The impact of weather on consumer behavior and retail performance: Evidence from a convenience store chain in China

Despite extensive use of weather data to adjust replenishment and inventory strategies in the retail industry, these companies do clearly know the effect of weather on consumer behavior and retail performance. How does weather affect consumers' purchasing behavior and thus retail performance? We study empirically these questions by analyzing more than 6 million transactions made by more than 1.62 million unique consumers at 146 convenience stores in a convenience store chain in China. We choose sun, rain, temperature, and air quality index as the main weather variables. We use the average number of items per order and the average price of each item in each order as indicators of consumer behavior, and use store daily sales as an indicator of retail performance. We found that under rainy weather, people will buy more products with higher item prices in one order. When temperature rises, people will buy fewer products with a lower item price in one order. In addition, sunny weather and rainy weather have a positive impact on daily sales than cloudy weather. Air quality has a negative impact on daily sales, while temperature has a positive impact on sales. Finally, we study the impact of weather on different product categories. We find that the results depend on the product category characteristics.     

Evaluating store location and department composition based on spatial heterogeneity in sales potential

In this paper, we extend a retail location evaluation model with the possibility to include the effect of department size adaptation at the store level. We relate department-level store sales to a store's competitive and demographic environment, thereby providing richer insights into the drivers of department sales than a model of just aggregate sales. Further, we accommodate heterogeneity in consumer characteristics over space by using zip code level data and unobserved spatial effects in department sales by including spatially autocorrelated error terms.Using spatial panel data for 30 clothing stores belonging to one Dutch retail chain, we demonstrate how to use the modeling approach to analyze and predict sales performance of new and existing stores. We show that the predictive performance of our model is superior to that of a benchmark model that does not include spatial autocorrelation.     

Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores

For brick-and-mortar retail operators, store location is an essential prosperity factor, affecting the volume and structure of sales. Understanding the complexity of location effects on sales dynamics and utilizing such information may be the key element of corporate success in a competitive market environment. In general, store locations can be characterized by representative sets of geo-spatial and socio-demographic features. Nowadays, multiple sources of location-related data are available from public authorities and other open sources. However, using such data may be a complex task: distinct location factors can have divergent effects on sales of different types of products. Hence, our objective is to quantify the effects of different measures of location on sales dynamics over a wide range of product categories. For this purpose, we introduce a methodology combining econometric modeling and cluster analysis. The presented empirical analysis is performed using data on 479 brick-and-mortar shops of a major drugstore chain operating in Czechia (2019 data are used to avoid distortions due to COVID-19). Besides estimating location effects on sales at the product-category level, we identify and evaluate groups (clusters) of product categories with similar sales dynamics. Both the methodology proposed and the empirical results presented can be utilized by different retail chains to assess and plan brick-and-mortar store locations. Also, the research presented can be instructive for academic researchers and other stakeholders in the fast-moving consumer goods sector.     

An Assessment of When,Where and Under What Conditions In-Store Sampling is Most Effective

In-store product sampling is a commonly used promotional technique designed to give prospective consumers an opportunity to experience a product prior to purchase. While prior research has documented a positive relationship between short-term sales and perceptual measures of the customer shopping experience, little is known about the long-term impact of sampling or factors that moderate its success. In this paper, we develop an empirical approach that allows us to study the short-term and long-term effects of in-store sampling on both own and competitive products. We apply our approach to six store-level scanner data sets across four different product categories and show that in-store sampling has both an immediate (short-term) and sustained (long-term) impact on sales. We also show that the impact of sampling on sales is moderated by the characteristics of the store conducting the event, and that repeated sampling for a single product leads to a multiplicative increase in its long-term sales performance. We find that, unlike many types of in-store promotion, sampling results in a category expansion effect as opposed to a pure substitution effect. We contrast the immediate and long-term sales patterns for in-store sampling to those of product displays and discuss managerially relevant differences. Finally, we demonstrate incremental profit implications and store selection scenarios for different incremental costs of conducting the in-store events using constrained optimizations.     

