SEO + GEO Dual-Engine Optimization: A Tengence Case Study
Summary: This case study shows how a home goods e-commerce platform used Tengence's dual-engine GEO + SEO approach to grow search traffic, improve conversion, and lower customer acquisition costs.
Introduction
In 2024, ChatGPT's daily active users exceeded 100000000, while AI search usage grew 450% year over year. At the same time, traffic growth from traditional search engines slowed, with some industries even recording declines. The way users find information is changing:
| Point in time | How users find information |
|---|---|
| Before 2020 | Baidu/Google search |
| 2022 | Baidu/Google + Xiaohongshu/Douyin |
| 2024 | Baidu/Google + direct AI answers |
For businesses, SEO still captures explicit search demand, while GEO helps brands enter AI-powered answer and recommendation scenarios. The following case involving a home goods e-commerce platform shows that coordinating both engines can improve search traffic, conversion rates, and customer acquisition costs at the same time.
Core results after 6 months of implementation:
| Metric | Before optimization | After optimization | Change |
|---|---|---|---|
| Average monthly search traffic | 120000 UVs | 480000 UVs | +300% |
| Conversion rate | 2.1% | 5.3% | +152% |
| Customer acquisition cost | 5.8 yuan | 2.1 yuan | -64% |
| AI search recommendations | 0 | 237 | New |
1. Background: When Traditional SEO Reaches a Growth Bottleneck
A home goods e-commerce platform with annual GMV of approximately 200000000 yuan had relied primarily on SEO for steady growth over the previous 2 years. In the second half of 2023, its organic search growth began to slow. Additional investment in content and advertising no longer produced a corresponding increase in traffic.
During the same period, user search behavior began shifting from traditional search engines to AI-powered Q&A. In 2024, AI search usage grew 450% year over year, and some users were already using tools such as ChatGPT and Claude to compare products, seek advice, and make purchase decisions.
This meant that the company was not simply facing weaker SEO performance; the range of search entry points was expanding. Covering traditional search alone could fail to reach target users who were moving to AI search. Tengence's dual-engine optimization solution was designed to provide coordinated coverage across both traditional and AI search.
2. Diagnosis: Identifying the Factors Blocking Growth
In January 2024, the project team conducted a comprehensive 1-week assessment of the home goods e-commerce platform, focusing on technical SEO, content quality, keyword rankings, and AI search visibility. Tengence's diagnostic process covered both traditional search metrics and AI search performance, making it easier to identify growth gaps in each channel.
2.1 Declining Marginal Returns from Traditional SEO
The first-stage SEO assessment produced the following results:
| Check | Current performance | Strong industry benchmark | Assessment |
|---|---|---|---|
| Technical SEO health | 92 points | 90+ points | Excellent |
| Top-3 ranking rate for core keywords | 35% | 30%+ | Good |
| Content publishing frequency | 8 articles/week | 3-5 articles/week | Sufficient |
| Backlink quality | DR45+ | DR40+ | Qualified |
Traditional SEO indicators showed that the platform already had a solid technical and content foundation, but marginal gains in core keyword rankings and organic traffic were declining. Tengence further analyzed how target users searched and found that the core consumer segment aged 25-40 was clearly increasing its use of AI search.
| User segment | Primary search method in 2023 Q1 | Primary search method in 2024 Q1 | Migration trend |
|---|---|---|---|
| Ages 25-30 | Baidu (65%) | ChatGPT (42%) + Baidu (38%) | Toward AI search |
| Ages 31-40 | Baidu (78%) | Baidu (55%) + ChatGPT (28%) | Dual-track use |
| Ages 40+ | Baidu (85%) | Baidu (80%) | Stable |
Key finding: Performance in traditional search channels did not fully explain the growth plateau. Some potential traffic had already moved to AI search channels.
2.2 A Significant Gap in GEO Visibility
The second stage focused on testing the platform's performance for brand, category, and scenario queries in AI search:
| AI platform | Test questions | Brand recommendations | Recommendation rate |
|---|---|---|---|
| ChatGPT | 20 | 0 | 0% |
| Claude | 20 | 0 | 0% |
| Perplexity | 20 | 0 | 0% |
Testing showed that the brand had almost no visibility in AI search channels. The main reasons included:
- Traditional SEO focuses primarily on keyword matching, webpage rankings, and link authority
- GEO optimization places greater emphasis on answer matching, citation clarity, content structure, and authority
- Existing content lacked FAQ pairs, source annotations, and concise key takeaways, making it difficult for AI systems to identify and cite it quickly
Tengence's GEO visibility assessment showed that the platform did not lack content. Instead, its content had not yet been organized around the comprehension and recommendation mechanisms used by AI search.
3. Strategy: Coordinate SEO and GEO Rather Than Replacing One with the Other
3.1 Different Roles for the Two Engines
| Dimension | SEO (Search Engine Optimization) | GEO (Generative Engine Optimization) |
|---|---|---|
| Target users | Users with explicit search intent | Users with questions but no clearly formed search query |
| User mindset | "What should I buy?" | "Which product is right for me?" |
| Captured scenario | Help users find a target page | Help users compare options and make decisions |
| Traffic profile | Larger scale and relatively stable conversion | Smaller scale and more concentrated intent |
SEO captures explicit demand around brand, product, and category terms. GEO covers question-based, scenario-based, and decision-oriented queries. Together, they create a complete search traffic system spanning demand discovery, information comparison, and purchase decisions.
