Real estate service platform testing method and device

Abstract

The invention provides a real estate service platform test method and device, and aims to solve the problem of inaccurate test results caused by characteristic differences of user groups when traffic is cut through user dimensions in the prior art. Different experiments are set, each experiment is provided with an experiment group, a blank control group and barrel numbers, a mark of each barrel number used for testing is formed, initialization of experiment configuration is completed, the experiment is performed according to the initialized experiment configuration, and analysis is performed through experiment data, so that the experiment efficiency is improved. And verifying the test result of the to-be-tested function or service. And the accuracy of a test result is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a real estate service platform testing method and device. Background Art

[0002] When designing a new functional module, planning an activity, or having multiple options but not knowing how to choose, you want to verify whether the new functional module or activity can bring significant benefits to the business. However, due to the limitations of personal thinking and the unresearchability of all users, there may be cognitive and practical differences between the expected effect of a function and the actual effect after it is launched.

[0003] Therefore, in order to more scientifically and rationally verify whether the launch of a new feature can bring significant benefits to the business, users themselves need to "vote with their feet" (that is, people express their attitudes and positions on something through actual actions). By analyzing the core indicators of user behavior data and seeing significant changes, the profit effect brought by the launch of the new feature can be verified.

[0004] For this purpose, most Internet companies will use AB testing to find functional solutions that can bring the greatest benefits to the core indicators they are concerned about.

[0005] Existing testing solutions can only cut traffic by user dimension and then perform data analysis on back-end business, which will lead to inaccurate results due to differences in the characteristics of the user groups themselves. Summary of the Invention

[0006] The present invention provides a real estate service platform testing method and device to solve the problem in the prior art of cutting traffic by user dimension, which leads to inaccurate test results due to differences in characteristics of user groups themselves.

[0007] In a first aspect, the present invention provides a real estate service platform testing method, which specifically includes the following steps:

[0008] Step S1: Obtain the target function or business of the real estate service platform to be tested;

[0009] Step S2: Initializing the experimental configuration according to the target function or business of the real estate service platform to be tested to form an initialized experimental configuration;

[0010] Step S3: Conducting experiments according to the initialized experimental configuration to generate experimental data;

[0011] Step S4: Analyze the experimental data to form a test result of the target function or business to be tested of the real estate service platform.

[0012] In a preferred embodiment, in step S1, the target functions or services to be tested include one or more functions or services such as real estate purchase, real estate sale, real estate rental, second-hand housing, new housing, housing recommendation, shared housing needs, video house viewing, moving assistance, full-process agency, house area, house orientation, house type, and apartment type.

[0013] In a preferred embodiment, in step S2, the experimental configuration is initialized according to the target function or business of the real estate service platform to be tested, specifically including the following steps:

[0014] Step S201: Initialize the experiment number, bucket number, and experiment group number. Each experiment includes multiple (i.e., at least two) experiment groups (each experiment group is assigned multiple experiment groups). The number of buckets in each experiment is the same, and each bucket includes multiple devices.

[0015] Step S202: For experiments with different numbers, set the experiment group number, the maximum bucket number allocation strategy, and the device allocation strategy in each bucket of the current experiment, and perform allocation processing to form all experiments after allocation processing, completing the initialization of the experiment configuration.

[0016] In a preferred embodiment, in step S202, the allocation strategies for experiments with different numbers are different.

[0017] In a preferred embodiment, in step S202, the experiment number value is 1, 2, ..., N (ie, the maximum experiment number is N), and the experiment group number of each experiment is A1, A2, ..., A N , the bucket number value is 1, 2, ..., B (that is, the maximum bucket number is B), and the number of devices is C; among them, N, B, C, A1, A2, ..., A N are all positive integers; specifically, step S202 includes the following steps:

[0018] Step S202a: Evenly distribute C devices into B buckets;

[0019] Step S202b: After the C devices are allocated, assign an experimental group number to each bucket according to the bucket number of the bucket, and set up an experimental group and a control group; wherein the experimental group includes one group and at least two groups;

[0020] Step S202c: assigning experiment numbers according to the assigned experiment group numbers to complete the assignment of experiment numbers;

[0021] Step S202d: Mark each bucket according to the allocated experimental equipment, bucket number, experimental group number and experimental number to complete the initialization of the experimental configuration.

[0022] In a preferred embodiment, in step S202b, each bucket completes the allocation of experimental group numbers in the form of a piecewise function. For example, 100 buckets are set. When the bucket number is greater than 0 and less than or equal to 20, the experimental group number is 1; when the bucket number is greater than 20 and less than or equal to 50, the experimental group number is 2; when the bucket number is greater than 50 and less than or equal to 100, the experimental group number is 3 (experimental group No. 3 is a blank control experimental group used for control experiments). Different experimental groups are used to test different target functions or businesses.

