WO2006040405A1 - An analyzer, a system and a method for defining a preferred group of users - Google Patents
An analyzer, a system and a method for defining a preferred group of users Download PDFInfo
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- WO2006040405A1 WO2006040405A1 PCT/FI2005/050322 FI2005050322W WO2006040405A1 WO 2006040405 A1 WO2006040405 A1 WO 2006040405A1 FI 2005050322 W FI2005050322 W FI 2005050322W WO 2006040405 A1 WO2006040405 A1 WO 2006040405A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/107—Computer-aided management of electronic mailing [e-mailing]
Definitions
- An analyzer a system and a method for defining a pre ⁇ ferred group of users
- the present invention relates to an analyzer, a system and a method for defining a preferred group of users from user data.
- Information of the preferred group of users may be utilized in e.g. new product launches, marketing cam- paigns, churn management, and planning marketing.
- the target group to which a marketing message is sent is defined usually by the user's demographics and/or previous purchase patterns.
- One of the typical ways to define the target group of users is to se ⁇ lect the most potential age and education level for a product. This way of selecting the target group of users to which marketing messages are sent is however ineffi ⁇ cient, in a way that large group of messages is sent to different users without any response from the potential buyers. Therefore large group of unnecessary messages are sent through a network (e.g. Internet) .
- the marketing message covers traditional mail, commercials (on TV or radio) , e-mails, mobile messages, etc.
- Another prior art solution that is used is to send e-mail messages to all possible e-mail addresses. This method is also called spamming.
- the recent studies have revealed that about half of the e-mails sent in communications net ⁇ works are already spam messages. This method causes a lot of unnecessary traffic in the communications networks.
- the present invention provides an analyzer, a system and a method to define a preferred group of users.
- the num- ber of marketing messages is reduced, the overall load of the communications network also reduces. Also unnecessary messages are reduced, which also reduces the overall costs that are needed for sales and marketing (of a new prod- uct) .
- an analyzer for defining a preferred group of users, the analyzer comprising: means for receiving data from a network node,- means for determining a social network of the users based on the received data,- means for determining a set of parameters for each user; and means for determining the preferred group of users based on said social network and said set of parameters.
- a system for defining a preferred group of users comprising: a plurality of users,- a network node connected to the plurality of users,- at least one database comprising data of the users,- and an analyzer connected to the network node, the ana- lyzer being arranged to define the preferred group of us ⁇ ers from the data obtained from said at least one database by determining a social network of the users and determin ⁇ ing a set of parameters for each user, and to provide user information of the preferred group of users, which is de- termined based on said social network and said set of pa ⁇ rameters, to the network node.
- a method for defining a preferred group of us ⁇ ers in an analyzer comprising: receiving user data from a database,- determining a social network of the users based on the received user data,- determining a set of parameters for each user; and combining the social network and the set of parame ⁇ ters to define the preferred group of users.
- a computer-readable medium having stored thereon instructions for defining a preferred group of us ⁇ ers, the instructions when executed by a processor cause the processor to: receive user data from a database,- determine a social network of the users based on the received user data,- determine a set of parameters for each user; and combine the social network and the set of parameters to define the preferred group of users.
- the pre ⁇ sent invention provides means and method for directing the marketing messages to the users that are interested in (certain) new products. More over, the present invention provides a solution in which it is possible to reduce the amount of unnecessary messages (for example of a product that is not interesting to some group of users) that are sent to the users. This also reduces the overall costs that are needed for sales and marketing of a new product. The present invention further enables faster product launch with decreased amount of costs.
- the information of the preferred group of users may also (not only in product launches) be utilized for example in marketing campaigns, churn management and planning marketing. Further advan ⁇ tages of the present invention are described in detailed description of the embodiments of the present invention with reference to the drawings .
- Figure 1 shows an inventive system of the present in- vention.
- Figure 2 shows an example of the social network map of the users .
- Figure 3 shows a flow chart illustrating the process of the present invention.
- Figure 1 shows an inventive system of the present inven ⁇ tion.
- Figure 1 shows users 1 of a service, a network node (or a service provider) 2, a database (or a server) 3 and an analyzer 4.
- the network node 2 in this connection may be for example a mobile telephone operator or an elec ⁇ tronic store.
- the service may be e.g. call connection be ⁇ tween two users 1 or selling e.g. books through the Inter- net.
- the following presentation considers us ⁇ ers (denoted as 1 in Figure 1) , the skilled person in the art realizes that the users of e.g. mobile communication system utilizes mobile terminals for connections to other users, i.e. a user uses his/her mobile terminal for util- izing a call (or sending a message) to another user.
- the network node 2 is connected to a database 3, which records the information of the users 1.
