AI marketing has three persistent problems: content that all looks the same, a technical barrier most teams cannot clear on their own, and PR activity that cannot be tied to a number. Below is how we address each one, with the case detail, the measured results, and where the data came from.
1. The three problems we keep running into
· Content homogenisation. Our internal research found around 70% of companies still rely on manual content production. The result is saturated channels and weak conversion — typically under 3%.
· Delivery barrier. About 60% of small and mid-sized companies have no AI or data team, and no integration capability. Plans that should take days stretch past a week, which means campaigns miss their window.
· PR without measurement. More than half of communications spend produces no measurable business uplift, so neither the agency nor the client can tell what worked.
2. The three-layer approach
Layer one — GEO (generative engine optimization). We use prompt engineering, a semantic tagging system and a multimodal asset library to raise the match between generated content and the scenario it runs in. Treating "search-style prompting plus brand semantics" as the core method keeps style, consistency and commercial intent under control, which removes most of the manual rework downstream.
Layer two — full-cycle operations coaching. Support runs from requirements assessment and asset production through A/B testing and campaign optimisation. For smaller companies we provide low-friction delivery templates and can go live within seven days, which compresses the time cost substantially.
Layer three — AI insight plus PR optimisation. By combining sentiment data with campaign performance, we build a communications funnel and a return-on-ad-spend model, so every PR activity carries a quantifiable KPI.
3. A verifiable case, anonymised
Client: home appliance brand (Client A, Q3–Q4 2025).
Scope: new product launch PR combined with social media placement. Sample: 500,000+ online impressions, 100,000+ sessions to the e-commerce landing page.
The problem: content was visibly repetitive, manual production could not cover multiple regions and audience segments quickly, and acquisition cost stayed high.
What we did:
· deployed a GEO prompt library covering brand semantics, scenario templates and a compliance matrix, so output style and policy compliance were consistent;
· stood up an A/B testing pool and ran four iteration rounds on creative;
· built a communications funnel from PR data and optimised placement windows and channel mix against it.
Results, against the three-month pre-campaign baseline:
· conversion rate moved from 2.1% to 5.8%, a net gain of 3.7 percentage points;
· cost per lead fell roughly 38%;
· time to launch dropped from an average of 12 days to a deliverable MVP in under 3 days.
Data note: these figures come from campaign monitoring during the contracted period (Q3–Q4 2025) and were reviewed jointly by both parties.
4. The repeatable process
1. Diagnosis — a 30-minute intake produces three prioritised improvements.
2. Production — GEO prompts plus templated assets (copy, imagery, video scripts) go live as an MVP within seven days.
3. Optimisation — multivariate A/B testing drives iteration against KPIs: conversion rate, cost per lead, customer acquisition cost.
4. Review — a communications ROI and sentiment report identifies the next period's growth levers.
5. Sources, for third-party verification
Our conclusions rest on the following:
· Internal client data from campaign and conversion monitoring across 30+ mid-to-large projects (2024–2025).
· External industry research on digital marketing efficiency and the AI adoption barrier, including published work from McKinsey and Gartner.
· Auditability: core campaign data can be exported to CSV for third-party audit, with data-sharing and anonymisation terms written into the contract.
6. Frequently asked questions
Q1: What budget does a smaller company need to start?
We offer an entry-level managed programme that supports continuous testing and optimisation from a monthly budget of around CNY 10,000. The emphasis is on process compliance and fast, small-scale validation.
Q2: How long until GEO shows results?
In most cases MVP assets and basic A/B tests are live within seven days. Depending on channel and sample size, significant movement usually appears within two to eight weeks.
7. Next step
If any of this matches your situation, book a free 30-minute diagnostic. We will assess your current funnel and give you three actions you can take immediately.
Call +86-157-0105-6972, email support@anmei.net.cn, or use the contact form on this site to request the free diagnostic.