IBBX Client Use Case

Hopara as a Sales Differentiator

Business Driver: Increase sales by adding a new data visualization element to their loT sensor reporting dashboard.

Use Cases

SVB | Improving client acquisition and retention

A US-based high-tech commercial bank, was looking to improve client acquisition and retention spending for its startup-focused outreach efforts. To optimize its investments in securing banking business among startups, SVB partnered with Hopara to create a visualization of key historical personal attributes of client management teams, cross-referenced by retention and profitability as a client. Using data from SVB’s CRM, Hopara applied machine learning algorithms to sort the data into clusters based on attributes such as school attended, current title, prior title, and prior employer.

The results showed that school attended and degree earned were key leading indicators of long-term market success among startup clients. SVB also found that when client organizations had more than one senior manager who had attended one specific university (confidential), their tenure with the bank was 5+ years. The visualization was deployed on AWS and made available to approved users within the bank, including non-techie marketing professionals who were able to navigate the Hopara App within minutes.

Agero | Optimizing Partner Performance and Contracts

A US transportation company that offers roadside assistance services to drivers across the US through a network of partners. However, due to the varying gas prices and distances, they faced difficulty in assessing the performance of their partners. The client used Hopara, a data visualization tool, to analyze nationwide incident data and find trends in customer response time and financial performance by partner and incident type.

This helped regional managers and corporate financial executives evaluate and potentially re-negotiate partner contracts based on actual expense variances. Hopara’s easy-to-use interface allowed for a quick analysis of regions with high profitability, streamlining the company-wide analysis process. The project identified the underlying cause of reduced performance in certain regions and helped the company enhance profitability per incident and net regional profitability.

MGH | Reducing infection spread in hospitals

A world-renowned hospital faced a challenge in identifying specific patients and locations of infectious disease incidents in order to prevent spread and identify underlying causes. To address this issue, Hopara deployed a visualization that incorporates daily data of infection rates by room and patient, on custom floor plans across multiple floors, with a heat map based on the infection rate by room.

The solution allowed MGH to identify hot spots quickly and share the information with various care team members. After further analysis, it was found that hotspots tended to center around one type of area common among all floors: the floor central nursing station. This discovery helped MGH identify areas that required comprehensive cleaning. Hopara’s solution helped MGH streamline its processes and better respond to infectious disease incidents.

NREL | Improved view of renewable energy performance

A federally funded research and development center that specializes in renewable energy, energy efficiency, energy systems integration, and sustainable transportation faced a business problem of lacking a holistic view of renewable energy generation with detailed information down to the individual town level. The solution provided by Hopara was a nationwide visualization of distributed wind generating capacity with real-time supply data from a nationwide network of wind power facilities, providing a ‘birds-eye’ view of net generating capacity by region with the ability to drill down to a single turbine in its specific geolocation.

The visualization helped our client share new capabilities with local, state and federal agencies, securing additional projects. A bonus value was that the visualization application could be used by multiple clients and stakeholders with varying skill levels in data analytics.

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