Oxford Retail Futures Conference: Big Data, Business Intelligence and Real-time Analytics in Retail

Transcription

1 Oxford Retail Futures Conference: Big Data, Business Intelligence and Real-time Analytics in Retail 10 th December, 2013

2 CONFERENCE TIMETABLE Venue: Lecture Theatre VI, West Wing, Saïd Business School 08:30 Coffee and registration (Club Room) 09:00 Welcome, introductions and opening remarks Richard Cuthbertson and Wojciech Piotrowicz, Oxford Institute of Retail Management, University of Oxford, UK 09:15 Opening talk - Big Data and new business models Janet Smart, Saïd Business School, University of Oxford, UK 09:45 Changing retail places in Britain Wojciech Piotrowicz and Jonathan Reynolds, Oxford Institute of Retail Management, University of Oxford, UK 10:15 Coffee/tea (Club Room) Sessions will be in the panel format: 10 minutes presentation per participant (maximum five slides), followed by discussion. 10:45 Panel one (Big Data in Retail) An exploratory study of Big Data utilisation within the Fashion Sector Karinna Nobbs, London College of Fashion, United Kingdom, Gretchen Harnick, Parsons, the New School, United States and Michaela Wolf, Independent Digital Luxury Marketer, UK Business Intelligence for building the competitive advantage in retail industry Celina Olszak, University of Economics in Katowice, Poland Big Data on the Web: using multistage competing risks approaches to model Web page transitions Horst Treiblmaier, Logistikum Steyr, Austria, Patrick Mair, Harvard University, USA and Paul Lowry, City University of Hong Kong Exploiting customer intelligence by retailers to transform inactive customers into active ones Sanda Renko, Faculty of Economics and Business, University of Zagreb, Croatia 12:30 Lunch (Hot and cold buffet, Pyramid Room) 2

3 13:45 Panel two (Loyalty programmes and online consumers) The effects of market structure on online consumer search: a cross-sector analysis of the German retail market Christopher Holland and Julia Jacobs, Manchester Business School, University of Manchester, UK Shopper cards: beyond data and discounts Don Schultz and Martin Block, Northwestern University, USA Does medium play a difference in promotional communication? Testing the effectiveness of promotional flyers through different channels Cristina Ziliani, University of Parma, Juan-Carlos Gazquez-Abad, University of Almerìa and Marco Ieva, University of Parma, Italy Exploring customer motivations to engage in virtual fashion communities: implications for retailers Nicoletta Occhiocupo and Mareike Friess, Oxford Brookes University, UK 15:15 Coffee/tea (Club Room) 15:45 Panel three (Retail supply chain management) Decisions in demand: exploring alignment between supply and sales forecasts in the retail food supply chain Amir M Sharif and Zahir Irani, Brunel Business School, Brunel University, UK Antecedents and consequences of supply chain management practices: a study of Indian organized retailing Mohua Banerjee and Gopal Das, IMI- Kolkata, India Supply chain management based on logistic and statistical indicators Marcin Hajdul and Karolina Kolińska, Institute of Logistics and Warehousing, Poland 17:00 Announcements Meng Lu, Coordinator, SoCool@EU; Dutch Institute for Advanced Logistics (Dinalog) 17:15 Closing remarks Richard Cuthbertson and Wojciech Piotrowicz, Oxford Institute of Retail Management, University of Oxford, UK 3

