Data Harvesting
20+
Data sources, including search, social, audio and mobile
3 million+
Content pages scanned each day
10,000
Dedicated micro-machines scouring the contentsphere
100,000+
Keywords examined
100,000+
Hours of audio analyzed
Data Processing
50+
NLP-based attributes categorized
100+
Corpora and lexical dictionaries refenced
10,000+
Data types personalized to the unique strategy of each client
25+
Machine learning models (including K-Means Clustering, DBScan and Random Forest) used to produce recommendations
10+
Advanced prediction algorithms
500+
Signals used by the machine-learning algorithms to identify trends
2 million (and counting)
Fake-news data points used to reveal unreliable sources
Business Results
10+
Competitors each client can monitor and benchmark against
20%+
Increase in audience engagement in 5 months after the Risk team at a Big 4 consultancy implemented Contrend’s recommendations
50%
Less time it took an international hotel-management company to create, approve, publish new content assets using Contrend’s workflow
37%
Increase in engagement compared to the hotel company’s competitive set
Increases after a global banking client implemented Contrend recommendations:
+881% New users
+385% Pages per Session
+437% Ave. Session Duration
+300% increase in conversions
Increases after a tech unicorn implemented Contrend recommendations:
+176% MQLs originating in search
+80% downloads/registrations
+149% LinkedIn followers