“One-deal-fits-all?” On Category Sales Promotion Effectiveness in Smaller versus Larger Supermarkets

Even within a store chain and format, supermarket outlets often exhibit substantial differences in selling surface. For chain managers, this raises the issue of correctly anticipating the promotion lift, and of profitably managing promotion activities, across these outlets. In this paper, we conceptualize why and how store size influences the category sales effectiveness of four promotional indicators (depth of the promotional discount, display support, feature support, and whether the promotion is quantity-based). We then estimate the net moderating effect on four product categories for 103 store outlets belonging to four chains. For each of the promotion instruments, we find the percentage sales increases to be lower in large stores. For instance, whereas a 10% point increase in feature activity enhances category sales by about 1.64% in a 700 m² store, this figure drops to only 1.03% in a 1300 m² store – a 59% reduction. This moderating effect is especially pronounced for discount depth, the relative sales lift from a typical price cut being about 78% lower in the larger-sized outlet. However, since large outlets also have larger base sales, the picture changes when we consider absolute sales effects. The net outcome is that deeper discounts or quantity-based promotions do not systematically generate larger or smaller absolute sales bumps in large stores, whereas for in-store displays and features, we obtain a clear positive (be it less than proportional) link between store size and absolute category sales lift. When it comes to margin implications, we show that large stores gain higher profit from price cuts than small outlets only as long as the retailer keeps part of the manufacturer discount to himself. Managers can use these insights to improve their promotional forecasts across outlets, as well as to tailor their mix of instruments to store selling surface.     

Bridge,Focus, Attack,or Stimulate: Retail Category Management Strategies with a Store Brand

We investigate a monopolist retailer's category management strategy where the main strategic decisions are how to horizontally position a store brand relative to the incumbent national brands and how to price the store and national brands for retail category profit maximization. We analyze a market composed of two consumer segments with differing tastes and heterogeneity with respect to willingness to pay and a product category consisting of two competing national brands and one store brand. We find that contrary to the existing literature, it is not always optimal for a retailer to position its store brand against the leading national brand; instead there are many situations where it is best to position the store brand close to the weaker national brand or to position it in the “middle” so it appeals to both national brands' target segments. In the process we identify four distinct category management strategies that a retailer can use with a store brand. In three of these the optimal store brand price is the brand's monopoly price, while in the remaining one strategy the price is lower. We also suggest an easy to implement means for a retailer to determine which strategy is best to use, depending on the particular competitive environment present before the introduction of the store brand and the relative quality of the store brand. We find that the store brand entry is most beneficial to the retailer when the national brands are moderately differentiated. Finally we show that introducing a store brand not only allows the retailer to garner a higher share of the channel profits through higher retail margins, but also often provides the retailer the benefit of increases in national brand unit sales as well as incremental sales from the store brand. JEL Classification: M310     

The importance of retail brand equity and store accessibility for store loyalty in local competition

Previous research shows that the success of a retailer depends on strong retail brands and attractive, easily accessible store locations. However, little is known about the relative importance of retail brand equity and store accessibility for store loyalty in different local competitive contexts. To provide insight into this issue, we conduct on a cross-sectional study of 4151 interviews and objective data on 30 stores of a focal retailer and its local competitors. We find that store loyalty benefits more from a strong brand than from a conveniently accessible location and that location can benefit from a strong brand. We also find that competitor’s brand equity has an especially negative influence on store loyalty towards a focal retailer and that the strength of the effects of brand equity and location accessibility on store loyalty depends on the local competitive context.     

An empirical analysis of tenant location patterns near department stores in planned regional shopping centers

The location of a store within a mall can affect the sales and profits of the store and its neighbors, and those of the mall׳s owner/developer. Because the interests of retail stores and the mall׳s owner/developer with respect to choice of location might not coincide, bargaining power might come into play. To assess empirically whether relative bargaining power as between a retail store and the mall owner/developer affects store location within a center, we focus on locations of stores near the department store tenants of malls. Department stores might have the bargaining power necessary to affect which tenants are chosen as neighbors of the department store.Using data collected from 148 regional shopping centers (malls) in 2007 in the five westernmost provinces of Canada, we examine the relationship between variables that reflect store location patterns near a department store׳s entrance, and variables associated with the bargaining power of developers. We find that the density of stores selling comparison shopping goods is larger near department stores within centers that are older or have a larger gross leasable area. In addition, such density is negatively related to the number of department stores contained in the center. Because a shopping center׳s age, gross leasable area, and the number of department stores in a center are expected to be associated with a developer׳s bargaining power, the above findings are consistent with the hypothesis that the store location patterns near department stores depend on the relative bargaining power of the developer and the department stores.     