[0023] In a preferred embodiment, in step S202d, each bucket is marked, and the mark is the experiment number + the experiment group number + the bucket number. For example, for the second experiment group of the second experiment, the 88th bucket is marked as 2#2#88.

[0024] In a preferred embodiment, in step S3, performing an experiment according to the initialized experimental configuration to generate experimental data specifically includes the following steps:

[0025] Step S301: assign corresponding functions or services to be tested to different devices according to the initialized experimental configuration;

[0026] Step S302: Platform users of different devices use the real estate service platform to generate experimental data.

[0027] In a preferred embodiment, in step S4, core indicators such as the number of clicks, conversion rate, and interest data of platform users in the experimental data are analyzed to verify whether the test results of the target function or business to be tested of the real estate service platform are valid.

[0028] In a second aspect, the present invention further provides a real estate service platform testing device, which specifically includes the following modules:

[0029] The target acquisition module to be tested is used to obtain the target function or business of the real estate service platform to be tested;

[0030] An initialization experiment configuration module is used to initialize the experiment configuration according to the target function or business of the real estate service platform to be tested, thereby forming an initialized experiment configuration;

[0031] An experimental data generation module is used to conduct experiments according to the initialized experimental configuration and generate experimental data;

[0032] The test result generation module is used to analyze the experimental data to form the test results of the target function or business to be tested of the real estate service platform.

[0033] In a preferred embodiment, in the target acquisition module to be tested, the target functions or services to be tested include one or more functions or services such as real estate purchase, real estate sale, real estate rental, second-hand housing, new housing, housing recommendation, shared housing needs, video house viewing, moving assistance, full-process agency, house area, house orientation, room type, and apartment type.

[0034] In a preferred embodiment, the initialization experiment configuration module specifically includes the following submodules:

[0035] Initialize the first submodule of the experiment configuration, which is used to initialize the experiment number, bucket number, and experiment group number; wherein each experiment includes multiple experimental groups, the number of buckets in each experiment is the same, and each bucket includes multiple devices;

[0036] The second submodule of the initialization experiment configuration is used to set the experimental group number, bucket number maximum allocation strategy and device allocation strategy in each bucket for experiments with different numbers, and perform allocation processing to form all experiments after allocation processing and complete the initialization of the experimental configuration.

[0037] In a preferred embodiment, in the second submodule of initializing the experiment configuration, the allocation strategies for experiments with different numbers are different.

[0038] In a preferred embodiment, in the second submodule of the initialization experiment configuration, the experiment number value is 1, 2, ..., N, and the experimental group number of each experiment is A1, A2, ..., A N , the bucket number is 1, 2, ..., B, and the number of devices is C; among them, N, B, C, A1, A2, ..., A N are all positive integers; specifically, the second submodule of the initialization experiment configuration includes the following units:

[0039] The first unit is used to evenly distribute C devices into B buckets;

[0040] The second unit is configured to assign an experimental group number to each bucket according to the bucket number of the bucket after the allocation of the C devices is completed, and set up an experimental group and a control group; wherein the experimental group includes one group and at least two groups;

[0041] The third unit is used to assign experimental numbers according to the assigned experimental group numbers and complete the assignment of experimental numbers;

[0042] The fourth unit is used to mark each bucket according to the allocated experimental equipment, bucket number, experimental group number and experiment number, and complete the initialization of the experimental configuration.

[0043] In a preferred embodiment, in the second unit, each bucket completes the allocation of experimental group numbers in the form of a piecewise function, and different experimental groups are used to test different target functions or services.

[0044] In a preferred embodiment, in the fourth unit, each barrel is marked, and the mark is experiment number + experiment group number + barrel number.

[0045] In a preferred embodiment, the experimental data generation module specifically includes the following submodules:

[0046] The first submodule of experimental data generation is used to allocate corresponding functions or services to be tested to different devices according to the initialized experimental configuration;

[0047] The second submodule of experimental data generation is used for platform users of different devices to use the real estate service platform to generate experimental data.

[0048] In a preferred embodiment, in the test result generation module, core indicators such as the number of clicks, conversion rate, and interest data of platform users in the experimental data are analyzed to verify the test results of the target function or business to be tested of the real estate service platform.

[0049] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a real estate service platform testing method as described in any one of the first aspects of the present application.

[0050] In a fourth aspect, the present invention further provides an electronic device comprising: a memory storing a computer program; and a processor communicatively connected to the memory for executing a real estate service platform testing method described in any one of the first aspects of the present application when the computer program is called.

