Contents of this document
- Increase in gross profit¥32 million
- Decrease in SG&A expenses¥-20 million
- Higher subcontracting expenses¥38 million
- Decrease in personnel and recruitment expenses¥-19 million
- Decrease in other expenses¥-2 million
- Transition in the business structure from a SaaS model to an AI Agent model
- Planned release of AI Concierge by SiTest Engage
- Planned release of AvaTwin Chatbot
- Launch of the AI avatar sales support service アバセル
- Strategic business partnership with PLAN-B
- Launch of a development project for RYUMA, an AI forecasting service for the U.S. horse-racing market
- Average active accounts931 Engagements
- Average SiTest churn rate1.3 %
- SiTest ARPU¥139,408
- Total SPAIA registrations159,561 peopleYear on year against the same period last year+17,970.0%
- SPAIA horse-racing paid conversion rate22.1 %
- Average active accounts931 Engagements
- SiTest ARPU¥139,408
- Average SiTest churn rate1.3 %
- SPAIA horse-racing paid conversion rate22.1 %
| Item | Details |
|---|---|
| Document type | Presentation materials for financial results |
| Fiscal Period Covered | First quarter of the fiscal year ending December 2026 |
| Net Sales | ¥502 million (YoY +12.6%) |
| Operating profit | ¥36 million |
| Ordinary income | ¥38 million |
| Net income | ¥40 million |
| Selling, general and administrative expenses | ¥293 million |
| Results for the three months of the current quarter | Net Sales ¥502 million / Operating profit ¥36 million / Ordinary income ¥38 million / Net income ¥40 million |
| Full-year earnings forecast | Operating profit ¥3 million |
| Progress against full-year forecast | Net Sales 28.4 % / Marketing DX business revenue 29.6 % / Technology business revenue 19 % / Operating profit 1,222 % |
| Self-assessment against the plan | Progressing steadily toward achieving the full-year plan |
| Segment results | Marketing DX Business Net Sales ¥449 million (YoY +21.6%) / Operating profit ¥219 million / Technology Business Net Sales ¥52 million (YoY -16.1%) / Operating profit ¥-64 million |
| Breakdown of Factors Affecting the Change | Factors Increase in gross profit / Amount ¥32 million, Factors Decrease in SG&A expenses / Amount ¥-20 million, Factors Higher subcontracting expenses / Amount ¥38 million, Factors Decrease in personnel and recruitment expenses / Amount ¥-19 million, Factors Decrease in other expenses / Amount ¥-2 million |
| Key KPIs | Indicator name Average active accounts / Value 931 Engagements / Year on year against the same period last year Not disclosed, Indicator name Average SiTest churn rate / Value 1.3 % / Year on year against the same period last year Not disclosed, Indicator name SiTest ARPU / Value ¥139,408 / Year on year against the same period last year Not disclosed, Indicator name Total SPAIA registrations / Value 159,561 people / Year on year against the same period last year 17,970 people, Indicator name SPAIA horse-racing paid conversion rate / Value 22.1 % / Year on year against the same period last year Not disclosed |
| Unit price and quantity metrics | Indicator name Average active accounts / Value 931 Engagements, Indicator name SiTest ARPU / Value ¥139,408, Indicator name Average SiTest churn rate / Value 1.3 %, Indicator name SPAIA horse-racing paid conversion rate / Value 22.1 % |
| Medium-term management plan targets | Target Sevenfold increase in operating income; market capitalization of ¥50 billion / Target fiscal year FY32 |
| New initiatives | Transition in the business structure from a SaaS model to an AI Agent model, Planned release of AI Concierge by SiTest Engage, Planned release of AvaTwin Chatbot, Launch of the AI avatar sales support service アバセル, Strategic business partnership with PLAN-B, Launch of a development project for RYUMA, an AI forecasting service for the U.S. horse-racing market |
Items this document does not state (14)
These are items the company does not state in this document. We do not leave them blank, nor fill them in from other sources or by inference.
The reasons the company gives
The company's own explanation, not something inferred from the numbers.The stated reasons were higher revenue in the Marketing DX business, driven by solid order acquisition; cost reductions accompanying the expansion of sales and the reduction of costs in unprofitable businesses; and reductions in personnel and SG&A expenses through the use of AI and the selective allocation and concentration of resources. In the Technology business, meanwhile, the allocation of resources to new service development and other initiatives, as well as development expenses incurred before monetization, were cited as factors weighing on revenue and profit.