A method, device and readable medium for analyzing pain points of clothes drying equipment products

Abstract

The present invention relates to a method, device and readable medium for analyzing pain points of clothes drying equipment products. A method for analyzing pain points of clothes drying equipment products, characterized in that it includes: obtaining comment data, performing data cleaning on multiple dimensions to obtain structured data; the dimensions include category, score, and time; performing word segmentation processing on the structured data based on a distributed search engine to obtain multiple word segmentation data related to product quality; sorting the multiple word segmentation data from high to low according to the first word frequency, and selecting the top n word segmentation data in the sorting as pre-selected word segmentations; for each pre-selected word segmentation, interpreting and analyzing several comment data from the comment data as pre-selected comment data to determine the product pain points. First, obtain comment data on clothes drying equipment, and then use a distributed search engine to perform word segmentation processing to obtain multiple word segmentation data, and then interpret and analyze the comment data including the pre-selected word segmentation to obtain the product pain points.

Description

Technical Field

[0001] The present invention relates to electronic equipment, and in particular to a method, device and readable medium for analyzing pain points of clothes drying equipment. Background Art

[0002] As time goes by and technology continues to develop, market competition in all walks of life is becoming increasingly fierce, and products are constantly updated and improved. In order to improve the competitiveness of industry products, it is necessary to understand user trends and discover user pain points.

[0003] The pain point itself corresponds to a point rather than a surface. The solution does not need to be perfect or comprehensive, but to find the right entry point. The pain point is not a demand directly raised by the user, but it comes from the demand and complements the demand. The demand is the source of the pain point, and the pain point is the inevitable result of the development of the demand to a certain stage. The problem caused by the pain point can correspond to multiple problems, and the pain point also hides this problem.

[0004] With the booming development of e-commerce shopping, users write their user experience of products into user reviews. User reviews can basically reflect the actual usage of users. This solution is to analyze user pain points through the reviews written by users, and use Chinese word segmentation technology to determine user pain points by the frequency of word segmentation, give a pain point ranking, and provide strong data support for corporate production and sales. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, an object of the present invention is to provide a method, device and readable medium for analyzing pain points of clothes drying equipment products, which can obtain product pain points by analyzing review data.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In one aspect, the present invention provides a method for analyzing pain points of a clothes drying equipment product, comprising:

[0008] Obtain review data, perform data cleaning on multiple dimensions, and obtain structured data; the dimensions include category, rating, and time;

[0009] Performing word segmentation processing on the structured data based on a distributed search engine to obtain a plurality of word segmentation data related to product quality; the word segmentation data includes a word segmentation name and a first word frequency;

[0010] Sorting the plurality of segmented word data from high to low according to the first word frequency, and selecting the first n segmented word data in the sorting as pre-selected segmented words;

[0011] For each of the pre-selected segmented words, a number of comment data are selected from the comment data to be interpreted and analyzed as pre-selected comment data to determine product pain points.

[0012] Furthermore, in the method for analyzing pain points of clothes drying equipment products, the data cleaning includes deduplication operations, special symbol removal operations, irregular data removal operations, null value removal operations, incoherent semantic removal operations, and completely positive data removal operations.

[0013] Furthermore, in the method for analyzing pain points of clothes drying equipment products, the review data is derived from multiple e-commerce platforms and is obtained on the multiple e-commerce platforms through crawler software.

[0014] Furthermore, the method for analyzing the pain points of the clothes drying equipment product, the interpretation and analysis specifically includes:

[0015] Extracting the context of the pre-selected word from the pre-selected comment data, and performing negative word screening to obtain a number of pain point words;

[0016] Performing semantic analysis on the pain point words, integrating pain point words with similar semantics to obtain pain point phrases; the pain point phrases include phrase names and second word frequencies;

[0017] The pre-selected segmented words corresponding to the pre-selected comment data are integrated with the pain point phrases to obtain product pain points corresponding to the pre-selected segmented words, wherein the product pain points are sorted from high to low according to the second word frequency.

[0018] Furthermore, in the method for analyzing pain points of clothes drying equipment products, the step of obtaining the segmentation data is:

[0019] Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data;

[0020] A screening operation is performed on multiple segmentation names to obtain segmentation names related to the product quality of the clothes drying equipment and corresponding first word frequencies to generate the segmentation data.

