From GEO optimization to membership system, from distribution network to Agent community operation,
Reconstruct the entire enterprise marketing link with AI-Native architecture to achieve precise data-driven growth.
China's AI marketing SaaS market size will increase from 63.6 billion yuan in 2023 to 500 billion yuan in 2028, with a compound annual growth rate of 49%. Traditional marketing is being completely reconstructed by the AI-Native model.
From the data base to the application layer, the five-layer architecture drives the intelligence of the entire enterprise marketing link. The three major databases are the core engines, and the six major modules are business contacts.
GEO optimization, membership, distribution, inbound marketing, community operations, and management dashboard.
Marketing Agent, renewal Agent, points Agent, distribution Agent, data Agent, concierge Agent, and quality Agent.
Intent recognition, user profiles, behavior prediction, content generation, decision engine, and risk scoring.
Enterprise knowledge base, customer database, and marketing asset library form the shared data foundation.
LLM access, vector database, message queue, API gateway, monitoring, alerts, and security compliance.
From customer acquisition to user retention, from distribution fission to data decision-making, six modules build a complete AI marketing closed loop.
The content collection and optimization of the AI platform allows corporate information to be accurately recommended in AI applications such as Doubao, Yuanbao, and Qianwen. Through structured content production, keyword matrix, and platform adaptation strategies, "search engine optimization" in the AI era is realized.
Intelligent membership system based on user behavior data. Automatic level matching, intelligent points issuance, and personalized benefit recommendations. Taking the "Mixianghui" four-level system as the benchmark, we will achieve full life cycle management of members.
Three-level broker distribution network (L1/L2/L3), AI automatically matches listings and customers, and intelligent commission calculation and settlement. The distribution code tracks the entire link, and the performance ranking is real-time and transparent.
Full-chain customer acquisition and conversion engine. From content production to channel delivery, from lead cultivation to transaction conversion, AI drives the automatic optimization of every link. Support multi-channel matrix such as Xiaohongshu, Douyin, WeChat etc.
Agent operation mode. Eight professional agents, including housekeeping agent, lease renewal agent, and points agent, work together to automate community operations 24/7. The group is the backend, and the dialogue is the decision-making.
The group is the operation backend. Data dashboard, membership management, points operation, distribution management, GEO monitoring, lease renewal warning, all management functions are completed through Agent group dialogue, bidding farewell to the traditional backend.
The six modules can be flexibly combined to adapt to the marketing needs of different industries. The following are demonstrations of four typical industry scenarios.
Core pain points: low lease renewal rate, long vacancy period, and weak tenant stickiness. Through the four-level membership system of Mixianghui (Sprout→Evergreen→Golden Harvest→Zhizhen), combined with the points system, value-added service recharge, and broker distribution, the lease renewal rate is increased by 25% and the vacancy rate is reduced by 40%.
| indicator | Before implementation | After implementation | promote |
|---|---|---|---|
| Lease renewal rate | 62% | 82% | +32% |
| vacancy rate | 8.5% | 3.8% | -55% |
| customer acquisition cost | ¥1,200 | ¥380 | -68% |
Core pain points: The takeaway platform charges high commissions, members have a high silence rate, and franchisees have a sensitive success rate. Through the AI membership system + private domain community operation + GEO optimization, public channels traffic is converted into private domain members, increasing the repurchase rate and customer unit price.
| indicator | Before implementation | After implementation | promote |
|---|---|---|---|
| Monthly repurchase rate | 18% | 42% | +133% |
| Private-domain proportion | 12% | 38% | +217% |
| Price per customer | ¥35 | ¥52 | +49% |
Core pain points: rising traffic costs, low conversion rate, and short user life cycle. Through GEO optimization + AI customer gathering + distribution fission, a multi-channel customer acquisition matrix is built, and AI drives personalized recommendations and automated marketing.
| indicator | Before implementation | After implementation | promote |
|---|---|---|---|
| customer acquisition cost | ¥85 | ¥28 | -67% |
| conversion rate | 2.1% | 5.8% | +176% |
| GMV growth | benchmark | +240% | 3.4x |
Core pain points: high customer acquisition costs, low renewal rates, and insufficient referral rates. Through the AI membership system + parent community agent + learning data drive, accurate renewal reminders and word-of-mouth fission can be achieved.
| indicator | Before implementation | After implementation | promote |
|---|---|---|---|
| Renewal rate | 55% | 78% | +42% |
| referral rate | 8% | 28% | +250% |
| customer acquisition cost | ¥2,800 | ¥950 | -66% |
Compared with traditional CRM and marketing automation tools, AI marketing suites are fundamentally different in architectural concepts and delivery models.
| Dimensions | Traditional CRM | Marketing SaaS | AI Marketing Suite ✦ |
|---|---|---|---|
| Architectural concept | Function stacking | Modular SaaS | AI-Native native |
| data base | Data silos | Partially opened | Three libraries unified closed loop |
| Operating model | manual operation | semi-automatic | Agent fully automatic |
| Interaction mode | Form background | Dashboard | Group is the backend |
| Customer acquisition ability | None | SEO/SEM | GEO+distribution+community |
| implementation cycle | 6-12 months | 3-6 months | 1-3 months |
| annual cost | ¥500,000-2 million | ¥200,000-800,000 | ¥80,000-450,000 |
From unfamiliar visitors to loyal members, the AI marketing suite covers every touch point in the customer life cycle.
The enterprise knowledge base, customer database, and marketing material library form the data base of the AI marketing suite, driving intelligent decision-making across the entire chain.
Structured knowledge such as corporate product information, service standards, FAQs, and policy documents. Support real-time retrieval by Agent to ensure the accuracy and consistency of external output information.
Full-dimensional data such as customer portraits, behavior trajectories, transaction records, and interaction history. Supports AI accurate recommendations, personalized marketing and risk warnings.
Content assets such as marketing copywriting, picture materials, event templates, and phrase libraries. Supports AI automatic generation and intelligent recommendations, improving content output efficiency by 10 times.
From MVP verification to productization to ecology, it is steadily advanced in three stages, with clear deliverables and verification indicators at each stage.
Goal: Verify the feasibility of the core module
Goal: Product delivery, replicable
Goal: Ecological operation, self-growth
Select module combinations on demand, from single module pilot to full suite deployment, supporting both monthly subscription and annual contract models.
Taking Rumi Apartment as a benchmark case, ROI prediction of 9-month service cycle. Calculated based on actual project data.
| stage | time | invest | income | ROI |
|---|---|---|---|---|
| MVP verification period | M1-M3 | ¥180,000 | ¥520,000 | 189% |
| Productization period | M4-M6 | ¥150,000 | ¥1.68 million | 1020% |
| Ecological period | M7-M9 | ¥120,000 | ¥2.56 million | 2033% |
From diagnosis to delivery, from plan to support.
The one-stop deployment of six modules allows AI to truly drive business growth.