Customer contact relationship evaluation method and system based on multi-feature quantification

Abstract

The invention relates to the technical field of customer relationship management, and discloses a customer contact relationship evaluation method and system based on multi-feature quantization, and the method comprises the following steps: recognizing a plurality of key persons in a customer organization; and carrying out quantitative evaluation on seven types of features of each key person, wherein the seven types of features comprise relationship closeness, scheme recognition degree, price acceptability, one-ticket overbiter, one-ticket approver, report relationship and influence relationship. According to the customer contact relationship evaluation method and system based on multi-feature quantification, a'seven-feature 'quantification model (relationship closeness, scheme recognition degree, price acceptability, one-ticket overtaker, one-ticket approver, report relationship and influence relationship) is created, so that an originally fuzzy and subjective customer relationship judgment standard is converted into a unified and objective numerical index; and subjective judgment which varies from person to person is eliminated, so that the customer relationship state becomes measurable, comparable and traceable, and a data foundation is laid for fine management.

Description

Technical Field

[0001] This invention relates to the field of customer relationship management technology, specifically to a method and system for evaluating customer social networks based on multi-feature quantification. Background Technology

[0002] In the existing fields of Customer Relationship Management (CRM) and Sales Decision Support, enterprises rely heavily on sales staff's personal experience, subjective judgment, and scattered notes to assess customer relationships. This approach is highly non-standardized, difficult to scale and pass on, leading to biases in judging key customer decision chains, delayed risk insights, and an inability to effectively quantify and continuously track the health of customer relationships. Although some advanced CRM systems attempt to improve this by recording contact frequency and business opportunity stages, they are essentially still records of "activities" rather than in-depth "quantitative analysis" of customer attitudes, decision-making influence, and internal relationship networks. They fail to build a scientific, systematic, and calculable relationship assessment model and cannot gain a macro-level insight into the overall attitudes of the entire decision chain or the customer organization.

[0003] In recent years, while some solutions have proposed using data analysis to assess customer value, most have been limited to historical analysis of transaction data, lacking a forward-looking, multi-faceted, and dynamic quantification of the human factor in the decision-making process. In particular, existing technologies lack effective means to identify, quantify, and utilize key competitive factors such as "veto power," "internal influence," and "private network value." This makes it difficult for companies to accurately allocate resources, formulate effective strategies, and maximize the potential of employee networks in complex sales projects, ultimately impacting the probability of winning deals and improving customer loyalty. Summary of the Invention

[0004] To address the problems mentioned in the background section, this invention provides the following technical solution: a customer network relationship assessment method based on multi-feature quantification, comprising the following steps:

[0005] Identify multiple key individuals within the client's organization;

[0006] Each key person is quantitatively evaluated based on seven categories of characteristics, including: relationship closeness, acceptance of the plan, price acceptance, veto power, approval power, reporting relationship, and influence relationship.

[0007] Based on the quantitative results of the seven types of characteristics, the analysis is carried out from four main lines: customers, decision-making chain, key people and influence.

[0008] Based on the analysis results of the four main lines, a visual report is generated from four perspectives: individual, team, our company, and competitors.

[0009] The report can guide customer relationship management, business opportunity incubation, or project decision-making.

[0010] Preferably, the quantitative values ​​of the relationship tightness, scheme acceptance and price acceptance range from -1 to 100, where -1 represents unknown, 0 represents strong opposition, 25 represents opposition, 50 represents neutrality, 75 represents support / approval / acceptance and 100 represents strong support / approval / acceptance.

[0011] Preferably, the quantified values ​​of the veto person and the approver are -1, 0, and 1, respectively, where -1 indicates unknown, 0 indicates that the attribute is not present, and 1 indicates that the attribute is present.

[0012] Preferably, the reporting relationship value is the direct superior of the key person; the influence relationship includes internal influence and external influence, the internal influence value is the customer's internal employees, and the external influence value is our company's or competitors' employees.

