The present invention relates generally to the field of sales and marketing. More particularly, the present invention relates to facilitating the development of leads or enhancement of consumer relationships.
The proliferation of on-line services has facilitated a variety of transactions between the buyers, sellers and other associated parties such as advertisers, agents, brokers and other intermediaries. In case of a real estate transaction, a buyer may simply log into, or otherwise access, a website that contains a number of listings in order to search for his or her desired real estate property. Such websites typically allow a buyer to narrow the search by specifying the desired property characteristics, such as the price range, square footage, number of rooms, zip code and other criteria. The buyer is then presented with a number of properties that meet the specified search criteria. Similarly, a seller of a property may list a property using an online service to make it available for viewing by hundreds or even thousands of potential buyers or renters.
Real estate agents have also benefited from the proliferation of real estate on-line services because companies that operate the on-line services often connect their website visitors with real estate agents and sales associates. The real estate agent or sales associate may, for example, place advertisements on the pages that contain the on-line listings. The agent or sales associate may also pay a subscription fee or a fee per lead to the on-line service for receiving leads (contact details of potential customers). Such leads are usually based on the information submitted by the consumers during the registration process. For example, a user of an on-line service may be prompted to provide contact information and desired property specifications so that he/she can be contacted by a real estate agent or receive email updates when new properties are listed that meet the user's search criterion. The agents may also restrict the received leads to correspond to properties within certain zip codes, price ranges and other characteristics. The on-line service then matches the incoming leads with the agent's preferences, and provides the matched leads to the appropriate agents and sales associates.
The disclosed embodiments of the present invention relate to devices, methods, and computer program products that may develop a lead or to enhance a relationship with a lead or a consumer.
Embodiments of the invention are described by referring to the attached drawings, in which:
In the following description, for purposes of explanation and not limitation, details and descriptions are set forth in order to provide a thorough understanding of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments that depart from these details and descriptions.
In various examples, devices, methods, and computer program products are provided that may automate the identification, selection, development or enhancement of relationships with various users, including sales leads, such as those generated from a real estate online service or imported from an existing sales lead database. Relationships may be developed or enhanced by monitoring and/or recording the behavior of the users as they use online service(s), such as websites, web apps, or mobile apps. Data from various sources, such as real estate property and listings data may be analyzed. Further, in various examples, personal information provided by either the clients (e.g., agents) or the users may also be analyzed. The analysis of the various information may be used to automatically detect useful, notable, relevant, or important events relevant to the user. Using the recorded and/or derived data, the devices, methods, and computer program products may automatically alert clients (e.g., agents) of the identified event and/or user, providing indications and details of the behavior and motivations of the user, as well as suggested actions the client should take. Further, messages may be automatically generated (e.g., selected from a database of messages) that are relevant, personal, and timely to the user in a manner such that the messages seem to be written by a human being.
As noted earlier, on-line real estate services often produce a volume of leads that make it difficult for a subscribing real estate agent or sales associate to efficiently sort through and respond to or follow up with potential customers or leads in a timely and effective manner. To overcome these obstacles, the agent is thus faced with a two-fold task. First, the agent needs a solution to identify which of the many leads is most likely to represent ureal buyer or seller in the near future so that the agent can best maintain the relationship with that lead, concentrate his/her attention on that lead and ultimately convert the lead into a sale. Second, the agent needs to communicate with a great volume of leads in the most specific manner possible because specific communication is more likely to be opened, read and responded to by consumers, whereas generic communication is generally deleted by consumers or marked as spam.
In various exampled described herein, the terms customers, consumers, leads, clients and users are used to describe users of the system that may be purchasers, sellers, potential purchasers or potential sellers, for example. The terms customers, consumers, leads, clients and users are used interchangeably herein. Further, in various examples, the users may be potential leads (e.g., a first-time interaction) or may be past relations (e.g., past buyers or sellers of property that have interacted in the past with the system and/or the agent).
