dbSeer Helps Petvisor Unlock Next-Level Data Potential

The Customer

The client, Petvisor, delivers a range of mobile-based technologies to various pet-care professionals to meet their needs. Petvisor is a leading tech company serving the veterinary health and pet services industries. Petvisor provides thousands of veterinary hospitals with the tools they need to engage their customers, streamline their operations, and grow their businesses. They hired dbSeer to help streamline and categorize the high volume of calls the company receives. 

“This was our second big project with dbSeer and they performed incredibly well. We leaned heavily on their NLP and AI expertise to deliver near-real time analysis of hundreds of thousands of calls across hundreds of clients. The project was delivered on time, on budget, as promised.” ~ Mikhail Opletayev

The Opportunity

When dbSeer initially started to work with Petvisor the request was to analyze the calls received and categorize them into different buckets: appointments, new customers, cancellations, etc. The client recognized that they had massive amounts of unstructured data that could be analyzed and harnessed for action.

The client initially wanted to answer standard questions, such as whether a call resulted in a booking, whether it involved a new or existing customer, and whether it was an urgent call or a routine appointment. Understanding that this data could unlock additional information critical to the success of their client, dbSeer suggested extending the analysis to categorize calls into more specific, predefined categories. This gave the client even more information to work with regarding its customer-base, allowing for better and more personalized customer service.

The Solutions

dbSeer used the initial recordings of the calls and transcribed them using AWS services. Once the text was obtained using Amazon AI services, dbSeer was able to summarize the call and identify key points, action items and provide a general summary. dbSeer categorized the calls and identified their intent.

The Results

As a result of dbSeer’s work for the client, several results have been attained.

• The client now has detailed information about calls, categorized in a centralized Tableau dashboard.
  • Categorization of calls: The calls could range from making an appointment, scheduling vaccinations or arranging daycare services. dbSeer helped automatically categorize these calls so staff could review them.
    • Calls could also be categorized on whether they were answered by an agent or went straight to voicemail.
    • Calls could also be categorized on whether this was a repeat client or new customer.
  • Tableau Dashboard: All the information will be saved and uploaded into a centralized dashboard where summaries and categories of calls will be uploaded, this will provide the client with detailed reports based on the call data.

• The client has saved massive amounts of time with automation.
  • Automation: The data was always available from the recordings, but previously someone had to manually listen to each of the calls and categorize them which required tedious work. With hundreds of calls received per day, not every call was able to be analyzed and understood. With the automation dbSeer provided, hours of work have been saved. This has allowed Petvisor to be more efficient and focus on their customers in a more meaningful way.

• The client has access to data it deemed unusable in the past.
  • In the past, the client was unable to analyze the high volume of calls due to time constraints and the inability to review them in such detail. The new system implemented by dbSeer allows the client to easily sift through calls, search specific topics and words and better categorize information leading to actionable insights.

• The client can unlock future potentials with new data obtained and reach next-level competitiveness.
  • On-the-Job Training: While this feature is not currently being explored with the client, the potential to do so exists. Using sentiment analysis via an AI model, the recorded calls could be analyzed and provided with a neutral, positive or negative impact label. This would further help agents understand how to better serve customers and provide opportunities for learning on the job. “