[0013] Preferably, it also includes a step of quantitative analysis of the decision chain, specifically including:

[0014] Calculate the average relationship tightness, average solution acceptance, and average price acceptance of all key individuals in the decision-making chain;

[0015] The average value is divided into four levels: poor, average, good, and excellent, based on a preset threshold.

[0016] Preferably, the grading standard for the average value is as follows:

[0017] The difference is greater than -1 and less than or equal to 40.

[0018] A score greater than 40 and less than or equal to 60 is considered average.

[0019] A score greater than 60 and less than or equal to 80 is considered good;

[0020] A score greater than 80 is excellent.

[0021] Preferably, it also includes a step of quantitative analysis of the customer relationship graph, specifically including:

[0022] Calculate the average relationship strength, average solution acceptance, and average price acceptance of all key individuals within the client organization;

[0023] The average value is divided into four levels: poor, average, good, and excellent, based on a preset threshold.

[0024] Preferably, it also includes a step of quantitative analysis of employees' private networks, specifically including:

[0025] Identify key customer contacts that employees can deeply influence, and build a subset of private networks;

[0026] Calculate the potential value of employee influence and the contribution of employee influence;

[0027] The potential value of an employee's influence is measured by the proportion of their private network to their public network.

[0028] The contribution of employee influence is measured by the proportion of projects or amounts won by leveraging employee influence.

[0029] A customer network relationship assessment system based on multi-feature quantification includes:

[0030] Key Person Identification Module: Used to identify key personnel within the client's organization;

[0031] The feature quantification module is used to quantify and evaluate seven types of features for each key person.

[0032] The main line analysis module is used to analyze from four main lines: customers, decision chain, key people and influence.

[0033] The perspective generation module is used to generate visual reports from four perspectives: individual, team, our company, and competitors.

[0034] The decision support module is used to output customer management or project decision recommendations based on reports.

[0035] Preferably, the decision chain quantification module is used to calculate and evaluate the average characteristic value of key individuals in the decision chain;

[0036] The customer relationship quantification module is used to calculate and evaluate the average characteristic values ​​of key personnel in a customer's organization;

[0037] The Private Domain Connections Quantification Module is used to identify and evaluate the value potential and contribution of an employee's private domain connections.

[0038] Compared with existing technologies, this invention provides a method and system for evaluating customer social networks based on multi-feature quantification, which has the following beneficial effects:

[0039] 1. This customer relationship assessment method and system based on multi-feature quantification transforms the originally vague and subjective customer relationship evaluation criteria into unified and objective numerical indicators by creating a "seven-feature" quantitative model (relationship closeness, solution acceptance, price acceptance, veto person, approval person, reporting relationship, and influence relationship). This eliminates subjective judgments that vary from person to person, making the customer relationship status measurable, comparable, and traceable, thus laying a data foundation for refined management.

[0040] 2. This customer relationship assessment method and system, based on multi-feature quantification, utilizes an analytical framework of "four main lines" (customer, decision-making chain, key personnel, and influence) and "four perspectives" (individual, team, our company, and competitors) to provide a comprehensive understanding of customer dynamics from micro to macro and from internal to external perspectives. This method not only analyzes the attitudes of individual key personnel but also comprehensively assesses the overall inclinations of the entire decision-making chain or customer organization, accurately identifying supporters, opponents, and wavers, and inferring competitive dynamics. This provides unprecedented data support for developing differentiated and highly precise operational strategies.

[0041] 3. This customer relationship assessment method and system, based on multi-feature quantification, can identify critical risks and key breakthroughs in projects in advance by clearly identifying and quantifying "veto persons" and "approvers," allowing for timely intervention. Simultaneously, continuous monitoring of the overall health of customer relationships helps to discover and proactively incubate potential business opportunities, transforming passive response into proactive management, significantly improving project win rates and customer lifetime value.

