Beijing ANMEI Technology builds AI marketing programmes around one question: what does a company actually need to change in order to grow? The answer has produced three services — generative engine optimization, operations coaching, and full-service PR. Below are the capabilities, where the numbers come from, and three anonymised client cases.
1. Generative engine optimization
Our GEO service is built on a proprietary AI marketing stack, structured as engine optimization plus scenario adaptation. It covers three stages: content generation, channel matching and performance iteration — with the process kept automated and explainable throughout.
· Generates scenario-specific copy, assets and landing pages, with support for multiple languages and industries.
· Continuously optimises placement and creative combinations through engine strategy plus A/B and multivariate testing.
· Connects to CRM, ad platforms and CDPs so the data loop actually closes.
Measured effects: content output efficiency up roughly 60%; precise reach up roughly 45%; customer acquisition cost down roughly 30%. Sources are listed below.
2. Operations coaching
This service supplies technical enablement, data analysis and hands-on delivery support, with a team attached to the project throughout, so an AI strategy turns into a repeatable marketing system rather than a slide deck.
· Customised delivery plans, training, and a KPI-driven iteration cadence.
· Key deliverables: new-customer system build-out, campaign templating, and migration of reporting dashboards.
In practice, the time to stand up a new-customer marketing system dropped to about 15 working days — roughly 40% faster than the industry average — and participating clients saw repeat purchase rates rise about 52%. Source: internal project records and client follow-up interviews.
3. PR, full service
Using AI analysis of public sentiment and audience preference, we build layered communications strategies and combine KOL and media placement with a content matrix to lift brand exposure and positive share of voice.
Typical effects: brand exposure up roughly 70%, positive sentiment share up roughly 65%. Source: post-campaign sentiment monitoring and third-party sentiment analysis reports.
Where the numbers come from
To make the figures checkable, we validated key metrics through more than one route:
· Internal A/B and multivariate control tests across 50+ campaigns in 2024–2025, used to assess output efficiency and conversion before and after engine optimisation.
· Client follow-up interviews and project close-out reports, based on the client's own KPIs, anonymised with their permission.
· Third-party measurement and sentiment monitoring, conducted blind with independent data platforms and research firms.
Note: the percentages above are weighted averages across multiple projects. Detailed metrics and raw data can be requested under an authorisation agreement, or specified directly in a cooperation contract.
Three anonymised client cases
Case A — manufacturing, content generation and acquisition. The problem: long creative production cycles, imprecise reach, high acquisition cost. Our work: GEO-driven automated scenario asset generation plus A/B-tested channel mix. Result over a three-month project: content output efficiency up roughly 60%, precise reach up roughly 45%, CAC down roughly 30%. Source: internal A/B testing and client follow-up.
Case B — retail chain, fast rollout via coaching. The problem: the AI strategy would not land, and the team had no implementation experience. Our work: technical enablement plus hands-on guidance to build the new-customer marketing system and automation workflows. Result: system build-out cut to 15 working days, about 40% faster, with campaign repeat purchase rate up roughly 52%. Source: project close-out report.
Case C — financial services, PR and share of voice. The problem: insufficient brand exposure, and negative sentiment affecting conversion. Our work: layered communications strategy built on AI sentiment analysis, executed with media and KOL placement. Result: brand exposure up roughly 70%, positive sentiment share up roughly 65%. Source: third-party sentiment monitoring and client follow-up.
All three are anonymised summaries of real engagements. For raw data or full case material, request data access through the contact details below.
How to start
1. Requirements diagnostic — send us your current position and objectives, by form or by phone.
2. Pilot — run a small-scale campaign and validate with one to three weeks of A/B testing.
3. Full deployment — based on pilot results, move into coaching and scaled placement and build a reusable marketing system.
Call +86-157-0105-6972, email us, or use the contact form on this site to begin.