A local flower and gift marketplace connects shoppers with flower shops and makers. Demand depends on the delivery city and occasion; seasonal peaks call for pages prepared in advance and dedicated work on local visibility.
Improve local-search visibility, especially for flower-related queries.
Examples included “flower delivery + city” and “bouquet + occasion”. The marketplace also needed a stronger presence in generative answers. Seasonality imposed a tight constraint: holiday pages needed time to gain rankings before peak demand. Approval terms did not allow raw metrics or the collaboration period to be published, so this case describes the approach and aggregated growth areas.
We split the work into two tracks—local SEO for traditional search and GEO for generative answers—and based both on flower-related demand, where locality and competition were especially pronounced.
- Prioritized flower-related keyword research: combinations such as “flower delivery + city/district” and “bouquet + occasion” (birthday, 14 February, 8 March, wedding), followed by gift categories and location-specific wording.
- Built a local structure with city and district pages containing real information about partners, range and delivery times; within each city, flower categories such as roses, tulips and custom bouquets targeted specific searches.
- Added structured data, including Product/Offer markup with prices and delivery times, partner shop profiles, and correct links between pages and cities.
- Prepared seasonal pages in advance for 14 February and 8 March. They went live several weeks before the peaks and had time to rank before holiday demand began.
- Audited GEO (Generative Engine Optimization): how AI systems answer “where can I order a bouquet delivered in [city]?” and whether the marketplace is mentioned.
- Prepared structured facts about the range, delivery times and cities served for models to reuse reliably in answers.
- Set up measurement with a sample of typical flower and gift prompts and regular tracking of the share of answers mentioning the brand.
The project showed that local visibility and GEO reinforce one another while solving different problems. City and flower pages built around real demand became a source of facts for AI answers, while the prompt sample gave the client a measurable way to track presence in generative channels.
Aggregated case results report a 65% increase in local impressions over six months, Top 10 visibility for key local queries in the main cities, and an increase in mentions across a test sample of AI prompts from about 12% to 34%. Seasonal traffic to flower categories was about ×2 the previous holiday peak.
| Metric | Result |
|---|---|
| Local search impressions over 6 months | +65% |
| Flower-delivery queries in main cities | Top 10 |
| Mentions in the AI prompt test sample | About 12% → 34% |
| Seasonal flower-category traffic | About ×2 the previous holiday peak |
Metrics are transcribed from the original case materials. A period is stated where it is recorded in the source.
The next opportunities we see for the project are:
- Expand the “city + flower categories” model to more locations where partners operate.
- Create separate pages for occasions such as weddings, graduations and corporate orders, and prepare them for indexing in advance.
- Run ongoing GEO monitoring to track citations in AI answers across a broader prompt sample.