[0021] In another aspect, the present invention provides a device for analyzing pain points of clothes drying equipment, comprising:

[0022] An acquisition module is used to acquire review data and clean the data in multiple dimensions to obtain structured data; the dimensions include category, rating, natural language review, and time;

[0023] A processing module is used to perform word segmentation processing on the structured data based on a distributed search engine to obtain multiple word segmentation data related to product quality; the word segmentation data includes a word segmentation name and a first word frequency; the multiple word segmentation data are sorted from high to low according to the first word frequency, and the first n word segmentation data in the sorting are selected as pre-selected word segmentations; for each pre-selected word segmentation, a number of comment data are selected from the comment data as pre-selected comment data for interpretation and analysis to determine product pain points.

[0024] Furthermore, in the clothes drying equipment product pain point analysis device, the data cleaning performed by the acquisition module specifically includes: deduplication operation, special symbol removal operation, irregular data removal operation, null value removal operation, illegal data removal operation, incoherent semantic removal operation, and completely positive data removal operation.

[0025] Furthermore, in the device for analyzing pain points of clothes drying equipment, the interpretation and analysis specifically includes:

[0026] Extracting the context of the pre-selected word from the pre-selected comment data, and performing negative word screening to obtain a number of pain point words;

[0027] Performing semantic analysis on the pain point words, integrating pain point words with similar semantics to obtain pain point phrases; the pain point phrases include phrase names and second word frequencies;

[0028] The pre-selected segmented words corresponding to the pre-selected comment data are integrated with the pain point phrases to obtain product pain points corresponding to the pre-selected segmented words, wherein the product pain points are sorted from high to low according to the second word frequency.

[0029] Furthermore, in the device for analyzing pain points of clothes drying equipment, the step of acquiring the segmentation data is as follows:

[0030] Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data;

[0031] A screening operation is performed on multiple segmentation names to obtain segmentation names related to the product quality of the clothes drying equipment and corresponding first word frequencies to obtain segmentation data.

[0032] On the other hand, the present invention provides a computer-readable medium storing a computer program, which, when executed by a processor, implements any of the aforementioned methods for analyzing pain points of clothes drying equipment products.

[0033] Compared with the prior art, the method, device and readable medium for analyzing pain points of clothes drying equipment provided by the present invention have the following beneficial effects:

[0034] Using the clothes drying equipment product pain point analysis method provided by the present invention, firstly, the review data about the clothes drying equipment is obtained, and then a distributed search engine is used to perform word segmentation processing to obtain a plurality of word segmentation data, and then the review data including the pre-selected word segmentations are interpreted and analyzed to obtain the product pain points, so that the operation personnel or the design personnel can obtain the product defects during the use of the product as soon as possible, and achieve the purpose of quickly optimizing the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1It is a flow chart of the method for analyzing pain points of clothes drying equipment products provided by the present invention.

[0036] Figure 2 It is a structural block diagram of the pain point analysis device for clothes drying equipment provided by the present invention.

[0037] Figure 3 It is a structural diagram of an embodiment of the method for analyzing pain points of clothes drying equipment provided by the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] Those skilled in the art will appreciate that the foregoing general description and the following detailed description are exemplary and illustrative of specific embodiments of the present invention and are not intended to limit the present invention.

[0040] The terms "comprises," "includes," or any other variation thereof, herein are intended to cover a non-exclusive inclusion, such that a process or method that includes a list of steps includes not only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, a reference to one or more devices or subsystems, elements or structures or components preceded by "comprises ... an" does not, without further limitations, exclude the presence of other devices or other subsystems or other elements or other structures or other components or other devices or other subsystems or other elements or other structures or other components. Throughout the specification, appearances of the phrases "in one embodiment," "in another embodiment," and similar language may, but do not necessarily, all refer to the same embodiment.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0042] See also Figure 1 The present invention provides a method for analyzing pain points of clothes drying equipment products, which can analyze product pain points based on the review data fed back by users on the e-commerce platform after purchase, and ensure that the newly launched products can solve the product quality problems fed back by users, thereby improving product quality and user experience.

