Zoomaya develops advanced video engagement and analytics tools for sales teams. Evolotek played a key role in helping Zoomaya grow by enabling sales efforts for their flagship product, ZoomTrack, through product demos, outreach assistance, and customer onboarding support. Additionally, Evolotek assisted in various software development tasks, including UI updates, backend improvements, bug fixing, testing, and sprint support. This ensured Zoomaya could accelerate product improvements while maintaining a smoother development cycle and delivering better experiences to their customers.
In today's hyperconnected world, data isn't just powerful — it's relentless. Consumer behaviors change overnight, cultural trends evolve, and market contexts shift faster than ever before. Yet, many businesses still struggle to truly listen to their customers in real time — to capture what people feel, need, and expect. Our client — a fast-growing consumer-tech brand — reached a critical inflection point. They had amassed a wealth of data: transaction logs, customer support feedback, social media chatter, survey responses, and web analytics. But this data lived in silos. The marketing team saw one picture, the product team another, and leadership had to rely on slow, outsourced research. They needed more than data: they needed a way to listen to their customers continuously, deeply, and in context. They needed a system that could turn unstructured signals into strategic decisions — a "consumer insights engine."
Evolotek architected Zoomaya as a multi-layer consumer insights platform combined with elegant dashboards and real-time alert systems. We proposed a bold vision: establish an internal, scalable "Insights Hub" that sits at the heart of the business, connecting data, design, and decision-making. We started by working with cross-functional stakeholders — marketing, product, operations, and leadership — to map out the insights journey. What business decisions needed the fastest feedback? Which customer behaviors were most critical? What data sources would be most valuable? We architected the hub on a foundation of modular data pipelines that ingested internal sources (CRM, support, sales), mined unstructured external data (social media, forums, reviews), and combined with traditional market research. All data flowed into a central, cloud-native platform for normalization, tagging, and analysis. Once the data was consolidated, we layered advanced analytics including trend detection to spot emerging consumer behaviors, sentiment analysis on user feedback and social conversations, AI-powered clustering to segment users by attitudes (not just demographics), and predictive models to forecast which trends could translate into product opportunities. Insights weren't locked behind reports. We built dashboards and alert systems that delivered insight-as-a-service: weekly trend summaries for marketing, real-time alerts for social spikes or emerging customer pain points, and deep-dive reports for product teams on feature usage, sentiment, and demand. The Insights Hub became more than a data project. It was embedded into the way the company made decisions: product teams used trend signals to prioritize the roadmap, marketing leveraged emerging insights to tailor campaigns on the fly, and leadership aligned around a shared perspective of what customers cared about.
Seamlessly ingest and normalize data from CRM, support systems, social media, surveys, and web analytics into a unified data lake
AI-powered algorithms that spot emerging consumer behaviors, sentiment shifts, and market trends as they happen
Advanced NLP that analyzes customer feedback, social conversations, and reviews to understand emotional drivers and brand perception
Machine learning models that segment customers by attitudes, behaviors, and needs — enabling personalized product and marketing strategies
Instant notifications for critical customer signals — spikes in negative sentiment, emerging pain points, or shifts in demand
Hours vs Weeks
Decision Speed
7+
Data Sources Unified
92%
Trend Detection Accuracy
100%
Cross-Team Alignment