4 An exploratory study of Big Data utilisation within the Fashion Sector Karinna Nobbs, London College of Fashion, United Kingdom, Gretchen Harnick, Parsons, the New School, United States and Michaela Wolf, Independent Digital Luxury Marketer, UK Today it can be argued that a fashion brand who does not embrace the potential of the hot topic that is big data will be left behind as its competitors flourish through the ability to predict what their customers want and create products and services to meet and exceed their expectations (Business of Fashion 2013, Mashable 2012). The aim of this study is to define the concept of big data within the context of the fashion sector and to investigate its level of adoption. Furthermore the research will adopt a holistic approach to the topic to include not just fashion businesses but it will consider the impact of big data on other stakeholders in the fashion supply/demand chain like investors, academia, media, consumers and manufacturing and supply. Due to the complex nature of the topic, the study adopts a qualitative interpretivist approach. Business Intelligence for building the competitive advantage in retail industry Celina Olszak, University of Economics in Katowice, Poland The main objective of the paper is to provide an overview of the issue of Business Intelligence (BI) and to explore the various BI applications for the retail industry. The research questions I ask in this study are as follows: what BI applications and tools should be used in the retail industry in order to take the competitive advantage on the market?. The study was based on: (1) a critical analysis of literature, (2) an observation of different BI initiatives undertaken in various retail organizations, (3) proposal of building the competitive advantage with BI for retail industry. The structure of this paper is organized as follows. Firstly, an overview of subject literature on BI has been conducted. Then, the model of building the competitive advantage through BI was explained. Next, the most important BI solutions for the retail industry have been preceded. Finally, some recommendations were provided in order to improve the using of BI applications in retail industry. 4

5 Big Data on the Web: using multistage competing risks approaches to model Web page transitions Horst Treiblmaier, Logistikum Steyr, Austria, Patrick Mair, Harvard University, USA and Paul Lowry, City University of Hong Kong In this paper we use competing risks models in order to show how dwell times can be applied to predict users online behavior. Unlike Markov chain approaches, survival analysis does not assume independence over time, and it allows for the inclusion of dwell times and covariates that may influence users navigation behavior. We model transitions between pages based upon the dwell time of the initial state and then analyze data from a retailer s web shop, illustrating how pages that are linked compete against each other. The preliminary results show significant differences in transition behavior between buyers and non-buyers, which allow organizations to identify potential customers dynamically online. We estimate relative risks for web page transitions based on the dwell time within a clickstream. Our method allows researchers and practitioners to perform clickstream analysis in a detailed manner not previously possible. The effects of market structure on online consumer search: a cross-sector analysis of the German retail market Christopher Holland and Julia Jacobs, Manchester Business School, University of Manchester, UK Online panel data is an important category of big data and creates new research opportunities to analyse online behaviour. The search process is a key aspect of online behaviour and an essential element of the competitive process. Consumer search is analysed in a cross-sector study of the German retail market. Two constructs are used to measure the search process: the online consideration set; and time spent per brand. The online consideration sets range from 2.31 to 2.6, which are much smaller than expected compared to pre-internet results and expected outcomes from economic theory. However, they are consistent with the few studies that used online panel data in the US and the UK. It is shown that the online consideration set is a function of market structure, and time spent per brand is related to product complexity and risk. Some possible theoretical explanations are proposed to explain the observed search process, and the managerial implications of the results are outlined. 5

6 Shopper cards: beyond data and discounts Don Schultz and Martin Block, Northwestern University, USA Based on responses to a U.S. online study of 1,100,000+ consumers over a ten year period ( ), covering 73 product categories and 1,500+ fast-moving-consumer-goods, it was found that Store Shopper Cards (loyalty cards) were the 4th most influential promotional technique out of a group of 23 in-store promotional tools. Cards were more influential than In-store Displays and Shelf Signs in influencing brand preference. Comparisons of consumer holdings, usage and impact of Store Shopper Cards in food, drug and electronics retailers are discussed. The study answers some of the questions regarding the value of Hi- Lo pricing and EDLP strategies. Exploiting customer intelligence by retailers to transform inactive customers into active ones Sanda Renko, Faculty of Economics and Business, University of Zagreb, Croatia Retailers have understood that customers are what sustain their business. Therefore, they need a full portrait of each customer and are collecting all kinds of data about them, i.e. information about customers existing and future needs, their profitability, behaviour and trends in purchasing. The repository for this large amount of data has become known as a data warehouse relies on data mining and together lead to customer intelligence. This paper is examining customer intelligence in providing insight into customer s needs, attitudes and behaviours towards particular retailer, and getting the true benefit of the data about customers. Based on the results of the study conducted among retail companies in different retail categories, which operate on the Croatian market, it was proved that Customer Intelligence helped retailers to evaluate their customers and to reactivate their purchases. 6

