Claims:We Claim:
1) A real estate marketing system, comprising of: programs to advertise an array of relevant real estate product and services to the targeted potential consumers based on pattern generated on commonalities between all the advertisement listings that the user viewed or liked, not limiting to just one product or service, ultimately enhancing probability of purchase.
2) A system of claim 1, wherein it can include aggregation of user click data and analysis
3) A system of claim 1, wherein it can include development of pattern based on user data analysis.
4) A system of claim 1, wherein it can include classification and listing of advertisement related to real estate properties based on user preferences
5) A system of claim 1 wherein, the marketing tool matches the user profiles with relevant real estate data set.
6) A system of claim 5 wherein, the marketing tool targets the matched users through relevant advertisements.
, Description:Technical Field of the Invention
The subject matter of the invention relates to the field of real estate. More particularly, the invention discloses artificial intelligence-based advertising method and computer application system to identify and target potential buyers on the basis of their own search patterns. Further, the system is integrated with real time real estate data and social networking platforms for promoting an array of similar real estate property advertisements based on the search history of the target consumers/ buyers.
Background of the Invention
Purchasing a real estate property is one of the most important decisions of a person’s life. Whenever a consumer wants to purchase a property, it has many emotional as well as practical considerations attached to it. A consumer has to spend a huge amount of money while purchasing a house of his own and that is one of the reasons why he prefers spending considerable amount of time on prior searching, before finalizing the purchase or renting of a real estate property. Property search is a time consuming process but is aided/ fastened by catalysts such as real estate brokers, agents or real estate companies or digital marketing solutions.
Several real estate agencies contact their potential consumers through various means such as hoardings, posters, announcements, expo, tele- calling, commercial advertisements, personal advertisements etc. In this era of digital marketing, personal advertisement is a potent tool used by real estate agencies/ firms/ companies to attract their consumers for their product and services.
The real estate digital marketing websites allow their users to search and determine property information as per their preferences. These websites rely on accessing users’ search history data to push advertisements through multiple digital channels. While this method can identify user’s real estate need but fails to give an output of multiple options with similar parameters. Patent application number KR100883700B1 effectively provide a wide range of product information tailored to the customer and various kinds of information relating to commerce but does not take into account advertising other similar products/ services that fit into consumer’s real estate preferences.
To give a technical solution to the above mentioned problems, the current invention approaches to create a self learning Artificial intelligence based algorithm.
Object of the Invention
The object of the present invention is to provide a real estate marketing system that provides information related to real estate product and services to the prospective clients based on customer preference data and pattern generated on commonalities between all the advertisement listings that the user viewed or liked so as to enhance the probability of purchase/ sale.
Summary of the Invention
In one embodiment of the invention, an advertising system is provided based on search patterns of the prospective users. The system advertises similar set of real estate properties that matches to the interests of the prospective users on behalf of advertisers, increasing the probability of purchase or sale.
Brief Description of the Drawings
Fig.1 shows an example of process and system for generation of list of advertisements in accordance with aspects of the present invention
Fig.2 shows an example of process and system for developing a user search pattern based on user click data along with generation of relevant list of real estate advertisements and display of array of similar real estate advertisement to targeted user profiles in accordance with aspects of the present invention.
Fig.3 shows an example of process and system for generation of user click data based on interests of the user in accordance with aspects of present invention.
Detailed Description of the Invention
Behavioural patterns of the consumers play a key role in transactions related to a real estate industry. Real estate property purchase being a costly affair, a consumer makes sure that the property he buys or rents, is as per his or her needs and aspirations. When it comes to selection of any real estate property, it is also a time consuming process as it needs a thorough searching and proper evaluation, till it fits in consumer’s preference criteria. Conventional methodologies to search and buy the real estate fail when consumer preferences are not taken into account. However, many of the above mentioned drawbacks can be eliminated by the system disclosed in the present invention.
In the present invention, a system is developed wherein a user click data, based on multiple factors related to real estate such as property type, budget, construction status, etc. is procured. This data is further evaluated using advanced AI-based methods to generate a pattern based on searches carried out and filters used by the user.
Another embodiment of present invention describes a system where the search pattern generated is further matched with information in the real estate digital market repository on the basis of which an array/ list of relevant targeted advertisements is generated.
Another embodiment of present invention describes a system where the array/ list of relevant, targeted advertisements generated is displayed/ presented frequently to the users on web application, enhancing the chance of purchase.
The source of data 101 may include digital market place logged in by the user 102 to carry out a search on real estate properties. The application 103 may aggregate user click data based on searches carried out by the user. The application 104 analyses the user click data and develops a pattern on the basis of which application 105 carries out listing of real estate property advertisements that matched the preferences of the user. The list of advertisements 106 is displayed to user interface 107. This system ameliorates the frequency of displaying a set of similar advertisement to the user 102 that fits his requirement criteria, which ultimately increases the possibility of property purchase.
The database 201 may include real estate data based on multiple factors related to real estate such as purchase price, rental price, business property details, brokerage details, loan details, immovable property details, neighbourhood, amenities, recreation, water supply, sewage & waste management, domestic help, layout, size of property, utilities, etc. The database 202 may include system to aggregate the data gathered from various sources. This data is further analysed by application 203 and classified into multiple advertisement categories such as C1, C2, C3.....Cn. This classified data is further analysed by application and multiple listings of advertisements 204 are developed and displayed to the user 206 on the web application 205 such as Advertisement No. 1, Advertisement No. 2, Advertisement No..... Advertisement No. n.
The application 302 may include real estate data filtration on user end wherein the filters such as property type, budget, construction status, number of rooms, property features, etc. depicted as F1, F2, F3, F4...Fn are the property parameters chosen by the user 301. The database 303 may include the user click data based on application 302 which is further used to develop a pattern based selection of advertisements for the user 301.