A method, device and readable storage medium for identifying an upward trend in a business metric

Abstract

The application provides a method, device and readable storage medium for identifying an upward trend of a business index, the method comprising: for each group of data in original data, determining an upward index value according to the size relationship between the current group of data and the previous group of data, and calculating the increase / decrease ratio between the current group of data and the previous group of data; calculating the sum of n upward index values between the ith group of data and the i-(n-1)th group of data to obtain L-n+1 upward trend values; screening a target upward trend group according to the upward trend values, the average value of the upward trend values of the target upward trend group being greater than or equal to a preset threshold; for each target upward trend group, determining a first target data and a second target data, and calculating the average value of the sum of the increase / decrease ratios of the first target data; determining the median of the increase / decrease ratio of the first target data; and eliminating an interference trend group. The application accurately identifies an upward trend and accurately obtains a user stickiness index part positively correlated with a business behavior frequency.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a method and device for identifying an upward trend of a business index and a readable storage medium. BACKGROUND

[0002] Currently, in operation, marketing, and advertising, attention is often paid to the relationship between certain business behaviors, such as clicking, collecting, and browsing, and user stickiness indicators, such as repurchase rate, retention rate, and click rate. Generally, the part of the business behaviors that is positively correlated with the user stickiness indicators is concerned.

[0003] However, the business behaviors and the user stickiness indicators are not linearly continuous, but are divided into multiple stages, some of which are positively correlated, some of which are negatively correlated, and some of which are not correlated, and in these stages, individual point fluctuations may occur, which leads to the inability to accurately identify the user stickiness indicators that are positively correlated with the business behaviors. SUMMARY

[0004] The embodiments of the present application provide a method and device for identifying an upward trend of a business index and a readable storage medium, which can solve the problem of the inability to accurately identify the user stickiness indicators that are positively correlated with the business behaviors.

[0005] In a first aspect, the embodiments of the present application provide a method for identifying an upward trend of a business index, comprising:

[0006] For each group of data in the original data, an upward index value is determined according to the size relationship between the current group of data and the previous group of data, and an increase / decrease ratio between the current group of data and the previous group of data is calculated, wherein the upward index value includes a first preset value and a second preset value;

[0007] The sum of n upward index values between the ith group of data and the i-(n-1)th group of data is calculated to obtain L-n+1 upward trend values, n≤i≤L, and n is a persistence length threshold value;

[0008] A target upward trend group is screened according to the upward trend values, and the average value of the upward trend values of the target upward trend group is greater than or equal to a preset threshold value;

[0009] For each target upward trend group, a first target data and a second target data are determined, and the average of the sum of the increase / decrease ratios of the first target data is calculated, and the upward index value of the first target data is a first preset value;

[0010] The median of the increase / decrease ratio of the first target data is determined;

[0011] discard an interference trend group, the interference trend group being a target rising trend group in which an absolute value of the increase-decrease ratio of the second target data is greater than the mean value, or a target rising trend group in which the absolute value of the increase-decrease ratio of the second target data is greater than the median value, the rising indicator value of the second target data being a second preset value;

[0012] The original data includes L groups of data, each group of data including a service behavior frequency and a user stickiness indicator corresponding to the service behavior frequency, and the service behavior frequencies in the L groups of data are different.

[0013] Optionally, the method further comprises:

[0014] For each target rising trend group, an absolute growth value of the user stickiness indicator and a relative growth rate of the increase-decrease ratio are calculated.

[0015] According to the absolute growth value and the relative growth rate, a category to which each target rising trend group belongs is determined.

[0016] According to the target rising trend group, a target user is screened.

[0017] Based on the category to which the target rising trend group belongs, a business strategy is adjusted.

[0018] Optionally, after the absolute growth value of the user stickiness indicator and the relative growth rate of the increase-decrease ratio are calculated, the method further comprises:

[0019] An absolute average growth value of the user stickiness indicator is calculated.

[0020] According to the absolute growth value, the absolute average growth value, and the relative growth rate, a category to which each target rising trend group belongs is determined.

[0021] Optionally, the absolute growth value of the user stickiness indicator is calculated by:

[0022] A difference between a user stickiness indicator of a first data and a user stickiness indicator of a last data in the target rising trend group is calculated to obtain the absolute growth value.

[0023] Optionally, the relative growth rate of the increase-decrease ratio is calculated by:

[0024] A sum of the increase-decrease ratios in the target rising trend group is calculated.

[0025] An average value of the sum of the increase-decrease ratios is calculated to obtain the relative growth rate.