[0042] 4. This multi-feature quantification-based customer network assessment method and system, by distinguishing between "public networks" and "private networks" and designing two major indicators—"employee influence value potential" and "employee influence contribution"—transforms, for the first time, the customer network resources held by individual employees, which are difficult to quantify, into manageable and assessable strategic assets for the enterprise. This incentivizes employees to share network resources and provides a scientific basis for optimizing resource allocation and leveraging collective strengths, greatly enhancing the organization's overall sales combat effectiveness.

[0043] 5. This customer relationship assessment method and system, based on multi-feature quantification, integrates with existing CRM, ERP, and other systems to achieve automatic data collection and interaction, avoiding information silos. Its automated calculation, visualization, and early warning functions greatly reduce the analytical burden on managers and improve the efficiency and scientific rigor of customer relationship management and sales decisions. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the customer network quantification model design of the present invention;

[0045] Figure 2 This is a schematic diagram illustrating the relationship between private and public networks in this invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figure 1-2 This invention provides a method and system for evaluating customer relationships based on multi-feature quantification. Its core lies in transforming subjective and ambiguous customer relationships into objective and quantifiable data through a structured model and algorithm, thereby providing precise data support for enterprise customer management, sales decisions, and resource allocation. The invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0048] Example 1: A Customer Network Relationship Assessment Method Based on Multi-Feature Quantification

[0049] The process of this method mainly includes three stages: data collection and quantification, multi-mainline analysis, and multi-perspective presentation. Figure 1 The diagram shows the design framework of the customer network quantification model, which constitutes the theoretical basis for the implementation of this method.

[0050] S1: Key Personnel Identification and Data Collection

[0051] First, the system integrates data with enterprise CRM (Customer Relationship Management) systems, ERP (Enterprise Resource Planning) systems, or manual data entry by sales personnel to identify all key individuals in the decision-making chain of target customers or target projects. Key individuals may include decision-makers, users, influencers, technology evaluators, purchasers, and other roles on the customer's side.

[0052] S2: Seven-Feature Quantitative Assessment

[0053] For each identified key individual, based on their historical interactions with our company, latest communication records, project participation, and other information, seven core characteristics are quantified through either automatic system scoring or manual sales evaluation. The quantification method is as follows:

[0054] 1. Quantification of Attitude Features:

[0055] Relationship Closeness: Assess the overall relationship between this key person and our company. For example, frequent technical exchanges and clear expressions of support can be rated 100 (Strong Support); willingness to receive but ambiguous attitude can be rated 50 (Neutral); explicit expressions of dissatisfaction can be rated 25 (Oppose). Initial status or indeterminate status is recorded as -1 (Unknown).

[0056] Solution Approval Rating: This rating is quantified based on the key person's evaluation of our product's technical solution. For example, excellent performance in testing and praise from the key person earns a rating of 100; some suggestions for improvement but overall positive feedback earns a rating of 75; and explicitly stating that the solution does not meet the key person's needs earns a rating of 25.

[0057] Price Acceptability: Assess the key person's attitude towards our quote. For example, a score of 100 is given for explicitly stating that the price is within budget and reasonable; a score of 75 is given for considering the price too high but still acceptable; and a score of 0 is given for strongly questioning the price and deeming it unacceptable.

[0058] 2. Importance feature quantification:

[0059] Veto power: Determined based on the client's organizational structure and decision-making processes. For example, the client's CFO typically has veto power over budget approvals; in this project, this veto power should be quantified as 1. Non-core members of the decision-making chain are quantified as 0.

[0060] One vote approver: Determines who has the final say. For example, the CEO or the project's top leader might be quantified as 1.

[0061] 3. Relationship-based feature quantification:

[0062] Reporting relationships: Obtained directly from the client's organizational chart, using the name or ID of the key person's direct superior as its value to construct a decision chain graph.

