High Tech Industry SolutionsLeading 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.
- 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
Machine and device event log data
Social media data
CRM application data
3rd party demographic and psychographic data
Web logs data
Advertising impression data across media; online, TV, radio, print, email
Karmasphere for TechnologyKarmasphere 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
Analyze structured, semi-structured and unstructured data.
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
Provide product managers with a self-service data analysis workspace.
Give customer support a self-service workspace to predict customers' problems.
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
Drive customer behaviors by adding personalization, online ad optimization and nurturing engines to applications.