[0026] Optionally, the increase-decrease ratio between the current group of data and the previous group of data is calculated by:

[0027] For each group of data in the original data, a difference value between a user stickiness indicator of the current group of data and a user stickiness indicator of the previous group of data is calculated;

[0028] According to the difference value between the current group of data and the previous group of data and the user stickiness indicator of the previous group of data, the increase / decrease ratio is calculated.

[0029] In a second aspect, an embodiment of the present application provides a device for identifying an upward trend of a business indicator, comprising:

[0030] A determination unit is configured to determine, for each group of data in original data, an upward indicator value according to a size relationship between a current group of data and a previous group of data, the upward indicator value comprising a first preset value and a second preset value;

[0031] For each target upward trend group, a first target data and a second target data are determined;

[0032] A median of the increase / decrease ratio of the first target data is determined;

[0033] A calculation unit is configured to calculate the increase / decrease ratio between the current group of data and the previous group of data;

[0034] For each target upward trend group, a sum of n upward indicator values between an i-th group of data and an i-(n-1)-th group of data is calculated, to obtain L-n+1 upward trend values, n≤i≤L, n being a persistence length threshold value;

[0035] For each target upward trend group, a mean value of a sum of the increase / decrease ratio of the first target data is calculated, the upward indicator value of the first target data being the first preset value;

[0036] A screening unit is configured to screen the target upward trend group according to the upward trend value, the mean value of the upward trend value of the target upward trend group being greater than or equal to a preset threshold value;

[0037] Interference trend groups are removed, the interference trend group being a target upward trend group in which an absolute value of the increase / decrease ratio of the second target data is greater than the mean value, or a target upward trend group in which an absolute value of the increase / decrease ratio of the second target data is greater than the median, the upward indicator value of the second target data being the second preset value;

[0038] The original data comprises L groups of data, each group of data comprising a business behavior frequency and a user stickiness indicator corresponding to the business behavior frequency, and the business behavior frequencies in the L groups of data are all different.

[0039] Optionally, the apparatus further comprises an adjusting unit;

[0040] The computing unit is further configured to calculate, for each target upward trend group, an absolute growth value of the user stickiness index and a relative growth rate of the increase-decrease ratio.

[0041] The determining unit is further configured to determine, according to the absolute growth value and the relative growth rate, a category to which each target upward trend group belongs.

[0042] The screening unit is further configured to screen target users according to the target upward trend groups.

[0043] The adjusting unit is configured to adjust a business strategy based on the category to which the target upward trend group belongs.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the method in any of the above first aspect when executing the computer program.

[0045] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executable by a processor to implement the method in any of the above first aspect.

[0046] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on an electronic device, causes the electronic device to perform the method in any of the above first aspect.

[0047] It can be understood that the beneficial effects of the above second aspect to fifth aspect can be referred to the related description in the above first aspect, and will not be repeated here.

[0048] Compared with the prior art, the embodiment of the present application has the beneficial effects that:

[0049] The embodiment of the present application determines the upward index value according to the size relationship between the current group data and the previous group data for each group of data in the original data, and calculates the increase-decrease ratio between the current group data and the previous group data; calculates the sum of n upward index values between the i-th group data and the i-(n-1)-th group data, to obtain L-n+1 upward trend values, n≤i≤L; and screens target upward trend groups according to the upward trend values, and the average value of the upward trend values of the target upward trend groups is greater than or equal to a preset threshold, to screen out the upward trend.

[0050] Then, for each target rising trend group, the first target data and the second target data are determined, and the mean of the sum of the increase-decrease ratios of the first target data is calculated, and the rising index value of the first target data is a first preset value; the median of the increase-decrease ratios of the first target data is determined; the interference trend groups are eliminated, the interference trend groups are target rising trend groups in which at least one second target data has an absolute value of the increase-decrease ratio greater than the mean, or target rising trend groups in which at least one second target data has an absolute value of the increase-decrease ratio greater than the median, and the rising index value of the second target data is a second preset value, so as to eliminate the trends not belonging to rising due to individual fluctuations, thereby accurately identifying the rising trend and accurately obtaining the user stickiness index part positively correlated with the business behavior frequency. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0052] Figure 1 is a first flowchart of a method for identifying a rising trend of a business index provided by an embodiment of the present application;

[0053] Figure 2 is a second flowchart of a method for identifying a rising trend of a business index provided by an embodiment of the present application;

[0054] Figure 3 is a structural diagram of an apparatus for identifying a rising trend of a business index provided by an embodiment of the present application;

[0055] Figure 4 is a structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0056] In the following description, specific details such as specific system structures, techniques, etc. are presented in order to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits and methods are omitted to avoid unnecessary details that hinder the description of the present application.