[0051] Compared with the prior art, the present invention has the following obvious outstanding substantial features and significant advantages:

[0052] The present invention provides a real estate service platform testing method and device to address the existing problem of inaccurate test results due to differences in user group characteristics when traffic is cut based on the user dimension. By setting up different experiments, each with an experimental group and a blank control group, as well as a bucket number, a label is formed for each bucket number used for testing, the experimental configuration is initialized, and experiments are conducted based on this initialized experimental configuration. The experimental data is analyzed to verify the test results of the function or service to be tested. This improves the accuracy of the test results. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the accompanying drawings:

[0054] Figure 1 This is a flow chart of a real estate service platform testing method according to a preferred embodiment of the present invention.

[0055] Figure 2 It is a structural schematic diagram of a real estate service platform testing device according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention provides a real estate service platform testing method and device. To make the objectives, technical solutions, and effects of the present invention more clear and explicit, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0057] It should be noted that the terms "first," "second," and the like in the specification and claims of the present invention and the accompanying drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this manner are interchangeable under appropriate circumstances. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatuses.

[0058] Example 1:

[0059] like Figure 1 As shown, the real estate service platform testing method described in this embodiment specifically includes steps S1 to S4.

[0060] Step S1, obtaining the target functions or services of the real estate service platform to be tested; wherein the target functions or services to be tested include one or more functions or services such as real estate purchase, real estate sale, real estate rental, second-hand housing, new housing, housing recommendation, shared housing needs, video house viewing, moving assistance, full-process agency, house area, house orientation, house type, and apartment type.

[0061] Step S2: Initialize the experimental configuration according to the target function or business of the real estate service platform to be tested to form an initialized experimental configuration.

[0062] Specifically, the step S2 includes steps S201 and S202.

[0063] Step S201 : Initialize the experiment number, bucket number, and experiment group number; wherein each experiment includes multiple experiment groups, the number of buckets in each experiment is the same, and each bucket includes multiple devices.

[0064] Step S202: For experiments with different numbers, set the experiment group number, the maximum bucket number allocation strategy, and the device allocation strategy in each bucket of the current experiment, and perform allocation processing to form all experiments after allocation processing, completing the initialization of the experiment configuration.

[0065] Optionally, in step S202, the allocation strategies for experiments with different numbers are different.

[0066] The experimental numbers are 1, 2, ..., N, and the experimental group numbers of each experiment are A1, A2, ..., A N , the bucket number is 1, 2, ..., B, and the number of devices is C; among them, N, B, C, A1, A2, ..., A N are all positive integers; specifically, step S202 includes steps S202a to S202d.

[0067] Step S202a: Evenly distribute the C devices into B buckets.

[0068] Step S202b: After the allocation of C devices is completed, each bucket is assigned an experimental group number according to the bucket number of the bucket, and an experimental group and a control group are set; wherein the experimental group includes one group and at least two groups.

[0069] Each bucket is assigned an experimental group number in the form of a piecewise function, and different experimental groups are used to test different target functions or businesses.

[0070] Step S202c: assigning experiment numbers according to the assigned experiment group numbers to complete the assignment of experiment numbers.

[0071] Step S202d: Mark each bucket according to the allocated experimental equipment, bucket number, experimental group number and experimental number to complete the initialization of the experimental configuration.

[0072] Each barrel is marked with the experimental number + experimental group number + barrel number.

[0073] Based on the above content, the following example is given.

[0074] Example 1:

[0075] For experiment number 1, it is divided into two experimental groups, namely blank control group 0 and experimental group 1, that is, divided into two groups; experimental group: group 0 has 10 buckets, 10w equipment, and 10% flow; blank control group: group 1 has 90 buckets, 90w equipment, and 90% flow; send (bucket number) is less than 10 and belongs to experimental group number 0, and send is greater than or equal to 10 and belongs to experimental group number 1; final mark: experimental number#experimental group number#bucket number, 1#0#88.

[0076] Example 2:

[0077] For experiment number 2, it is divided into three experimental groups, namely experimental group 0, experimental group 1 and blank control group 2, that is, divided into three groups; experimental group 0: 20 buckets in group 0, 20w equipment, 20% flow, experimental group 1: 30 buckets in group 1, 30w equipment, 30% flow, blank control group 2: 50 buckets in group 2, 50w equipment, 50% flow; send less than 20 belongs to experimental group 0, send greater than or equal to 20 and less than 50 belongs to experimental group 1, send greater than or equal to 50 and less than 100 belongs to blank control group 2; final mark: 2#2#88.

