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https://doi.org/10.22201/fca.24488410e.2024.5198

Artículos

Omnichannel; Consistency in a retail brand's channel integration

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Barón López, Ena Yuritze*1

Author affiliation
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  • 1 Universidad Central, Colombia.
Author notes
* Autor para correspondencia. Correo electrónico: ebaronl@ucentral.edu.co (E. Y. Barón López).
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Abstract

The rise of digital brands has forced traditional retail brands to introduce the digital channel in the purchase of goods and services. Traditional retail brands went from having only physical points to having digital channels and applications, becoming multichannel businesses, and more recently omnichannel. In Latin America, the adoption of the digital channel has intensified due to the increase in digital culture during the Covid 19 pandemic, however, at the beginning of the pandemic, consumers are still exploring digital channels as an option for purchase. of essential products. This article presents exploratory results on the use of retail brand channels in Colombia, specifically presenting the results on the perception of consistency between them and their relationship with retail brands of consumer products, this being one of the essential conditions of the integration. The data was collected during the months of April and May 2020 and is part of a study that seeks to understand the omnichannel purchasing behavior of consumers in emerging economies. Through the approach of a model type SEM (Structural Equation Model) revised with the PLS software, the relationship between the concepts of consistency and brand value is analyzed. The results confirm the relationship between brand value and consistency between channels.

JEL Code::
N16, M31, M15

Keywords::
omnichannel, emerging countries, consistency, retail brand

Introduction

Omnichannel is a shopping experience where consumers can shift between the physical and digital channels offered by brands. It represents an integrated sales experience that combines the advantages of physical store shopping with online shopping (Rigby, 2011). Omnichannel integrates online and offline channels to satisfy the consumer. The consumer is expected to experience this satisfaction during the shopping journey and at every touchpoint where they encounter the brand (Verhoef et al., 2015). While multichannel (separate channel experience) and omnichannel (integrated channel experience) models emerged before the pandemic, the increase in digital culture and competition in the post-pandemic retail sector has put even more pressure on brands to offer consumers both online and offline channels, whether click-and-collect or delivery (Nielsen, 2020).

The progress from multichannel to omnichannel differs in all territories, depending on cultural, technological, and social factors. In Colombia, where this research occurred, consumers have traditionally preferred the physical channel. Nonetheless, consumers have been gradually adopting the digital channel, much more so after the pandemic, because they feel increasingly comfortable using technologies to choose and buy products, especially those that support the integration of online and offline channels and services (La Republica, 2022).

Since omnichannel is not adopted in the same way in all countries (Piotrowicz & Cuthbertson, 2014), it is relevant to review how brands and consumers in different territories embrace it. Moreover, it is a key issue for the retail sector, which is one of the most important in the generation of jobs for the economy in Colombia, with an increase of 23.4% in sales between 2019 and 2023 and in employed personnel of 2.3% in the same period (DANE, 2023). Given the above, this study aims to shed light on the purchasing behavior of Latin American consumers in integrated channel environments. The goal is to test whether consistency among integrated channels influences retail brand equity in Colombia, understanding that integration is essential to an omnichannel strategy.

The article is structured as follows. In the introduction, the interests of the study and its rationale are presented; then, in the theoretical framework, the results of the bibliographic review leading to the hypothetical approach are presented. The methodology presents the data on the sample, the scales used for the study, and the data collection instruments, followed by an analysis and a discussion of the results. Finally, the paper concludes with the analysis and discusses the implications, limitations, and future lines of research.

Theoretical and conceptual framework

Differences between multichannel and omnichannel

In recent years, particularly after the pandemic, digital commerce and consumer isolation pressure have forced retailers to include the online channel, making them multichannel retailers (Frasquet et al., 2015). Multichannel focuses on the operation of channels, differentiating physical from digital (Melero et al., 2016; Piotrowicz & Cuthbertson, 2018). Nonetheless, just as retailers were forced to convert to multichannel, they must now integrate channels to respond to consumer demands and become omnichannel retailers.

Omnichannel is the evolution of multichannel. The main difference is that instead of operating the channels independently, the channels in the omnichannel are integrated, allowing the consumer to use them simultaneously (Lazaris & Vrechopoulos, 2014; Verhoef et al., 2015). In omnichannel, consumers can access the multiple products and services that brands offer from the comfort of their homes in an integrated shopping experience (Rigby, 2011). The synergy between channels empowers the consumer to interact with them and use them simultaneously (Verhoef et al., 2015). Table 1 shows the main characteristics and differences between omnichannel and multichannel from a brand and consumer point of view.