[0057] It should be understood that the word “comprise” or variations such as “comprises” or “comprising”, when used in this specification and in the accompanying claims, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0058] It should also be understood that the term “and / or” when used in this specification and in the claims which follow, unless otherwise stated, means one or both of the stated items can be present at the same time.

[0059] As used in this specification and in the claims, the term “if’ can be construed to mean “when” or “once” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a described condition or event] is detected” can be construed to mean “once it is determined” or “in response to determining” or “once [the described condition or event] is detected” or “in response to detecting [a described condition or event],” depending on the context.

[0060] In addition, the terms “first”, “second”, “third”, etc. are used in the description and in the claims of this application only to distinguish different instances of a description, and cannot be interpreted to imply or suggest relative importance.

[0061] Reference in the specification to “one embodiment” or “some embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrase “in one embodiment” or “in some embodiments” in various places in the specification are not necessarily all referring to the same embodiment, although it can. The terms “including,” “comprising,” “having” and variations thereof are meant to encompass the items listed thereafter and equivalents thereof as well as additional items.

[0062] Figure 1 is a first flowchart of a method for identifying an upward trend of a business index according to an embodiment of the present application. As shown in Figure 1 The method comprises:

[0063] S11: For each group of data in the original data, according to the size relationship between the current group of data and the previous group of data, determine an upward index value, and calculate the increase / decrease ratio between the current group of data and the previous group of data.

[0064] The ascending index value includes a first preset value and a second preset value. The original data includes L groups of data, each group of data including a service behavior frequency and a user stickiness index corresponding to the service behavior frequency, and the service behavior frequencies in the L groups of data are different. The user stickiness index data corresponding to a service behavior frequency is from data of multiple users in big data. The service behavior refers to a single behavior, which can be specifically a comment, a like, a collection, etc. The user stickiness index can be a click rate, a retention rate, etc. For example, in the original data, each group of data includes a browsing frequency and a click rate corresponding to the browsing frequency, and the browsing frequency is 1 to 18 times. When the browsing frequency is 1 time, the corresponding click rate is 1.09%; represented as sequence number i = 1, d1 = 1.09%. When the browsing frequency is 2 times, the corresponding click rate is 1.84%, represented as sequence number i = 2, d2 = 1.84%, and so on.

[0065] In the application, when the user stickiness index of the current group of data is greater than the user stickiness index of the previous group of data, the ascending index value is set as the first preset value. When the user stickiness index of the current group of data is less than or equal to the user stickiness index of the previous group of data, the ascending index value is set as the second preset value. The first preset value is set as 1, and the second preset value is set as 0. For example, the browsing frequency of the first group of data is 1 time, and the click rate is 1.09%, and the ascending index value is directly assigned as 1. The browsing frequency of the second group of data is 2 times, and the click rate is 1.84%, which is greater than 1.09%, and the ascending index value is 1. The browsing frequency of the third group of data is 3 times, and the click rate is 2.09%, which is greater than 1.84%, and the ascending index value is 1. The browsing frequency of the fourth group of data is 4 times, and the click rate is 2.01%, which is less than 2.09%, and the ascending index value is 0.

[0066] Then, for each group of data in the original data, the increase-decrease difference value between the user stickiness index of the current group of data and the user stickiness index of the previous group of data is calculated; and the increase-decrease ratio is calculated according to the increase-decrease difference value of the current group of data and the user stickiness index of the previous group of data.

[0067] The formula for calculating the increase-decrease difference value is D i = d i - d i-1 ; and the formula for calculating the increase-decrease ratio is T i = (D i / d i-1D is the difference between the increase and decrease, T is the increase and decrease ratio, and i is the serial number corresponding to each group of data. For example, the user stickiness index of the first group of data is 1.09%, and the increase and decrease difference and ratio are directly assigned as 0. The user stickiness index of the second group of data is 1.84%, the increase and decrease difference D2 = 1.84% - 1.09% = 0.75%, and the increase and decrease ratio T2 = (0.75% / 1.09%) x 100% = 68.83%. The user stickiness index of the third group of data is 2.09%, the increase and decrease difference D3 = 2.09% - 1.84% = 0.25%, and the increase and decrease ratio T3 = (0.25% / 1.84%) x 100% = 13.21%. The user stickiness index of the fourth group of data is 2.01%, the increase and decrease difference D4 = 2.01% - 2.09% = -0.08%, and the increase and decrease ratio T4 = (-0.08% / 2.09%) x 100% = -3.74%.

[0068] S12: Calculate the sum of n rising index values between the ith group of data and the i-(n-1)th group of data, to obtain L-n+1 rising trend values, n≤i≤L.

[0069] Wherein, n is the persistence length threshold. In order to better identify the user stickiness index of the rising trend, the value range of n is [3, L].

