Artificial Intelligence Proactive Business Growth System
Patent Information
- Authority / Receiving Office
- TW · TW
- Patent Type
- Utility models
- Current Assignee / Owner
- 曾慧玉
- Filing Date
- 2026-05-28
- Publication Date
- 2026-08-01
Smart Images
Figure 00000000_0000_ABST
Abstract
Claims
1. An AI-driven proactive business growth system, comprising: an electronic information device; and a server platform connected to the electronic information device, wherein the electronic information device performs data input, command triggering, and result reception; wherein, The server platform includes: an external intelligence database for storing and updating market intelligence data from external sources, including at least industry trend data, customer behavior data, competitor information, and purchase intent data, connected to the electronic device to receive data input; an internal enterprise database for storing internal operational data, including at least product knowledge data, customer relationship management data, transaction record data, and service history data, connected to the electronic device; an AI-powered market focusing and strategic customer acquisition analysis module connected to the external intelligence database and the internal enterprise database to integrate internal and external data and perform market analysis to generate ideal customer profiles (ICPs) and target market positioning results; and an AI-powered automated customer list search module connected to the AI-powered market focusing and strategic customer acquisition analysis module to automatically search for and generate global customer lists based on the ideal customer profile, forming sales funnel input data. An AI-powered decision chain insight and cross-platform interaction module, connected to the AI-powered automated customer list search module, analyzes the decision chain structure within a customer's organization and performs automated interaction, message delivery, and interaction record capture through multiple communication platforms. An AI-powered opportunity screening and dynamic status management module, connected to the AI-powered decision chain insight and cross-platform interaction module, screens, scores, and updates the status of opportunities based on interaction data and multi-dimensional evaluation indicators, generating opportunity priority ranking results. An AI-powered negotiation and sales empowerment module, connected to the AI-powered opportunity screening and dynamic status management module, automatically generates sales scripts, proposal content, competitor strategies, and pricing or contract documents based on opportunity status. It also includes a business management visualization and intelligent inheritance central module, which establishes bidirectional data transmission connections with the AI market focusing and strategic customer acquisition analysis module, the AI automatic customer list search module, the AI decision chain insight and cross-platform interaction module, the AI opportunity screening and dynamic status control module, and the AI negotiation and sales empowerment module, respectively, to receive the operating status information of each module and perform analysis, monitoring and control command feedback to drive the dynamic adjustment of each module.
2. The AI-driven proactive business growth system as described in claim 1, wherein, This AI-powered opportunity screening and dynamic status management module includes an FSQL (Fit Score & Qualification Logic) scoring mechanism. This mechanism quantifies and scores potential customers based on multiple opportunity evaluation characteristics. The scoring mechanism integrates and analyzes multiple dimensions of characteristics, including customer interaction behavior data, decision chain completeness, purchase intent signals, budget matching degree, competitive pressure, project progress momentum, and performance risk. It also dynamically adjusts the weight of each characteristic based on historical transaction data to generate opportunity maturity scores and priority ranking results, thereby improving the accuracy and predictive ability of opportunity screening.
3. The AI-driven proactive business growth system as described in claim 2, wherein, The FSQL (Fit Score & Qualification Logic) scoring mechanism further includes a dynamic weighting learning mechanism to automatically adjust the weights of each evaluation feature based on the transaction results of historical business opportunity data. The historical business opportunity data includes at least the interaction records of completed and uncompleted cases, business opportunity scoring results, and final result labels. The dynamic weighting learning mechanism trains and updates this data through machine learning algorithms, so that the weights of each feature are adaptively adjusted according to different industries, sales stages, or customer types, thereby improving the predictive accuracy of business opportunity scoring.
