Large Technology vendor achieved mass personalized customer engagement with social media analytics
Company Size
1,000+
Country
- United States
Product
- Social Media Analytics
Tech Stack
- Data Integration
- Data Visualization
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Brand Awareness
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Big Data Analytics
- Application Infrastructure & Middleware - Data Visualization
Applicable Functions
- Sales & Marketing
Services
- Data Science Services
About The Customer
The customer is a leading software, services, and solutions company in the technology industry. They are a large-scale enterprise with a global presence. The company was seeking to enhance its customer engagement and acquisition strategies by leveraging social media analytics. They wanted to move away from a one-size-fits-all approach in their marketing campaigns and instead, adopt a more personalized engagement model based on digital profiles. The company aimed to target profitable segments more effectively and boost digital utilization among its customers. They also sought to drive customer brand advocacy through increased engagement.
The Challenge
The client, a large technology company, wanted to better target profitable segments for acquisition and enhance engagement with their profitable customers to drive digital utilization. They also wanted to propagate engagement to drive customer brand advocacy. The company asked Blueocean Market Intelligence to create more personalized engagement initiatives based on digital profiles. They specifically wanted to avoid one-size-fits-all approach in the marketing campaigns and consider customer preference in defining engagement models.
The Solution
Blueocean Market Intelligence conducted a detailed and in-depth social intelligence process to build an initial understanding of the depth and breadth of digital behaviors and attitudes. They identified the primary behaviors and attitudes of customers and prospects. The team then enhanced the existing customer segmentation by segmenting the customer base by overlaying with existing new norms segmentation. They developed a model and attribute segments on top of the client database. This unique approach provided the client with a well-rounded understanding of how their customers use social media for work and leisure, and how susceptible they are to engaging with the client through this forum.
Operational Impact
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