Indegene’s AI solution cuts time to market by 90% and improves content discoverability for a global pharma company

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The Customer

A global pharma leader with 350+ products spanning 150+ markets faced limitations with their existing closed-loop marketing (CLM) application. Limited content discoverability, laborious file searches, and inadequate customer insights were hindering their time-to-market efficiency.

Indegene first introduced Indegene Closed Loop Marketing (iCLM), a customizable search interface for tagged keyword–based content discoverability. Taking it a step further, Indegene implemented its proprietary artificial intelligence (AI) platform, Read more about Indegene’s NEXT Technology PlatformsNEXT Commercial Content Intelligence, as a fully automated keyword tagging solution.

Team reviewing data analytics on a large display

Challenges

  1. Manual keyword generation and entry into systems of record led to inconsistent selection of potential keywords, which in turn resulted in increased review and approval efforts.

  2. Manual keyword generation required an increased dependency on medically trained personnel.

  3. Scaling resources based on fluctuating content tagging demand proved challenging.

  4. Generating keywords in multiple languages required recruitment and extensive collaboration of language experts, medical specialists, approval teams, and the program management team, proving nearly impossible to operate efficiently.

The Solution

Indegene’s proprietary AI platform, NEXT Commercial Content Intelligence, was introduced to address the challenges faced in manual keyword generation. This AI platform:

  • Scanned content present in digital assets and auto-identified keywords aligned with search behavior, while adhering to the language and business requirements.
  • Enabled keyword identification across 18+ languages, including English, German, French, Spanish, Portuguese, Turkish, Italian, and Chinese.
  • Provided solutions that were customized and configured with specific machine learning (ML) models, user interfaces, report generation, and deep integration using workflow management platforms, such as Indegene’s NEXT Content Collaboration, to cater to the customer’s specific needs.
  • Ensured that the models were continually retrained using ML pipelines with feedback from content SMEs and market stakeholders, helping it expand its scope from 7 categories to 28 and achieving optimal discoverability.

Outcomes

After a successful pilot in a single market, the customer expanded automated keyword generation using NEXT Commercial Content Intelligence keyword tagging to 30+ markets in 18+ languages, while tagging over 200,000 pages of content in the process. This solution has also been integrated into their content production process and marketing technology platforms for continuously tagging newly generated content, greatly enhancing the content discoverability and use of content by teams the world over.

28%

reduction in repeated searches

<1%

customer change requests

90%

improved time to market

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