Modern Grocery Retailing Consumer’s Profile Is There a Need for Convenience Stores to Redefine Precision Marketing Strategy in Romania? Post Covid Outbreak Analyze

Introduction

The COVID-19 pandemic has generated significant mutations in modern retail, more than had been permanently affected by the evolution of technology and has determined the accelerating need to implement smart operational solutions.

The retail industry has been upended by COVID-19 outbreak, forcing the closure of some physical stores, especially nonfood stores and causing uncertainty for the future of the in-store experience. These abrupt shifts have left many retailers scrambling to effectively serve customers through other channels. Digital-first and omnichannel retailers have pivoted more easily, but retailers that prioritized physical stores and face-to-face engagement over omnichannel strategies have struggled to respond (Briedis et al., 2020).

The purpose of this paper is to see what has been changed for convenience stores. Has this format been affected by pandemic? What consumer profile is frequenting the convenience store now? Is it necessary for retailers to respond to the online threat? Is there a need to redefine the precision marketing strategy?

Literature Review

Precision marketing is a term which can be described as technology-enabled process for capturing and managing customer data, analyzing those data and using in order to reach more efficient and profitable customers interactions (Zabin and Brebach, 2004). 

In a broad sense, precision marketing refers to market segmentation as Smith affirmed more than half a century ago: ’’precise adjustment of product or marketing effort to consumer or user requirements’’.  

Companies are using information about customers to enact precision marketing designed to build strong long-term relationships (Kotler, Gregor and Rodgers, 1989). But long-term sustainable relationship retailers should build both with suppliers and customers and for doing so Zhu and Gao (2019) recommended the applicability of precision marketing strategy based on digital marketing mode from three aspects: customer segmentation, targeting customers and positioning on the market.

Zoratti and Gallagher (2012) described the process of precision marketing consisting of six steps. Firstly, should be determined the objective of precision marketing. Then, organization can start the data gathering process where all consumer touch points are considered in order to align with internal data. After that the data sources are analyzed and based on the analysis, models are created to represent the consumer segments. Next point is to target the defined consumer segments. These strategies consist of: defining the right communication channels, developing relevant content with the right messages at the right time (Credle et al., 2010). Lastly, these strategies are deployed and with the right measurement tools in-place, the success rate of these strategies can be measured. This process is iteratively improved based on the results measured in order to align with the changing consumer wants and needs (Zabin and Brebach, 2004).

In the last years, the retail industry entered the big data era with the development of technology and increasing of digitalization. Retailers are collecting more data, including purchase data (e.g., quantity purchased, price and cost of each item, size of discounts applied, composition of shopping basket, and time and date of purchase (Grewal, Roggeveen and Nordfalt, 2017) but also social media and demographic information about customers (Karadag and Engers, 2017). Big data allows retailers to combine multiple data as customer loyalty data, demographic information (e.g., age, gender), and geographic data (e.g., store locations, weather forecasts) (Grewal, Motyka and Levy, 2018).

Retail market segmentation is necessary and often critical for the development of marketing strategies in the context of a competitive market (Segal and Giacobbe, 1994). Retailers are increasingly facing competition between ” inter ” (how to operate, online or in-store) and ” in ” (the store format in which they are operational) (Kim, Ha and Park, 2019), which is why customer segmentation is essential.  

Identifying and grouping customers with similar characteristics and behaviors will help retailers develop strategies to meet the specific needs of target customers (Blackwell, Miniard, & Engel, 2006).

Modern retailers normally use unified or traditional segmentation, ignoring the characteristics and requirements of basic and potential consumers. For convenience stores, segmentation can be applied and extended from store clusters to different market segments. It was estimated that this store format, in terms of its characteristics (location and trading history) can not provide conclusive data on consumer preferences and behavior (Han et al., 2014). However, the literature highlights variables that define the buying behavior and motivations of consumers who choose and patronize this store format. Based on these, modern local retailers will be able to segment their market, identify target customers and build marketing strategies designed to attract them, to retain them in the long run. The main criteria used for marketing segmentation are demographic, geographic, psychographic and behavioral and are presented as following.

