Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0029
A. Godfrey, Kathleen Seiders, Glenn B. Voss
Abstract In an effort to build long-term, profitable relationships, many companies systematically engage in multichannel relational communication - personalized messages sent to existing customers through various channels as part of a broader relationship marketing strategy. However, too much of a good thing might actually ultimately have a bad effect.Whether ongoing direct communication with customers is perceived positively depends on its volume, the mix of communication channels, and the alignment of those channels with customers’ preferences. There is an ideal level of communication. If it is exceeded, customers react negatively and this negative response can be exacerbated by the use of multiple channels. The ideal level differs depending on individual channel preferences. Aligning channels with customer preferences is advisable to optimize repurchase rates.
{"title":"When Is Enough Enough? Balancing on the Fine Line in Multichannel Marketing Communications","authors":"A. Godfrey, Kathleen Seiders, Glenn B. Voss","doi":"10.2478/GFKMIR-2014-0029","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0029","url":null,"abstract":"Abstract In an effort to build long-term, profitable relationships, many companies systematically engage in multichannel relational communication - personalized messages sent to existing customers through various channels as part of a broader relationship marketing strategy. However, too much of a good thing might actually ultimately have a bad effect.Whether ongoing direct communication with customers is perceived positively depends on its volume, the mix of communication channels, and the alignment of those channels with customers’ preferences. There is an ideal level of communication. If it is exceeded, customers react negatively and this negative response can be exacerbated by the use of multiple channels. The ideal level differs depending on individual channel preferences. Aligning channels with customer preferences is advisable to optimize repurchase rates.","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"1 1","pages":"8 - 15"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78537485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0034
John H. Roberts, P. Danaher, K. Roberts, A. Simpson
Abstract This article describes the application of a dynamic choice model of consumer preferences. It supported Jetstar, a subsidiary of Australia’s leading airline, QANTAS, to effectively and profitably compete in the low-cost carrier marketplace. The evolution of the Jetstar strategy is traced from its initial position through to its efforts to attain price competitiveness and service parity. The model helped service design and pricing initiatives to shift the perceived performance of Jetstar relative to its competitors. It further indicated how the airline could move market preferences towards areas in which it had competitive advantage. The Jetstar market share went from 14.0 % to 18.1 % during the first five quarterly waves of the research, while profits went from US $ 79 million 2006 / 07, before the study was commissioned, to US $ 124 million in 2008 / 09. Today, Jetstar remains the only successful low-cost offshoot of a full service airline in terms of shareholder returns
{"title":"Jetstar Airways: How Modeling Guided the Brand Migration Strategy of a Low-Cost Carrier","authors":"John H. Roberts, P. Danaher, K. Roberts, A. Simpson","doi":"10.2478/GFKMIR-2014-0034","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0034","url":null,"abstract":"Abstract This article describes the application of a dynamic choice model of consumer preferences. It supported Jetstar, a subsidiary of Australia’s leading airline, QANTAS, to effectively and profitably compete in the low-cost carrier marketplace. The evolution of the Jetstar strategy is traced from its initial position through to its efforts to attain price competitiveness and service parity. The model helped service design and pricing initiatives to shift the perceived performance of Jetstar relative to its competitors. It further indicated how the airline could move market preferences towards areas in which it had competitive advantage. The Jetstar market share went from 14.0 % to 18.1 % during the first five quarterly waves of the research, while profits went from US $ 79 million 2006 / 07, before the study was commissioned, to US $ 124 million in 2008 / 09. Today, Jetstar remains the only successful low-cost offshoot of a full service airline in terms of shareholder returns","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"25 1","pages":"42 - 51"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80306837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0032
Neeraj Bharadwaj, Rebecca Walker Naylor, F. T. Hofstede
Abstract Customers are increasingly buying package offerings that consist of a combination of goods and/or services. They often have the choice of purchasing either an available standardized, off-the-shelf package or a customized offering designed to match their specific preferences. The position espoused in many books on one-to-one marketing and customer relationship management is that everyone is attracted to the latter. However, recent research is starting to challenge the universal appeal of mass customization. This project investigates if the preference for either a customized or standardized offer depends on whether they are experts or rather inexperienced in the product category. It further sheds light on repurchasing after buying standardized or customized products and if retailer reputation makes a difference.
