IN THE CHAT

CUSTOMER SERVICE ON SOCIAL MEDIA

OVERVIEW

InTheChat provides a set of solutions that companies or customer service individuals can use to track and serve their customers across social media.

These solutions gather, segment, and funnel relevent content from social media websites in real time. This content is made available to users for tracking and responding to their customers' concerns, queries, and feedback.

We has been involved with InTheChat through out different stages of development from prototyping to launching a production system.

PROTOTYPE

Research was carried out to identify relevant social data channels and APIs. An initial proof of concept was built after wire framing the user flow.

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RESEARCH
img-wireframe
WIREFRAME
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RAPID PROTOTYPE
RUBY ON RAILS
RESQUE
MONGO DB
FACEBOOK GRAPH API
TWITTER STREAMING API

PRODUCT PLAN

InTheChat provided us with refined requirements and product expectations based on the feedback it collected. A comprehensive product plan with timeline, scope, and risk evaluation was developed.

BETA PRODUCT

Scalable data aggregators were implemented to work with enterprize grade data providers to collect relevent social content.

A servicing dashboard was developed which enabled users with the ability to use a single platform for interactions with customers across distinct social media channels.

An additional dashboard provided users with insights on segmented data.

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DATA
COLLECTORS
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SERVICING
DASHBOARD
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INSIGHTS
DASHBOARD
JSF 2.0
MONGO DB
SPRING INTEGRATION
GNIP STREAMING API
RADIAN 6 API
RABBIT MQ
HAZEL CAST

BETA RELEASE

The product was released to a selected enterprise customer base. Informative and actionable feedback and stats from actual users helped refine the requirements for the release version of the product.

PRODUCTION

We redesigned the user experience based on feedback gathered by InTheChat.

Architectural improvements were shaped to make the system more efficient and ready for a broader audience.

Tools were developed to monitor and manage the infrastructure in real-time. Automatic alerting systems were created and put in place to ensure minimum system down time.

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IMPROVED
UI
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REFINED
ARCHITECTURE
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INFRASTRUCTURE
MONITORING
RUBY ON RAILS
BOOTSTRAP + LESS
RJB (RUBY JAVA BRIDGE)

OPTIMIZATION & RELIABILITY

AWS AutoScaling and optimal redistribution of load was setup to reduce running costs and provide greater scalibility. Replication policies for operations and data servers was enforced to ensure continuous and reliable availability of the service.

MONGO DB
AMAZON WEB SERVICES
PAGER DUTY