[0043] The product pain point analysis method includes:

[0044] Obtain review data, perform data cleaning on multiple dimensions, and obtain structured data; the dimensions include category, rating, and time; specifically, the category is the type of product involved in the review content, such as clothes drying equipment, remote control equipment, etc.; the rating is the score given by the user to the product when commenting, such as five-star praise, one-star bad review, etc.; the time dimension is divided into days, months, quarters, years, etc. When data cleaning is performed on multiple dimensions here, some null value data, garbled data, special symbol data, and duplicate data are filtered out to make the review data used in subsequent steps simpler, clearer, and easier to process. Furthermore, the structured data is stored in a database, which includes an SQL database, an Oracle database, a DB2 database, a Shenzhou general database, a Renmin University of China Jincang database, and the like.

[0045] Based on the distributed search engine, the structured data is segmented to obtain multiple segmentation data related to product quality; the segmentation data includes the segmentation name and the first word frequency (i.e., the number of times the same segmentation appears); specifically, the distributed search engine performs Chinese segmentation on the natural language comments of the review content, thereby obtaining multiple segmentations and the corresponding first word frequencies, and then screens out the segmentations related to product quality to generate segmentation data, which is intuitive and simple. Those skilled in the art can select the appropriate distributed search engine to perform segmentation on the structured data according to actual needs.

[0046] The plurality of segmented word data are sorted from high to low according to the first word frequency, and the first n segmented word data in the sorting are selected as pre-selected segmented words; preferably, n is preferably 10-15, and more preferably 10.

[0047] For each of the pre-selected segmented words, a number of review data are selected from the review data as pre-selected review data for interpretation and analysis to determine product pain points. The product pain points are product defects that the corresponding products should solve and need to solve. Interpretation and analysis can quickly determine the corresponding product defects under each segmented word data item, and show that the pain points can be quickly located, so that the staff can provide optimization solutions for specific product pain points.

[0048] Furthermore, for each product pain point, historical rectification plans are retrieved from the solution library, and the product pain points and corresponding historical rectification plans are displayed in descending order according to the first word frequency. Specifically, the historical rectification plan refers to the response plan used for similar problems in the past product sales or production process, and the effect of the solution is also explained, so that researchers can quickly know whether the next plan is appropriate, and can also provide guidance for the next processing plan.

[0049] Using the clothes drying equipment product pain point analysis method provided by the present invention, firstly, the review data about the clothes drying equipment is obtained, and then a distributed search engine is used to perform word segmentation processing to obtain a plurality of word segmentation data, and then the review data including the pre-selected word segmentations are interpreted and analyzed to obtain the product pain points, so that the operation personnel or the design personnel can obtain the product defects during the use of the product as soon as possible, and achieve the purpose of quickly optimizing the product.

[0050] Further, as a preferred solution, in the method for analyzing the pain points of clothes drying equipment products described in this embodiment, the data cleaning includes deduplication operation, special symbol removal operation, irregular data removal operation, null value removal operation, illegal data removal operation, incoherent semantic removal operation, and complete positive data removal operation. Specifically, the deduplication operation is used to remove duplicate values ​​in the comment data, that is, to filter out the comment data with the same user name, category, rating, and comment content, so that the data is objective and avoids being affected by the same comment content multiple times by the same user. The special symbol removal operation is used to remove irregular inputs, such as comments that are all special symbols, which can be deleted to reduce the workload of subsequent processing. The irregular data removal operation is used to remove some comment content that is all letters. The null value removal operation is used to remove comment data whose comment content is empty or automatically defaults to positive comments in the comment data. The incoherent semantic removal operation is used to remove comment data whose comment content is randomly input Chinese characters. The complete positive data removal operation is used to filter out useless data. The technical solution provided by the present invention is used to screen pain points. Too much positive data will not be conducive to the determination of pain points, and it also reduces the amount of calculation in the subsequent steps. It is understandable that, in order to achieve the above purpose, those skilled in the art may select a suitable data cleaning method for application, and the present invention does not limit this.

[0051] For further information, see Figure 3 As a preferred solution, in the method for analyzing pain points of clothes drying equipment products described in this embodiment, the comment data is derived from multiple e-commerce platforms and is obtained on multiple e-commerce platforms through crawler software. Specifically, the sales data and corresponding comment data of multiple e-commerce platforms can be automatically obtained through crawler software, and it can be automatically run as long as the corresponding crawling rules are set. The e-commerce platforms include Taobao, JD.com, Pinduoduo, Suning, etc. Those skilled in the art can select appropriate crawler software to obtain comment data according to actual needs.