Segmentation by demographic criteria

Consumer needs and preferences change with age. From a very early age, children accompany their parents for shopping. Modern retailers are concerned with serving the needs of each generation as well as possible because regardless of the stage of the life cycle the customer goes through, it is important to remain loyal to them.

Demographic variables such as age, gender, marital status, income, education, occupation, number of household members, exert an enormous influence in the choice and patronage of the modern food retail store (Pan and Zinkan, 2006; Blut, Teller and Floh, 2018; McGoldrick and Andre, 1997; Carpenter and Moore, 2006).

The literature highlights segmentation by generation in terms of preference for a particular format or purchasing behavior. Given the large number of types of retail formats, identifying customers who frequent a particular format is crucial (Kim, Ha and Park, 2019).

Generation cohort analysis is a common method of segmentation (Schewe and Noble, 2000) and very useful as each cohort can highlight values, attitudes and consumption patterns (Holt, 1997; Parment, 2013) that will ultimately lead to improved outcomes. company (Lissitza and Kol, 2019).

The following cohort generations are defined in the literature: the “Seniors” generation, born before 1946; the Baby-Boomers generation, born between 1946 and 1965; Generation X, born between 1966 and 1980; Generation Y, born between 1981 and 1994 and Generation Z, born after 1995 (Reeves and Oh, 2007; Chaney, Touzani and Slimane, 2017; Brosdahl and Carpenter, 2011). Recently, it is considered necessary to introduce in the cohort analysis and the Alpha generation (born after 2010) taking into account the particularities of this generation – born and raised in the digital age with preferences aimed at looking for shopping experiences or easy, comfortable shopping, also having a strong influence on the parents’ buying decision (Strătilă, 2020).

The “Baby-Boomers” generation buys rationally and are often influenced by experts or friends (Valkeneers and Vanhoomissen, 2012). Their purchases are planned, and aimed at price reductions, staff friendliness, easy finding of goods and socialization (Martin, 2009; Moschis, Ferguson and Zhu, 2011). Recently, the representatives of the “Baby-Boomers” generation show interest in smart shopping and a higher level of use of mobile networks (Atkins and Hyun, 2016; Lissitza and Kol, 2019).

Generation X is known to prefer convenience, efficient shopping and is informed on the internet (Williams and Page, 2011; Lissitza and Kol, 2019).

Generation Y consumers, also known as “Millennials”, prefer fast transactions, do not want to interact with store staff but appreciate and expect timely communication and reliable information (Harris, Stiles and Durocher, 2011); possesses skills in the field of information technology and the purchase decision is made after research and is informed in advance (Rahulan et al. 2015).

Generation Z defines consumers who have been trained mainly in the context of modern retail and is a major challenge as it requires modern retailers to be smart (” smart retailers ”) leading them to allocate considerable budgets for investments in technology and smart applications. Being permanently connected through mobile networks, Generation Z consumers expect from merchants fast transactions, information provision, convenience and convenience (Priporas, Stylos and Fotiadis, 2017). This market segment includes the most educated consumers (Chaney, Touzani and Slimane, 2017), selective, innovative and constantly looking for change (Wood, 2013; Smith, 2019).

The literature considers that studies that have been limited to the analysis of only one generation, cannot be sufficient, as the differences between the cohorts are highlighted. Given the stage in the client’s life cycle, it is recommended to approach inter-cohort segmentations (between generations), in order to determine the differences between successive generations, such as generation Y versus Baby Boomers (Parment, 2013) or generation Y versus generation X (Gurău, 2012) as well as intra-cohort segmentation (within a generation).

For example, intra-cohort segmentation can follow the transitions from child to adolescent or from adolescent to adult (Arnett, 1997, 2000) that can cause social differences, change in decision-making power, the transition from hedonistic to utilitarian needs (Pentecost, Donoghue and Thaicon, 2019) or may detect abnormalities such as adultization (children or adolescents behaving as adults) or infantilization (adults behaving as children) (Postman, 1985; Bernardini, 2014).

Another example is the segmentation into subdivisions (cluster type) that Oeser et al. (2018) made it for German consumers over the age of 65, depending on the size of their motivations for shopping. Thus, seven types of elderly customers were identified (regardless of, short-term shopping-oriented, convenience-oriented, who prefer shopping assistance, who prefer in-store order, high-quality products-oriented and service-oriented) whose motivations for shopping differ significantly in terms of quality, shopping experience and socialization, service and support, assortment, convenient location and fast services and product size (packaging).

