It is important to ensure that consumers trust the way the company uses their data; when giving consent, they expect that the company will be transparent and fair with their data. If the question arises about exploitation, the users will lose their trust in the company, especially if the data was used without consent and…… Continue reading Ethical E-commerce: Navigating the Data Maze
Category: E-commerce
Understanding Your Audience: ACUA’s Age Analytics
In the dynamic landscape of social media, understanding your audience is crucial. The nuances of demographics often hold the key to crafting engaging and targeted content strategies. One of ACUA’s standout features lies in dissecting the age demographics of your audience, providing invaluable insights into the age groups engaging with your content. Actionable Use Cases…… Continue reading Understanding Your Audience: ACUA’s Age Analytics
What Information to Include in a Persona Profile?
Algorithmically generated personas have emerged as quintessential tools for understanding audiences, customers, and users, bridging data analytics and human-centric experiences. These algorithmically-generated personas (APGs) are at the intersection of user experience research, marketing strategies, and product development, and APGs are realistically crafted identities that mirror the varied facets of a target audience, customer, or user…… Continue reading What Information to Include in a Persona Profile?
Boosting Your Startup’s Reach: The Power of ACUA’s Story-Optimizer
Story-Optimizer is a feature in the ACUA system that leverages Large Language Models to generate content tailored for different social media platforms. When provided with a publication prompt, this tool refines the input and produces captions/titles optimized for each specific platform i.e. a suitable Facebook post, an appropriate YouTube video title, an effective Instagram post,…… Continue reading Boosting Your Startup’s Reach: The Power of ACUA’s Story-Optimizer
How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation
What algorithm to choose for customer segmentation? Should you use one algorithm or many? How many customer segments should you create? How to evaluate the results? In this research, we conduct a systematic literature review to address such central questions in customer segmentation research and practice. The results from extracting information from 172 relevant articles…… Continue reading How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation
Personas for our forthcoming book, “Understanding Audiences, Customers, and Users via Analytics”
For our forthcoming book, “Understanding Audiences, Customers, and Users via Analytics”, we have three personas that we used to focus the book’s content: one designer, one professor, and one industry researcher. Mary is a senior user experience designer who wants her organization to use analytics for several major projects. She is familiar with some analytics…… Continue reading Personas for our forthcoming book, “Understanding Audiences, Customers, and Users via Analytics”
Analytics Systems are Sporadic Use but Constant Collection
Analytics systems are information services that are used to analyze and interpret data to gain insights, identify patterns, and support decision-making processes. Analytics systems are one of the unique information services that are a combination of sporadic use but require constant data collection. Sporadic or occasional use information systems are information services that are used…… Continue reading Analytics Systems are Sporadic Use but Constant Collection
Will They Take This Offer? A Machine Learning Price Elasticity Model for Predicting Upselling Acceptance of Premium Airline Seating
Employing customer information from one of the world’s largest airline companies, we develop a price elasticity model (PREM) using machine learning to identify customers likely to purchase an upgrade offer from economy to premium class and predict a customer’s acceptable price range. A simulation of 64.3 million flight bookings and 14.1 million email offers over three years…… Continue reading Will They Take This Offer? A Machine Learning Price Elasticity Model for Predicting Upselling Acceptance of Premium Airline Seating
Comparison of Google Analytics and SimilarWeb for Web Analytics
Approaches to collecting website analytics data can be grouped by the focus of data collection efforts, resulting in the emergence of three general methodologies, namely: user-centric, site-centric, and network-centric. Two industry standard and popular web analytics platforms are Google Analytics and SimilarWeb. Google Analytics is a site-centric service, and SimilarWeb is a user-centric service that…… Continue reading Comparison of Google Analytics and SimilarWeb for Web Analytics
Measuring user interactions with websites: A comparison of two industry standard analytics approaches using data of 86 websites
Measuring user interactions with websites: A comparison of two industry standard analytics approaches using data of 86 websitesThis research compares four standard analytics metrics from Google Analytics with SimilarWeb using one year’s average monthly data for 86 websites from 26 countries and 19 industry verticals. The results show statistically significant differences between the two services…… Continue reading Measuring user interactions with websites: A comparison of two industry standard analytics approaches using data of 86 websites