[0052] Further, as a preferred solution, in this embodiment, the interpretation and analysis specifically includes:

[0053] The pre-selected comment data is intercepted with the context of the pre-selected segmented words, and negative word screening is performed to obtain several pain point words; for example, the pre-selected segmented words include clothes drying rod, thin, wire rope, shaking, logistics, installation, and remote control. Taking the clothes drying rod as an example, the corresponding negative words include unstable, loose, and cannot be pulled out.

[0054] Perform semantic analysis on the pain point words, and integrate semantically similar pain point words to obtain pain point phrases; the pain point phrases include a phrase name and a second word frequency; in this embodiment, unstable and unsteady can be integrated to obtain unstable / unsteady or other similar forms of phrase expressions (e.g., unstable-unsteady, unstable*unsteady, etc.), and then the first word frequencies of multiple pre-selected participles are added to obtain the second word frequency.

[0055] The pre-selected segmented words corresponding to the pre-selected review data are integrated with the pain point phrases to obtain product pain points for the corresponding pre-selected segmented words, wherein the product pain points are sorted from high to low according to the second word frequency. In this embodiment, the product pain points are finally expressed as unstable / unstable / loose clothes drying rods, etc. The product pain points can be clearly given, such as thin clothes drying rods, short clothes drying rods, complicated installation, too soft wire ropes, and crooked wire ropes.

[0056] Furthermore, as a preferred solution, the method for analyzing the pain points of clothes drying equipment described in this embodiment displays the pain points of the products in a visual chart. Specifically, the visual chart is a bar chart, a pie chart, etc., which can intuitively show the first word frequency corresponding to each word segment name, so that the operator can clearly understand the current product pain points and facilitate subsequent work.

[0057] Further, as a preferred solution, in the method for analyzing pain points of clothes drying equipment products described in this embodiment, the step of obtaining the segmentation data is:

[0058] Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data;

[0059] A screening operation is performed on multiple segmented word names to obtain segmented word names related to the product quality of clothes drying equipment and the corresponding first word frequencies to generate the segmented word data. Specifically, the segmented word names related to the product quality of clothes drying equipment include clothes drying rod, thin, wire rope, shaking, logistics, installation, and remote control. According to the sorting analysis of the first word frequencies of the corresponding segmented word names, the higher the first word frequency, the more users' concerns and pain points are here, which provides a direction for future product quality improvement.

[0060] See also Figure 2 The present invention also provides a device for analyzing pain points of clothes drying equipment, comprising:

[0061] An acquisition module is used to acquire review data and clean the data in multiple dimensions to obtain structured data; the dimensions include category, rating, natural language review, and time;

[0062] A display module is used to display the word segmentation data; preferably, the display module is a visual display platform or device.

[0063] The processing module is used to perform word segmentation processing on the structured data based on a distributed search engine to obtain multiple word segmentation data related to product quality; the word segmentation data includes a word segmentation name and a first word frequency; for each word segmentation name, a historical rectification plan is retrieved from a plan library, and the word segmentation data and the corresponding historical rectification plan are sent to a display module in a descending order according to the first word frequency for display.

[0064] Further, as a preferred solution, in the clothes drying equipment product pain point analysis device described in this embodiment, the data cleaning performed by the acquisition module specifically includes: deduplication operation, special symbol removal operation, irregular data removal operation, null value removal operation, illegal data removal operation, incoherent semantic removal operation, and completely positive data removal operation.

[0065] Further, as a preferred solution, in the clothes drying equipment product pain point analysis device described in this embodiment, the acquisition module also includes crawler software for acquiring comment data from multiple e-commerce platforms.

[0066] Further, as a preferred solution, in the clothes drying equipment product pain point analysis device described in this embodiment, the step of obtaining the segmentation data is:

[0067] Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data;

[0068] A screening operation is performed on multiple segmentation names to obtain segmentation names related to the product quality of the clothes drying equipment and corresponding first word frequencies to obtain segmentation data.

[0069] The present invention also provides a computer-readable medium storing a computer program, which, when executed by a processor, implements the method for analyzing pain points of clothes drying equipment products according to any of the aforementioned embodiments.

[0070] More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk-read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0071] In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above.