Table 1
Multichannel vs. omnichannel
Multichannel strategy Omnichannel strategy
Concept Division between channels Extended channel integration
Level of integration Partial Total
Scope of the channel Retail channels: store, website, and mobile channel Retail channels: store, website, social media, consumer touchpoints
Consumer relation approach: brands vs. channels Channel focus on the consumer Consumer-retail channel-brand focus
Targets Channel targets (sales per channel, experience per channel) All channels are integrated to offer a holistic consumer experience.
Channel Management By channel / Management of touchpoints between channels and consumers aimed at optimizing the experience with each one / Perceived interaction with the channel Channel crossover/synergy in the management of channels/touchpoints toward the engagement of a holistic consumer experience/perception of brand integration
Consumers Unable to trigger interaction / Use of parallel channels Can trigger full interaction / Simultaneous channel usage
Retailers It is not possible to control the interaction of the channels Full control of the integration of all channels
Vendors Does not adapt to purchasing behavior Adaptation to purchase behavior depending on the needs of each consumer and product knowledge
Source: created by the author based on Juaneda-Ayensa, Mosquera, and Sierra Murillo (2016)

The brand in omnichannel

The omnichannel experience is particularly related to the brand. A brand with the ability to integrate the different sales channels to offer the consumer a consistent experience in prices, services, products, promotions, information, and processes at each touchpoint during the shopping journey is considered an omnichannel brand. The success of omnichannel depends on the adequate management of the brand at each of the touchpoints (Verhoef et al., 2015).

The brand is the most sensitive element of communication of products and services in assessing the omnichannel experience, because it is where the purchase results are channeled. This is mainly because the brand represents the organization in the consumer's mind; hence, managers should be concerned about managing the brand properly (Neslin et al., 2014). Essentially, the challenge for omnichannel brand managers is to make the right choice of sales and communications channels to improve the experience in the shopping journey at each touchpoint the customer has with the brand.

During the shopping journey, consumers encounter the brand at touchpoints, i.e., when they consult a product on the website and then decide to visit the store. In each of these moments, there is an opportunity to add value to the brand through the customer experience, resulting in an overexposure of the brand in the consumer's interaction with it at the different touchpoints (Neslin et al., 2014). Hence, managers must take advantage of consumers' individual assessments at each point to project that assessment throughout the omnichannel strategy (Keller, 2010).

These repeated interactions between the consumer and the brand build an emotional bond and give the omnichannel brand a privileged position compared to online-only retail brands (Frasquet-Deltoro et al., 2021). In addition, they generate belonging, affiliation, and loyalty on the part of consumers, which contributes to positive Net Promoter Score (NPS) ratings (Almquist, Senior, & Bloch, 2016).

The concept of brand equity

Brand equity refers to the elements that define a brand that confer esteem and awareness in the minds of consumers that impact its economic value. Keller (1993) points out that brand equity levels can be broadly captured in 5 hierarchical aspects, in the following order from the lowest to the highest: brand awareness, brand associations, brand attitude, brand bonding, and brand activity. Aaker (1997) defines these dimensions as: loyalty, quality perception and leadership measures, associations and different measures, brand awareness, and market behavior measures.

In multichannel and omnichannel environments, brand equity is projected in the integrated experience of the channels. Therefore, the construction must be done from the various channels to the total brand strategy so the consumer adds value to the brand, not only from each touchpoint but from the overall consumer experience (Keller, 2010).

Notwithstanding, the generation of brand equity in omnichannel can occur in isolation, i.e., when the sale occurs without the influence of any other marketing measure such as promotions in other channels than the sales channel; or it can occur indirectly, i.e., when the consumer decides to buy due to the influence of communications and promotions in a channel other than the one where the purchase occurs (Keller, 2010). In other words, marketing measures for a specific purpose, such as promoting products, can affect brand equity at other times during the shopping journey. Hence, the complexity of omnichannel management lies in controlling the interactions between the customer, brand, and channel and in reviewing how each touchpoint with the customer affects the performance of the retail brand (Verhoef et al., 2015).