7 Does medium play a difference in promotional communication? Testing the effectiveness of promotional flyers through different channels Cristina Ziliani, University of Parma, Juan-Carlos Gazquez-Abad, University of Almerìa and Marco Ieva, University of Parma, Italy With new media and touch points emerging every day and shoppers taking advantage of multiple channels, retailers are called to review their strategies in a multichannel perspective, including communication and promotional strategies. The promotional flyer an old media still commanding 50% of retail communication budget in many countries is mutating accordingly: retailers are investing in the digital version of the flyer, aiming for substitution of the print version on the grounds of cost, environmental and targeting opportunities offered by the former. The trade-off between print and screen investment should be guided by evaluation of the differential effects. This work in progress proposes an attempt to measure the impact of medium, i.e. channel of delivery, of promotional communication on customer behavior and attitudes. A field experiment at a 37-store retail chain is being developed that employs a basic randomized design comparing three treatments with control group to measure print/digital flyer impact on behavioral measures based on loyalty database records (with pre-test) and on self-reported measures based on a questionnaire (without pre-test). Exploring customer motivations to engage in virtual fashion communities: implications for retailers Nicoletta Occhiocupo and Mareike Friess, Oxford Brookes University, UK A growing body of the academic literature focuses on the use of social media and online platforms as a marketing tool and a way to interact with customers. This paper aims to understand customer motivations to engage in virtual fashion communities. In-depth semistructured interviews have been conducted via Skype. Findings show that customers tend to engage for personal rather than product-related motives, such as recognition, selfexpression, relationship building, and skill development. Three customer segments were generated: Fashion Lovers, Designers and Artists. Retailers should focus on creating a compelling, interactive, engaging and supportive community, bearing in mind customer motivations to engage can lead to satisfaction, brand loyalty and value co-creation. Secondly, data generated within virtual fashion communities can lead to enhanced understanding of customers unmet needs and predict trends. Finally, customers expect a responsive approach from the retailer when setting up a virtual community, as lack of interaction can lead to demotivation to engage in the community. 7

8 Decisions in demand: exploring alignment between supply and sales forecasts in the retail food supply chain Amir M Sharif and Zahir Irani, Brunel Business School, Brunel University, UK The forecasting of consumer demand within the FMCG sector can be affected by a range of complex factors which include seasonality, logistics performance, and consumption trends. Demand-led forecasting also encompasses a linkage between production and supply forecasts and sales promotion cycles. There is a need to understand the relationship between demand- and sales-based forecast approaches. Within the food supply chain, this alignment affects the forward and reverse 3PL (waste) supply chains. This research seeks to report on the exploration of demand and sales-based forecasting decisions within a large UK-based food manufacturer within this context. The empirical research is based upon qualitative responses to decision behaviours which impact upon the implementation of sales-, and hence demand-driven production forecasts via a quantitative "soft" modelling approach based upon concepts found in the field of systems dynamics as well as cognitive mapping. Antecedents and consequences of supply chain management practices: a study of Indian organized retailing Mohua Banerjee and Gopal Das, IMI- Kolkata, India The understanding of supply chain management (SCM) practices has a key role for an organization in staying competitive and enhancing profitability in the increasingly competitive global marketplace. One problem for managing SCM practice is handling the enormous information regarding its members. This study explores retail SCM practice from business intelligence (BI) perspective as its antecedents level of information sharing, and quality of information sharing; and subsequently its consequences in terms of competitive advantage, financial performance and organizational performance. The study collected data from 400 SCM executives. Analysis is conducted using descriptive and inferential statistics. This report would make a contribution towards foreign retailers acquiring knowledge for developing appropriate strategies for entering and competing in the Indian marketplace. 8

9 Supply chain management based on logistic and statistical indicators Marcin Hajdul and Karolina Kolińska, Institute of Logistics and Warehousing, Poland The choice of suitable indicators which support making decisions at individual stages of management is a vital element which has an influence on the efficiency of the actions taken and on the shape of a company s policy. An additionally important element in a management process is setting current values of individual indicators, defining the target (normative) value of these indicators as well as the targets for which individual indicators are measured. This article presents Logistic indicators and standards and statistical indicators and standards vital for making decisions on particular management stages. Additionally shows the method of determining the relationship between the indicators with the use various correlation coefficients, depending on the type of data. 9