Segmentation by geographical criteria

For modern retail, store location is a key factor in gaining a competitive advantage (Gonzalez-Benito, Bustos-Reyes, & Munoz-Gallego, 2007). This aspect has been analyzed in the literature both in terms of competition between different merchants operating either different formats or the same format in nearby areas, and in terms of locating a store according to the area of ​​interest and accessibility, according to the daily itinerary and travel (on foot, by car or by public transport). Selecting a store location is a topic that has shown interest in both Retail Management and Retail Geography (Wood and Browne, 2006; Birkin, Clarke, & Clarke, 2002; Smith and Sanchez, 2003; Gonzalez Benito and Gonzalez Benito, 2005; Major, Delmelle and Delmelle, 2018).

Geodemographic segmentation has the role of removing spatial heterogeneity by classifying intra-urban areas based on the characteristics of residents. The possibility to identify the needs and buying habits from different geographical areas, makes the geodemographic segmentation to be a very useful tool for the realization of the location strategy (Gonzalez – Benito and Gonzalez – Benito, 2005). Geodemographic segmentation is based on data from geographic information systems that use advanced technology to design a spatial dimension of a commercial area. Thus, a division of an intra-urban area is reached according to the demographic, socio-economic and psychographic characteristics of the residents (Gonzalez-Benito, Bustos-Reyes and Munoz-Gallego, 2007).

Confirming the main role of proximity (spatial convenience) in choosing a format, Gonzalez-Benito, Bustos-Reyes and Munoz-Gallego (2007) by geodemographic segmentation also identified the quality of residents as well as their preferences regarding the format they choose for shopping. Their results showed that families with higher socioeconomic status choose to shop in the local supermarket while families whose members work in areas with activities in the primary sector or construction and a lower level of education choose hypermarkets. discount stores or stores.

More recently, a geographic study (Major, Delmelle, and Delmelle, 2018) highlighted seven clusters in segmenting an access area for food shopping in North Carolina, based on socioeconomic indicators provided by the U.S. Census, distances measured up to at grocery stores, traditional markets or convenience stores and a walking index. Regarding the geodemographic segmentation used exclusively for convenience stores, the literature is quite poor.

An analysis by authors Wood and Browne (2006) on the selection of the location of a convenience store, highlighted some aspects that limited the interest of practitioners and researchers to apply geodemographic segmentation for this format. According to them, the locations of convenience stores were established on the basis of experience and intuition, on basic market analysis, as a result of the organic decrease in consumer interest for large formats; geodemographic segmentation was not used due to the lack of data at the micro-scale level but also the small budget that a small format has allocated to achieve the profit target, while emphasizing the need to increase the level of sophistication for this modern format. In general, the literature shows that the short distance to the store influences the decision to choose that store and the greater this distance the greater the number of alternatives involved and thus decreases the likelihood of patronizing that store (Loudon and Della Bitta , 1993).

Segmentation by psychographic and behavioral criteria

Psychographic factors define and measure the lifestyle of consumers, interests and opinions (Tam and Tai, 1998). Psychographic dimensions are measurements of the consumer’s mind that highlight how they think, react, and reflect (Roy and Goswami, 2007). Their role is to highlight consumer segments according to their activities, interests, opinions (Goswami, 2007), needs, perceptions, lifestyle and attitudes (Prasad and Aryasry, 2010).

To study how to choose the store format, depending on the variables that define the lifestyle (AIO – attitudes, interests, opinions), Prasad and Aryasry (2010) identified five clusters of customers: the hedonic type (25.3%, do shopping where it is fun and discovering experiences, aged between 25 and 40), utilitarian type (23.7%, predominantly women, planned shopping, basic needs, choose proximity and convenience to save time and reduce effort, moderate as frequency shopping but with an interest in quality and variety), autonomous type (20.6%, active people, busy, busy saving time, choose proximity formats, which offers convenience and accessibility), conventional type (17.3%, does not show high interest in quality and assortment, prefers traditional shops nearby) and the sociable type (casual shopping, but are looking for shopping and socializing experiences).