- the information may com ⁇ prise communication data of the users 1, the earlier pur ⁇ chase history of the users 1, possible recommendation his ⁇ tory of the users 1, and demographics of the users 1 (age, marital status, etc.) .
- the communication data may include information of all type of contacts of the users 1, e.g. telephone calls, mobile messaging, e-mails, product recom ⁇ mendation messages, and instant messaging.
- the earlier purchase history may comprise e.g. what kinds of products the user 1 has purchased.
- the recommendation history may comprise information of what kind of products the user 1 has recommended to other users 1 (e.g. all purchased prod ⁇ ucts and to whom the user 1 has recommended different products) .
- the analyzer 4 is connected to the network node 2.
- the analyzer may also be connected directly to the database 3.
- the network node 2 (and possibly also the database 3) may be connected directly or through a communications network (which is not shown in Figure 1) to the analyzer 4.
- the network node 2 owner wants to find out a preferred group of users (that may be called as alpha us- ers) to more efficiently target the marketing resources so that the fastest possible product launch could be achieved.
- the alpha users are persons who are interested to buy new products, willing to recommend them to their friends, and have influence in his/her social network.
- a request to define a preferred group of users is provided to the ana ⁇ lyzer 4.
- the network node 2 may provide the analyzer 4 the data regarding the users 1 from the da- tabase 3.
- the analyzer 4 requests the data from the database 3 (directly or through the network node 2) after receiving the request to find the preferred group of users from the network node 2.
- the analyzer 4 analyzes the information in the following way.
- the analyzer 4 first analyzes the data to find out the contacts of the users 1 (e.g. which user has recommended a product to another user) to build a social network map be ⁇ tween the users.
- An example of the users' social network map is shown in Figure 2.
- the social network map may be built by means of a computer program comprising an algo ⁇ rithm for building the social network map, which computer program is implemented in the analyzer 4.
- the analyzer 4 will define most potential buy- ers or users by formulating an innovator score (which measures whether the subscriber was (or how likely the subscriber will be) the first adopter of the product in his local social network) from purchase and usage data provided from the server 3.
- an innovator score which measures whether the subscriber was (or how likely the subscriber will be) the first adopter of the product in his local social network
- the analyzer 2 also defines a repeat user score from the previous product purchase history (which score measures whether the subscriber has taken (or how likely the sub ⁇ scriber will take) the product into routine use after first trial) .
- the analyzer 4 also defines a social network influence score (which measures the social influence of a given sub ⁇ scriber in the social subnetwork relevant to the product) .
- the analyzer 4 defines an alpha user score (which score measures the net value of the subscriber in accelerating the product launch) for each user 1.
- the alpha user score may be de- fined e.g. such that each of the above scores are multi ⁇ plied with a weighting value, and the weighted sum or weighted average defines the alpha user score.
- the person skilled in the art appreciates that the order of the scoring steps above may be varied without departing from the scope of the invention. Also the steps may be processed essentially at the same time.
- the process may be such that after defining each score, only certain number of users are selected, i.e. further scores are defined only to those users. This may be achieved e.g. with following two ways. In first alter- native only those users that have gained higher score than certain predefined score are selected to the next phase (for example if the highest possible value for a score is 100, it may be defined that only those users that receive a score 70 or above are selected for next phase) . In sec- ond alternative only a certain predefined number of users receiving the highest score are selected for next phase
- the analyzer 4 After defining the alpha user scores for each user 1, the analyzer 4 will define the preferred group of users that were requested. Thereafter the analyzer 4 sends indication
- the indication sent to the network node 2 may be used to target more efficiently marketing messages to the users 1. This way the sent messages from the net ⁇ work node to different users may be reduced, and therefore also the overall loading of the network may be reduced. Finding alpha users also increases the efficiency of the product launch so that more possible users will know about the new product than by randomly picking up the users to which the marketing messages are sent (this will also de ⁇ crease the costs needed for sales and marketing) .
- the marketing message covers traditional mail, commercials (on TV or radio) , e-mails, mobile messages, etc.
- Figure 2 shows a social network map that illustrates con ⁇ tacts between users to each other.
- This information may be defined on the basis of the call data records when the in ⁇ formation is analyzed.
- the first group of users (only one of which is shown in Figure 2) are denoted as A.
- the users of the first group i.e. users A
- the sec ⁇ ond group of users may be user A' s family, friends, co- workers, etc.
- the user A is directly connected to the second group of users (i.e. users B) .
- Users B are fur ⁇ ther connected to a third group of users that are denoted as C in Figure 2.
- the user A has more contacts to others users than any other user. Therefore in word-of-mouth method, the user A would be the best target to start the marketing efforts.