The Magnitude of Change Effect in Store Remodeling

While store remodeling can increase customer sales, not all remodeling efforts are successful. In this study, two treatment stores from a large national retailer are matched with control stores in a field experiment. Even though the cost of remodeling the treatment stores was the same, and the remodeled stores had identical layout, color, furnishing and interior design, one store had a 12% lift in sales while the other had only 1%. We show that a key determinant of remodeling success is the perceived magnitude of change between the initial and final condition of the store. Indeed, customer psychological and sales responses are greater when the perceived magnitude of change between the condition of the store prior to remodeling and the store after remodeling is larger. Importantly, these positive effects continue for as long as 12 months after remodeling. We further find that the profile of customers drawn to the remodeled stores differs based on the perceived magnitude of change, as do the environmental attributes that contribute to customer perceptions of the remodel.     

Drivers of the synergy between price cuts and store flyer advertising at supermarkets and discounters

Despite retailers’ intense use of both price cuts and store flyer advertising, it is still unclear whether and when it is beneficial for retailers to combine the two promotion tools at the same time as opposed to using them separately. We systematically investigate synergies between price cuts and store flyers for a broad set of 488 brands from 44 consumer packaged goods categories across six leading German retailers. We find that a clear majority of the brands benefit from positive synergies and hence, combining price cuts and store flyer advertising is recommended, especially at supermarkets. This synergy can be strong. For instance, a 15 % price cut without store flyer support at a supermarket, on average, increases sales by 11 %, and medium spending on store flyers for the brand at its regular (non-promoted) price results in a sales lift of 8 %. The combined use of both tools, however, increases sales by 52 %, much more than the sum of their separate effects (11 % + 8 % = 19 %). Yet, there is also substantial variance in the synergy, which we explain with retailer format (supermarkets versus discounters) as well as various brand and category characteristics. Our findings have important implications for the coordination of promotion activities by retailers.     

Open all hours: spatiotemporal fluctuations in U.K. grocery store sales and catchment area demand

Conventional population estimates do not account for spatiotemporal fluctuations in populations over a diurnal timescale at the level of retail store catchments. This presents challenges for the retail location-based decision making process which seeks to predict sales volumes and their temporal characteristics prior to new store construction. We present a novel analysis of the temporal fluctuations of store sales, evidencing links between the spatiotemporal distribution of specific population subgroups and temporal store sales. Previous research linking spatiotemporal populations and store sales is limited owing to the fact that commercial data are not openly available to academic research. However, this research has unprecedented access to store level temporal sales data and an established loyalty card scheme from a major UK grocery retailer making these analyses possible for the first time. Additionally, we demonstrate that current store classifications were inadequate for grouping stores with similar sales profiles and propose four new clusters of stores based on the times of the day that they generate revenues. This development has clear academic and commercial benefits, aiding our understanding of consumer behaviours and a novel solution for improved location modelling. We lay the foundations for further research building spatiotemporal demand fluctuations into retail location models.     

Modelling the effect of store flyers on supermarket sales: An application to olive oil demand

In this paper we study the effect of store flyers on supermarket sales while controlling for other promotional strategies. We use a dataset of weekly sales of 16 olive oil products from a Spanish supermarket chain during the year 2017. We estimate a dynamic panel data model by GMM which allows us to examine both the short- and long-run effects of displaying products in store flyers. Our estimates show that products being featured in a store flyer exhibit 85 percent higher sales in the short-run, being the effect in the long-run of 109 percent. We also provide evidence that olive oil is a highly price-elastic product. Our estimates also indicate that placing the products on the end-of-aisle increases olive oil sales. Conversely, multibuy promotions are negatively related with sales.     

The impact of advertising along the conversion funnel

We assemble a unique data set that combines information on supermarket feature advertising with path-tracking data on consumers’ movement within the store as well as purchase information. Using these novel data, we trace out how advertising affects consumer behavior along the path-to-purchase. We find advertising has no significant effect on the number of consumers visiting the category being advertised. The null effect is precisely estimated. At the upper bound of the confidence interval, a one-standard-deviation shift in advertising increases category traffic by only 1.3%. We do find a significant effect at the lower end of the conversion funnel. A one-standard-deviation change in advertising (evaluated at the point estimate) increases category-level sales by 10%. We further decompose the impact on sales and find the increase is driven by the same number of consumers buying a larger number of products of the same brand. We find no evidence of spillover effects of advertising between categories that are stocked in proximity of each other, nor between different products in the same category. Two mechanisms are consistent with these patterns: consumers retrieve memory of the ad only when interacting with the category or only consumers wanting to purchase the brand choose to consume the ad.     