[0070] In application, after determining the value of n, from i = n, the n groups of data between the ith group of data and the i-(n-1)th group of data are grouped into a rising trend group, until i = L, to obtain L-n+1 rising trend groups.

[0071] According to the formula, the sum of the rising index values of the rising trend group is calculated: PW(n, i) = ∑W i = W i + W i-1 + W i-2 + W i-3 +...+ W i-(n-1) , PW is the sum of the rising index values of the n groups of data with continuous rising trend, i is the serial number corresponding to each group of data, and W is the rising index value.

[0072] From i = n, the rising trend value of the first rising trend group is calculated, then i = n+1, the rising trend value of the second rising trend group is calculated, and so on, until i = L, to obtain the rising trend values of the L-n+1 rising trend groups.

[0073] For example, after determining n=4, four groups of data between the 4th group of data and the 1st group of data form a first rising trend group. In the first rising trend group, the rising indicator value of the 1st group of data is W1=1; the rising indicator value of the 2nd group of data is W2=1; the rising indicator value of the 3rd group of data is W3=1; and the rising indicator value of the 4th group of data is W4=0. PW(4, 4)=W4+W3+W2+W1=3. The rising trend values of other rising trend groups are calculated in the same way.

[0074] S13: Screening a target rising trend group according to the rising trend value.

[0075] The average value of the rising trend values of the target rising trend group is greater than or equal to a preset threshold value. The formula for calculating the average value of the rising trend values is m=PW(n, i) / n.

[0076] In application, the selected target rising trend group may reflect the rising trend and may belong to the user stickiness indicator data positively correlated with the business behavior frequency.

[0077] The rising trend group that cannot reflect the rising trend is eliminated, and the proportion of data with the rising indicator value of 1 in the rising trend group is generally required to be greater than 0.75, so that the selected target rising trend group can reflect the rising trend. For example, when n=4, the rising trend group includes four groups of data, and the rising indicator value of at least three groups of data in the four groups of data is required to be 1. When n=8, the rising trend group includes eight groups of data, and the rising indicator value of at least six groups of data in the eight groups of data is required to be 1.

[0078] For example, the preset threshold value is set to 0.75. The rising trend value of the first rising trend group is PW(4, 4)=3. The average value of the rising trend value is m=PW(4, 4) / 4=3 / 4=0.75. Since the average value of the rising trend value of PW(4, 4) is 0.75, 0.75 is equal to the preset threshold value 0.75, and PW(4, 4) is the target rising trend group.

[0079] S14: For each target rising trend group, determining a first target data and a second target data, and calculating the average value of the sum of the increase / decrease ratios of the first target data.

[0080] The rising indicator value of the first target data is a first preset value, and the rising indicator value of the second target data is a second preset value.

[0081] In the target upward trend group, the data with the upward index value being the first preset value is determined as the first target data, and the data with the upward index value being the second preset value is determined as the second target data. For example, the upward index value of the first group of data is 1, and the first group of data is determined as the first target data. The upward index value of the second group of data is 1, and the second group of data is determined as the first target data. The upward index value of the third group of data is 1, and the third group of data is determined as the first target data. The upward index value of the fourth group of data is 0, and the fourth group of data is determined as the second target data.

[0082] In application, based on the increase / decrease ratio, the mean value of the sum of the increase / decrease ratios of the first target data is calculated, and the calculation formula is: u = (∑T i ) / h, W = 1. u is the mean value, T is the increase / decrease ratio, i is the serial number corresponding to each group of data, W is the upward index value, and h is the number of the first target data in the target upward trend group.

[0083] For example, PW(4, 4) is the target upward trend group, the first group of data, the second group of data, and the third group of data are the first target data, and h is 3. The sum of the increase / decrease ratios of the corresponding first target data is ∑T i = 0 + 68.83% + 13.21% = 83.04%, and the mean value of the sum of the increase / decrease ratios is: u = 83.04% / 3 = 27.34%.

[0084] S15: The median of the increase / decrease ratio of the first target data is determined.

[0085] In application, in the target upward trend group and in all the first target data, the median of the increase / decrease ratio of the first target data is determined.

[0086] S16: Interference trend groups are removed.

[0087] The interference trend group is a target upward trend group in which the absolute value of the increase / decrease ratio of at least one second target data is greater than the mean value, or a target upward trend group in which the absolute value of the increase / decrease ratio of at least one second target data is greater than the median.

[0088] In application, the absolute value of the increase / decrease ratio of each second target data is taken, the absolute value of the increase / decrease ratio of each second target data is compared with the mean value, and the absolute value of the increase / decrease ratio of each second target data is compared with the median. If the absolute value of the increase / decrease ratio is greater than the mean value or the absolute value of the increase / decrease ratio is greater than the median, the corresponding target upward trend group is an interference trend group and needs to be removed.

