Multi-channel analysis method and device based on analytic hierarchy process

An AHP and analysis method technology, applied in the field of multi-channel analysis methods and devices based on AHP, can solve problems such as inaccuracy, lack of comparability at the data level, and inability to effectively evaluate the optimal channel, etc. The effect of outcome science

Inactive Publication Date: 2014-06-25
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, these two schemes have the following disadvantages: 1). Dimensionless: the scores of existing channels are calculated based on absolute or relative quantities to obtain their quantitative values, and there are differences in unit quantification for different channel quantities (ie The order of magnitude is different, there is no comparabili...

Method used

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  • Multi-channel analysis method and device based on analytic hierarchy process
  • Multi-channel analysis method and device based on analytic hierarchy process
  • Multi-channel analysis method and device based on analytic hierarchy process

Examples

Experimental program
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Effect test

no. 1 example

[0022] figure 1 It is a schematic flow chart of the multi-channel analysis method based on the analytic hierarchy process provided by the first embodiment of the present application. Please refer to figure 1 , the multi-channel analysis method based on the analytic hierarchy process provided in the first embodiment of the present application includes the following steps:

[0023] S11: Obtain the sub-goals of each channel and the indicators corresponding to each sub-goal, construct a pairwise comparison matrix table of sub-target layers with the sub-goals corresponding to each channel as factors, and build an index layer with the indicators corresponding to each sub-goal of each channel as factors pairwise comparison matrix table, calculate the corresponding weight coefficients of each sub-goal of each channel according to the paired comparison matrix table of the sub-target layer, and calculate each sub-goal of each channel according to the paired comparison matrix table of t...

no. 2 example

[0054] This embodiment is described by taking a website as an example of a multi-channel task by cooperating with other affiliated websites, and the final cooperation effect is the "overall goal". . The indicators of the flow include, for example: PV, UV, and QV. Indicators of user quality include, for example: retention and second hop. The index of the conversion rate includes, for example: UV conversion, new UV conversion, and active conversion.

[0055] First, according to the step S11 in the first embodiment, the sub-target layer paired comparison matrix table is established, as shown in Table 4, the weight coefficient corresponding to each sub-target of each channel is calculated according to the sub-target layer paired comparison matrix table , see the last column of Table 4.

[0056] Table four

[0057] factor

flow

Conversion rate

user quality

weight factor

flow

1

1 / 4

1 / 5

0.1

Conversion rate

4

1

1 / ...

no. 3 example

[0069] Figure 4 It is a schematic structural diagram of the multi-channel analysis device based on the analytic hierarchy process provided by the third embodiment of the present application. Please refer to Figure 4 The AHP-based multi-channel analysis device 20 provided in the fourth embodiment of the present application includes: a weight coefficient generation module 21 , an effect score generation module 22 , and an evaluation result acquisition module 23 .

[0070] The weight coefficient generation module 21 is used to obtain the sub-goals of each channel and the indicators corresponding to each sub-goal, construct the sub-goal layer pairwise comparison matrix table with the sub-goals corresponding to each channel as factors, and use the indicators corresponding to each sub-goal of each channel Construct index layer pairwise comparison matrix table for factor, calculate the corresponding weight coefficient of each sub-goal of each channel according to described sub-tar...

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Abstract

The application provides a multi-channel analysis method and a multi-channel analysis device based on an analytic hierarchy process. The method comprises the steps of: acquiring a sub-target of each channel and an index corresponding to each sub-target, building a sub-target layer paired comparison matrix table by using the sub-targets corresponding to the channels as factors, building an index layer paired comparison matrix table by using the indexes corresponding to the sub-targets of the channels as factors, computing a weight coefficient corresponding to each sub-target of each channel according to the sub-target layer paired comparison matrix table, computing a weight coefficient corresponding to each index in each sub-target of each channel according to the index layer paired comparison matrix table, acquiring a quantity value of each channel at the same index, setting an effect value of each channel at each index according to the quantity value, and weighting the weight coefficients and the effect values to obtain a final assessing score of the channel. According to the multi-channel analysis method and device based on the analytic hierarchy process, a more scientific and accurate multi-channel assessing result can be provided.

Description

technical field [0001] The present application relates to the technical field of computer analysis, in particular to a multi-channel analysis method and device based on analytic hierarchy process. Background technique [0002] In the field of marketing, it is often necessary to evaluate the value of market channels. The usual method is to quantitatively evaluate the value of the channel from a single dimension; or to evaluate the value of the channel simply and comprehensively from several dimensions. For example, carry out several promotional channel activities for a new product, and evaluate the effect of each promotional channel activity. [0003] The existing schemes include the split method and the simple comprehensive weighting method. The split method separates a certain indicator from several promotion channel activities for evaluation and comparison. For example, compare the conversion rate of new users in several promotion channel activities, and sort the results...

Claims

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Application Information

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IPC IPC(8): G06F19/00
Inventor 陈斌吴志坚周霄骁覃武权庄子明邹永林松
Owner TENCENT TECH (SHENZHEN) CO LTD
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