Multiple store patronage: The effects of store characteristics

The present study contributes to the literature on multiple store patronage in two important directions. First, it examines whether consumers׳ perceived importance of store characteristics have effects on multiple store patronage. Second, it examines the relationship between multiple store patronage and consumers׳ share of wallet at the primary store. Our results show that consumers who attach high value to sales promotions are more likely to visit multiple stores. However, store characteristic factors generally did not exert significant effect on multiple store patronage. Furthermore, we find that multiple store patronage and share of wallet are not interdependent and the profiles of consumers in terms of them do not share many common characteristics.     

Store-, Market-, and Consumer-Characteristics: The Drivers of Store Performance

Four factors have traditionally been identified in influencing store performance: store-, market-, and consumer characteristics and competition. Given partially conflicting and, in some cases, dated findings in the literature we want to re-assess the effects. In particular, past research has usually considered only two out of the four constructs at any time, which is likely to result in erroneous interpretation of results. We draw upon a unique cross-sectional sample of grocery stores with a wide array of store characteristic, store performance, trade area, and consumer demographic variables. Using structural modeling, our prime interest is to assess the differential impact of store attractiveness, market potential, and socio-economic status on two different store performance measures, while controlling for competitive effects. We find that the market potential of a store is by far the most important driver of store sales performance and sales productivity performance. With one exception, the model and the data support the hypothesized relationships about the direction and the strength of the impact of a store's attractiveness, market potential and socio-economic characteristics of the trade area on a store's performance.     

Local competition, entry, and agglomeration

This paper analyzes competition between two spatially differentiated multi-product retailers who encounter entry from a low-cost discounter. We assess how entry affects the pricing of the incumbent stores and the role played by the location of the entrant. Our primary objective is to identify how traditional retailers respond to new forms of low-cost retailing. Results show that post entry, the prices for some products are higher than the pre entry. However, which product prices increase depends on the incumbent’s location. Contrary to conventional wisdom, we find that the store closer to the entrant is better off compared to the incumbent located further away. We empirically demonstrate the main workings of our theory using sales data from several grocery stores that saw entry by discount stores in their trading areas.     

Joint In-Season and Out-of-Season Promotion Demand Forecasting in a Retail Environment

Inaccurate forecasts of demand during promotions diminish the already meager profit margins of retailers. No forecasting method described in the literature can accurately account for the combination of seasonal sales variations and promotion-induced sales peaks over forecasting horizons of several weeks or months. We address this research gap by developing a forecasting method for seasonal, frequently promoted products that generates accurate predictions, can handle a large number of sales series, and requires minimal training data. In our method's first stage, we forecast the seasonal sales cycle by fitting a harmonic regression model to a decomposed training set, which excludes promotional and holiday sales, and then extrapolate that model to a testing set. In the second stage, we integrate the resulting seasonal forecast into a multiplicative demand function that accounts for consumer stockpiling and captures promotional and holiday sales uplifts. The final model is then fitted using ridge regression. We use sales data from a grocery retailing chain to compare the forecasting accuracy of our method with popular seasonal and promotion demand forecasting models at multiple aggregation levels for both short and long forecasting horizons. The significantly more accurate forecasts generated by our model attest to the merit of the approach developed here.     

Effectiveness of In-Store Displays in a Virtual Store Environment

This article examines in-store display effectiveness in an online grocery store and concentrates on two main issues. First, considering the more artificial and functional virtual store environment, we examine whether online in-store displays (ISD) produce a similar boost in sales as they do in offline stores. Second, we examine the moderating effect of display characteristics by comparing the effects of different display types. The results show that (1) online ISD can substantially increase brand sales and (2) ISD that preempt competition through a first-order and isolated position outperform ISD that attempt to make the product stand out in the shopping zone.     

Industry relatedness in trade sales and venture capital investment returns

We investigate relationships between the industry relatedness of venture capital-backed companies and their strategic acquirer in trade sales and the achieved investment returns of venture capitalists. Using a proprietary data set of 716 trade sales, we analyze return differences between lateral and synergetic trade sales, as well as between horizontal and vertical trade sales. We find that venture capitalists achieve higher returns with lateral rather than synergetic trade sales, and that the difference is greater for deals involving early stage companies characterized by strong information asymmetries. In addition, horizontal trade sales yield higher returns than vertical trade sales; however, in boom phases of the venture capital market, this effect reverses. Finally, we find that experienced venture capitalists are able to overcome disadvantageous situations in trade sales, resulting in comparable returns across all trade sale categories.     

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.