Traditional lead generation methods also produce a large number of leads based on an initial snapshot of consumer interests that are not updated based on the consumers' ongoing behavior and updated interests. In high-valued transactions with long sales cycles, the consumers often conduct additional searches and/or make further refinements to their initial selections. For example, a real estate consumer may return to an on-line real-estate service to narrow the price range, modify the neighborhoods that are being searched or fine-tune additional search criteria, over the course of a long sales cycle.
The disclosed embodiments improve and facilitate communication with a user to, for example, produce a high-quality relationship between the agent and the user. The user may be, for example, a lead or a current client.
The on-line services may allow access to different types of properties and services. In the on-line real estate service example, the properties can include residential, commercial, industrial and/or other types of property listings, as well as associated websites, databases and services. An example real estate listing may include property specifications that are represented in text, picture and/or video formats. Such listings often allow a user who conducts a property search to specify the desired property characteristics, such as price range, address, zip code, square footage, number of rooms and the like. A user can thus search for and obtain a list of the desired properties. Such listings may, for example, be obtained through Multiple Listing Service (MLS) database. A typical web page associated with the on-line services may also include advertisements and/or information associated with one or more real estate agents, lenders, contractors or other persons or entities promoting their products or services. In some variations, the on-line services may be incorporated into the website of a particular real estate professional.
Referring back to
The processing center 106 of
In an example scenario, a user of the on-line services may log into, or otherwise access, an on-line real estate services website. A new user may initially be asked to provide certain identification information, such as name, email address, phone number, mailing address and the like. The user may then start using the on-line services. For example, a user may browse a number of property listings in a particular neighborhood in order to evaluate, and perhaps ultimately purchase, a listed property. Before any purchase, however, a user often returns to the on-line service's website to expand or narrow the search premises, view additional properties and/or revisit some of the properties that he/she has already viewed. It is unlikely that while in this investigatory phase, the user intends to receive unsolicited phone calls or emails from a real estate agent or broker. From a client's (e.g., an agent or sales associate) perspective, making initial or follow-through personal contact with the user, e.g., through emails and phone calls, may only be worthwhile if the user has exhibited a certain amount of interest in a property or neighborhood. Further, as noted above, since a large number of users may access the on-line services, the client can become inundated with a large volume of leads and lead information that must be further analyzed to determine the value (e.g., the level of interest or price point) of the generated leads.
Referring now to
At block 204, it is determined whether or not a user activity has occurred. If no user activity is detected (“NO”), the process returns to block 202 to continue monitoring user activities. If a user activity is detected (“YES”), the procedure continues to block 206, where the user activity is recorded. Such a recording may, for example, comprise storing one or more of the following: a description of the activity (or a code that identifies that activity), the identity of the user, the identity of an associated client and the like. At block 208, the cumulative record associated with the user is evaluated. For example, such cumulative record may include all recorded activities associated with the user since the delivery of the last intelligent auto responder to that user. In some examples, the cumulative record may comprise all activities ever recorded for that user and/or all activities of the user since a given date (e.g., in the last month). Such records may also include additional information that may have been obtained from the user (e.g., during the initial registration process, after the registration process, through comments on on-line forums, etc.), as well as information added to the records by the client. In still other examples, the cumulative record may include information added to the profile of the user by the system. For example, the system may acquire demographic information for the user from various other sources (e.g., public records, social media networks, etc.). Such information may include birthday, leisure activities, charitable interests, etc.
At block 210, it is determined whether a user-related event has been triggered. As described below, a user-related event may be triggered based on certain actions of the user, whether an individual action or a cumulative record of actions.
In various examples, an event may be triggered by comparing accumulated user activities to predetermined metrics that, for example, demonstrate information of particular interest to the user. Further, an event may be triggered when a user designates a particular property as his/her favorite property by marking the property as a “Favorite”. As further examples, events may be triggered if the user views a particular property for the fifth time in a month or searches for properties above a certain price.