Consistency in channel integration

Cross-channel consistency is an essential condition defined as the ability of brands to provide an undifferentiated shopping experience across channels (Gao & Huang, 2021). It is evidenced in the uniformity of services provided in both physical and digital channels (Sousa & Voss, 2006), specifically in the uniqueness of products, prices, offers, communications, payment methods, and technological devices available in any of the company's channels (Rodriguez-Torrico et al., 2020).

It is considered that when there is consistency between sales channels, customers will perceive better quality in the degree of channel integration because they will have greater satisfaction in their shopping journey (Sousa & Voss, 2006). In fact, it is consumers who determine the quality of channel integration. Their perceptions of the company's ability to integrate its channels and their level of satisfaction derived from this ability finally allow them to classify channels as consistent or not (Neslin, 2022). This positive perception of consistency between channels gives consumers confidence, influences their purchasing decisions and therefore benefits brands (Huré et al., 2017; Jocevski et al., 2019).

Companies should not only aim to achieve the greatest possible uniqueness of service experience across channels but also strive to constantly review consumer feedback on their shopping experience derived from consistency across channels to assess the quality of their integration and manage it accordingly.

Hypothesis

Relation between brand equity and perceived channel consistency

In omnichannel, experience satisfaction results from the perceived consistency of the retail mix across channels, i.e., that products, prices, promotions, and services are the same across channels (Huré et al., 2017). The perception of consistency across channels influences brand equity because in omnichannel the brand is exposed to the consumer's assessment in each interaction across channels during the shopping journey (Neslin et al., 2014). Consumers expect products, services, and communications offered and displayed in the different channels to be the same (Carlson et al., 2015). Consequently, the perceived consistency across channels can affect brand equity.

Research addressing the integration of digital and physical channels in multichannel and omnichannel contexts has confirmed that consistency is an essential factor because it positively influences the perception of the services offered (Sousa & Voss, 2006), the perception of channel fluidity (Rodriguez-Torrico et al., 2020; Shen et al., 2018), customer loyalty to the brand (Gao & Huang, 2021), and the service experience in the interaction with different channels (Rodriguez-Torrico et al., 2020). Therefore, it is considered that consistency influences brand equity; hence, the following hypothesis is proposed:

H1: Perceived consistency influences retail brand equity in an integrated channel environment.

Thumbnail
Hypothetical model proposed for the research
Figure 1
Hypothetical model proposed for the research

Methodological design

Context

The research was developed in the city of Bogota during the COVID-19 lockdown. Even during these months, consumers were still figuring out how to adapt to the new living conditions. Nevertheless, in 2020 a 387% growth in e-commerce penetration was reported (Espectador, 2020). However, Colombia is still in a multichannel period, and omnichannel is still growing in the Colombian retail market (Diaz-Pardo, 2020). According to the E-commerce Observatory, consumers visit an average of two channels to consult or search for products or services online (ACIS, 2021), and it is important to analyze how the process of adaptation to multichannel is progressing and whether it is ready for omnichannel.

Research, universe, and sampling method

The research design is descriptive in the collection of data. The population universe comprises women and men between 18 and 55 years old, inhabitants of Bogota, who use online and non-retail channels to purchase food and toiletries. The type of sampling carried out was that of convenience that allows selecting those accessible cases that agree to be included, based on the convenient accessibility and proximity of the subjects for the researcher (Otzen & Manterola, 2017), this being the most appropriate due to the lockdown circumstances of the time when the fieldwork was carried out-between April and May 2020.

Characteristics of the sample

While 361 observations were collected, only 83 observations were used (those that complied with the condition of using multiple channels). The population universe was made up of inhabitants of Bogota. 41% of the respondents were men and 59% were women. The respondents ranged between 18 and 55 years old, with the majority being between 25 and 34 (42%), followed by people between 25 and 44 (33%). 67% of the respondents were employees, 23% were students, 7% were self-employed, and 3% were unemployed. Table 2 shows the demographic characteristics of the sample population.