[0078] Step S3: Conducting experiments according to the initialized experimental configuration to generate experimental data;

[0079] Specifically, the step S3 includes steps S301 and S302.

[0080] Step S301: assign corresponding functions or services to be tested to different devices according to the initialized experimental configuration.

[0081] Step S302: Platform users of different devices use the real estate service platform to generate experimental data.

[0082] Specifically, the experimental data format is as follows:

[0083]

[0084]

[0085] As can be seen from the above, the data pattern includes the experiment ID (experiment number), the experimental group traffic ratio, the experiment description and whether it is valid. In this embodiment, for experimental group 0, its traffic ratio is 15%, and for experimental group 1, its traffic ratio is 85%.

[0086] Step S4: Analyze the experimental data to form a test result of the target function or business to be tested of the real estate service platform.

[0087] Specifically, the core indicators such as the number of clicks, conversion rate, and interest data of the platform users in the experimental data are analyzed to verify the test results of the target function or business to be tested of the real estate service platform. As shown in Table 1, it is the experimental test result of the average daily lead conversion rate. Table 1 shows that for the pre-login function test of the real estate service platform, the average daily lead conversion rate of the blank control group of the Android client (Android client) is 6.74%, and the average daily lead conversion rate of the experimental group is 7.18%, which is 0.44% higher than that of the blank control group. The average daily lead conversion rate of the blank control group of the Apple client (IOS client) is 7.59%, and the average daily lead conversion rate of the experimental group is 7.82%, which is 0.23% higher than that of the blank control group. It can be seen that the pre-login function of the real estate service platform can bring beneficial effects.

[0088] Table 1 Average daily lead conversion rate comparison table

[0089] Segment Filter Platform client type average value Blank control group Android client 6.74％ Experimental group (pre-login) Android client 7.18％ Blank control group IOS client 7.59％ Experimental group (pre-login) IOS client 7.82％

[0090] Example 2:

[0091] like Figure 2 As shown, the real estate service platform testing device described in this embodiment specifically includes a test target acquisition module, an initialization experiment configuration module, an experiment data generation module and a test result generation module.

[0092] The target acquisition module to be tested is used to obtain the target functions or services of the real estate service platform to be tested; wherein, in the target acquisition module to be tested, the target functions or services to be tested include one or more functions or services such as real estate purchase, real estate sale, real estate rental, second-hand housing, new housing, housing recommendation, shared housing needs, video house viewing, moving assistance, full-process agency, house area, house orientation, house type, and apartment type.

[0093] The initialization experiment configuration module is used to initialize the experiment configuration according to the target function or business of the real estate service platform to be tested to form an initialized experiment configuration.

[0094] The initialization experiment configuration module specifically includes an initialization experiment configuration first submodule and an initialization experiment configuration second submodule.

[0095] Initialize the first submodule of the experiment configuration, which is used to initialize the experiment number, bucket number, and experiment group number; wherein each experiment includes multiple experimental groups, the number of buckets in each experiment is the same, and each bucket includes multiple devices;

[0096] The second submodule of the initialization experiment configuration is used to set the experiment group number, the maximum bucket number allocation strategy, and the device allocation strategy within each bucket for each numbered experiment. It then performs allocation processing to form all the allocated experiments and complete the initialization of the experiment configuration. In the second submodule of the initialization experiment configuration, the allocation strategies for the differently numbered experiments are different.

[0097] Specifically, in the second submodule of the initialization experiment configuration, the experiment number value is 1, 2, ..., N, and the experimental group number of each experiment is A1, A2, ..., A N , the bucket number is 1, 2, ..., B, and the number of devices is C; among them, N, B, C, A1, A2, ..., A N All are positive integers.

[0098] The second submodule of the initialization experiment configuration includes a first unit, a second unit, a third unit and a fourth unit.

[0099] The first unit is used to evenly distribute C devices into B buckets.

[0100] The second unit is used to assign an experimental group number to each bucket according to the bucket number of the bucket after the allocation of C devices is completed, and to set up an experimental group and a control group; wherein the experimental group includes one group and at least two groups; wherein each bucket completes the allocation of the experimental group number in the form of a piecewise function, and different experimental groups are used to test different target functions or services.

[0101] The third unit is used to assign experiment numbers according to the assigned experiment group numbers, thereby completing the assignment of experiment numbers.

[0102] The fourth unit is used to label each bucket according to the assigned experimental equipment, bucket number, experimental group number and experimental number, and complete the initialization of the experimental configuration. Each bucket is labeled with the experimental number + experimental group number + bucket number.

