High Tech Industry Solutions
Leading brands in the technology industry are incorporating data-driven insights into their product lines, and it shows. Enhance your engineering, product management, marketing, and support departments by incorporating multi-structured data from multiple sources. Karmasphere can help you improve your processes and boost the value of your products and services.Business Challenges
- Products can fail at any time – delivering a quality product means being able to predict these incidents.
- Today’s customers expect everything to be smart – including your product – so you have to anticipate their needs.
- Your bottom line depends on well-informed, well-developed marketing programs.
Promise of Big Data for the Technology Industry
Improve the quality and stickiness of your product.
- Incorporate sensor data and device data to proactively determine when service will be needed.
- Analyze customer usage to improve your product roadmap.
Understand your customer across all product lines.
- Personalize the customer experience by monitoring customer behavior.
- Provide proactive customer service and support based on insights from event and usage logs.
Take advantage of new revenue opportunities.
- Upsell and cross-sell to customers who are most likely to buy by cross-analyzing online and transactional data.
- Identify segments to market to by correlating product purchases with geo-location, psychographic, demographic, and social media data.
Technology Data Sources
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Machine and device event log data
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Social media data
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CRM application data
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3rd party demographic and psychographic data
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Web logs data
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Geo-location data
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Clickstreams
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Advertising impression data across media; online, TV, radio, print, email
Karmasphere for Technology
Karmasphere provides a unified analytics workspace for sales, marketing, customer support, and product management to analyze multi-structured Big Data from internal and external sources, create visualizations, and extract valuable insights to share with colleagues and business partners.Analyze a wide variety of Big Data
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Analyze structured, semi-structured and unstructured data.
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Aggregate large volumes of product and usage logs.
- Cross-analyze traditional data sources with new, identified data.
Offer insights to marketing, product managers, engineering, and customer support
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Provide product managers with a self-service data analysis workspace.
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Give customer support a self-service workspace to predict customers' problems.
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Equip engineering with a self-service product performance analysis workspace to determine product enhancements and roadmap.
- Supply marketers with a self-service workspace to conduct program and customer analysis.
Embed models, algorithms and query results into applications
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Drive customer behaviors by adding personalization, online ad optimization and nurturing engines to applications.