[0072] It is understandable that those skilled in the art can make equivalent substitutions or changes based on the technical solution and inventive concept of the present invention, and all these changes or substitutions should fall within the protection scope of the claims attached to the present invention.

Claims

1. A method for analyzing pain points of clothes drying equipment products, characterized in that: include: Obtain comment data, clean the data in multiple dimensions, and obtain structured data; The dimensions include category, rating, and time; Performing word segmentation processing on the structured data based on a distributed search engine to obtain a plurality of word segmentation data related to product quality; the word segmentation data includes a word segmentation name and a first word frequency; Sorting the plurality of segmented word data from high to low according to the first word frequency, and selecting the first n segmented word data in the sorting as pre-selected segmented words; For each of the pre-selected participles, a number of comment data are selected from the comment data as pre-selected comment data; Extracting the context of the pre-selected word from the pre-selected comment data, and performing negative word screening to obtain a number of pain point words; Performing semantic analysis on the pain point words, integrating pain point words with similar semantics to obtain a pain point phrase; the pain point phrase includes a phrase name and a second word frequency, where the second word frequency is obtained by adding the first word frequencies of pre-selected participles related to each pain point word in the pain point phrase; The pre-selected segmented words corresponding to the pre-selected comment data are integrated with the pain point phrases to obtain product pain points corresponding to the pre-selected segmented words, wherein the product pain points are sorted from high to low according to the second word frequency.

2. The method for analyzing pain points of clothes drying equipment products according to claim 1, characterized in that: The data cleaning includes deduplication operations, special symbol removal operations, irregular data removal operations, null value removal operations, incoherent semantic removal operations, and completely positive data removal operations.

3. The method for analyzing pain points of clothes drying equipment according to claim 1, characterized in that: The review data originates from multiple e-commerce platforms and is obtained from multiple e-commerce platforms through crawler software.

4. The method for analyzing pain points of clothes drying equipment according to claim 1, characterized in that: The steps for obtaining the word segmentation data are as follows: Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data; A screening operation is performed on multiple segmentation names to obtain segmentation names related to the product quality of the clothes drying equipment and corresponding first word frequencies to generate the segmentation data.

5. A pain point analysis device for clothes drying equipment, characterized in that: include: The acquisition module is used to obtain comment data, clean the data in multiple dimensions, and obtain structured data; The dimensions include categories, ratings, natural language reviews, and time; A processing module is used to perform word segmentation processing on the structured data based on a distributed search engine to obtain a plurality of word segmentation data related to product quality; the word segmentation data includes a word segmentation name and a first word frequency; the plurality of word segmentation data are sorted from high to low according to the first word frequency, and the first n word segmentation data in the sorting are selected as pre-selected word segmentations; for each pre-selected word segmentation, a plurality of comment data are selected from the comment data as pre-selected comment data; Extracting the context of the pre-selected word from the pre-selected comment data, and performing negative word screening to obtain a number of pain point words; Performing semantic analysis on the pain point words, integrating pain point words with similar semantics to obtain a pain point phrase; the pain point phrase includes a phrase name and a second word frequency, where the second word frequency is obtained by adding the first word frequencies of pre-selected participles related to each pain point word in the pain point phrase; The pre-selected segmented words corresponding to the pre-selected comment data are integrated with the pain point phrases to obtain product pain points corresponding to the pre-selected segmented words, wherein the product pain points are sorted from high to low according to the second word frequency.

6. The device for analyzing pain points of clothes drying equipment according to claim 5, characterized in that: The data cleaning performed by the acquisition module specifically includes: removing duplicate operations, removing special symbols, removing irregular data operations, removing null value operations, removing illegal data operations, removing incoherent semantic operations, and removing completely positive data operations.

7. The device for analyzing pain points of clothes drying equipment according to claim 5, characterized in that: The steps for obtaining the word segmentation data are as follows: Using the distributed search engine to obtain multiple word segment names and corresponding first word frequencies in the structured data; A screening operation is performed on multiple segmentation names to obtain segmentation names related to the product quality of the clothes drying equipment and corresponding first word frequencies to obtain segmentation data.

8. A computer-readable medium, characterized in that A computer program is stored, and when the computer program is executed by a processor, the method for analyzing pain points of clothes drying equipment products according to any one of claims 1-4 is implemented.

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