[0089] In actual situation, the target upward trend group as a whole shows upward trend, but if the downward amplitude brought by the downward data in the target upward trend group is greater than the upward amplitude brought by the upward data, the target upward trend group will be affected, and it is not the user stickiness index data positively correlated with the business behavior frequency. The target upward trend group with this part of interference trend group needs to be removed. After removing this part of interference trend group, the final target upward trend group is more accurate data of upward trend.

[0090] For example, after various calculations on the original data, the following table shows the results; in the table, the frequency is represented by the business behavior frequency, L = 18; the click rate is the user stickiness index data, n = 4, and the preset threshold is 0.75.

[0091]

[0092]

[0093] wherein, W i = 1, d i > d i-1 ; W i = 0, d i ≤ d i-1 ; i is the serial number, corresponding to the frequency and the click rate.

[0094] According to the formula PW(4, i) = ∑W i = W i + W i-1 + W i-2 + W i-3 , the upward trend value of the upward trend group is calculated, and then the target upward trend group is screened according to PW(4, i) / 4 ≥ 0.75, and PW(4, 4) and PW(4, 5) are screened out.

[0095] Then, PW(4, 4) is verified. For the first target data, the mean u = (0 + 68.83% + 13.21%) / 3 = 27.34% is calculated; and the median is 13.21%.

[0096] For the second target data, |T4| = 3.74%, because |T4| ≤ 27.34% and |T4| ≤ 13.21%, PW(4, 4) is not an interference trend group, and is retained.

[0097] PW(4, 5) is verified. For the first target data, the mean u = (68.83% + 13.21% + 262.66%) / 3 = 114.9% is calculated, and the median is 68.83%.

[0098] For the second target data, |T4| = 3.74%, since |T4| ≤ 27.34% and |T4| ≤ 13.21%, PW(4, 5) is not an interference trend group, and is retained.

[0099] The embodiment determines an ascending index value according to the size relationship between the current group of data and the previous group of data, and calculates an increase-decrease ratio between the current group of data and the previous group of data for each group of data in the original data; calculates a sum of n ascending index values between the ith group of data and the i-(n-1)th group of data, to obtain L-n+1 ascending trend values, n ≤ i ≤ L; and screens a target ascending trend group according to the ascending trend values, so as to screen out a trend that is possibly ascending, where an average value of the ascending trend values of the target ascending trend group is greater than or equal to a preset threshold value.

[0100] Then, the first target data and the second target data are determined for each target ascending trend group, an average value of a sum of increase-decrease ratios of the first target data is calculated, an ascending index value of the first target data is a first preset value, a median of the increase-decrease ratios of the first target data is determined, an interference trend group is eliminated, the interference trend group is a target ascending trend group in which an absolute value of at least one increase-decrease ratio of the second target data is greater than the average value, or a target ascending trend group in which an absolute value of at least one increase-decrease ratio of the second target data is greater than the median, an ascending index value of the second target data is a second preset value, and individual fluctuations are eliminated to obtain a trend that does not belong to ascending, so that an ascending trend is accurately identified, and a user stickiness index part that is positively correlated with a business behavior frequency is accurately obtained.

[0101] Figure 2 FIG. 2 is a second flowchart of a method for identifying an ascending trend of a business index according to an embodiment of the present application. As shown in FIG. 2, the method further includes: Figure 2

[0102] S21: For each target ascending trend group, an absolute growth value of the user stickiness index and a relative growth rate of the increase-decrease ratio are calculated.

[0103] In application, the absolute growth value of the user stickiness index is calculated by calculating a difference between the user stickiness index of the first data and the user stickiness index of the last data in the target ascending trend group, to obtain the absolute growth value.

[0104] Wherein, the target ascending trend group includes n groups of data. The calculation formula is K = k n -k1, T is the absolute growth value, k n ​K4 is the user stickiness index of the last data in the target ascending trend group, and k1 is the user stickiness index of the first data in the target ascending trend group. For example, the first ascending trend group is the target ascending trend group, and includes the first group data, the second group data, the third group data, and the fourth group data. In the first ascending trend group, the first data is the first group data, and the last data is the fourth group data. Therefore, k1 is the user stickiness index of the first group data, and k4 is the user stickiness index of the fourth group data. n K4 is the user stickiness index of the last data in the target ascending trend group, and k1 is the user stickiness index of the first data in the target ascending trend group. For example, the first ascending trend group is the target ascending trend group, and includes the first group data, the second group data, the third group data, and the fourth group data. In the first ascending trend group, the first data is the first group data, and the last data is the fourth group data. Therefore, k1 is the user stickiness index of the first group data, and k4 is the user stickiness index of the fourth group data.