Table 2
Characterization of the population sample
Gender Absolute values Percentage
Men 38 46%
Women 44 54%
Total 83 100%
Age Absolute values Percentage Activity Absolute values Percentage
Between 18 and 24 12 14% Employee 47 56%
Between 25 and 34 24 29% Unemployed 3 4%
Between 35 and 44 32 39% Pensioner 2 2%
Between 45 and 54 12 14% Independent 16 20%
55 or older 3 4% Student 15 18%
Total 83 100% Total 83 100%
Educational level Absolute values Percentage Income Absolute values Percentage
Baccalaureate 4 5% 1 to 3 minimum wages 23 28%
Undergraduate 40 48% 3 to 5 minimum wages 26 31%
Technical 7 8% 5 to 7 minimum wages 18 22%
Postgraduate 32 39% 7 to 9 minimum wages 7 8%
Over 9 minimum wages 8 10%
Less than one minimum wage 1 1%
Total 83 100% Total 83 100%
Source: created by the author

Questionnaire items

The questionnaire items were taken from the consumer-based Multidimensional Brand Equity (MBE) scale developed by Yooa and Donthu (2001). The Omnichannel Shopping Value (Omnichannel SV) scale by Huré, Picot-Coupey and Ackermann (2017) was considered for the omnichannel items. Both scales are considered for their statistically proven and validated psychometric qualities. The items that proved most suitable for addressing the concepts of omnichannel, consistency, and brand equity were chosen.

The questionnaire design was tested by experts in questionnaire design and initially tested to verify the comprehension and clarity of the questions. It was then provided electronically. The operationalization of the variables was done with 5-point Likert-type scales related to the variables of interest.

Table 3
Scales and dimensions used in the questionnaire
PERCEIVED CONSISTENCY BETWEEN CHANNELS AUTHOR
PC-1 Price: Do you consider that the prices of the products in the different sales locations of the brand you chose are: (Sales locations such as physical stores and online channels). Huré, Picot-Coupey, and Ackermann (2017)
PC-2 Offers: Do you consider that the offers of the products in the different sales locations of the brand you chose are: (Sales locations such as physical stores and online channels).
PC-3 Information: Do you consider that the information offered by the brand you have chosen in the different sales locations is: (Sales locations such as physical stores and online channels)
PC-4 Product diversity: Do you consider that the diversity of products offered by the brand you chose in the different sales locations is: (Sales locations such as physical stores and online channels).
OMNICHANNEL BRAND EQUITY Boonghee Yooa and Naveen Donthu (2001)
DIMENSION: LOYALTY
LO-1 I consider myself loyal to the brand I have chosen.
DIMENSION: PERCEIVED QUALITY
PQ-1 I consider that the brand I chose sells products of great quality!
PQ-2 I can trust that the brand I chose sells the products I want at the prices I'm looking for at the place that suits me!
DIMENSION: BRAND RECALL AND ASSOCIATIONS
R-A-1 I can recognize the brand I chose among other competing brands!
R-A-2 I quickly remember some characteristics of the brand I chose!
R-A-3 I can quickly remember the symbol or logo of the brand I chose!
R-A-4 I can bring to my mind the brand I chose with no problem!
Source: created by the author based on the referenced authors

Analysis of the results

Psychometric characteristics

The psychometric characteristics of the scales were analyzed before contrasting the proposed hypotheses resulting from the theoretical and conceptual research. The proposed model is reflective in nature. According to the literature on brand equity and online channels, the relation of the variables is reflective (Christodoulides et al., 2006). The choice of measurement perspective (formative vs. reflective) is based on the literature findings (Diamantopoulos & Siguaw, 2006).

Thumbnail
Structural model, variables, and indicators Source: created by the author
Figure 2
Structural model, variables, and indicators

Subsequently, the structural equation model was verified using the Partial Least Squares (PLS) method. Internal consistency was checked with the result of p-values and loadings results. Hair et al. (2019) recommend loadings above 0.7 as they indicate that the construct explains more than 50 percent of the variance of the indicator, thus providing an acceptable element of reliability. The statistical significance of the p-values was <0.05, indicating 95% confidence and confirming what is indicated by the theory.

The loading data were revised. After the first estimation of the model in PLS, indicator PC-2 (Perceived Consistency 2) was removed from the PC factor (perceived consistency). This improved the reliability and validity results. As for BE (Brand equity), although the Loyalty (LO) dimension loadings and p-values do not meet these conditions, it is not removed since it is essential to measure the factor. As Manzano and Jimenez (2017) pointed out, the researcher must be aware that automatically removing any indicator with a loading lower than 0.7 may decapitalize content validity.

