Guavus Case Studies MNO Maximizes Campaign Performance for Advertisers using Guavus-IQ Analytics

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	MNO Maximizes Campaign Performance for Advertisers using Guavus-IQ Analytics Guavus

MNO Maximizes Campaign Performance for Advertisers using Guavus-IQ Analytics

Guavus

Technology Category	Analytics & Modeling - Big Data Analytics Analytics & Modeling - Machine Learning
Applicable Industries	Telecommunications
Applicable Functions	Sales & Marketing
Services	Data Science Services
Challenge	The marketing team of a Mobile Network Operator (MNO) was struggling to build rich customer profiles to present relevant offers and ads to their subscribers. They needed to match individual preferences and browsing behaviors with subscriber IDs. Additionally, they needed to accurately categorize website URLs viewed with accuracy levels of 80% or greater. However, they were unable to achieve this with the software tools they had in place. Read More
About Customer	The customer in this case study is a Mobile Network Operator (MNO). The MNO's marketing team was facing challenges in understanding their customers' preferences to provide advertisers with accurate information. They were unable to accurately categorize the websites visited, track Ad-IDs, and match these with subscribers to build rich customer profiles. The MNO needed a solution that could help them understand their customers better, categorize websites quickly, reduce time to market, correlate IMSI to Ad-ID at a subscriber level while keeping subscribers’ details private, and improve the customer experience by making more relevant marketing offers based on comprehensive subscriber profiles. Read More
Solution	The MNO implemented Service-IQ Marketing Analytics, a product of Guavus-IQ. This solution provides content categorization on a per subscriber basis that can be used to create personalized and relevant offers. It uses advanced machine learning algorithms to automatically categorize web pages visited to characterize subscribers’ interests. The machine interprets the page content semantically, not just syntactically word by word, achieving over 94% accuracy in the categorization. Service-IQ Marketing Analytics also manages the matching of individual preferences and browsing behaviors with subscriber IDs to build rich customer profiles. This helps marketers make the correct assumptions about the content that their audiences like. The solution also tracks the Ad-ID of digital assets throughout their network and associates it to an individual’s international mobile subscriber identity (IMSI), keeping the identity of the user private while providing the advertising agencies and businesses the information they need. 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

The marketing team of a Mobile Network Operator (MNO) was struggling to build rich customer profiles to present relevant offers and ads to their subscribers. They needed to match individual preferences and browsing behaviors with subscriber IDs. Additionally, they needed to accurately categorize website URLs viewed with accuracy levels of 80% or greater. However, they were unable to achieve this with the software tools they had in place.

About Customer

The customer in this case study is a Mobile Network Operator (MNO). The MNO's marketing team was facing challenges in understanding their customers' preferences to provide advertisers with accurate information. They were unable to accurately categorize the websites visited, track Ad-IDs, and match these with subscribers to build rich customer profiles. The MNO needed a solution that could help them understand their customers better, categorize websites quickly, reduce time to market, correlate IMSI to Ad-ID at a subscriber level while keeping subscribers’ details private, and improve the customer experience by making more relevant marketing offers based on comprehensive subscriber profiles.

Solution

The MNO implemented Service-IQ Marketing Analytics, a product of Guavus-IQ. This solution provides content categorization on a per subscriber basis that can be used to create personalized and relevant offers. It uses advanced machine learning algorithms to automatically categorize web pages visited to characterize subscribers’ interests. The machine interprets the page content semantically, not just syntactically word by word, achieving over 94% accuracy in the categorization. Service-IQ Marketing Analytics also manages the matching of individual preferences and browsing behaviors with subscriber IDs to build rich customer profiles. This helps marketers make the correct assumptions about the content that their audiences like. The solution also tracks the Ad-ID of digital assets throughout their network and associates it to an individual’s international mobile subscriber identity (IMSI), keeping the identity of the user private while providing the advertising agencies and businesses the information they need.

Impact #1	Better understanding of customers through the collection and categorization of subscribers’ interests.
Impact #2	Quick categorization of websites visited to reveal customer preferences using machine learning.
Impact #3	Understanding of what customers need faster to present more desirable offers.

Impact #1

Better understanding of customers through the collection and categorization of subscribers’ interests.

Impact #2

Quick categorization of websites visited to reveal customer preferences using machine learning.

Impact #3

Understanding of what customers need faster to present more desirable offers.

Benefit #1	94% accuracy in website content categorization per subscriber.
Benefit #2	Processing of over 32 billion records per day.

Benefit #1

94% accuracy in website content categorization per subscriber.

Benefit #2

Processing of over 32 billion records per day.

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Overview

MNO Maximizes Campaign Performance for Advertisers using Guavus-IQ Analytics

Operational Impact

Quantitative Benefit