This Global Fast Food Chain has been in India for more than 10 years and it is the fastest growing restaurant company in the country. It is predicted that India will have the largest consuming class in the world by 2030. This growth can be attributed to a successful brand building strategy focused on providing exceptional customer service, deep penetration across Tier I and Tier II cities, localized menu offerings and skilled yet diverse workforce. Brands are appealing to a growing middle class and youth looking for aspirational, affordable and innovative experiences in fast food restaurant place.
Considering the tremendous growth of internet usage in India, and growing consumer voices available on the internet such as social networking sites, domain specific sites, various blogs and forums, and those influencing brand reputation big time, our client intends to deploy technology (the only way to handle the Volume, Velocity and Variety of information) to have an Omni channel listening platform connected to analytics for actionable knowledge and a close loop customer feedback management process.
To address the above problem, Abzooba with its extensive expertise in data science and machine learning, used its proprietary product XpressoInsightsTM to develop a customized solution for this unique problem.
To address this widespread problem of Customer 3600 feedback management, we have used our XpressoInsightsTM Platform, which has primarily following 3 modules –
Apache Storm (A superfast parallel data processing infrastructure) was developed to crawl huge volume of data, in near real time. Purpose of creating this Big Data System is getting relevant consumer feedbacks from varied sources, with minimum time lag.
Voice of Customers are available primarily across the following category and each have their own nature and impact.
|Social Media||Facebook, Twitter||High Coverage, High Impact for reputation management, Higher noise (lower percentile of relevant feedback), Global|
|Domain Specific Sites||Zomato, Google business Review||Moderate Coverage, High influence, Lower noise (higher percentile of relevant, well thought and detailed review), Local – typically outlet wise|
|Enterprise Feedback||CRM, Email||Different platform, the feedback needs to be managed|
API connects and custom crawlers will source the public domain data. The high level feedback collection technology stack as follows.
In Second step, we have customized our home grown natural language processing Engine Xpresso.NLP to distil the feedback across various aspects (Food, Service, Ambiance, etc.) with associated sentiments (positive, negative, neutral, none) and expressions (complaints, advocacy, suggestion, opinion)
Output of Xpresso NLP engine was represented through Xpresso.VIZ (An easy to use, highly configurable, database & platform agnostic visualization tool), in the form of dashboard delivered over a secured web application. Relevant connectors was built to connect with a ticket management system for close room management of complaints.
XpressoInsightsTMis a complete solution package (on top of Apache Spark, Xpresso.NLP & Xpresso.VIZ) to understand and listen your social/enterprise customer, prevent brand dilution, create tickets and manage/response your customers from the solution itself.
Following is a high level solution snapshot of XpressoInsightsTM, for the mentioned client –
While it was very difficult to understand the business benefits in monetary terms, following are some metrics –
- MoM 3% and 35.1% average increase of followers in FB & Twitter respectively
- Zomato rating has been increased from 2 to 4.1
- Approximately 27% reduction of consumer complaint combining Enterprise CRM & Email
Currently we are working on Visual analytics to understand store wise product preference, queue optimization, space management.