[0105] The relative growth rate of the increase-decrease ratio is calculated, including: calculating the sum of the increase-decrease ratios in the target ascending trend group; and calculating the average value of the sum of the increase-decrease ratios to obtain the relative growth rate.

[0106] The average value of the sum of the increase-decrease ratios is calculated according to the formula S=(∑T i ) / n, where S is the average value, T is the increase-decrease ratio, and i is the serial number of each group of data.

[0107] S22: According to the absolute growth value and the relative growth rate, determine the category to which each target ascending trend group belongs.

[0108] In the application, the absolute growth value and the relative growth rate of each target ascending trend group are compared in size, and the target ascending trend group with a larger value is classified into the optimal category, and the target ascending trend group with a smaller value is classified into the suboptimal category.

[0109] According to the absolute growth value and the relative growth rate, the target ascending trend group with a more obvious ascending trend is screened out.

[0110] For example, for PW(4, 4), the absolute growth value is calculated as K(4, 4)=2.01%-1.09%=0.92%.

[0111] The relative growth rate is calculated as S(4, 4)=(0+68.83%+13.24%-3.74%) / 4=19.57%.

[0112] For PW(4, 5), the absolute growth value is calculated as K(4, 5)=7.29%-1.84%=5.45%. The relative growth rate is calculated as S(4, 5)=(68.83%+13.24%-3.74+262.66%) / 4=85.24%.

[0113] Since K(4, 5) is greater than K(4, 4), and S(4, 5) is greater than S(4, 4), PW(4, 5) is determined as the optimal category, and PW(4, 4) is determined as the suboptimal category.

[0114] S23: According to the target ascending trend group, screen the target user.

[0115] S24: Adjust the business strategy based on the category to which the target upward trend group belongs.

[0116] In application, the target upward trend group belonging to the optimal category is the user stickiness index data positively correlated with the frequency of business behavior, which needs to be focused on. The target upward trend group belonging to the sub-optimal category is the user stickiness data positively correlated with the frequency of business behavior, which needs to be focused on, but the degree of attention is determined according to the actual situation. For example, for strong business indicators, the user group needs to have high stickiness. When screening users for precision marketing, the target upward trend group belonging to the optimal category is screened, and the business strategy of the target upward trend group belonging to the optimal category is adjusted to the business strategy of the user group with high stickiness. If the number of user groups under strong business indicators is insufficient, the target upward trend group belonging to the sub-optimal category can be screened to make up the number.

[0117] In one embodiment, after step S21, it further includes:

[0118] The absolute average growth value of the user stickiness index is calculated.

[0119] In application, the calculation formula is K U = K / n, K U is the absolute average growth value, and K is the absolute growth value.

[0120] According to the absolute growth value, the absolute average growth value, and the relative growth rate, the category to which each target upward trend group belongs is determined.

[0121] In application, the absolute growth value, the absolute average growth value, and the relative growth rate of each target upward trend group are compared in size, and the target upward trend group with a larger value is divided into the optimal category, and the target upward trend group with a smaller value is divided into the sub-optimal category.

[0122] For example, for PW(4, 4), the absolute average growth value K U (4, 4) = 0.92% / 4 = 0.23%. For PW(4, 5), the absolute average growth value K U (4, 5) = 5.45% / 4 = 1.36%.

[0123] Since K(4, 5) is greater than K(4, 4), S(4, 5) is greater than S(4, 4), K U (4, 5) is greater than K U (4, 4), PW(4, 5) is determined as the optimal category, and PW(4, 4) is determined as the sub-optimal category.

[0124] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0125] Corresponding to the method described in the above embodiments, only the part related to the embodiments of the present application is shown for the convenience of illustration.

[0126] Figure 3 is a structural schematic diagram of an apparatus for identifying an upward trend of a business index provided by an embodiment of the present application. As shown in Figure 3 , the apparatus comprises:

[0127] The determining unit 10 is configured to determine, for each group of data in the original data, an upward index value according to a size relationship between the current group of data and the previous group of data, the upward index value comprising a first preset value and a second preset value.

[0128] The determining unit is configured to determine, for each target upward trend group, a first target data and a second target data.

[0129] The determining unit is configured to determine a median of an increase / decrease ratio of the first target data.

[0130] The calculating unit 11 is configured to calculate an increase / decrease ratio between the current group of data and the previous group of data.

[0131] The calculating unit is configured to calculate a sum of n upward index values between the i-th group of data and the i-(n-1)-th group of data, to obtain L-n+1 upward trend values, n≤i≤L, n being a persistence length threshold.

