<![CDATA[The real estate industry has seen more dependence on SaaS solutions as tools for efficiencies, data, and CRM. However, the best SaaS products are the services they provide and the sales funnel that results in customer acquisition and profitability. This paper aims to review the major steps of the SaaS sales funnel and its application in the real estate industry of Reonomy Company, where these stages involve: awareness, consideration, decision, onboarding, and retention. They all have a significant function of transferring potential buyers from when they get their attention to when they become loyal customers. Many struggles often come with SaaS having high churn rates, which are dangerous for revenues. It also shows how ML can be used in this case to help predict and even prevent churn by defining high-risk customers. Promotional emails, offers, discounts, and dynamic pricing models are discussed as important techniques that address customer churn and retention. Contacting all the users based on real-time data, SaaS companies provide value to both nominally logged-in and highly active customers. Analyzing Reonomy’s application of customer retention with ML reveals the potential of a highly designed funnel for preserving customer bases and maximizing CLV. The observation supports the need to synchronize the data collected by machine learning algorithms with the company’s marketing and customer service strategies as critical for sustainable growth in the highly competitive real estate SaaS industry. Based on the analysis in this paper, it becomes clear that data analytic approaches help to cultivate sustainable consumer relationships and business profitability.]]>
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