4. The AI-driven proactive business growth system as described in claim 1, wherein, Further, an event-triggered feedback mechanism is included, which is set between the AI decision chain insight and cross-platform interaction module, the AI opportunity screening and dynamic status control module, and the AI negotiation and sales empowerment module, and forms a two-way data feedback connection with the AI market focusing and strategic customer acquisition analysis module. The event-triggered feedback mechanism is used to monitor and identify abnormal events or key status changes that occur during customer interaction, opportunity evaluation, or sales negotiation. These abnormal events include at least one of the following: decision-maker changes, interaction interruption, weakening purchase intention, abnormal budget conditions, competitive intervention, or project progress stagnation. When such abnormal events are detected, the event-triggered feedback mechanism will send the corresponding event data and status information back to the AI market focusing and strategic customer acquisition analysis module to re-execute market focusing analysis, revise the ideal customer profile (ICP), or reconstruct customer acquisition strategies, and drive the dynamic adjustment of subsequent modules, so that the overall system forms an event-driven closed-loop adaptive control architecture.
5. The AI-driven proactive business growth system as described in claim 1, wherein, This AI-powered negotiation and sales empowerment module further includes a Battlecard generation mechanism. This mechanism uses correlation analysis and strategy deduction based on customer characteristics data of business opportunities, competitor information, historical transaction case data, and strategy knowledge base to automatically generate a Battlecard strategy data set. This Battlecard strategy data set includes at least the results of comparative analysis of the advantages and disadvantages of competing products, differentiated value proposition content, suggestions for responding to customer objections and risks, pricing strategy configuration schemes, and negotiation script template components. It can be dynamically updated and adjusted based on real-time interaction records and changes in business opportunity status, so that sales personnel or AI agents can call upon it in real time during sales interactions or negotiations, forming a situation-adaptive sales Battlecard support mechanism.
6. The AI-driven proactive business growth system as described in claim 1, wherein, The AI-powered business opportunity screening and dynamic status control module further includes a sales funnel health assessment mechanism to score a business opportunity from multiple dimensions. This assessment mechanism is based on a weighted integration of multiple characteristic indicators to generate a business opportunity health score. These multiple characteristic indicators include at least: customer interaction frequency and quality indicators, reflecting the frequency, depth, and abnormal interaction states; decision chain integrity indicators, assessing the coverage of decision-making levels within the customer's organization and stakeholder participation; and external purchasing intent and demand alignment indicators. The indicators are: 1) To determine the customer's purchasing intention and the degree of match between their needs and the product / service; 2) To assess the compatibility between the customer's budget and the transaction terms; 3) To reflect the degree of competitor involvement and the competitive landscape; 4) To assess the speed of business opportunity development and any stagnation; and 5) To assess the performance risk and legal disputes during contract negotiation. Each indicator is assigned a weight according to its importance, and the overall health score of the business opportunity is calculated accordingly.
7. The AI-driven proactive business growth system as described in claim 6, wherein, The weights of each characteristic indicator are dynamically adjusted based on the sales stage of the business opportunity and historical transaction results, so that the evaluation mechanism can self-optimize over time and improve the accuracy of business opportunity evaluation.
8. The AI-driven proactive business growth system as described in claim 6, wherein, Each of these characteristic indicators is quantified based on at least one behavioral event or data condition, including: the customer interaction frequency and quality indicator is determined based on customer response frequency, interaction interval, dialogue content depth, and the ratio of interaction between the two parties; the decision-making chain integrity indicator is determined based on the corresponding job level, the degree of participation of decision-makers, and the participation status of multiple stakeholders; the external purchase intention and demand alignment indicator is determined based on customer behavior trajectory, intention signals, and the degree of demand disclosure; the budget and business conditions matching indicator is determined based on customer budget information, payment terms, and price sensitivity; the competitive pressure indicator is determined based on the number of competitors, their level of participation, and comparative behavior; the project timeline and progress momentum indicator is determined based on the project dwell time, the completion status of progress nodes, and changes in the expected transaction time; and the performance risk and legal friction indicator is determined based on the number of contract negotiations, the frequency of clause modification, and the degree of dispute over performance conditions.
9. The AI-driven proactive business growth system as described in claim 6, wherein, The business opportunity health score is further used to control the operation of the sales process, including: when the score is below a preset threshold, an automatic follow-up mechanism is triggered or business resources are reallocated; when the score shows an abnormal decline, an event feedback mechanism is triggered to re-execute market focus and strategy analysis; when the score is above a preset threshold, the business opportunity is prioritized for negotiation or transaction processing.