Monitor the Chinese Electric Vehicle Market
The RIWI Alpha Electric Vehicle (EV) datastream aggregates Chinese consumer sentiment data to provide early market indicators. The datastream uses high-frequency data to outline short and long-term trends shaping the automotive industry. With input from consumers across all Chinese provinces, investors and analysts monitoring the Chinese automotive sector with the datastream will have access to more complete and representative key performance metrics of brands within the EV market.
The datastream is accessible via RIWI’s real-time dashboard, allowing for in-the-moment insights as new products are released or the industry is impacted by new policies and factors. RIWI’s proprietary technology aggregates consumer and market data to generate trend scores, purchase signals, and consumer demand signals, providing our clients with easy-to-understand company sentiment scores necessary to navigate the fast-changing Electric Vehicle market in China.
Uncover the truth about what Chinese consumers really think, want and observe about brands including:
What the RIWI Alpha China Electric Vehicle Market Datastream Measures:
- Electric vehicle adoption and purchase intent
- Adoption hesitancy and EV-specific concerns
- The factors driving interest in specific EV brands
- The importance of manufacturing location when evaluating electric vehicle brands
- Brand perceptions, evaluations, and preferences
- Expectations for vehicle regulations in China
- Demographic factors including age, gender, income and location
The Alpha Edge
- RIWI is the only technology that can gather data from respondents online in all Chinese provinces, including those in rural and hard-to-reach areas, providing a far more representative, unbiased data sample to evaluate demand and greatly improve investment decisions.
- Accurate consumer sentiment data are updated live in RIWI ‘s secure interactive dashboard.
- Unlike social app sentiment, web scraping and transaction data, RIWI’s sentiment-based indicators gather a more accurate signal of consumer preferences, outlook and purchase intent.
- We avoid the biases of habitual survey-takers, paid surveys, focus groups, and social media analytics technology.
- We engage a unique subset of the web-using population that is diverse, unincentivized and inaccessible to legacy data collection methods, providing a more representative sample of consumer populations.