{"title":"Off-The-Shelf or Tailored to Your Needs: Is Customization Always Superior?","authors":"Neeraj Bharadwaj, Rebecca Walker Naylor, F. T. Hofstede","doi":"10.2478/GFKMIR-2014-0032","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0032","url":null,"abstract":"Abstract Customers are increasingly buying package offerings that consist of a combination of goods and/or services. They often have the choice of purchasing either an available standardized, off-the-shelf package or a customized offering designed to match their specific preferences. The position espoused in many books on one-to-one marketing and customer relationship management is that everyone is attracted to the latter. However, recent research is starting to challenge the universal appeal of mass customization. This project investigates if the preference for either a customized or standardized offer depends on whether they are experts or rather inexperienced in the product category. It further sheds light on repurchasing after buying standardized or customized products and if retailer reputation makes a difference.","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"23 1","pages":"29 - 31"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74020231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0031
Koert van Ittersum, F. Feinberg
Abstract Two of the most critical uncertainties associated with new technology introductions are whether and when the target market will adopt them. A new scale integrates cumulative time intervals and predicts adoption more accurately. Behavioral data collected during a two-year longitudinal study provides empirical evidence for its accuracy. The new measure outperformed two single-intent measures and achieved a hit rate of more than 80 % in predicting whether and when a cell-phone technology was adopted. Adoption likelihood can be estimated without actual sales data and thus be determined prior to the launch of a new product
{"title":"I Will … Sooner or Later. Predicting Whether and When Consumers Intend to Adopt New Technologies","authors":"Koert van Ittersum, F. Feinberg","doi":"10.2478/GFKMIR-2014-0031","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0031","url":null,"abstract":"Abstract Two of the most critical uncertainties associated with new technology introductions are whether and when the target market will adopt them. A new scale integrates cumulative time intervals and predicts adoption more accurately. Behavioral data collected during a two-year longitudinal study provides empirical evidence for its accuracy. The new measure outperformed two single-intent measures and achieved a hit rate of more than 80 % in predicting whether and when a cell-phone technology was adopted. Adoption likelihood can be estimated without actual sales data and thus be determined prior to the launch of a new product","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"27 1","pages":"24 - 28"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80328968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0030
Hans Haans, E. Gijsbrechts
Abstract Retail chains often face tough competition and permanently seek to increase profitability. Closing outlets is a common strategy, even if knowledge about its implications is limited. Indeed, chain sales losses from store closure of a multi-outlet retailer operating multiple formats vary widely across outlets (ranging from less than 30 % to more than 80 % of the closed outlet’s revenue) and depend not only on the closed store’s format and distance to competitors, but also on the profile of its clientele and type of shopping trip. Analyzing these criteria helps to predict the magnitude of these losses for specific store closures using a new model. It offers guidance to retailers in deciding whether a particular store closure is beneficial to the chain or, if the objective is to prune an overly dense network, which of a set of local outlets is the best candidate for closure
{"title":"To Close or not to Close? Assessing the Impact of Outlet Closures on Retail Chains","authors":"Hans Haans, E. Gijsbrechts","doi":"10.2478/GFKMIR-2014-0030","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0030","url":null,"abstract":"Abstract Retail chains often face tough competition and permanently seek to increase profitability. Closing outlets is a common strategy, even if knowledge about its implications is limited. Indeed, chain sales losses from store closure of a multi-outlet retailer operating multiple formats vary widely across outlets (ranging from less than 30 % to more than 80 % of the closed outlet’s revenue) and depend not only on the closed store’s format and distance to competitors, but also on the profile of its clientele and type of shopping trip. Analyzing these criteria helps to predict the magnitude of these losses for specific store closures using a new model. It offers guidance to retailers in deciding whether a particular store closure is beneficial to the chain or, if the objective is to prune an overly dense network, which of a set of local outlets is the best candidate for closure","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"3 1","pages":"16 - 23"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81531175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-01DOI: 10.2478/GFKMIR-2014-0033
Harald J. van Heerde, Shuba Srinivasan, M. Dekimpe
Abstract To evaluate the success of a new product, managers need to determine how much of its new demand is due to cannibalizing the company’s other products, rather than drawing from competition or generating primary demand. A new model allows managers to estimate cannibalization effects and to calculate the new product’s net demand, which may be considerably less than its total demand. The new methodology is applied to the introduction of the Lexus RX 300 using detailed car transaction data. This case is especially interesting since the Lexus RX 300 was the first crossover SUV, implying that its demand could come from both the SUV and the Luxury Sedan categories. As Lexus was active in both categories, there was a double cannibalization potential. Indeed, demand is shown to originate from different sources and to vary over time. The results contain valuable insights for evaluating and managing brand extensions.
