　customer　segmentation,　which　can　be　further　applied　in　practice.