Editorial

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The retail sector is evolving from a structurally rather rigid and somewhat un-emotional mainstay in the economy to a most dynamic field where old business models cease to exist, and new business models and players are bustling. As more and more customers prefer the convenience of internet-based shopping and direct-to-home delivery, many traditional retailers are forced to break fresh ground.
Today, retailers must achieve relevance and meaning in the daily life of consumers and develop significance beyond the interaction in the store. They have to be easily accessible both physically and digitally. Retailers still need to fulfill the classic retail functions but on top they need to develop digitally-enabled value creation sources. How well they succeed in implementing automation, individualization, life-embeddedness, interaction as well as transparency and control will determine whether they will persist in the new retailing environment. Only those retailers will survive who are able to translate the new value adds into meaningful and positive experiences that last beyond the purchase itself.
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Reinventing the Retailer: Retaining Relevance and Customer Access

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With the rise of digital technologies, retailing has become a field of value co-creation. Rather than selling readymade products and services, retailers now offer means for creating value together with their customers through manifold interactions. To enable co-creation, they need to develop digital interactive platforms (DIPs) around retail-related activities. Typically, individuals engage with a retail DIP offering in their particular contexts of interactions with apps or similar components. By delving deeper into the nature of the individual interactions, hidden and untapped sources of value can be revealed. Shoppers get more engaged, and retail managers gain more insights and can design ecosystems that allow a more effective creation of “all-win more” outcomes in more profitable ways. To be successful, retailers need to incorporate a broader view of value creation into their operations. They will be successful with hybrid-delivery systems in which consumers can use a range of interface technologies across multiple channels. Being able to interact with informational content, human actors, and technical resources at different stages of the decision making and shopping process will enable rewarding shopping experiences for customers and retailers alike.
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Digitalized Interactive Platforms: Turning Goods and Services into Retail Co-Creation Experiences

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Though some managers question the success of loyalty programs (LPs), the core idea of leveraging information gained through loyalty initiatives remains stronger than ever. But as LP membership penetration reaches all-time highs, customers demand more value from LPs. LP managers should leverage opportunities that mobile devices offer in increasing the convenience and communication with LP members. The integration of LPs with digital payment systems like mobile wallets seems particularly promising. Another way to become more attractive is by forming partnerships with other companies at which customers can collect and/or redeem points. Such partnership LPs hold appeal for retailers, particularly if potential partners might benefit from synergies. In the future of linked data, companies further need to be more flexible in terms of the types of customer engagements that will be rewarded. Many companies already move towards rewarding not only on past transactions, but also activities on social media. In the digital age, customers still enjoy some form of loyalty rewarding and expect retailers to acknowledge their purchases as investments in relationships.
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Keeping Loyalty Programs Fit for the Digital Age

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Price differentiation is a longstanding marketing instrument in retailing. In our digital omni-channel environment its implementation may get technically easier, but also more transparent and obvious. As consumers generally consider price differentiation as unfair, systems need to be implemented cautiously and hold potential benefits for all parties. Some practices are perceived as more unfair than others. Dissimilarity of the purchase situation, control over the final price, the suspected motive of the company, and fairness of the pricing rule are decisive factors in the consumer evaluation process of price differentiation measures.
To avoid detrimental effects like perceptions of unfairness or permanent damage of the relationship, companies must strike a balance between their own and consumers’ interests. The latter need to feel the advantage of price differentiation to appreciate it, especially the price-sensitive segment. However, from a company perspective, there is a profitability boundary to giving away free lunch. One way out of this dilemma is to foster self-selection into low-price offerings but preventing bargains for everyone by increasing the effort or time to get better prices. If head-on price differentiation is unavoidable, negative reactions can be attenuated by embedding pricing rules in social norms.
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University of Cologne and Director of the Center for Research in Retailing (IFH)