{"title":"Sibling Rivalry: Estimating Cannibalization Rates for Innovations","authors":"Harald J. van Heerde, Shuba Srinivasan, M. Dekimpe","doi":"10.2478/GFKMIR-2014-0033","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0033","url":null,"abstract":"Abstract To evaluate the success of a new product, managers need to determine how much of its new demand is due to cannibalizing the company’s other products, rather than drawing from competition or generating primary demand. A new model allows managers to estimate cannibalization effects and to calculate the new product’s net demand, which may be considerably less than its total demand. The new methodology is applied to the introduction of the Lexus RX 300 using detailed car transaction data. This case is especially interesting since the Lexus RX 300 was the first crossover SUV, implying that its demand could come from both the SUV and the Luxury Sedan categories. As Lexus was active in both categories, there was a double cannibalization potential. Indeed, demand is shown to originate from different sources and to vary over time. The results contain valuable insights for evaluating and managing brand extensions.","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"81 1","pages":"32 - 41"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85776401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-05-01DOI: 10.2478/GFKMIR-2014-0041
Marc Fischer, S. Albers, Nils Wagner, M. Frie
Abstract Marketing budget decisions are critical and should be fact based rather than intuitive. Profit can be improved by better allocating a fixed budget across products or regions. The Excel-based decision support model presented in this article makes it possible to determine near-optimal marketing budgets and represents an innovative and feasible solution to the dynamic marketing allocation budget problem for multi-product, multi-country firms. The model accounts for marketing dynamics and a product’s growth potential as well as for trade-offs with respect to marketing effectiveness and profit contribution. It was successfully implemented at Bayer, one of the world’s largest firms in the pharmaceuticals and chemicals business. The profit improvement potential in this company was more than 50 % and worth nearly EUR 500 million in incremental discounted cash flows.
{"title":"Dynamically Allocating the Marketing Budget. How to Leverage Profits across Markets, Products and Marketing Activities","authors":"Marc Fischer, S. Albers, Nils Wagner, M. Frie","doi":"10.2478/GFKMIR-2014-0041","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0041","url":null,"abstract":"Abstract Marketing budget decisions are critical and should be fact based rather than intuitive. Profit can be improved by better allocating a fixed budget across products or regions. The Excel-based decision support model presented in this article makes it possible to determine near-optimal marketing budgets and represents an innovative and feasible solution to the dynamic marketing allocation budget problem for multi-product, multi-country firms. The model accounts for marketing dynamics and a product’s growth potential as well as for trade-offs with respect to marketing effectiveness and profit contribution. It was successfully implemented at Bayer, one of the world’s largest firms in the pharmaceuticals and chemicals business. The profit improvement potential in this company was more than 50 % and worth nearly EUR 500 million in incremental discounted cash flows.","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"7 1","pages":"50 - 59"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2478/GFKMIR-2014-0041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72502654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-05-01DOI: 10.2478/GFKMIR-2014-0038
Blair Kidwell, D. Hardesty, Brian R. Murtha, S. Sheng
Abstract Emotional intelligence (EI) is important in many business contexts. Knowing how sales professionals use emotions to facilitate positive outcomes for their firms, themselves and their customers is particularly important for managing marketing exchanges. To leverage EI it is necessary to accurately measure it. Existing scales are of limited value and therefore a new scale to measure EI in marketing exchange is presented here. It focuses on EI related abilities in the specific context of marketing exchange and effectively demonstrates how EI interacts with sales, customer orientation, the extent of influence of a sales rep in an encounter, customer retention and cognitive ability. The new tool helps to diagnose individual levels of marketing exchange EI. It can be very useful for employee selection and designing specific sales training in order to improve exchange relationships and interactions between buyers and sellers, in particular.