Cronbach's Alpha (CA) was tested for all latent variables. The CA explains the proportion of the scale's total variance attributed to the latent variable (Manzano & Jimenez, 2017). Values greater than 0.70 demonstrate a good consistency of the construct, which was the case of the results obtained. Consistency was tested with the composite reliability (CR) indicator. According to Hair, Ringle, and Sarstedt, (2011), it should be higher than 0.70 (in exploratory research, 0.60 and 0.70 are considered acceptable). The results obtained show values between 0.80 and 0.90. Table 4 shows the results of the measurement instruments' reliability and convergent validity tests.

Table 4
Reliability, internal consistency, and convergent validity coefficients
FACTORS CONVERGENT VALIDITY RELIABILITY
PERCEIVED CONSISTENCY PC Item Loadings t-values p-values CA CR AVE
PC-1 0.755*** 4.946 0.000 0.717 0.828 0.618
PC-3 0.721*** 4.573 0.000
PC-4 0.873*** 12.813 0.000
BRAND EQUITY BE LO 0.518** 2.282 0.023 0.703 0.810 0.599
PQ 0.857*** 6.969 0.000
BRA 0.890*** 6.567 0.000
ƛ Loadings; t-values; **p-values; ***p-values; CA (Cronbach’s alpha); CR (composite reliability); AVE (average variance extracted); PC (perceived consistency); BE (brand equity); LO (loyalty); PQ (perceived quality); BRA (brand recognition and associations). Source: created by the author

Convergent validity and discriminant validity of the scales

An AVE was used to determine discriminant validity. The Fornell and Larcker criterion and the HTMT coefficient were reviewed. The AVE values must exceed 0.50 (Manzano & Jiménez, 2017). All latent variables yielded a result greater than 0.50 (see Table 1). The Fornell and Larcker coefficient is observed in Table 5 at the square root of the AVE of the latent variables (diagonal values). The AVE should be greater than the correlations of that variable with the rest of the variables (Hair et al., 2011). Table 5 shows the coefficients and correlations of the first-order variables. The square root of the AVE is shown in black.

Table 5
Fornell-Larcker criterion
FACTORS CORR AVE
PERCEIVED CONSISTENCY PC 0.283 0.786
BRAND EQUITY BE 0.293 0.774
Source: created by the author

The HTMT coefficient was obtained by bootstrapping. Values above 0.90 demonstrate problems in discriminant validity. In this respect, all latent variables yield results below 0.90. The HTMT value cannot exceed 0.90 (Manzano & Jiménez, 2017). For conceptually different constructs, HTMT <0.85 (Hair et al., 2019).

Table 6
HTMT Index
Heterotrait-Monotrait Ratio (HTMT) Value
FACTORS
PC -> BE 0.334
HTMT < 0.90. Source: created by the author

The factorial cross-loadings of indicators show that the loadings of indicators constituting a latent variable are higher on their own latent variable than the values of other variables (Henseler et al., 2009).

Table 7
Cross-loadings of the indicators
FACTORS INDIC PC BE
PERCEIVED CONSISTENCY PC PC-1 0.756 0.218
PC-3 0.721 0.140
PC-4 0.874 0.284
BRAND EQUITY BE LO 0.084 0.519
PQ 0.225 0.858
B-R-A 0.295 0.891
Source: created by the author Loadings of the indicators corresponding to the latent variable are gray, all higher than the other variables.

Hypothesis testing and predictability of the model

To review the causal relations between the constructs and test the theoretical model, p-values, t-values, and the Q² coefficient were tested, as proposed by Hair et al., (2019).

Hypothesis:

H1: Perceived channel consistency affects brand equity

The results of the t-values and p-values reflect hypothesis H1. The p-values less than 0.05 confirm that the proposed hypothesis is accepted and that there is a relation between consistency and brand equity, where brand equity is positively affected by consistency between channels. The Variance Inflation Factor (VIF) parameter showing the collinearity of the model is less than 3, indicating no collinearity problems (Joe F. Hair et al., 2014).

Table 8
Hypothetical testing
Hypothetical relations Hypothesis t-values P-Values VIF(Col)
H1: Perceived consistency -> Brand equity Accepted 2.901 0.004 1.87
Source: created by the author

The Q² index confirms the prediction of the model. Specifically, the literature indicates that a value greater than zero is significant (Hair et al., 2019).

