How Apollo Hospitals Utilized Locobuzz During COVID-19 to Bolster Customer Experience

Apollo Hospitals, India’s first corporate healthcare provider, sought the assistance of Locobuzz during the COVID-19 pandemic to streamline their CX processes and serve customers promptly and efficiently.

Apollo Hospitals, present across social media, has over three million followers and regularly utilizes digital channels to resolve customer queries. There was, understandably, a huge surge in the number of queries and complaints during the pandemic. To effectively track and respond to each incoming query and complaint without compromising the quality of resolution, Apollo Hospitals engaged Locobuzz to achieve several CX goals.

Objectives

Diligently sorting and handling the many incoming queries and inquiries about the availability of COVID facilities and services was the topmost priority along with drastically reducing the response time so as to resolve the maximum number of queries as fast as possible. Another important aspect of Apollo Hospitals’ CX goals was to properly define the Category Map to benefit the overall Customer Experience while providing personalized/customized responses based on the demand of the situation.

Using Locobuzz, Apollo Hospitals planned to perfect the automation of the categorization of user feedback from every digital channel into a one-view CRM as opposed to manual classification.

Solutions

To achieve these goals, Apollo Hospitals deployed the Social Listening feature to track brand mentions across all digital platforms. It also tracked its own social media reputation score, turnaround time, and first-level response in real-time. The healthcare provider used Competition Benchmarking to meticulously track the online activities of competitors in terms of turnaround time, engagement, Share of Voice, and social media reputation score. Apollo Hospitals also tracked user conversations around useful subjects such as cancer and cardiac treatments in order to gather and mine public opinion.

In order to respond to customers in an efficient manner, Locobuzz provided Apollo with a holistic view of all conversations classified into functional categories and sentiments making the generation of tickets with classified actionable conversations super easy. The automation of the categorization into a one-view CRM was also achieved along with the setting up of automated alerts based on influencers and engagement. Locobuzz also helped Apollo with the channel-wise sorting of brand mentions for accurate Sentiment Analysis.

Outcomes

After the deployment of Locobuzz, Apollo saw 63% of tickets being replied to within the benchmark time of 30 minutes and 76% of tickets closed within the benchmark time of 2 hours.

No. of tickets

The average time for first-level response was reduced to just 6 minutes and 34 seconds and the turnaround time for average closure was 18 minutes and 14 seconds! Daily, weekly and monthly reports were generated for valuable insights. Also, daily enhanced response management increased to over 12 hours.

Akhil-Kapoor-Digital-Marketer
We’re proud to partner with Locobuzz to lead the transformation in customer care & conversation insights during the pandemic. We’re happy to extend our care and support to netizens across digital channels and solve problems through automation and service insights. As partners, we have to lead the next revolution in customer care.
AKHIL KAPOOR
Digital Marketing Associate, Apollo Hospitals
Rahul-Dubey
We partnered with Locobuzz to enhance our relationship with our users across different digital channels. We initiated a personalized approach with our response strategy, to provide care and support for all our patients across the world during the COVID-19 pandemic.
RAHUL DUBEY

Social Media Marketing & ORM Head at Apollo Hospitals

Total number of online mentions segregated by Sentiment
Channel Wise Engagement
Category Wise Distribution

Apart from all this, Apollo witnessed a 30% drop in tickets within a month due to the careful refinement of actionable rules saving time, money, and, human effort. Mentions were highly demarcated according to sentiment, categories, location, etc. while the category map was redesigned and revamped leading to a much simpler data sorting process.

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