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AWS Media and Entertainment India

ShemarooMe

Marketing Personalization

Shemaroo Entertainment Ltd. (Shemaroo) is a media company in India specializing in creating, aggregating, and distributing a wide range of content, including Bollywood blockbusters, classic movies, regional films, and originals.

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"By using Amazon Personalize, we increased video watch time by more than 80 percent, and we eventually increased the number of viewers who watch our short videos by 88 percent,"...
"The algorithm and its implementation have contributed to the development of a precise recommendation engine, which has resulted in increased engagement and a better experience...
80% increase in video watch time
88% increase in short video viewers

Reported impact

Business outcome

Since implementing Amazon Personalize, ShemarooMe experienced a significant boost in video viewer uplift, which measures overall minutes of watch time. "By using Amazon Personalize, we increased video watch time by more than 80 percent, and we eventually increased the number of viewers who watch our short videos by 88 percent," says Kinnari.

  • Customer Experience
  • Revenue Growth

Solution

Shemaroo Entertainment Limited , a media and entertainment conglomerate in India, operates multiple broadcast channels, including its OTT platform ShemarooMe, and more than 50 YouTube channels. The company built a new short video offering, Clips, on its ShemarooMe mobile app, using Amazon Personalize With Amazon Personalize bringing users tailored content on Clips based on their consumption patterns, geolocation, language, and genre, ShemarooMe increased video watch time by almost 80 percent and expects to see revenue growth through increased retention and engagement, aiding uptake in subscriber growth as well as monetizable advertising inventory. Since its inception, the ShemarooMe OTT platform has been running on Amazon Web Services (AWS), utilizing AWS services like Amazon Simple Storage Service (Amazon S3), Amazon CloudFront AWS Lambda , and Amazon Elastic Compute Cloud (Amazon EC2).

Data flow

When users view popular short videos on ShemarooMe, these interactions are ingested into Amazon Personalize in real-time, to further fine tune the recommendations based on data points collected.

Solution architecture

5 components · 3 layers
  1. Compute
    • AWS Lambda Executes serverless processing and workflow glue for the personalization and recommendation workflows.
    • Amazon EC2 Provides scalable compute capacity for the personalization and recommendation workflows.
  2. Storage
    • Amazon S3 Stores source data, documents, or generated artifacts used by the personalization and recommendation workflows.
  3. Serving
    • Amazon Personalize Generates individualized recommendations for the personalization and recommendation workflows.
    • Amazon CloudFront Delivers content for the user-facing parts of the personalization and recommendation workflows.

Architecture clues

  • When users view popular short videos on ShemarooMe, these interactions are ingested into Amazon Personalize in real-time, to further fine tune the recommendations based on data points collected.

Evidence from the source

Amazon Personalize helps developers build and deploy curated recommendations and intelligent user segmentation using machine learning (ML) technology.
For its Clips platform, ShemarooMe opted for Amazon Personalize, integrating advanced artificial intelligence (AI) capabilities into the short video platform to achieve a higher level of personalization and enhance business value.
Shemaroo's over-the-top (OTT) platform, ShemarooMe , streams content to millions of users and provides access to more than 4,300 movies, television shows, music videos, and channels.
Since its inception, the ShemarooMe OTT platform has been running on Amazon Web Services (AWS), utilizing AWS services like Amazon Simple Storage Service (Amazon S3), Amazon CloudFront AWS Lambda , and Amazon Elastic Compute Cloud (Amazon...
The Amazon Personalize algorithm is continuously being refined and complemented with rich data sets for the business, and the flexibility of the solution allows ShemarooMe to incorporate its own user-level consumption into the...
The company built a new short video offering, Clips, on its ShemarooMe mobile app, using Amazon Personalize With Amazon Personalize bringing users tailored content on Clips based on their consumption patterns, geolocation, language, and...
Transparency Evidence & methodology 95/100 reference value · 87% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. AWS

    ShemarooMe customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/shemaroo/
    Source type
    Vendor-published customer story
    Published
    Apr 19, 2024
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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