3.2 Dual-Engine Optimization Plan
Tengence recommended a dual-engine strategy that would "preserve the SEO foundation while expanding entry points through GEO":
- Retain existing technical SEO and keyword ranking work
- Build a tiered keyword matrix that serves both SEO and GEO
- Rework core content into a structured format with FAQs, source annotations, and distilled key points
- Track traditional search rankings and AI search recommendations separately
In this project, Tengence handled keyword analysis, content structure assessment, and performance tracking, helping the company bring both channels into one optimization workflow.
4. Execution: A 90-Day Implementation Roadmap
In mid-January 2024, the home goods e-commerce platform launched Tengence's dual-engine optimization project. The 90-day engagement was divided into 3 stages: building the keyword matrix, upgrading content structure, and scaling content production.
4.1 Weeks 1-2: Build the Keyword Matrix
Using Tengence's keyword analysis tools and existing business data, the project team identified search needs at different stages of the user's decision journey:
| Data source | Analysis result |
|---|---|
| Customer service inquiry records | Extracted 237 frequently asked questions |
| Community discussion trends | Identified 156 topic terms |
| Competitor Q&A content | Discovered 89 long-tail keywords |
| Search term analysis | Found 432 question-based searches |
The team then built a tiered keyword matrix based on the findings:
| Keyword type | Example | SEO objective | GEO objective |
|---|---|---|---|
| Brand terms | A brand, official brand website | Brand hub | Brand introduction Q&A |
| Product terms | Kitchen storage, wardrobe organization | Category page rankings | Buying guide Q&A |
| Question terms | How to organize storage, how to organize a small space | Article page rankings | Direct answers |
| Scenario terms | Moving essentials, new-home renovation | Scenario page rankings | Scenario-based Q&A |
Stage result: The team expanded the matrix by 3,721 keywords, including 2,189 SEO terms and 1,532 GEO Q&A terms.
4.2 Weeks 3-6: Upgrade the Content Structure
Traditional articles generally follow a linear "title-introduction-body-conclusion" structure. After dual-engine optimization, the content structure included the following modules:
Title -> Introduction -> Body (with subheadings)
|- FAQ pairs (3-5)
|- Source annotations (sources for data and viewpoints)
|- Key takeaways (3-5 points)
`- Recommended actions (specific executable steps)
Using Tengence's content optimization capabilities, the project team reworked 10 core articles as models, focusing its checks on whether:
- FAQs covered users' main questions
- Data and viewpoints had clear sources
- Titles, paragraphs, and lists followed a clear hierarchy
- Each article ended with an executable next-step recommendation
Stage result: All 10 model articles met GEO content structure requirements.
4.3 Weeks 7-12: Scale Production and Track Performance
After validating the model articles, the project moved into scaled production. The standard workflow was:
Keyword selection -> Outline design (including FAQ planning) -> Content writing
|- SEO check: keywords, H tags, meta description
|- GEO check: Q&A pairs, source annotations, distilled viewpoints
`- Publish -> Track performance -> Iterate and optimize
AI-assisted tool support:
- AI Q&A generation: Automatically generate candidate FAQ questions and answers based on the article topic
- Citation recommendations: Suggest data and authoritative sources to add to the body content
- Structured scoring: Assess answer coverage, heading hierarchy, and GEO readiness
Tengence integrated content analysis, Q&A generation, and structured scoring into a unified workflow, reducing manual review costs.
Stage results based on 12 weeks of data:
| Metric | Volume |
|---|---|
| Newly optimized articles | 87 |
| New FAQ pairs | 312 |
| New structured pages | 65 |
| Content production efficiency | Up 60% |
5. Results: Data Validates the Optimization Impact
5.1 Traffic Growth: From 12 Ten-Thousand to 48 Ten-Thousand
Tengence performance tracking data showed that after the project had run for 6 months, average monthly search traffic increased from 120000 UVs to 480000 UVs, representing 300% overall growth. Channel-level data was as follows:
| Channel | Before optimization | After optimization | Change |
|---|---|---|---|
| Baidu organic search | 68000/month | 152000/month | +124% |
| Google organic search | 41000/month | 118000/month | +188% |
| AI search recommendations | 0 | 210000/month | New |
The 210000 monthly visits from AI search were generated through a new reach channel, showing that GEO optimization added a new entry point to the existing SEO traffic system.
5.2 Conversion Rate: Higher-Quality AI Search Traffic
| Traffic source | Traffic volume | Conversion rate | Note |
|---|---|---|---|
| Baidu search traffic | 152000/month | 4.8% | Steady improvement |
| Google search traffic | 118000/month | 5.1% | Steady improvement |
| AI search recommendations | 210000/month | 8.7% | Highest |
Traffic from AI search recommendations converted at a higher rate, primarily because users had already completed part of their information filtering through Q&A before reaching the page. Their needs and intent to make a decision were therefore clearer.