If the event triggering criteria is not satisfied (“NO”), the process returns to block 202 to continue monitoring user activities. If, on the other hand, an event triggering criteria is satisfied (“YES”), a lead communication process may be launched. One example of a lead communication process is illustrated in
Referring now to
In one example, an event may be triggered without any activity by the user. For example, account information for a user may be added or updated by another use or a system administrator. The account information may include an address associated with the user, and the system may identify a real-estate event based on the address. For example, a property in the neighborhood may be listed for sale. The system may use this to trigger an event.
In another example, the system may detect the closing of a sale of a property in the geographic area of a user's property. The system may trigger an event if the closing price of the property sold is significantly higher than the average price in the area.
Upon detection of an event, the system may identify information relevant to the event or the user (block 304). In this regard, the system may generate a message to be delivered to the user on behalf of an agent. Various examples of relevant information and generated messages associated with various events are provided below.
The system may notify the agent associated with the event (block 306), informing the agent of the detected event and the message to be sent to the user. The agent may be provided with the option to override the system (block 308), thereby preventing the generated message from being sent to the user. If the agent overrides the generated message, the system follows the agent's instructions (block 310). For example, the system may allow the agent to modify the generated message, delete the message, or send the message to various other users. If, on the other hand, the agent does not override the generated message, the system provides the message to the user on behalf of the agent.
In various examples, the message is an automatically generated message that may be structured to appear as if written in a personalized manner by an individual.
Referring now to
Upon detection of an event, the system may identify information relevant to the event or the user (block 404). Various examples of relevant information and generated messages associated with various events are provided below.
The system may provide a draft of the message to the agent associated with the event (block 406). The draft message may be accompanied by an indication of the detected event to notify the agent of the origin of the draft message. The agent may be provided with the option to approve the draft message (block 408). If the agent approves the message, the message is sent to the user on behalf of the agent (block 410). Otherwise, the agent may be provided the opportunity to edit the message (block 412), and the edited message is then sent to the user on behalf of the agent (block 414). Of course, the agent may elect that the message not be sent to the user and may be provided with the option to delete the draft message (not shown in
Thus, the system is able to monitor a user's on-line behavior to detect possible desires or preferences of the user. The system can also use data analytics, such as information that may be gathered or generated from information in a database (e.g., a real-estate database of sales and listings). In this regard, various forms of data analytics may be performed to identify information that may be of interest to various users (e.g., agents, buyers, sellers, etc.). For example, data analytics may be used to identify trends in various communities. The system can then identify information that may be of interest to the user and provide the information to the user on behalf of an agent. In various examples, the agent may be an individual or a real estate related company, such as a national real estate portal. Thus, the system may be useful in improving or deepening the relationship between the user and the agent. In some examples, the system can identify information that may be of interest to the user and provide the information directly to the agent so that the agent can provide the information in a manual way to the particular user.
The following provides various examples of events and associated messages which may be sent to the user. In these examples, the field %{lead_first}% represents the user (e.g., potential buyer or seller), %{search_city}% represents the city that is the focus of user's search, %{rep_first}% represents a particular client of the online services (e.g., a real estate agent), %{prop_city}% represents the city in which the property is located, %{prop_address}% represents the address at which the property is located and %{site_url}% represents the link to a particular website.
In one example, an event may be generated upon a regular (e.g., monthly) update of a database of recently listed or sold properties. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated upon the listing of a property similar to a property or types of properties of interest (e.g., in a particular neighborhood) to a user. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated upon the sale of a property similar to a property or types of properties of interest (e.g., in a particular neighborhood) to a user. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated upon the sale of a property similar to a property or types of properties of interest (e.g., in a particular neighborhood) to a user. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated upon the saving of a property to a “Favorites” folder by a user. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated upon the increase of a price of a property for sale in a neighborhood of interest to a user. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when an offer is made on a property that is in the “Favorites” folder of a user. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a property that is in the “Favorites” folder of a user has been on the market for a particular number of days (e.g., an excessive number of days). The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on an update of a database indicating how many times a property has been viewed by various users. The message may indicate the most popular (e.g., most viewed) properties that match a user's preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a property matching a user's preferences is sold above a listing price. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a property near a user's property is sold above a listing price. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when property trends of interest to the user are identified. The trends may be identified based on, for example, update of a database or the analysis of a user's preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when property trends of interest to the user are identified. The trends may be identified based on, for example, update of a database or the analysis of a user's preferences. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when the inventory of available properties decreases. The event may be identified based on the update of a database, for example. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when the inventory of available properties decreases. The event may be identified based on the update of a database, for example. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the inventory of available properties increases. The event may be identified based on the update of a database, for example. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated on a particular schedule (e.g., weekly, monthly, etc.) to indicate one or more users viewed the listings of the particular agent. The generated message may be targeted to the particular agent and may include a listing of all users and properties viewed by the users.
