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Personalise product recommendations to target prospective customers

Personalise product recommendations and advertising to target individual consumers who are not yet customers (according to pre-defined internal data - this may not necessarily be the consumer''s perspective).

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Revenue

Revenue - Sales effectiveness improvement

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Revenue

Revenue - Personalisation

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Revenue

Revenue - Customer experience

Description

Personalise product recommendations to target prospective customers

Benefits & ROI

1.1

Linked Case Studies

Namaste Technologies

Namaste Technologies plans to increase average order value, customer retention and conversion rates using machine learning through acquisition of Findify technology

Atolla Skin Lab

Atolla identifies skin health issues and recommends skin care products using machine learning

Sears exceeded the target customer numbers in 50% less time by better segmenting customers to improve loyalty programme and marketing campaign effectiveness with machine learning

Carrefour increased online sales by targeting customers on multiple devices

Cosabella increased ROAS to 336% by segmenting target markets, and optimising channel selection, campaign content, and paid search using Adgorithm''s deep learning

Google YouTube drives 60% of video clicks through its machine learning recommendation system for users

Amazon makes personalised product recommendations to customers with machine learning

Trulia achieves double-digit increase in consumer engagement through a more personalized, predictive experience using machine vision

Amazon provides customers with product suggestions according to its recommendation algorithm which improves upon machine learning techniques to scale with its large product catalogue

''Rooms to go'' uses Machine Learning to offer tailored add-on options to customers

Target increases express shopping via Google by 20% with personalised recommendations using machine learning

Baidu improves ad targeting for its online users resulting in increased advertising revenue through deep learning

My Beauty Matches

My Beauty Matches drives higher conversion rates and life time value for retail partners using machine learning to personalise customer recommendations

Smashbox cosmetics improves mobile app conversion rates by 27% using eye-tracking technology to improve customer user experience

TGI Fridays creates a customised beverage recommendation system on the restaurant''s mobile app

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Source: mckinsey.com · Editor: original-sdg