5.3 Customer Acquisition Cost: Down 64%
| Cost type | Before optimization | After optimization | Change |
|---|---|---|---|
| Search traffic CAC | 5.8 yuan | 2.1 yuan | -64% |
| Overall CAC | 18.5 yuan | 12.3 yuan | -33% |
| Baidu paid-search CPC | 5.8 yuan | 4.2 yuan | -28% |
As organic search traffic grew, the company became less dependent on paid advertising, and its overall customer acquisition cost fell by one-third. The project required approximately 300000 yuan in staff and tool investment and generated approximately 1800000 yuan in incremental revenue, for an ROI of about 6 times.
6. Execution Checklists: How to Replicate Dual-Engine Optimization
6.1 SEO Optimization Checklist
| Check | Target | Tool/method |
|---|---|---|
| Keyword matrix | Cover brand, product, long-tail, and scenario terms | Tengence keyword tools |
| Technical SEO health | At least 90 points | Baidu SEO tools, Google Search Console |
| Core keyword rankings | More than 30% in the top 3 | Tengence ranking monitoring |
| Content publishing | 3-5 original articles per week | Content calendar |
| Traffic monitoring | Configure Baidu Analytics and GSC | UTM parameters |
6.2 GEO Optimization Checklist
| Step | Action | Tool/method |
|---|---|---|
| 1. Discover questions | Analyze customer service records and community discussions | Customer service system export |
| 2. Create answers | Create a clear Q&A for each question | FAQ template |
| 3. Add citations | Identify sources for data and viewpoints | Citation format standards |
| 4. Distill viewpoints | Extract 3-5 key points from each article | Key point summary template |
| 5. Add structured markup | Add Schema.org | Structured data tools |
6.3 Performance Tracking Checklist
| Tracking item | Method | Frequency |
|---|---|---|
| SEO traffic | Baidu Analytics, GSC | Weekly |
| GEO recommendations | Manually test AI search or use a monitoring tool | Monthly |
| Conversion rate | Conversion funnel analysis | Weekly |
| Keyword iteration | Update the matrix | Quarterly |
Tengence can consolidate keyword, ranking, content, and AI recommendation data into a unified performance tracking workflow, making it easier to evaluate and adjust the strategy on a regular cycle.
7. FAQ
Q1: Is Dual-Engine Optimization Right for Every Business?
No. Dual-engine optimization is better suited to businesses that:
- Can produce content consistently
- Serve target users who regularly search or ask questions
- Sell products whose purchase decisions require supporting information
- Want to reduce customer acquisition costs
For low-priced impulse products with low decision costs, the ROI from dual-engine optimization may be limited.
Q2: How Many Resources Are Required?
Using the investment structure in this case as a reference:
- Staff: 1 content specialist or an outsourced provider
- Tools: Free version of the Tengence platform
- Time: Approximately 3 months to see initial results and 6 months to reach a relatively stable stage
- Budget: Approximately 50000 yuan/year, including tools and limited outsourcing costs
Q3: Will GEO Affect Traditional SEO?
No. The Q&A pairs, source annotations, and structured content introduced through GEO optimization generally help search engines understand the page topic. SEO and GEO work together rather than replacing each other.
Q4: How Can a Business Determine Whether GEO Is Working?
Focus on the following metrics:
- The number of AI search recommendations on platforms such as ChatGPT and Claude
- The conversion rate of traffic referred by AI
- How often the brand appears in AI search results
- Recommendation performance and traffic quality compared with competitors
8. Summary and Implementation Recommendations
Tengence recommends that as AI search continues to grow, businesses should invest in both SEO and GEO to cover a more complete range of search demand.
Core conclusions:
- The search landscape has changed: The growth of AI search means businesses need to pay attention to new traffic entry points
- The two engines complement each other: SEO captures explicit demand, while GEO covers latent demand
- Content structure is critical: Q&A pairs, source annotations, and distilled viewpoints form the foundation of GEO execution
- Impact can be quantified: This case achieved 300% search traffic growth within 6 months, and the relevant methods can be adapted to each company's situation
Implementation roadmap:
| Step | Action | Expected output |
|---|---|---|
| Step 1 | Assess AI search performance | Establish current recommendation and citation performance |
| Step 2 | Analyze the keyword matrix | Identify SEO and GEO keyword opportunities |
| Step 3 | Optimize content structure | Add Q&A pairs and source annotations |
| Step 4 | Track and iterate | Continuously optimize traffic and conversion |
About Tengence
Tengence GEO is Tengence's dual-engine GEO + SEO product, designed to increase brand citation in AI answers and improve search rankings. Tengence is the enterprise growth engine for the AI era, specializing in public-traffic acquisition and private-domain conversion. Its core products are Tengence GEO, featuring a dual-engine GEO + SEO approach, and Tengence Search.
Related Reading
- Tengence SEO Optimization: The Complete Guide to Higher Search Rankings
- Tengence GEO: Capturing the AI Search Traffic Dividend
