Gravity Digital proves value by tightening up client lead response time
公司规模
11-200
地区
- America
国家
- United States
产品
- CallRail Call Tracking
- Form Tracking
- Form Submission Notifications
技术栈
- Google Search Ads
- Youtube Ads
- Facebook Ads
实施规模
- Departmental Deployment
影响指标
- Customer Satisfaction
- Productivity Improvements
技术
- 分析与建模 - 实时分析
适用行业
- 医疗保健和医院
适用功能
- 销售与市场营销
服务
- 数据科学服务
关于客户
Gravity Digital is a Houston-area boutique video agency that specializes in producing creative content for their healthcare clients. The founder of Gravity Digital is Casey OʼQuinn. The agency drives client leads via Google Search Ads, Youtube Ads, Facebook Ads, and more. They use call tracking to monitor account performance from timely appointment booking through prompt reminders and follow-ups. However, they faced challenges in tracking requests from website form submissions.
挑战
Gravity Digital, a boutique video agency, was driving client leads via Google Search Ads, Youtube Ads, Facebook Ads, and more. However, they were unsure if clients were actually following up with them. The agency used call tracking to monitor account performance from timely appointment booking through prompt reminders and follow-ups. But calls weren't the only way patients booked appointments. Tracking requests from website form submissions was a completely different ball game. The HIPAA compliant forms they were using were too complicated. Gravity's team couldn't tell which leads were truly qualified, and they didn't have the insights they needed to hand them off to the booking team to close them.
解决方案
Gravity Digital decided to take a deeper look into the features of Form Tracking, a product they were already using. They discovered Form Submission Notifications and its Quick and Automated Response features. These features ensured that all form leads were routed to the right front desk staff and enabled Gravity Digital's clients to provide prompt follow-up. Quick Response puts staff members a click away from following up with a lead via email, text, or phone call. If they're busy working with another patient, they can set up an Automated Response to let leads know that their request has been received and when they can expect a staff member to reach out to them.
运营影响
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Hospital Inventory Management
The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.
Case Study
Gas Pipeline Monitoring System for Hospitals
This system integrator focuses on providing centralized gas pipeline monitoring systems for hospitals. The service they provide makes it possible for hospitals to reduce both maintenance and labor costs. Since hospitals may not have an existing network suitable for this type of system, GPRS communication provides an easy and ready-to-use solution for remote, distributed monitoring systems System Requirements - GPRS communication - Seamless connection with SCADA software - Simple, front-end control capability - Expandable I/O channels - Combine AI, DI, and DO channels
Case Study
Driving Digital Transformations for Vitro Diagnostic Medical Devices
Diagnostic devices play a vital role in helping to improve healthcare delivery. In fact, an estimated 60 percent of the world’s medical decisions are made with support from in vitrodiagnostics (IVD) solutions, such as those provided by Roche Diagnostics, an industry leader. As the demand for medical diagnostic services grows rapidly in hospitals and clinics across China, so does the market for IVD solutions. In addition, the typically high cost of these diagnostic devices means that comprehensive post-sales services are needed. Wanteed to improve three portions of thr IVD:1. Remotely monitor and manage IVD devices as fixed assets.2. Optimizing device availability with predictive maintenance.3. Recommending the best IVD solution for a customer’s needs.
Case Study
HaemoCloud Global Blood Management System
1) Deliver a connected digital product system to protect and increase the differentiated value of Haemonetics blood and plasma solutions. 2) Improve patient outcomes by increasing the efficiency of blood supply flows. 3) Navigate and satisfy a complex web of global regulatory compliance requirements. 4) Reduce costly and labor-intensive maintenance procedures.
Case Study
Harnessing real-time data to give a holistic picture of patient health
Every day, vast quantities of data are collected about patients as they pass through health service organizations—from operational data such as treatment history and medications to physiological data captured by medical devices. The insights hidden within this treasure trove of data can be used to support more personalized treatments, more accurate diagnosis and more advanced preparative care. But since the information is generated faster than most organizations can consume it, unlocking the power of this big data can be a struggle. This type of predictive approach not only improves patient care—it also helps to reduce costs, because in the healthcare industry, prevention is almost always more cost-effective than treatment. However, collecting, analyzing and presenting these data-streams in a way that clinicians can easily understand can pose a significant technical challenge.