[0063] Influence Relationships: This field identifies who can significantly influence the decision-making of this key individual through research and analysis. For example, a technical expert (internal influence) or a senior consultant from our company (external influence) might be entered in this field. The system supports multiple names and allows differentiation of the source of influence (internal / external, our company / competitors).

[0064] S3: Quantitative Analysis of Decision Chain

[0065] On a project-by-project basis, aggregate quantitative data of all identified key individuals in the decision-making chain for overall evaluation:

[0066] Calculate the average relationship strength as follows: ∑ Relationship strength of each key person / Number of key people.

[0067] Calculate the average approval rating of the solution = ∑ approval rating of each key person / number of key people.

[0068] Calculate the average price acceptance rate as: ∑ Price acceptance rate per key person / Number of key people.

[0069] The system compares the calculated average value with preset thresholds [40, 60, 80] and automatically generates a rating of "poor, average, good, excellent". The system can visually display the attitude tendencies of the entire decision-making chain. For example, if the "average solution acceptance" is "excellent" but the "average price acceptance" is "poor", the system will prompt "value delivery and price negotiation need to be strengthened".

[0070] S4: Quantitative Analysis of Customer Relationships

[0071] By aggregating quantitative data on all key individuals within a single client, the system calculates average relationship tightness, average solution acceptance, and average price acceptance, and assigns a rating accordingly. This analysis helps assess the overall health of the client's relationships, identify weaknesses, and inform long-term client relationship strategic planning.

[0072] S5: Quantitative Analysis of Private Domain Connections

[0073] like Figure 2 As shown, the system identifies a subset of public contacts (all key customer contacts) that can be deeply influenced by company employees (especially non-sales positions such as product managers, delivery engineers, and executives), and defines them as private contacts.

[0074] Calculate the employee's influence value potential: Number of key clients influenced by the employee / Total number of key clients for that client. This metric measures the breadth and depth of the employee's network.

[0075] Calculate employee influence contribution: This metric calculates the percentage of successful deals that leveraged the employee's influence (by number of projects or monetary value). This measure reflects the actual business value of the employee's network.

[0076] S6: Multi-perspective visualization and report generation

[0077] Based on the above quantitative results, the system generates dynamic and visual analysis dashboards from four perspectives:

[0078] Personal perspective: Focusing on a single key person's seven-characteristic radar chart and influence relationship diagram.

[0079] Team perspective: Show the attitude distribution of the entire decision-making chain or the client team, and analyze the support / opposition camps.

[0080] Our company's perspective: A comprehensive presentation of our company's overall strengths, weaknesses, risks, and opportunities in this client or project.

[0081] Competitor Perspective: Based on the information obtained (such as frequent interactions between a key person and a competitor), infer and demonstrate the competitor's potential sphere of influence and competitive position.

[0082] Finally, based on the analysis results, the system automatically generates action suggestions, such as: "It is recommended to make a high-level visit to Zhang San (veto person, relationship closeness: 25) to improve the relationship"; "Li Si (technology influencer, solution approval rate: 100) can serve as our internal advocate (Coach)".

[0083] Example 2: Customer Network Relationship Assessment System Based on Multi-Feature Quantification

[0084] This system is used to implement the above methods, and its hardware foundation includes servers, databases, network equipment, and user terminals. The system's software logic mainly includes the following modules:

[0085] Data Acquisition and Integration Module: Extracts customer and contact data from systems such as CRM and ERP via API interface, and provides a manual data entry interface.

[0086] Key Person Identification and Feature Quantification Module: This is the core module, providing a UI interface for users to score key persons based on seven features and store the quantification results.

[0087] Model calculation engine module: responsible for executing all core algorithms such as average calculation, level determination, and private domain network indicator calculation.

[0088] Analysis and Visualization Module: Responsible for generating decision chain graphs, customer relationship health dashboards, private domain network value reports, and four-perspective analysis dashboards.