Table 9
Stone-Geisser test as a criterion of Q²
FACTORS Q²
BRAND EQUITY BE 0.033
Source: created by the author

Conclusions

This research aimed to elucidate the relation between brand equity and the perception of consistency between sales channels in retail brands. The hypothesis was confirmed. It was possible to verify that there is an impact on brand equity when consumers perceive consistency between physical and virtual channels (website, mobile application, or physical store).

Consistency has been confirmed as essential for integrating retail brand channels in emerging countries. The aim is for consistent communication, distribution, logistics, and pricing across all available channels.

Omnichannel retailing ensures an integrated process that provides an integrated perspective of a product or service to the consumer in terms of purchase, return, and exchange in each channel (Chong, 2018, cited in Adivar et al., 2019, p. 258). Therefore, proper consistency management across channels contributes to the consumer's positive perception of the brand. This reinforces the findings of the work of Huré, Picot-Coupey, and Ackermann, who state that the consistency of an omnichannel experience is evaluated on three elements: product, price, and services, and any failure to meet these expectations is negatively perceived and resented by consumers (Huré, Picot-Coupey, & Ackermann, 2017, p. 321). Consistency immediately benefits retail consumers as it helps lower the perceived risks of the omnichannel experience (Quach et al., 2020).

Implications

Omnichannel is a relevant topic that has advanced significantly but is still under exploration, especially in countries where omnichannel is recent. Practical and academic marketing research has been interested in reviewing how consumers respond in this new environment. Because of their relevance, some topics should be reviewed, such as brand equity (Keller, 2010; Verhoef et al., 2017). Considering that channel consistency is about comprehensive information across all channels, carefully managing the unified strategy across all channels is relevant to maintaining a positive brand equity.

Consistency is an essential factor in channel integration studies since, according to research, it impacts consumer perceptions of trust and loyalty (Mainardes et al., 2020; Quach et al., 2020; Shen et al., 2018). Regarding brand equity, it is important to explore further the utility that arises for the consumer from a consistent brand experience across retail channels (Carlson, O'Cass, & Ahrholdt, 2015).

During the shopping journey, the consumer interacts with the brand through touchpoints. The brand tracks the customers’ journey through these touchpoints, allowing it to determine which are the most important in generating value (Lemon & Verhoef, 2016). In the end, the moment of purchase is where it is concluded which of these points produces the most value for consumers and for the brand (Neslin et al., 2014). This way, retailers can take advantage of the tracking they do to the consumer during their shopping journey and develop strategies to benefit both (Blom et al., 2017). To this end, omnichannel brand managers should focus on developing brand equity in the communicative and strategic aspects to take advantage of the benefits brought by the constant interaction of the brand at each of the touchpoints and ensure that it is positive by providing a positive experience based on the consistency between shopping channels.

Limitations

Colombia is still in the multichannel development stage, and omnichannel is only emerging. Although Colombia is a country that is working to improve its technological conditions, it is far behind advanced economies in terms of the value of ICT (Information and Communication Technologies) assets (MinTic-Colombia, 2019). Accordingly, the country is in a process of technological development that promotes the use of devices and technologies for its population. The development of omnichannel is not uniform throughout the world. Some markets and sectors are ahead, while others are trying to replicate the emerging model (Piotrowicz & Cuthbertson, 2019). This conditions the results of the study.

On the other hand, there is still no balance between the preference for digital and physical channels, and this was evidenced in the sample (only 83 people out of 361 answered the omnichannel experience filter questions correctly). The Ministry of Technologies and Communication in Colombia states that only 2 out of every 10 internet users over 15 years of age perform e-commerce (Buy and pay online) (MinTic-OE, 2019).

Future lines of research

Future lines of research regarding branding are linked to technological developments that support retailers’ branding strategies. Based on big data, leveraging consumer knowledge will be essential to take advantage of data generated at touchpoints and along the consumer journey. This will be the new way to find what consumers want to say about their experience in the various channels.

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Omnichannel; Consistency in a retail brand's channel integration
  • Contad. Adm  vol. 69n. 2Omnichannel; Consistency in a retail brand's channel integration Barón López Ena Yuritze * 1 Author affiliationPermissions
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