In another example, an event may be generated when a user saves one or more listings of the particular agent to a “Favorites” folder. The generated message may be targeted to the particular agent and may include a listing of all users and properties saved to the “Favorites” folder.
In another example, an event may be generated based on a user's visiting an agent's website. The event may be identified based on the actions of the user, for example. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on a user's saving of a property to a “Favorites” folder for which the agent is the listing agent. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on a user's saving of a property to a “Favorites” folder and for which the property has a low listing price per square foot. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on a user's saving of a property to a “Favorites” folder and for which the property has a high listing price per square foot. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on the identification of a user as a frequent browser on the system. The event may be triggered based on the user's behavior, such as visiting the site a certain number of times in a certain time period, saving a minimum number of properties to the “Favorites” folder, or opening of a certain number of property update emails. The triggering of the event may also take into consideration the user's profile, such as the user's address. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated based on the user's behavior of searching properties different than saved property preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on the user's behavior of searching properties in a location that is different than saved property preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on the user's behavior of searching properties built in years that are different than saved property preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on the user's behavior of searching properties that are larger in square footage than saved property preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated based on the user's behavior of searching properties that are smaller in square footage than saved property preferences. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a user saves a property to his “Favorites” folder and the property is contingent. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a property in the user's “Favorites” folder returns to market from a contingent status. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a property in the user's “Favorites” folder is taken off the market. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with large lot sizes. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties on lots of over one acre. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with large garages. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with at least three-car garages or if the user includes three-car garage in an advanced search criteria. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for single-story homes. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties that are single story. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with a pool. The event may be triggered if, for example, 80 percent of the user's searches or clicks are for properties that include a swimming pool or if the user is mostly saving properties (e.g., 80 percent of saved properties) to favorites that have a pool. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that are newly constructed. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties that are new construction or if the user indicates property age must be in the last five years in their search criteria. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that are in a specific neighborhood. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties in the same neighborhood or community. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have an ocean view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with an ocean view or if the user indicates such a preference in their search criteria or if the user mostly saves homes to favorites that have an ocean view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a lake view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a lake view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a river view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a river view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a water view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a water view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a city view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a city view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a mountain view. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a mountain view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties that have a view of a golf course. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a golf-course view. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with a community golf course. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a community golf course. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with community tennis courts. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with community tennis courts. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with horse facilities. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with horse facilities. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties in senior communities. The event may be triggered if, for example 80 percent of the user's searches or clicks are for senior community properties. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with community parks. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties with community parks. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with boating facilities. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties with boating facilities. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with community security. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties that have community security. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with disability features. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties that have disability features. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties in a cul-de-sac. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties located in a cul-de-sac. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties on a corner lot. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties located on a corner lot. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with recreational vehicle (RV) or boat parking. The event may be triggered if, for example 50 percent of the user's searches or clicks are for properties with RV or boat parking. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with a basement. The event may be triggered if, for example 80 percent of the user's searches or clicks are for properties with a basement. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties with air conditioning. The event may be triggered if, for example 25 percent of the user's searches or clicks are for properties with air conditioning. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated upon the listing of an open house for a property which sufficiently matches the user's preferences. The event may be triggered if, for example, the open house has square footage within 20 percent of the user's preference and in a neighborhood of interest to the user. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a sufficient interest in two or more neighborhoods. For example, the event may be triggered when the user views at least 5 properties in each of two or more neighborhoods within a 30-day period. The event may cause a message to be sent to the user providing the user with a comparison of certain features. The generated message may be targeted to users that may be potential property buyers. In one example, the message may provide the user with a comparison of property appreciation for the two or more neighborhoods. For example, the message may include:
In other examples, the user may be provided with a price appreciation comparison of two or more particular properties of interest to the user. For example, the message may include:
In other examples, various other parameters may be compared between neighborhoods, types of neighborhoods (e.g., coastal versus inland, urban versus suburban) or types of properties (e.g., single-family homes versus condos). A user may be provided with comparisons of property appreciation, crime rates, quality of schools, or various other parameters. In other examples, the user may be provided with comparisons of two or more particular properties, whether in the same neighborhood or different neighborhoods. For example, the user may be provided with a comparison of the property appreciation of two or more properties for which the user may have clicked at least 3 times each.
