Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal The Eastasouth Journal of Information System and Computer Science
Goel, Krupa
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Optimal Sales Funnel for a SaaS Product in Real Estate Goel, Krupa
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 01 (2023): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i01.449

Abstract

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.
Lead Prioritization: A guide to maximizing sales using analytics and AI in Real Estate Goel, Krupa
The Eastasouth Journal of Information System and Computer Science Vol. 1 No. 03 (2024): The Eastasouth Journal of Information System and Computer Science (ESISCS)
Publisher : Eastasouth Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/esiscs.v1i03.450

Abstract

In this highly competitive market, selecting the right lead that would bring significant sales conversion is one of the keys to an effective real estate business. In the following paper, we discuss the function of analytics and artificial intelligence in transforming lead management in the real estate industry. Conventional methods of lead prioritizing involve the rote use of the gut feeling of a salesperson, which, although inefficient, leaves much room for potential errors. Incorporating AI and analytics lead management thrust real estate agents into data analysis, where agents can make predictive and behavioral decisions based on stated data. Through lead scoring tools and other intelligent platforms such as AI, an agent can determine high probable lead conversion, directing efforts to more converting leads. Furthermore, this paper examines the use of big data analytics in predicting market trends and buying behavior to improve the position of agents competing in a highly technological marketplace. The paper also discusses changes in buyers' needs, including the interest in customization and environmental sustainability, which are gaining importance in lead selection processes. For this, adopting these technologies not only makes operations more efficient but also assists agents in building better client relations by initiating marketing that would capture the clients' interest and subsequently follow up on them. The lead management of the real estate industry will only improve due to enhanced artificial intelligence and analytics in the future. This paper acts as a reference for real estate agents trying to incorporate current tools in managing their leads to improve their chances of closing deals.
Co-Authors