- a plurality of mobile telephone users 1 are con ⁇ nected to a mobile telephone operator 2.
- the mobile tele ⁇ phone network and its functioning are known to the person skilled in the art, and therefore, they are not described more detailed herein. It is enough to mention that the mo- bile telephone network may be a traditional second or third generation mobile telephone network. Also what is send (in case of messages sent from one user to another) between the users (users' mobile terminals) is not rele ⁇ vant in this embodiment of the present invention.
- the mobile telephone operator is connected to a database (or a server) 3, wherein the records of the communication data (i.e. data of calls and sent messages between users) is stored.
- the records may be call data records or alike, which indicates each user's 1 connections to other users 1.
- the operator 2 and the database 3 are il ⁇ lustrated as separate (i.e. may be physically separated to different locations) , the skilled person in the art real- izes that they may be situated in the same location.
- the operator 2 is further connected to an analyzer 4.
- the database (or server) 3 may be directly connected to the analyzer 4 as indicated by the dash line.
- the analyzer 4 may also be connected through a communications network (not shown in Figure 1) , e.g. the Internet, without departing from the scope of the present invention.
- this information may be utilized to define the connections between the users 1.
- This communication data may be utilized to find out the users 1 that are so called alpha users. More over, the communication data may be utilized to define the preferred group of users.
- the op ⁇ erator 2 requests the analyzer 4 to define the preferred group of users so that the operator may market their new product with so few marketing messages to be sent to the users 1 as possible.
- the operator 2 may send the call data records to the analyzer 4 or the analyzer 4 may request the infor ⁇ mation from the operator 2 or the database 3.
- the analyzer 4 After receiving the call data records from the database 3 (whether through the operator 2 or directly from the data- base 3) , the analyzer 4 builds a social network from the communication data. From the social network the analyzer 4 defines a social network influence score, which measures the social influence of a given subscriber in the social subnetwork relevant to the product. From the subscribers' previous product purchase history, the analyzer 4 defines an innovator score, which measures whether the subscriber was (or how likely the subscriber will be) the first adopter of the product in his local social network. The analyzer will also define a repeat user score from the previous product purchase history, which score measures whether the subscriber has taken (or how likely the sub ⁇ scriber will take) the product into routine use after first trial .
- the analyzer 4 will define an alpha user score for each user 1, which score measures the net value of the subscriber in accelerating the product launch.
- the analyzer 4 may define the most potential marketing targets, i.e. the preferred group of users .
- a plural- ity of Internet users 1 are connected (e.g. by means of a computer connected to a communications network) to an Internet Service Provider (ISP) 2.
- the ISP 2 is connected to (or contains) a database (or a server) 3, which com ⁇ prises traffic information between the users 1 of the Internet service. This information contains e.g. which user 1 has sent an e-mail message to another user (and also to whom) 1 or information of the parties of instant messaging.
- the ISP 2 is further connected to an analyzer 4.
- the analyzer 4 may further be connected directly to the database 3.
- the process to define the preferred group of users follows the process as defined in the first embodiment of the present invention.
- a plurality of electronic store users 1 are connected to an electronic store 2 in the Internet. There is further shown a database
- the database 3 comprises information of how different us ⁇ ers 1 have recommended products of the store 2 to other users 1.
- the database further comprises e.g. users' 1 demographic information that may be utilized in marketing purposes.
- the process according to this embodiment of the present invention includes the data gathering on all product pur ⁇ chases and recommendations to friends, and storing the in- formation to the database 3.
- the electronic store 2 owners wish to launch a new product marketing campaign (or other marketing effort) , it requests the analyzer 4 to define the preferred group of users from all users in the database 3.
- the analyzer 4 may request the data from the database 3 directly or through the proc ⁇ essing equipment of the electronic store 2.
- the processing equipment of the electronic store 2 pro- vides the information from the database 3 to the analyzer
- the analyzer 4 When receiving the data from the database 3 in the ana ⁇ lyzer 4, the analyzer 4 builds a social network (i.e. which user 1 has recommended a product to which ones of his/her friends) from the recommendations information. Thereafter, the analyzer 4 analyzes the purchase and usage data to find out the users 1 that are most potential buy ⁇ ers of the product (building innovator score) . The ana- lyzer 4 also differentiate regular customers of a new product from trial purchasers from the information re ⁇ ceived from the database 3 (building repeat user score) . Then the analyzer 4 analyzes the information to define the most influential persons in the network (to build social influence score) . The above steps are processed practi ⁇ cally almost at the same time, even though they are de ⁇ scribed as chronological steps above. Also the order of performing the scoring phases may vary.
