PriceLabs Uses Mindtickle Call AI to Train, Onboard Reps, and Fine-Tune Products
Customer Company Size
SME
Region
- America
Country
- United States
Product
- Mindtickle Call AI
Tech Stack
- AI
- Real-time transcription
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Industries
- Software
Applicable Functions
- Sales & Marketing
- Product Research & Development
Use Cases
- Predictive Quality Analytics
- Real-Time Location System (RTLS)
Services
- Data Science Services
About The Customer
PriceLabs is a leading revenue management platform for vacation and short-term rentals. The company is headquartered in Chicago and was founded in 2014. With a team size of 25, PriceLabs operates in the mid-market software/travel industry. The company has been experiencing rapid growth, having doubled its team in the past six months and planning to double it again in the next six months. PriceLabs is committed to understanding its customers' needs and sentiments, and to improving its product offerings based on this understanding.
The Challenge
PriceLabs, a leading revenue management platform for vacation and short-term rentals, was seeking a solution to record customer calls. The aim was to uncover customers’ sentiment and gain insight into their needs. The product team felt that there were new solutions that weren’t being adequately pitched. Recorded calls would help PriceLabs share feedback with the product team and also help identify where the team was missing the mark on explaining its product. This was particularly important as PriceLabs had doubled its team in the previous six months, and planned to double the team again in the following six months.
The Solution
PriceLabs implemented Mindtickle's conversation intelligence solution, Call AI. With Call AI, PriceLabs could automatically record and transcribe reps’ customer meetings in real time, generating actionable insights based on the customer voice. These insights informed decisions around product features and functionality. In addition, reps could learn from real-life scenarios, accelerating onboarding and informing learning paths. Call recordings and transcripts provided real-world conversations from sales calls, which new hires could use to inform their learning during their onboarding. This capability led to a 20% reduction in ramp time for new reps.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Factor-y S.r.l. – Establishes a cost-effective, security-rich development environment with SoftLayer technology
Factor-y S.r.l., a web portal developer, was faced with the challenge of migrating its development infrastructure to a reliable cloud services provider with highly responsive technical support. The company needed a solution that would not only provide a secure and reliable environment but also support its expansion by providing resources to create and deliver innovative offerings.
Case Study
Darwin Ecosystem: Accelerating discovery and insight through cutting-edge big data and cognitive technologies
Darwin Ecosystem was founded with a unique vision of harnessing chaos theory mathematics to uncover previously hidden connections in unstructured data. The company’s algorithms can look at all the data generated by any source (such as news, RSS feeds and Twitter), and analyze how a specific set of concepts within that data are evolving over time. This is particularly valuable in situations such as business and competitive intelligence, social research, brand monitoring, legal discovery, risk mitigation and even law enforcement. A common problem in these areas is that a regular web search will only turn up the all-time most popular answers to a given question – but what the expert researcher is actually interested in is the moment-tomoment evolution of the data available on that topic. Darwin’s algorithm is computationally intensive, and the sources of data it correlates can be vast. To bring its benefits to a larger commercial audience, Darwin needed to find a way to make it scale.
Case Study
Zend accelerates, simplifies PHP development
Zend Technologies, a major contributor to the PHP open source community, needed to keep pace with emerging trends such as mobility, agile development, application lifecycle management and continuous delivery. The company needed to provide the right tools to the worldwide community of PHP developers. The challenge was to support enterprise-class capabilities from end to end, including mobile, compliance and security. The pace of business required developers to show results fast across a variety of devices without compromising quality or security.
Case Study
Delivering modern data protection with cloud scale backup from Cobalt Iron and IBM
Organizations are struggling to modernize their legacy data protection environments in the face of growing demands around new infrastructure, new applications, and budget consolidation. Virtualization and modern application development processes have significantly outgrown legacy backup architectures. In response, infrastructure teams have created multiple backup solution types to handle the varying SLAs (performance, scale, cost) required by their business sponsors. However, the sheer number and variety of solutions in this uncontrolled expansion creates huge amounts of work, threatening to overwhelm the IT team in many organizations. Today, developers may add new applications and virtual server instances by the hundreds per day without accounting for the restrictions of the existing backup infrastructure. They leverage the cloud for immediate compute and storage resources, yet rarely communicate succinctly with corporate IT to ensure that the appropriate data protection services are in place.
Case Study
Achieving near limitless scalability and flexibility with data in the cloud
Web-based publishing platform SpaceCraft found that as its client base grew, it was spending an increasing amount of time managing its databases, distracting its focus from product innovation. As its user base rapidly expanded, data volumes at SpaceCraft began to rise dramatically. Along with their main focus on maintaining and further developing a great platform for web publishing, the SpaceCraft team had the added pressure of managing the increasing quantities of data while ensuring ongoing high performance for clients.
Case Study
nViso SA – Delivers emotion recognition solutions worldwide with a scalable SoftLayer hosting solution
nViso SA, a company that provides emotion recognition solutions, was in need of a high-performance cloud hosting infrastructure. The company wanted to extend its services to a global customer base. The challenge was to find a solution that could handle the demands of their growing customer base and the need for high performance and reliability.
