Define monitoring questions
Establish a consistent recurring sampling scope for Dola around brands, products, competitors, topics, regions, and languages.
DAGENO / MODEL COVERAGE
ByteDance’s AI assistant for international markets, formerly Cici, focuses on regions including Southeast Asia and Latin America and provides writing, Q&A, and creative capabilities. Public information from late 2025 indicates it surpassed 10 million daily active users.
This figure is Dola’s global daily active user scale, not web traffic share. Its users are more concentrated in international markets including Southeast Asia and Latin America.
Within the target market and project configuration, Dageno can monitor brand mentions, recommendation context, competitive performance, and visible sources in Dola answers, then compare them with other configured models using consistent definitions.
Configure the analysis scope by topic, model, region, and sampling time while retaining the corresponding samples and sources.
Does Dola mention the brand in relevant demand and comparison questions in target markets?
How do Dola's multilingual answers describe the brand, products, and use cases?
How does the brand co-occur with local and global competitors?
A focused view of the evidence, comparisons, and actions behind this capability.
Establish a consistent recurring sampling scope for Dola around brands, products, competitors, topics, regions, and languages.
Record Dola questions, answers, sampling times, and visible sources instead of explaining brand performance with an aggregate score alone.
Place Dola and other configured models in the same framework to examine differences in brand mentions, competitive context, and sources.
Original Dola answer samples
Brand and competitor mention comparison
Visible sources, when available
Cross-model difference summary
Select the brands, competitors, topics, markets, and languages to validate in Dola.
Collect answers according to the configuration, then return to original samples to review brand context and visible sources.
Send persistent gaps to content, brand, SEO, or marketing teams for further validation and action.
Findings come from configured Dola answer samples and retain the user question, region, language, and sampling time.
Model patterns are identified by continuously comparing externally observable results and do not depend on internal ranking algorithms, complete indexes, or training data.
AI answers change over time. Trend comparisons require a consistent scope and sampling method.
Understand data coverage, metric definitions, and usage.
Using configured question samples, Dageno observes whether the brand appears, how it is described or compared, which competitors appear alongside it, and which sources are explicitly displayed in the answer. Specific dimensions depend on the project configuration and model output.
Not necessarily. Dola’s source display depends on the product mode, region, and answer. Dageno analyzes only links and textual evidence explicitly visible in sampled results.