- the analyzer 4 After receiving the above scores, the analyzer 4 forms an alpha user score (which is a combination of above scores) to define the preferred group of users.
- the analyzer 4 will provide the indications of which users are within the preferred group of users to the processing equipment of the electronic store 2, which may utilize this information to target their marketing to cer ⁇ tain users 1 of the service.
- Figure 3 shows a flow chart illustrating the process of the present invention.
- the process starts, in step 300, with sending a request to define a preferred group of users (with respect to certain product) from a network node to an analyzer.
- the network node may also send an indication of how many users with highest possible score it wishes to re ⁇ ceive (i.e. determine the number of users) and/or indica ⁇ tion of lowest user score that it wishes to receive (i.e. the score value limit over which the users that are sent back to the network node must have) .
- An example of the first of the above indications may be such that the net ⁇ work node may define that it wishes to receive indication of 500 best scoring users.
- An example for the latter indi ⁇ cation may be such that when the total score is between 1 and 100, the network node wishes to receive indication of users scoring above 85.
- the analyzer After receiving the request, the analyzer will receive data, step 302, whether from a network node or directly from one or a plurality of databases.
- the data may be ob ⁇ tained in the following ways.
- the network node may send the data to the analyzer together with the request or af ⁇ ter certain time period.
- the network node may also in- struct a database (or several databases) to provide the data to the analyzer.
- the network node may provide to ⁇ gether with the request e.g. IP address (es) of data ⁇ base (s) , where from the analyzer may request the data.
- the database (s) may be physically located in or operationally connected to a network node.
- the analyzer After receiving the data, the analyzer starts to define the preferred group of users as requested by the network node.
- the social network may be built as a map (one type of which is illustrated in Figure 2) illustrating the contacts between the users.
- the analyzer de- fines a set of parameters for each user.
- the analyzer may form (or define) an innovator score, step 306, a repeat user score, step 308, and a social network influence score, step 310, for each user.
- the analyzer combines the social network and the set of parameters (or the above scores) into a one score, which may be called as alpha user score, in step 312.
- the alpha user score may be cal- culated on the basis of weighting different scores (or pa ⁇ rameters) and whether to calculate a weighted score sum or weighted score average for each user.
- the analyzer may sort the users from highest to lowest score (or in any other way of sort ⁇ ing the data) .
- the analyzer defines the preferred group of users, step 314.
- the group may comprise a predetermined number of users or all users above certain predefined score limit (as described with reference to the preferred embodiment of the present in- vention) .
- the analyzer sends information of the users in the preferred group of users to the network node, step 316.
- the net- work node may utilize the received list of users by send ⁇ ing a message (or such information) of new product (or such) to the listed users.
- Defining the preferred group of users may be implemented by a computer-readable medium having stored thereon in ⁇ structions for defining a preferred group of users.
- the instruc ⁇ tions cause the processor to: receive user data from a da- tabase,- determine a social network of the users based on the received user data,- determine a set of parameters for each user; and combine the social network and the set of parameters to define the preferred group of users.
- the mobile network operator (as de ⁇ fined in the first embodiment of the present invention) may also act as an ISP (as defined in the second embodi ⁇ ment of the present invention) .
- the analyzer may locate in operator's facilities or may be connected through a communications network.
Abstract
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Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
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US11/665,069 US20090055435A1 (en) | 2004-10-12 | 2005-09-21 | Analyzer, a system and a method for defining a preferred group of users |
EP05789917A EP1836675A4 (en) | 2004-10-12 | 2005-09-21 | An analyzer, a system and a method for defining a preferred group of users |
Applications Claiming Priority (2)
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FI20041323A FI20041323A (en) | 2004-10-12 | 2004-10-12 | Analyzer, system, and method for determining the desired user population |
FI20041323 | 2004-10-12 |
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WO2006040405A1 true WO2006040405A1 (en) | 2006-04-20 |
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PCT/FI2005/050322 WO2006040405A1 (en) | 2004-10-12 | 2005-09-21 | An analyzer, a system and a method for defining a preferred group of users |
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US (1) | US20090055435A1 (en) |
EP (1) | EP1836675A4 (en) |
CN (1) | CN101076826A (en) |
FI (1) | FI20041323A (en) |
WO (1) | WO2006040405A1 (en) |
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Also Published As
Publication number | Publication date |
---|---|
FI20041323A0 (en) | 2004-10-12 |
EP1836675A4 (en) | 2010-03-17 |
EP1836675A1 (en) | 2007-09-26 |
US20090055435A1 (en) | 2009-02-26 |
CN101076826A (en) | 2007-11-21 |
FI20041323A (en) | 2006-04-13 |
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