{"title":"A Closer Look at Emotional Intelligence in Marketing Exchange","authors":"Blair Kidwell, D. Hardesty, Brian R. Murtha, S. Sheng","doi":"10.2478/GFKMIR-2014-0038","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0038","url":null,"abstract":"Abstract Emotional intelligence (EI) is important in many business contexts. Knowing how sales professionals use emotions to facilitate positive outcomes for their firms, themselves and their customers is particularly important for managing marketing exchanges. To leverage EI it is necessary to accurately measure it. Existing scales are of limited value and therefore a new scale to measure EI in marketing exchange is presented here. It focuses on EI related abilities in the specific context of marketing exchange and effectively demonstrates how EI interacts with sales, customer orientation, the extent of influence of a sales rep in an encounter, customer retention and cognitive ability. The new tool helps to diagnose individual levels of marketing exchange EI. It can be very useful for employee selection and designing specific sales training in order to improve exchange relationships and interactions between buyers and sellers, in particular.","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"13 1","pages":"24 - 31"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75900688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-05-01DOI: 10.2478/GFKMIR-2014-0042
A. Jolibert
Abstract The cereal industry is characterized by heavy competition and a pressure to reinvent itself to meet changing consumer lifestyles and retail environments. Jeff Cooper, Director of Consumer Insights of CPW, one of the world’s biggest players in cereals, offers some interesting information on how to keep this business growing in a difficult market environment
{"title":"MIR talks to Jeffrey S. Cooper, Director of Consumer Insights CPW-Cereal Partners Worldwide","authors":"A. Jolibert","doi":"10.2478/GFKMIR-2014-0042","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0042","url":null,"abstract":"Abstract The cereal industry is characterized by heavy competition and a pressure to reinvent itself to meet changing consumer lifestyles and retail environments. Jeff Cooper, Director of Consumer Insights of CPW, one of the world’s biggest players in cereals, offers some interesting information on how to keep this business growing in a difficult market environment","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"20 1","pages":"60 - 65"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87284119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-05-01DOI: 10.2478/GFKMIR-2014-0039
Ralf van der Lans, G. V. van Bruggen, J. Eliashberg, B. Wierenga
Abstract In a viral marketing campaign organizations stimulate customers to forward marketing messages to their contacts. To optimize a viral campaign it is necessary to predict how many customers will be reached, how this reach evolves, and how it depends on promotion activities. a new Viral Branching model can provide these results. It is based on insights from epidemiology and the spread of viruses and was adapted to a marketing context and an electronic environment. The model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign and serves as a valuable tool to support marketing decisions related to online campaigns
{"title":"Seeding a Message to Harvest Reach. Predicting and Optimizing the Spread of Electronic Word-of-Mouth","authors":"Ralf van der Lans, G. V. van Bruggen, J. Eliashberg, B. Wierenga","doi":"10.2478/GFKMIR-2014-0039","DOIUrl":"https://doi.org/10.2478/GFKMIR-2014-0039","url":null,"abstract":"Abstract In a viral marketing campaign organizations stimulate customers to forward marketing messages to their contacts. To optimize a viral campaign it is necessary to predict how many customers will be reached, how this reach evolves, and how it depends on promotion activities. a new Viral Branching model can provide these results. It is based on insights from epidemiology and the spread of viruses and was adapted to a marketing context and an electronic environment. The model is applied to an actual viral marketing campaign in which over 200,000 customers participated during a six-week period. The results show that the model quickly predicts the actual reach of the campaign and serves as a valuable tool to support marketing decisions related to online campaigns","PeriodicalId":30678,"journal":{"name":"GfK Marketing Intelligence Review","volume":"21 1","pages":"32 - 41"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86089263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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