The Perils of Retail Price Differentiation: Why Nobody Wins When Customers Lose

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Big data are taking center stage for decision-making in many retail organizations. Customer data on attitudes and behavior across channels, touchpoints, devices and platforms are often readily available and constantly recorded. These data are integrated from multiple sources and stored or warehoused, often in a cloud-based environment. Statistical, econometric and data science models are developed for enabling appropriate decisions. Computer algorithms and programs are created for these models. Machine learning based models, are particularly useful for learning from the data and making predictive decisions. These machine learning models form the backbone for the generation and development of AI-assisted decisions. In many cases, such decisions are automated using systems such as chatbots and robots.
Of special interest are issues such as omnichannel shopping behavior, resource allocation across channels, the effects of the mobile channel and mobile apps on shopper behavior, dynamic pricing, data privacy and security. Research on these issues reveals several interesting insights on which retailers can build. To fully leverage big data in today’s retailing environment, CRM strategies must be location specific, time specific and channel specific in addition to being customer specific.
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Big Data and Analytics in Retailing

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To remain competitive in a connected world, offline retailers have responded with integrating digital in-store technologies into their physical servicescapes. Often, the introduction of multichannel connecting services like click &amp; collect or order from or return to store are first steps.
Shopper-facing advanced technologies can be key to creating a different physical shopping experience for consumers and delivering benefits to retailers such as improved traffic, conversion and baskets or streamlined operational cost. In general, consumers consider retailing technologies as useful. However, shoppers assess the fairness of the exchange about procedures, outcome and treatment and the value of the technology they receive compared to what the retailer gets. Also, satisfaction, trust and privacy concerns are relevant for customers. Retail managers need to ensure the functionality and safety of their application and take consumer concerns seriously. Also, they need to address privacy concerns and build trust, if they want proximity marketing to deliver on its promise of increasing basket size or attracting new shoppers.
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E-Commerce in a Physical Store: Which Retailing Technologies Add Real Value?

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Visitors of an online retailer’s website leave digital traces. Every click and each interaction on the website generate information about a customer while many traditional retailers tend to know very little about their customers. However, market incumbents need not watch this development in passive awe. Many technologies are already available that help brick-and-mortar stores gather more valuable information about their customers, allowing them to improve shopper experience, retain customers, and ultimately increase profits. If used in a smart, transparent and non-offending way, technologies like in-store cameras, smart sensors, virtual reality or augmented reality can make a physical store almost as data-rich as a website. Retailers can be enabled to track the customer journey, observe product interactions in front of shelfs, recognize customers and identify segments, detect emotional states automatically and understand their customers’ information needs and decision making processes. Virtual reality offers retailers environments for controlled experimentation so that they can employ A/B tests to optimize customer experience and turnover and do not fall behind online retailers. New technologies need to be introduced carefully and consider people’s needs for transparency and control.
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Nuremberg Institute for Market Decisions (NIM)

Head of Behavioral Science, Nuremberg Institute for Market Decisions (NIM)

Trends and Data Science, Nuremberg Institute for Market Decisions (NIM)

Technologies Turning Future Brick-and-Mortar Stores into Data-Rich Environments

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Auction thrill for everybody – no matter if you are the buyer or seller – that´s what has made eBay famous and attractive in its early years. The internet pioneer was already born in the last millennium and has revolutionized the consumer to consumer business. Originally the first supra-regional, electronic flea market, eBay has evolved into one of the world’s largest retailing platforms. A lot has happened and the auctions that once constituted the core of the brand are more of a sideshow nowadays. In the following interview, Eben Sermon, Vice President of eBay Germany, explains how the brand has been reinventing itself and talks about eBay’s innovations within the highly competitive field of e-commerce.
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eBay: Transforming an Auction House into a Retailing Platform

AHEAD OF PRINT

Volume 16 (2024): Issue 1 (May 2024) Generative AI – Reshaping the Marketing Landscape

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Volume 14 (2022): Issue 2 (November 2022) MarTech and SalesTech

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Volume 13 (2021): Issue 2 (November 2021) Brand Activism

Volume 13 (2021): Issue 1 (May 2021) The Dark Sides of Digital Marketing

Volume 12 (2020): Issue 2 (November 2020) The Reputation Economy

Volume 12 (2020): Issue 1 (May 2020) Crowd Innovation: Hype or Help

Volume 11 (2019): Issue 2 (November 2019) AI and the Machine Age of Marketing

Volume 11 (2019): Issue 1 (May 2019) The Future of Retailing

Volume 10 (2018): Issue 2 (October 2018) IoT - Consumers and the Internet of Things

Volume 10 (2018): Issue 1 (May 2018) Brand Risk Matters

Volume 9 (2017): Issue 2 (November 2017) The Connected Consumer

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Volume 11 (2019): Issue 1 (May 2019) - The Future of Retailing