Google A Room with a View: Understanding Users Stages in User Manual

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A Room with a View: Understanding
UsersStages in Picking a Hotel Online
Abstract
We describe how we built a model for user decision-
making during local search tasks, specifically hotels. We
differentiate between affective and functional needs and
identify the following stages and related information
needs: 0. Lay of the land; 1. Generating options; 2.
Scanning for attractors and detractors; 3. Due
diligence. We contrast this framework with existing
consumer decision-making models. We close by
describing how this model influenced the development
of the recently launched experiment, Google Hotel
Finder.
Keywords
Local search; consumer decision-making; online search
ACM Classification Keywords
H.5.2. [User Interfaces]: User-centered design;
General Terms
Design, Human Factors
Introduction
A quick comparison of a set of typical local searches,
such asshops’, ‘bars,restaurants’, ‘hotelsshows that
searches for hotels were the most frequent of this
group in the US in 2010 [2]. Yet choosing a hotel
Copyright is held by the author/owner(s).
CHI 2012, May 5–10, 2012, Austin, TX, USA.
ACM 978-1-4503-1016-1/12/05
Jens Riegelsberger
Google UK
76 Buckingham Palace Road
London, SW1W 9TQ, UK
Michelle Lee
Google Inc.
76 Ninth Avenue
New York, NY 10011, US
mishmosh@gmail.com
Scott Lederer
Google Inc.
76 Ninth Avenue
New York, NY 10011, US
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Summary of Contents

Page 1 - Introduction

A Room with a View: Understanding Users’ Stages in Picking a Hotel Online Abstract We describe how we built a model for user decision-making during

Page 2 - Findings

should be less frequent than choosing a restaurant: for 3-day trip, a traveler might choose 3 restaurants, but stay at only 1 hotel. The disproportio

Page 3 - Implementation

Figure 1: 4 stages of hotel search STAGES. Across participants we could see stable stages of decision-making (Figure 1). Note that these stages are t

Page 4 - Conclusions

users not familiar with an area, highlighting busy areas vs. residential ones. Location / Price / Quality: An editable polygon allows filtering on lo

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