[0132] The calculating unit is configured to calculate, for each target upward trend group, a mean of a sum of the increase / decrease ratios of the first target data, the upward index value of the first target data being the first preset value.

[0133] The screening unit 12 is configured to screen the target upward trend group according to the upward trend value, the mean of the upward trend values of the target upward trend group being greater than or equal to a preset threshold.

[0134] The screening unit is configured to eliminate an interference trend group, the interference trend group being a target upward trend group in which at least one second target data has an absolute value of the increase / decrease ratio greater than the mean, or a target upward trend group in which at least one second target data has an absolute value of the increase / decrease ratio greater than the median, the upward index value of the second target data being the second preset value.

[0135] The original data comprises L groups of data, each group of data comprising a business behavior frequency and a user stickiness index corresponding to the business behavior frequency, and the business behavior frequencies in the L groups of data are all different.

[0136] In an embodiment, the apparatus further comprises an adjusting unit.

[0137] The calculating unit is further configured to calculate, for each target upward trend group, an absolute growth value of the user stickiness index and a relative growth rate of the increase / decrease ratio.

[0138] The unit is also used to determine the category to which each target upward trend group belongs based on the absolute growth value and the relative growth rate;

[0139] The filtering unit is also used to filter target users based on target upward trend groups;

[0140] The adjustment unit is used to adjust business strategies based on the category to which the target upward trend group belongs.

[0141] In one embodiment, the calculation unit is also used to calculate the absolute average growth value of user stickiness metrics;

[0142] The unit is also used to determine the category to which each target upward trend group belongs based on the absolute growth value, the absolute average growth value, and the relative growth rate.

[0143] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 4 As shown, the electronic device 2 of this embodiment includes: at least one processor 20 ( Figure 4 (Only one is shown in the diagram), memory 21, and computer program 22 stored in said memory 21 and executable on said at least one processor 20, wherein said processor 20 executes said computer program 22 to implement the steps in any of the above method embodiments.

[0144] The electronic device 2 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device 2 may include, but is not limited to, a processor 20 and a memory 21. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 2 and does not constitute a limitation on electronic device 2. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, etc.

[0145] The processor 20 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0146] The memory 21 can be an internal storage unit of the electronic device 2 in some embodiments, such as a hard disk or a memory of the electronic device 2. The memory 21 can also be an external storage device of the electronic device 2 in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, and the like equipped on the electronic device 2. Further, the memory 21 can include both the internal storage unit and the external storage device of the electronic device 2. The memory 21 is used to store an operating system, an application program, a boot loader, data, and other programs, such as program codes of the computer program, and the like. The memory 21 can also be used to temporarily store data that has been output or is to be output.

[0147] It should be noted that the information interaction, execution process, and the like between the above apparatuses / units are based on the same concept as the method embodiments of the present application, and specific functions and brought technical effects can be referred to the method embodiments part, which will not be described herein.

[0148] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above-mentioned division of functional units and modules is exemplified, and in actual application, the above-mentioned functions can be completed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or software. In addition, the specific names of each functional unit and module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the unit and module in the system can refer to the corresponding process in the foregoing method embodiments, which will not be described herein.

[0149] The present embodiment also provides a computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps in each of the above method embodiments can be implemented.

[0150] The present embodiment provides a computer program product. When the computer program product is run on an electronic device, the steps in each of the above method embodiments can be implemented.

[0151] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the present application can implement all or part of the processes in the above-mentioned embodiment methods through a computer program to instruct relevant hardware to complete, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms. The computer readable medium at least includes any entity or device capable of carrying the computer program code to the photographing device / terminal equipment, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium. For example, U disk, mobile hard disk, magnetic disk or optical disk, etc. In some jurisdictions, according to legislation and patent practice, the computer readable medium can not be an electrical carrier signal and a telecommunication signal.