The study conducted in India, highlighted that the concerns of saving time and searching for information are the variables in which customers algae the format of proximity. Another behavioral study conducted among Swedish consumers (Nilsson et al., 2015) identified five different consumer segments based on how they buy (major or complete purchases) and where they buy from (supermarket or modern convenience store): City Dwellers, Social shoppers, Pedestrians, Planning Suburbans and Flexible. Pedestrians represent the segment of consumers who make major purchases in modern convenience stores; they are young, live in the center, near the store they frequent most often and do not use the car frequently. City Dwelles (residents) are consumers who do full shopping in modern convenience stores; they live centrally, near the store they frequent most often, are very busy and do their shopping on the way from work to home.

Other studies have focused on studying a possible link between time and buying behavior (McDonald, 1994, Chettamrongchai and Davies, 2000; Darian and Cohen, 1995; Smith 1969; Gahinet and Cliquet, 2018). A study in the north of England, in the Borough of Backburn area (Chettamrongchai and Davies, 2000), indicated that segmentation based on time orientation and buying motivations can provide a clearer picture of consumer behavior than the separate use of socio-demographic variables or purchasing attitudes. Thus, four clusters were identified: Time pressured convenience seekers (consumers who seek convenience, being pressed by time, are young, educated, busy, future-oriented, do not like shopping, perceive time as a succession of events and seek convenience in shopping ); Hedonists (consumers looking for the pleasures, experiences and entertainment of shopping that they consider an event, are rather older, focused on what is happening now); Apathetic but regular (apathetic consumers but who show a normal behavior, do not like shopping but do not look for convenience in shopping, oriented to the past and present, perceive shopping as a routine activity); Convenience seekers (consumers looking for convenience when shopping, are rather men, are less oriented towards the past but are not influenced by traditional views when it comes to food shopping).

Also in order to minimize the investment of time, money and effort and to maximize the value of shopping, Atkins, Kumar and Kim (2016), based on activities that define a smart buying process (information seeking, shopping planning, effort reduction, obtaining the most suitable product, money saved, time saved), identified three categories of buyers: spontaneous and intelligent (unplanned shopping, little search for information, willing to minimize effort, interested in saving time, are mostly representatives of the Baby Boomers generation are not open to make recommendations to acquaintances, but rather on social networks motivated by promotions, contests), apathetic and intelligent (low interest in all activities defined as smart to buy, except for the search for information, mainly represented by generation X, manifests smart behavior more online than in the store, but worth the convenience and are sensitive to price reductions), involved and intelligent (they value the hedonic character of shopping, price reductions and the reduction of time allocated to shopping, being oriented towards convenience).

The pressure of time and the orientation towards convenience also brought attention to the on-the-go consumption. Unlike more traditional, planned or temporary consumption, consumption on the go combines convenience and speed (Malison, 2016). It is a new model of consumer behavior, generated by societal mutations at the macro level such as eating routine, increasing work schedule, increasing the number of extracurricular activities (Janssen, Davies and Richardson, 2018; Welch et al., 2009).

Given that consumers of this type of product, patronize different formats in their search, but especially convenience formats (Benoit, Evanschitzky and Teller, 2019), to identify the reasons behind this consumption behavior, Sands et al . (2019) identified three consumer segments for on-the-go products based on socio-demographic and behavioral variables: Frequent Vice Consumers (customers who show frequent consumption of addictions, which has become a habit, more than once a week, based on the least healthy diet, even during the three main meals – breakfast, lunch and dinner, low level of education, low income; Occasional consumers (occasional consumers, who consume rarely and who show a low level of time pressure Conflicted Health-Conscious Consumers (Conflicted Health-Conscious Consumers) (consumers who show interest in healthy eating but also interest in this consumption, are confused and this predisposes them to regularly consume such products, they are impulsive and pressed for time, young, with a high level of education).