The comparisons may also take the form of contrasting different search behavior by the same consumer so as to draw meaningful conclusions for the user and impact their future behavior. For example, if the user is looking at two and three bedroom condos and houses in two different communities, the system may identify which of the three parameters (bedrooms, property type, and community) has the greatest impact on asking price per square foot, and which historically has the largest appreciation trend associated with it. This information may be provided to the user, for example, through the agent. The user can use this knowledge to inform and modify search and purchase behavior.
In another example, an event may be generated by comparing a user's behavior to non-real estate data. For example, if the user is searching a mix of properties with and without a boat dock, the system may identify and provide to the user a study that illustrates the costs associated with boat ownership and a study demonstrating the relative happiness of boat owners with their purchase over a five-year period. In another example, if the user is searching in a particular school district, the user may be provided with a study showing SAT scores from the local high school or a list of prominent alumni from that school.
In another example, an event may be generated when the user's behavior indicates a preference for properties in neighborhoods or communities with a young median age. The event may be triggered if, for example, the neighborhood with the most property clicks by the user has a median age below 30 years old. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a preference for properties in neighborhoods or communities identified as “booming”. The event may be triggered if, for example, the neighborhood with the most property clicks by the user, or a neighborhood with 10 or more property clicks within a 30-day period, has had a population increase of at least 25 percent in the last 10 years. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a sufficient interest in two or more neighborhoods and the user's profile indicates the user has a child under 18-years old. For example, the event may be triggered when the user views at least 5 properties in each of two or more neighborhoods within a 30-day period. The event may cause a message to be sent to the user providing the user with a comparison of schools in the two or more neighborhoods. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when the user's behavior indicates a strong preference for a particular property. The event may be triggered if, for example, the user clicks on the same property ten times within a 5-day period. A message may be generated to offer the user a viewing of the property. The generated message may be targeted to users that may be potential property buyers and may include:
In another example, an event may be generated when a user frequently searches homes listed for sale and also owns a property in the same area. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when a user frequently searches for properties listed for sale in an area where the agent has credible success metrics to share that match the area, such as active listings, reviews or testimonials from past clients, or historical closed transactions in the area. The generated message may be targeted to users that may be potential property buyers or sellers and may include:
In another example, an event may be generated when a user frequently searches homes listed for sale and also has a property listed for sale. The message may provide the user with information relevant to the listed homes, such as price appreciation. The generated message may be targeted to users that may be potential property sellers and may include:
In another example, an event may be generated when the user's behavior and/or profile indicate the user is a potential seller (e.g., has a home listed or has searched recent sales of similar homes). The messages may provide or offer to provide a variety of information that may be useful to a seller. For example, the generated message may include:
In another example, the generated message may include:
In another example, the generated message may include:
In another example, the generated message may include:
In another example, an event may be generated when the user's behavior and/or profile indicate the user is a potential seller (e.g., has a home listed or has searched recent sales of similar homes) and is searching for a larger home. The messages may provide or offer to provide a variety of information that may be useful to the user. For example, the generated message may include:
In another example, an event may be generated when the user's location indicates the user is visiting a city in which he has indicated an interest. For example, a user living in city A may have previously conducted searches for homes in city B. An event may be triggered when a geo-location data indicates the user is in the vicinity of city B. The messages may offer the user a viewing of various properties in city B. For example, the generated message may include:
In another example, an event may be generated when the user's location indicates the user is in the vicinity of a property in which he has expressed an interest. For example, the user's geo-location may indicate that the user is within a block of a property the user has saved to his “Favorites” folder. For example, the generated message may include:
Of course, those skilled in the art will appreciate that other examples are possible and are contemplated within the scope of the present disclosure. The above list of examples is neither exhaustive nor limiting.
