MSc (University of Warwick), PhD (University of Portsmouth), Fellowship (Haas School of Business, University of California, Berkeley, US)
Assistant Professor in Marketing
Department: MarketingE-mail: Amir.Homayounfard@nottingham.ac.ukTel: +44 (0) 115 8466133
Location: B71 (North Building, Jubilee Campus)
Amir Homayounfard holds a BSc, MSc, and Ph.D. He serves as an Assistant Professor of Marketing and a fellow in Business Innovation at the Haas School of Business, University of California, Berkeley, US.
He actively collaborates with companies across the UK to address industry challenges in marketing, digital and data analytics, and developing innovation capabilities. Amir has 17 years of extensive experience in driving growth and leading marketing initiatives across IT, digital solutions, e-commerce, wholesale, and ESG. He specializes in crafting data-driven marketing strategies and excels at leveraging AI techniques, analytics, and digital tools to optimize search capabilities, automation, and campaign performance. His expertise also includes information retrieval from structured and unstructured data sources, semantic analysis, predictive search and analytics, machine learning, ranking and prioritisation, A/B testing, entity recognition, and delivering measurable KPIs and ROIs.
He has been involved in different projects focused on utilizing analytics for diverse marketing initiatives. Amir has a proven track record of leading cross-functional teams, managing multi-channel marketing campaigns, and executing budget-conscious strategies focused on measurable outcomes. He is skilled in utilizing AI search capabilities, CRM, and CMS tools for customer engagement, with advanced proficiency in digital and data analytics and BI tools. Additionally, he has led projects targeting bespoke marketing initiatives, budget and KPI management, data-driven ROI management, stakeholder and agency collaboration, data-driven campaign management, team building and mentorship, cross-functional leadership, and data wrangling and modeling. His budget management skills ensure marketing solutions that maximize resources and finances with measurable KPIs.
Amir's industry involvement has generated case studies with practical and managerial impacts, as well as grants and funding, including those from Innovate UK and Innovation Vouchers Schemes, alongside publications with practical implications. Before joining NUBS, he worked across sectors in the UK and was an Assistant Professor of Marketing & Analytics at the Essex Business School, University of Essex, UK.
Areas of ExpertiseAmir's work and interests are centered on empirical and methodological outputs, utilizing quantitative, qualitative, or both methods.
His research interests revolve around service research, analytics, B2B marketing, and innovation management. These encompass B2B services, industrial relationships, services and AI, data analytics, statistical analytics, digital analytics, data-driven services, customer experience (CX), service innovation, high-tech services, leveraging technological innovation, marketing strategy, and customer relationship management (CRM).
Amir is open to supervising Ph.D. applicants aligned with his research interests.
The following lists my publications from 2014 to the present day.
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Amir has served as the module convenor (leader) for various modules including PG Generating Customer Insights and Analytics, PG Digital Customer Experience and Applications, Executive MBA Marketing, Full-time and Executive MBA B2B Marketing, UG Marketing Analytics, and Full-time MBA Strategic Market Relations, across both UK and International campuses.
He is also a Fellow of the Higher Education Academy (FHEA).
Amir is module convenor of the following module(s):
MSc
Digital Customer Experience and Applications (BUSI4649)
Digital Marketing Challenge (BUSI4653)
Generating Customer Insights and Analytics (BUSI4652)
MBA
Strategic Market Relations: Building, Managing, & Leveraging Market Relationships (BUSI4388)
Details of all modules can be found on
MyNottingham
Amir's work and interest focus on empirical and methodological outputs, utilizing quantitative, qualitative, or both methods. He has been published in various peer-reviewed international journals, such as the Journal of Business Research, IEEE Transactions on Engineering Management, and Service Industries Journal.
Amir regularly serves as an ad-hoc reviewer for international, peer-reviewed journals, including Industrial Marketing Management (IMM), Journal of Business Research (JBR), and Technological Forecasting & Social Change (TFSC).
He is currently involved in three nationally funded projects, acting as the principal and co-investigator. These projects focus on incorporating marketing and analytics techniques and tools, developing SaaS (Software as a Service), AaaS (Analytics as a Service), PaaS (Platform as a Service), and IaaS (Infrastructure as a Service) capabilities, along with enhancing customer experience (CX). These initiatives also encompass knowledge transfer partnerships (KTP) like Business KTP, Management KTP, and Engineering KTP, supported by various governmental bodies.
1- AI & SaaS Product Design and Strategy Lead (focused on high-tech B2B services, machine learning, CX, digital technologies/ digital business)
This project aims to drive a transformation of an AI-specialized business, enabling greater productivity and a scale of impact in their mission to build AI capability in a B2B enterprise. Incorporating marketing and leveraging digital and data analytics, the project focuses on building the skills and systems of a scalable SaaS business. Mastering a go-to-market strategy will empower us to forge robust partnerships and scalable business models for our expanding AI SaaS platform. By employing predictive search, we will enhance our B2B service targeting and elevate the overall B2B CX. Our initiative will transform operations by boosting B2B scalability and driving an increase in success for the firm, clients, and partners. It will also harness machine learning algorithms for search relevance, facilitating cross-functional collaboration and delivering unparalleled results.
2- Productivity, Organizational Change, and Technology Implementation (focused on professional services, AI search capabilities, CX, AaaS, IaaS, and digital technologies/ digital business)
The project aims to transform current management practices to enhance optimization and boost profits by integrating marketing, digital, and data analytics throughout all aspects of the business. It will support the achievement of strategic and technological objectives by developing digital and data-led capabilities and enhancing the B2B customer experience. This includes utilizing digital and analytics tools for strategic product/pricing, process and system efficiency, and automation, as well as establishing and applying data-led and measurable KPIs to evaluate the current market position. The project will revamp systems by implementing an ERP system and designing innovative CRM platforms. It will harness marketing insights, digital strategies, and data analytics to boost efficiency and effectiveness across multiple customer touchpoints. By deploying machine learning algorithms and semantic search for search relevance, it will empower predictive decision-making and enhance strategic outcomes. The initiative innovatively transformed customer engagement, demonstrating our leadership and excellence in cross-functional collaboration. By integrating information retrieval from structured and unstructured sources, the project increased customer interaction, driving substantial improvements in user satisfaction and loyalty.
3- AI-driven Systems for emerging service clusters (focused on high-tech services, machine learning, AI search capabilities, AaaS, CX, and PaaS)
The project targets an improvement in both B2B and B2C CX by innovating machine learning models to proactively recognize personalization opportunities and enhancements. It aims to harness predictive analytics to increase sales forecasting accuracy and speed across varied price points. This involves assessing critical factors such as market conditions, product popularity, features, pricing, branding, and promotional strategies. The method incorporates active learning for ranking and prioritization, informed by journey mapping and technical feasibility studies. It analyzes and optimizes content generation processes and modeling techniques while refining channel and platform strategies to enhance customer engagement. Through rigorous user testing, the project aims for a user satisfaction increase as part of the CX journey. The project tackles complex data management challenges, utilizing machine learning algorithms for search relevance to recommend impactful actions for both B2B and B2C clients. Through dynamic cross-functional collaborations, the project also utilizes semantic search to understand context, boosting efficiency and productivity.
Amir is currently the lead supervisor for the following PhD students:
Mingyu Yuan
I Gde Yudhi Hendrawan
Ke Wang
Amir is currently supervising the following Research Students:
I Gde Yudhi Hendrawan
Mingyu Yuan
School Administrative Roles
Co-Director of MSc Digital Marketing