[0103] The experimental data generation module is used to conduct experiments according to the initialized experimental configuration to generate experimental data.

[0104] The experimental data generation module specifically includes an experimental data generation first submodule and an experimental data generation second submodule.

[0105] The first submodule of the experimental data generation is used to allocate corresponding functions or services to be tested to different devices according to the initialized experimental configuration.

[0106] The second submodule of experimental data generation is used for platform users of different devices to use the real estate service platform to generate experimental data.

[0107] The test result generation module is used to analyze the experimental data to form the test results of the target function or business to be tested of the real estate service platform.

[0108] The test results of the target function or business to be tested of the real estate service platform are verified by analyzing the core indicators such as the number of clicks, conversion rate, and interest data of the platform users in the experimental data.

[0109] While the specific embodiments of the present invention have been described in detail above, these are merely exemplary and the present invention is not limited thereto. For those skilled in the art, any equivalent modifications and substitutions to the present invention are also within the scope of the present invention. Therefore, any equivalent changes and modifications made without departing from the spirit and scope of the present invention are intended to be encompassed within the scope of the present invention.

Claims

1. A real estate service platform testing method, characterized in that: The specific steps include: Step S1: Obtain the target function or business of the real estate service platform to be tested; Step S2: Initializing the experimental configuration according to the target function or business of the real estate service platform to be tested to form an initialized experimental configuration; Step S3: Conducting experiments according to the initialized experimental configuration to generate experimental data; Step S4: Analyze the experimental data to form a test result of the target function or business to be tested of the real estate service platform.

2. A real estate service platform testing method according to claim 1, characterized in that: In step S1, the target functions or services to be tested include one or more of real estate purchase, real estate sale, real estate rental, second-hand housing, new housing, housing recommendation, shared housing needs, video house viewing, moving assistance, full-process agency, house area, house orientation, house type, and apartment type.

3. A real estate service platform testing method according to claim 1, characterized in that: In step S2, the experimental configuration is initialized according to the target function or business of the real estate service platform to be tested, which specifically includes the following steps: Step S201: Initialize the experiment number, bucket number, and experiment group number; each experiment includes multiple experiment groups, the number of buckets in each experiment is the same, and each bucket includes multiple devices; Step S202: For experiments with different numbers, set the experiment group number, the maximum bucket number allocation strategy, and the device allocation strategy in each bucket of the current experiment, and perform allocation processing to form all experiments after allocation processing, completing the initialization of the experiment configuration.

4. A real estate service platform testing method according to claim 3, characterized in that: In step S202, the experiment number values ​​are 1, 2, ..., N, and the experimental group numbers of each experiment are A1, A2, ..., A N , the bucket number is 1, 2, ..., B, and the number of devices is C; among them, N, B, C, A1, A2, ..., A N are all positive integers; step S202 includes the following steps: Step S202a: Evenly distribute C devices into B buckets; Step S202b: After the C devices are allocated, assign an experimental group number to each bucket according to its bucket number, and set up an experimental group and a control group; wherein the experimental group includes one group and at least two groups; Step S202c: assigning experiment numbers according to the assigned experiment group numbers to complete the assignment of experiment numbers; Step S202d: Mark each bucket according to the allocated experimental equipment, bucket number, experimental group number and experimental number to complete the initialization of the experimental configuration.

5. A real estate service platform testing method according to claim 4, characterized in that: In step S202b, each bucket is assigned an experimental group number in the form of a piecewise function, and different experimental groups are used to test different target functions or services.

6. A real estate service platform testing method according to claim 1, characterized in that: In step S3, an experiment is performed according to the initialized experimental configuration to generate experimental data, which specifically includes the following steps: Step S301: assign corresponding functions or services to be tested to different devices according to the initialized experimental configuration; Step S302: Platform users of different devices use the real estate service platform to generate experimental data.

7. A real estate service platform testing method according to claim 1, characterized in that: In step S4, the test results of the target function or business to be tested of the real estate service platform are verified by analyzing the click volume, conversion rate, and interest data of the platform users in the experimental data.

8. A real estate service platform testing device, characterized in that: Specifically, it includes the following modules: The target acquisition module to be tested is used to obtain the target function or business of the real estate service platform to be tested; An initialization experiment configuration module is used to initialize the experiment configuration according to the target function or business of the real estate service platform to be tested, thereby forming an initialized experiment configuration; An experimental data generation module is used to conduct experiments according to the initialized experimental configuration and generate experimental data; The test result generating module is used to analyze the experimental data to generate the test results of the target function or business to be tested of the real estate service platform.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements a real estate service platform testing method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements a real estate service platform testing method as described in any one of claims 1 to 7.

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