UBS Evidence Labs - API - 12 data products
KNOEMA COMMENTS:
API integration overview. easy-moderate amount of work. Difficult because they will change a number of products in it a bunch on us, which means we can't build and just let it run. Will require maintenance.
PRODUCTS
PRODUCTS | PRODUCT SUMMARY |
---|---|
appMonitor | What apps are trending best and worst? UBS Evidence Lab tracks daily rankings for thousands of mobile applications in the iOS and Google Play store across more than 50 countries to help answer this question. |
searchMonitor | What are search trends across geographies? UBS Evidence Lab developed a proprietary technique, that enables comparisons beyond the limitations of the Google Trends site, to answer this question. |
appUsageMonitor | What are the app trends in China? UBS Evidence Lab tracks weekly usage metrics for thousands of mobile applications in the iOS and Android stores in China to help answer this question. |
bestSellers | Which products and brands are most popular with Amazon shoppers? UBS Evidence Lab leverages its proprietary database of over 200 million products and ranks to help answer this question. This asset is searchable across ~100 Consumer Goods, Single-Serve Coffee, and Personal Care Appliances brands. |
brandTracker | The Brand Tracker [ Instagram ] identifies top performing and emerging brands by monitoring a suite of engagement and interaction metrics. UBS Evidence Lab has collected data from 200+ Luxury & Premium, Sportswear, Beauty & Boutique, Fast Fashion, and Restaurant brands that have 2mn+ posts and a combined 30bn+ interactions. See what new brands and comp sets are being added. |
earningsCallAnalyzer | This Earnings Call Analyzer provides a sub-industry-level view of the characteristics and content of earnings call discussion measured using proprietary natural language processing algorithms. Comparison tools offer the ability to contrast the sentiment, emotion, stability, and confidence of language used and the topics discussed against competitors and the sector-at-large. |
competitionModel | An introduction to competition, overlap, and cannibalization analyses. For more advanced time-series analyses, see the Location Market Quality Monitor. This builds upon the Regional Exposure and Demographic Models. |
regionalExposureModel | See locations on a map with metrics showing regional distribution/exposure and capacity share which can be thought of as a proxy measure of local market share. For further analysis, see the Demographic Model, Location Competition Model, and Location Market Quality Monitor |
demographicModel | See differences in demographic market quality exposure across competitors. Demographic metrics vary by country, but can include measures such as per capita income, total households, income, and age. Market quality is assessed by overlaying demographics on our Regional Exposure Model. |
airlineReview | Which Airlines lead and lag based on customer reviews? UBS Evidence Lab has collected more than 2 million reviews across 500+ distinct airlines to help answer this question. |
autoPortals | How are leading auto portals doing in terms of performance and growth? UBS Evidence Lab has collected millions of records at the Portal and Advertiser level to provide insights into the growth and performance of the target site. |
glassdoor | Which companies lead and lag based on Employee Satisfaction and CEO Approval? UBS Evidence Lab has collected more than 3 million reviews across 7000+ distinct employers to help answer this question. |
API SPECS
Thanks again for taking the time to meet today. I’ve attached the documentation, notes, and examples we reviewed today. Please let me know if you have any additional questions.
You can request that Southpoint provide the JWT token, which they can generate here: https://neo.ubs.com/ubs-evidence-lab/api-keys
PDF One-Page (attached, api-user-guide-en.pdf)
API Catalogue: https://neo.ubs.com/api/evidence-lab/catalogue
Airline Reviews Example Assets: https://neo.ubs.com/api/evidence-lab/airlineReview/assets
Airline Reviews Example Data: https://neo.ubs.com/api/evidence-lab/airlineReview?page=1&limit=3000&dataAssetKey=10004
Data Dictionary (attached, el-api-data-dictionary.xlsx) for each product and metadata fields
Other Notes:
Bearer token expires after 1 year
The full history of data is updated with each refresh of a dataset
Max limit parameter = 10000
All datasets within a single product endpoint share the same schema
I will follow up with our engagement managers to understand if we can set up a secondary contact to communicate any future changes
The following products will be updated soon to include the new normalized schema
brandTracker
appMonitor