Another trend of food consumption that is starting to gain considerable momentum is the consumption of local products (of local origin) (Noll, 2014). A local or regional foodstuff refers to a specific geographical area where those foods are produced and sold. Consumers want to know more and more about the traceability of products in order to be convinced of the quality of a diet or the correctness of a healthy diet. Another reason is to increase the level of awareness among the population regarding the impact on the environment, thus wanting to reduce the share of industrially manufactured products and the conservation of natural resources (Zerbe, 2010). At the same time, consumers are more concerned about the local economy and are motivated to buy local products to support the local economy and business (Bond, Thilmany and Bond, 2008) although still the marketing infrastructure and the entire supply chain have limited operating capabilities (Kumar and Smith, 2017).

To determine the attitudes that determine the motivations for buying local products, Kumar and Smith (2017) identified four segments based on lifestyle manifested in food consumption: Impromptu Novelty Explorer (explorers of unplanned notes, shows a high level of awareness of the importance health, responsible for the environment, subjective and eager to buy local products, are mostly part of Generation Y who not only seek freshness, healthy and sustainable food, but also convenience; Uninvolved Connoisseur (non-involved connoisseurs, as the name implies, are interested in local products but are not involved in any component of the purchasing process – planning, information retrieval, purchasing, want high accessibility, such as monthly delivery of packages by producers or farmers; Involved Information Seeker (involved in the search for information, representatives of the Baby Boomers generation, show little interest in buying these products although they are aware of the importance of healthy eating, are suspicious, look for information that on product labels and on the manufacturer’s website and are not influenced by social pressure); Apathetic Local Food Consumer (consumers indifferent to the consumption of local products, are often confused and the reasons why they choose products from local producers are not concrete, have nothing to do with healthy eating, face responsibility environment or community, but rather because they have no other options in modern retail).

Another study conducted in two stores in France by Lombart et al. (2018) identified three segments of consumers of regional products, based on their reactions at the point of sale, under the application of different techniques and strategies of visual merchandising and placing the goods on the shelf: The Indifferents (Indifferent) are not interested in products regional), The Ultra – regionalists (ultra-regionalists, as the name suggests, show a high interest in regional products, but modern grocery stores are not the preferred distribution chain), The moderates and The regionals – (regionalists who are most receptive to products) regional from the assortment of modern food stores). The study also highlighted the importance of merchandising techniques and theatrical performances at the point of sale; these strategies increase the visibility of regional products on the shelf, improve the store’s image at the local level and increase customer loyalty.

Depending on the assortment and with the help of the data provided by the category management tools, (Han et al. 2014) proposed segmenting convenience stores into four clusters, depending on the role (importance for customers, importance for the merchant – how sales perform and importance for the market – current and future trends) and the index of categories included in the assortment: C4> C3 > C2> C1 (from the widest assortment to the smallest; provided that even the smallest includes between twenty and thirty categories in order to meet customer needs).

Recently, purchasing behavior studies have used sales data to segment customers according to CLV (Customer Lifetime Value) using methods such as RFM (Recency, Frequency, Monetary), PPS (Purchased Products Structure), SM (Shopping Mission), cluster-type analyzes (Aeron, Kumar, & Moorthy, 2012; Chen et al. 2009; Sokol and Holy, 2020; Sabuncu, Turkan, Polat, 2020; Yang, 2004; Russel and Kamakura, 1997). Such an analysis highlighted that for convenience stores, customer visits are for specific product categories such as: snacks, beverages (alcoholic and soft drinks), snacks and beverages, sandwiches, diet menus and breakfast (Griva et al., 2018). Other segmentation methods analyzed have recommendations for using data provided by social networks (Narwal, 2017) or technologies such as RTLS (Real Time Locating System), GPS (Global Positioning System), RFID (Radio-Frequency Identification) (Ferracuti et al ., 2019; Liu et al., 2007; Zeimpekis, Giaglis and Lekakos, 2002).

Research Question

The purpose of this paper is to see what has been changed for convenience stores. Has this format been affected by pandemic? What consumer profile is frequenting the convenience store now? Is it necessary for retailers to respond to the online threat? Is there a need to redefine the precision marketing strategy?

Research Methodology

Based on secondary data, the paper presents the Romanian context for convenience store format through the main challenges caused by COVID -19 outbreak and the new customer profile.

After a period of breath during the summer when things were hoped to get to normal, in September, the second wave of COVID-19 outbreak and the new restrictions applied after Romanian pools have probably boosted the digital transformation of retail.

