Dataiku Case Studies Predictive Content Management for PagesJaunes

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	Predictive Content Management for PagesJaunes Dataiku

Predictive Content Management for PagesJaunes

Dataiku

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning
Applicable Industries	Telecommunications
Applicable Functions	Sales & Marketing
Services	Data Science Services
Challenge	PagesJaunes.fr, the French equivalent of the YellowPages, is a leader in local advertising and information on web, mobile, and print, generating hundreds of millions of queries each year. The quality and relevance of results is a top priority for PagesJaunes. Category managers are responsible for maintaining the quality and relevance of the directory by creating the pertinent associations between terms and categories. The challenge was to improve user experience without increasing workload. The client wanted a solution that would help them measure and improve customer satisfaction, help Category Managers automatically detect and correct problematic queries, and optimize the quality of results to improve customer satisfaction. Read More
About Customer	PagesJaunes.fr is the French equivalent of the YellowPages. It is the French leader in local advertising and information on web, mobile, and print, with annual revenue of over $1Billion. More than 80% of the French rely on PagesJaunes.fr to get information or promote their activity. The company is one of Dataiku’s core clients. PagesJaunes is constantly looking to improve customer satisfaction while also improving Category Manager’s productivity. Read More
Solution	With Data Science Studio (DSS), PagesJaunes built an app that scores customer satisfaction. The app gathers search engine data and analyses them to isolate unsuccessful queries. An algorithm was created to compute a score for every query and is then used to predict which queries will provide unsatisfactory results for users. The algorithm is fed with qualified and enriched usage data. The technology eventually targets the engine’s failures enabling category managers to focus their operations on those failures. The solution also involved training more than ten PagesJaunes’ collaborators in Big Data technologies such as Hadoop, machine learning, and statistics with DSS. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Analytics & Modeling - Machine Learning

Applicable Industries

Telecommunications

Applicable Functions

Sales & Marketing

Services

Data Science Services

Challenge

PagesJaunes.fr, the French equivalent of the YellowPages, is a leader in local advertising and information on web, mobile, and print, generating hundreds of millions of queries each year. The quality and relevance of results is a top priority for PagesJaunes. Category managers are responsible for maintaining the quality and relevance of the directory by creating the pertinent associations between terms and categories. The challenge was to improve user experience without increasing workload. The client wanted a solution that would help them measure and improve customer satisfaction, help Category Managers automatically detect and correct problematic queries, and optimize the quality of results to improve customer satisfaction.

About Customer

PagesJaunes.fr is the French equivalent of the YellowPages. It is the French leader in local advertising and information on web, mobile, and print, with annual revenue of over $1Billion. More than 80% of the French rely on PagesJaunes.fr to get information or promote their activity. The company is one of Dataiku’s core clients. PagesJaunes is constantly looking to improve customer satisfaction while also improving Category Manager’s productivity.

Solution

With Data Science Studio (DSS), PagesJaunes built an app that scores customer satisfaction. The app gathers search engine data and analyses them to isolate unsuccessful queries. An algorithm was created to compute a score for every query and is then used to predict which queries will provide unsatisfactory results for users. The algorithm is fed with qualified and enriched usage data. The technology eventually targets the engine’s failures enabling category managers to focus their operations on those failures. The solution also involved training more than ten PagesJaunes’ collaborators in Big Data technologies such as Hadoop, machine learning, and statistics with DSS.

Impact #1	Closely monitoring and managing unsuccessful searches
Impact #2	Automatically detecting the most critical signals & applying the most relevant rules when interpreting a query
Impact #3	Targeting and fixing false query results

Impact #1

Closely monitoring and managing unsuccessful searches

Impact #2

Automatically detecting the most critical signals & applying the most relevant rules when interpreting a query

Impact #3

Targeting and fixing false query results

Benefit #1	30% Boost in Category Manager Productivity
Benefit #2	Improved Customer Satisfaction
Benefit #3	Easy Integration in Big Data Environment (>10Tb)

Benefit #1

30% Boost in Category Manager Productivity

Benefit #2

Improved Customer Satisfaction

Benefit #3

Easy Integration in Big Data Environment (>10Tb)

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Overview

Predictive Content Management for PagesJaunes

Operational Impact

Quantitative Benefit