[0152] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0153] Those of ordinary skill in the art can understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0154] In the embodiments provided by the present application, it should be understood that the disclosed apparatus / network device and method can be implemented in other ways. For example, the above-described apparatus / network device embodiments are merely schematic, for example, the division of the modules or units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed each other can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0155] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may also be distributed to multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0156] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for identifying an upward trend in business metrics, characterized in that, The method comprises the following steps: For each group of data in the original data, determining an upward index value according to the size relationship between the current group of data and the previous group of data, and calculating the increase / decrease ratio between the current group of data and the previous group of data, wherein the upward index value comprises a first preset value and a second preset value; Calculating the sum of n upward index values between the i-th group of data and the i-(n-1)-th group of data, to obtain L-n+1 upward trend values, wherein n≤i≤L, and n is a persistence length threshold; According to the upward trend values, screening a target upward trend group, wherein the average value of the upward index values of the target upward trend group is greater than or equal to a preset threshold; For each target upward trend group, determining a first target data and a second target data, and calculating the average value of the sum of the increase / decrease ratios of the first target data, wherein the upward index value of the first target data is the first preset value; Determining the median of the increase / decrease ratios of the first target data; Eliminating an interference trend group, wherein the interference trend group is a target upward trend group in which the absolute value of the increase / decrease ratio of at least one second target data is greater than the average value, or a target upward trend group in which the absolute value of the increase / decrease ratio of at least one second target data is greater than the median, and the upward index value of the second target data is the second preset value; The original data comprises L groups of data, each group of data comprises a business behavior frequency and a user stickiness index corresponding to the business behavior frequency, and the business behavior frequencies in the L groups of data are all different. The method comprises the following steps: For each group of data in the original data, calculating the increase / decrease difference value between the user stickiness index of the current group of data and the user stickiness index of the previous group of data; According to the increase / decrease difference value of the current group of data and the user stickiness index of the previous group of data, calculating the increase / decrease ratio.

2. The method of claim 1, wherein, The method further comprises the following steps: For each target upward trend group, calculating the absolute growth value of the user stickiness index and the relative growth rate of the increase / decrease ratio; According to the absolute growth value and the relative growth rate, determining the category to which each target upward trend group belongs; According to the target upward trend group, screening a target user; Based on the category to which the target upward trend group belongs, adjusting a business strategy.

3. The method of claim 2, wherein, After calculating the absolute growth value of the user stickiness index and the relative growth rate of the increase / decrease ratio, the method further comprises the following steps: Calculating the absolute average growth value of the user stickiness index; According to the absolute growth value, the absolute average growth value and the relative growth rate, determining the category to which each target upward trend group belongs.

4. The method of claim 2 or 3, wherein, The method of calculating the absolute growth value of the user stickiness index comprises the following steps: Calculating the difference value between the user stickiness index of the first data in the target upward trend group and the user stickiness index of the last data, to obtain the absolute growth value.

5. The method of claim 2 or 3, wherein, The method of calculating the relative growth rate of the increase / decrease ratio comprises the following steps: Calculating the sum of the increase / decrease ratios in the target upward trend group; Calculating the average value of the sum of the increase / decrease ratios, to obtain the relative growth rate.

6. An apparatus for identifying an upward trend in a business metric, the apparatus comprising: The method comprises the following steps: The determining unit is configured to determine, for each group of data in the original data, an upward index value according to a size relationship between the current group of data and the previous group of data, the upward index value including a first preset value and a second preset value; The determining unit is configured to determine, for each target upward trend group, a first target data and a second target data; The determining unit is configured to determine a median of an increase / decrease ratio of the first target data; The calculating unit is configured to calculate the increase / decrease ratio between the current group of data and the previous group of data; The calculating unit is configured to calculate a sum of n upward index values between the i-th group of data and the i-(n-1)-th group of data, to obtain L-n+1 upward trend values, n≤i≤L, n being a persistence length threshold value; The calculating unit is configured to calculate, for each target upward trend group, a mean value of a sum of increase / decrease ratios of the first target data, the upward index value of the first target data being the first preset value; The screening unit is configured to screen the target upward trend group according to the upward trend value, the mean value of the upward index value of the target upward trend group being greater than or equal to a preset threshold value; The screening unit is configured to eliminate an interference trend group, the interference trend group being a target upward trend group in which an absolute value of the increase / decrease ratio of the second target data is greater than the mean value, or a target upward trend group in which an absolute value of the increase / decrease ratio of the second target data is greater than the median, the upward index value of the second target data being the second preset value. The original data includes L groups of data, each group of data including a service behavior frequency and a user stickiness index corresponding to the service behavior frequency, and the service behavior frequencies in the L groups of data are all different. The calculating unit is specifically configured to calculate, for each group of data in the original data, an increase / decrease difference value between a user stickiness index of the current group of data and a user stickiness index of the previous group of data, and calculate the increase / decrease ratio according to the increase / decrease difference value of the current group of data and the user stickiness index of the previous group of data.

7. The apparatus of claim 6, wherein, The adjusting unit is further included. The calculating unit is further configured to calculate, for each target upward trend group, an absolute growth value of the user stickiness index and a relative growth rate of the increase / decrease ratio. The determining unit is further configured to determine a category to which each target upward trend group belongs according to the absolute growth value and the relative growth rate. The screening unit is further configured to screen a target user according to the target upward trend group. The adjusting unit is configured to adjust a service policy based on the category to which the target upward trend group belongs.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 8. The computer program is executed by the processor to implement the method in any one of claims 1 to 5.

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