Convenience store represents the format that benefited from grocery outlets, being allowed to stay open throughout the COVID-19 lockdown (Euromonitor, 2021). Proximity, convenience, quick and efficient shopping in order to stay safe, close to home or in the neighborhood, helped the channel grow and support the growing trend which have started since 2018.

Euromonitor Country Report analysis (2021) highlighted that international retail chains which operate convenience store format in Romania were not very impacted by COVID-19 outbreak, as they had opened new stores according to expansion strategy (Profi, Mega Image). To the opposite, the local players were very affected by people becoming more cautious about spending during the crisis and were more consistently reliant on fresh food produced in their backyards, so the crisis impact was bigger at the regional level than Bucharest.

The report (Euromonitor, 2021) also revealed the following threats for convenience stores:

• The rise of food and drink e-commerce.
• The poor implementation of omnichannel strategy as people needed to stay home and relied on delivery.
• Need for engagement and establishing close personal relation with customers (e.g. Paco, the local player implemented phone orders and delivery during pandemic).
• Need for better supply for local players and competitive prices which have increased pressure to come together under convenience store brands (e.g.’’La doi pași’’ remodeling of Metro Group).
• The lack development of associations of producers and retailers in order to sustain local food.

Another report (Delloitte, 2020) consumers’ profile based on three months analyze (June, July and September) have encountered a slight change in September, by comparison to July and June. The socially conscious shopper who supports local brands remained the dominant type and the second most common profile is the convenience seeker, representing those consumers who prefer to shop in their neighborhood. The report (Delloitte, 2020) also revealed that Romanians were more inclined towards online shopping or towards a mix of online and offline shopping, during all analyzed periods (June, July and September).

Considering these aspects, next questions are imminent:

• did the pandemic bring new threats for convenience stores or boosted the one who appeared before pandemic?
• if the convenience seeker is the main profile of consumer who makes shopping in the neighborhood, is there a real threat the rise of food and drink e-shops? It’s necessary to retargeting market for convenience stores?

Results and Discussions

According to Pareto’s Law of 80/20, 20% of all the customers represent the important customers who create 80% of enterprise’s profit. These customers are the most ideal and retailers should maintain them in the marketing process. The second is represented by the sub-valuable customer which have low loyalty and are easily tempted by other competitors and retailers should take action to avoid that (Zhu and Gao, 2019).

Thus, considering only these two major target groups for convenience stores – convenience seekers who buy in the neighborhood and those who mix online and offline shopping, we can admit that convenience store format wasn’t very impacted by COVID-19 pandemic.

Conclusion and Recommendations

For precision marketing strategy is crucial to analyze customers behaviors. The literature review presents above a comprehensive analyze for retail customers profile based on most common segmentation variables – demographic, geographic, psychographic and behavioral.

Through data mining, marketing statisticians can extract from the mass of data useful information about individuals, trends, and segments. In general, companies can use their databases in five ways: to identify prospects; to decide which customers should receive a particular offer; to deepen customer loyalty; to reactivate customer purchases; to avoid serious customer mistakes (Kotler and Keller, 2016, p. 663).

As the worlds of online and offline are converging, retailers need to embrace the new and emerging technologies to make their customers even more engaged, and also their lives simpler. Knowing what is different and what is similar in these two worlds, as well as how new technologies are going to impact both, is key for the future of retailing (Grewal, Roggeveen and Nordfält, 2017).  

Designing goods that offer value to consumers is critical to success of retailers and service providers and creating a superior customer experience can differentiate companies (Grewal, Levy, and Kumar 2009; Verhoef et al.2009).

Customer experience should be developed both in store (store atmosphere, assortment, merchandising, price) and online (by leveraging social media) in order to reach the highest level of engagement so that customers should identify with retailer (Grewal, Roggeveen and Nordfält, 2017) through the most actual trends as local or healthy food assortment or socially responsible retailer’s attitude for people, environment or sustainable consumption (Bălan, 2021).

So, as Zhu and Gao (2019) stated the precision marketing strategy should continue with an accurate market positioning, providing personalized product marketing and precisely pushing goods for customers.

Acknowledgment

This paper is co-financed by The Bucharest University of Economic Studies during the PhD program.

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