[0089] Decision support and early warning module: Based on preset rules (such as finding that the relationship closeness of a veto person is "oppose"), send early warning prompts and action suggestions to relevant responsible persons.

[0090] Through the specific implementation methods described above, this invention transforms abstract customer relationship management into an executable, measurable, and optimizable data-driven process, greatly improving the refinement and scientific level of enterprise customer management.

[0091] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A customer network relationship assessment method based on multi-feature quantification, characterized in that, Includes the following steps: Identify multiple key individuals within the client's organization; Each key person is quantitatively evaluated based on seven categories of characteristics, including: relationship closeness, acceptance of the plan, price acceptance, veto power, approval power, reporting relationship, and influence relationship. Based on the quantitative results of the seven types of characteristics, the analysis is carried out from four main lines: customers, decision-making chain, key people and influence. Based on the analysis results of the four main lines, a visual report is generated from four perspectives: individual, team, our company, and competitors. The report can guide customer relationship management, business opportunity incubation, or project decision-making.

2. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, The quantitative values ​​for the closeness of the relationship, the acceptance of the proposal, and the price acceptance range from -1 to 100, where -1 indicates unknown, 0 indicates strong opposition, 25 indicates opposition, 50 indicates neutrality, 75 indicates support / approval / acceptance, and 100 indicates strong support / approval / acceptance.

3. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, The quantified values ​​for the veto person and the approver are -1, 0, and 1, respectively, where -1 indicates unknown, 0 indicates that the attribute is not present, and 1 indicates that the attribute is present.

4. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, The reporting relationship value is the direct superior of the key person; the influence relationship includes internal influence and external influence, the internal influence value is the customer's internal employees, and the external influence value is our company's or competitors' employees.

5. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, It also includes the step of quantitative analysis of the decision chain, specifically including: Calculate the average relationship tightness, average solution acceptance, and average price acceptance of all key individuals in the decision-making chain; The average value is divided into four levels: poor, average, good, and excellent, based on a preset threshold.

6. The customer network relationship evaluation method based on multi-feature quantification according to claim 5, characterized in that, The grading criteria for the average value are as follows: The difference is greater than -1 and less than or equal to 40. A score greater than 40 and less than or equal to 60 is considered average. A score greater than 60 and less than or equal to 80 is considered good; A score greater than 80 is excellent.

7. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, It also includes the step of quantitative analysis of the customer relationship graph, specifically including: Calculate the average relationship strength, average solution acceptance, and average price acceptance of all key individuals within the client organization; The average value is divided into four levels: poor, average, good, and excellent, based on a preset threshold.

8. The customer network relationship evaluation method based on multi-feature quantification according to claim 1, characterized in that, It also includes steps for quantitative analysis of employees' private networks, specifically including: Identify key customer contacts that employees can deeply influence, and build a subset of private networks; Calculate the potential value of employee influence and the contribution of employee influence; The potential value of an employee's influence is measured by the proportion of their private network to their public network. The contribution of employee influence is measured by the proportion of projects or amounts won by leveraging employee influence.

9. A customer network relationship evaluation system based on multi-feature quantification, characterized in that, include: Key Person Identification Module: Used to identify key personnel within the client's organization; The feature quantification module is used to quantify and evaluate seven types of features for each key person. The main line analysis module is used to analyze from four main lines: customers, decision chain, key people and influence. The perspective generation module is used to generate visual reports from four perspectives: individual, team, our company, and competitors. The decision support module is used to output customer management or project decision recommendations based on reports.

10. A customer network relationship evaluation system based on multi-feature quantification according to claim 9, characterized in that, Also includes: The decision chain quantification module is used to calculate and evaluate the average characteristic values ​​of key individuals in the decision chain; The customer relationship quantification module is used to calculate and evaluate the average characteristic values ​​of key personnel in a customer's organization; The Private Domain Connections Quantification Module is used to identify and evaluate the value potential and contribution of an employee's private domain connections.

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