London, NW1 0TU,
United Kingdom
Queen Mother Hospital For Small Animals Technographics
Discover the latest software purchases and digital transformation initiatives being undertaken by Queen Mother Hospital For Small Animals and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 1100 Queen Mother Hospital For Small Animals employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that Queen Mother Hospital For Small Animals has purchased the following applications: Microsoft Azure Cloud Services for Application Hosting and Computing Services in 2014, New Relic APM for Application Performance Management in 2014, Geomant Buzzeasy In-Queue Callback for Call Tracking and Recording in 2020 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems Queen Mother Hospital For Small Animals is running and its propensity to invest more and deepen its relationship with Microsoft , New Relic , Geomant or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing Queen Mother Hospital For Small Animals revenues, which have grown to $181.0 million in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for Queen Mother Hospital For Small Animals intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| Microsoft | Legacy | Microsoft Azure Cloud Services | Application Hosting and Computing Services | IaaS | n/a | 2014 | 2014 | ||
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Content Delivery Network | IaaS |
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2015 | 2015 |
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ITSM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| New Relic | Legacy | New Relic APM | Application Performance Management | ITSM | n/a | 2014 | 2014 |
CRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
|---|---|---|---|---|---|---|---|---|---|
| Geomant | Legacy | Geomant Buzzeasy In-Queue Callback | Call Tracking and Recording | CRM | n/a | 2020 | 2020 | In 2020, Queen Mother Hospital For Small Animals deployed Geomant Buzzeasy In-Queue Callback across multiple Royal Veterinary College departments. The rollout targeted Call Tracking and Recording requirements and introduced multichannel contact centre capabilities, specifically IVR and webchat, while enabling extended in-queue callback functionality to manage waiting callers. Configuration work centered on the Geomant Buzzeasy In-Queue Callback application, implementing in-queue callback queuing logic, IVR menu routing, webchat session handling, and supervisor and agent dashboards for real-time monitoring. CRM popup integration was implemented to surface caller context to agents at the point of answer, improving agent context and streamlining contact handling workflows. Operational coverage spanned multiple RVC departments in the United Kingdom, impacting contact centre agents and supervisors supporting clinical and client-facing communications at the Queen Mother Hospital For Small Animals. Integrations explicitly included CRM popups and the multichannel contact channels IVR and webchat, creating a unified Call Tracking and Recording layer that orchestrated queue management and callback offers. Governance emphasized use of supervisor and agent dashboards and formalized callback workflows to offer callers callbacks when agents became available, reducing perceived wait time as documented in the case study. The case study explicitly reports callback and IVR usage and improved agent context via CRM popups, with no quantified financial outcomes provided in the source. | |
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Customer Experience | CRM |
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2014 | 2014 |
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Marketing Automation | CRM |
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2019 | 2019 |
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Marketing Automation | CRM |
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2020 | 2020 |
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Collaboration
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
Insight Source |
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Collaboration | Collaboration |
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2015 | 2015 |
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| Date | Company | Status | Vendor | Product | Category | Market |
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