Further, while the above examples indicate various examples of triggering criteria for the various messages, those skilled in the art will appreciate that various other triggers may be used and are contemplated within the scope of the present disclosure. For example, various triggers may be based on an indication of a preference via saved properties to favorites or various searches conducted by the user.
As noted earlier, while the above examples describe an on-line service that relates to the real estate environment, the disclosed examples are equally applicable to other on-line environments associated with other products or services besides real estate.
The messages that are generated in accordance with the disclosed examples may include information produced by monitoring the actions of each user in real time and on a cumulative basis, by analyzing the collected information using rules and logic programmed into an analysis engine, and by enabling clients to augment the messages with additional information.
It is understood that the various embodiments of the present invention may be implemented individually, or collectively, in devices comprised of various hardware and/or software modules and components. These devices, for example, may comprise a processor, a memory unit, an interface that are communicatively connected to each other, and may range from desktop, server and/or laptop computers to consumer electronic devices such as mobile devices and the like. For example,
Similarly, the various components or sub-components within each module of the present invention may be implemented in software, hardware, and/or firmware. The connectivity between the modules and/or components within the modules may be provided using any one of the connectivity methods and media that is known in the art, including, but not limited to, communications over the Internet, wired, or wireless networks using the appropriate protocols.
Various embodiments described herein are described in the general context of methods or processes, which may be implemented in one embodiment by a computer program product, and embodied in a computer-readable medium, including computer executable instructions, such as program code, executed by computers in networked environments. A computer-readable medium may include removable and non-removable storage devices including, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), compact discs (COs), digital versatile discs (DVD), etc. As such, the various disclosed embodiments can be implemented by computer code embodied on nontransitory computer readable media. Generally, program modules may include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps or processes. In particular, the various steps that are described in the various block diagrams throughout this application are considered example, and it is understood that the steps may be performed in different order than what is shown. In addition, fewer or additional steps may be included.
The foregoing description of embodiments has been presented for purposes of illustration and description. The foregoing description is not intended to be exhaustive or to limit embodiments of the present invention to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of various embodiments. The embodiments discussed herein were chosen and described in order to explain the principles and the nature of various embodiments and its practical application to enable one skilled in the art to utilize the present invention in various embodiments and with various modifications as are suited to the particular use contemplated. The features of the embodiments described herein may be combined in all possible combinations of methods, apparatus, modules, systems, and computer program products.
Furthermore, embodiments of the present invention may be implemented in software, hardware, application logic or a combination of software, hardware and application logic. The software, application logic and/or hardware may reside on a client device, a server or a network component. If desired, part of the software, application logic and/or hardware may reside on a client device, part of the software, application logic and/or hardware may reside on a server, and part of the software, application logic and/or hardware may reside on a network component. In an example embodiment, the application logic, software or an instruction set is maintained on any one of various conventional computer-readable media. In the context of this document, a “computer-readable medium” may be any media or means that can contain, store, communicate, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer. A computer-readable medium may comprise a computer-readable storage medium that may be any media or means that can contain or store the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer. In one embodiment, the computer-readable storage medium is a non-transitory storage medium.
This application claims the benefit of co-pending U.S. Provisional Application Ser. No. 61/887,257, filed on Oct. 4, 2013, which is related to U.S. application Ser. No. 12/828,172, filed on Jun. 30, 2010, and titled “LEAD GENERATION AND UTILIZATION”, which is hereby incorporated by reference in its entirety for all purposes.
Number | Date | Country | |
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61887257 | Oct 2013 | US |