The Evolution of E-commerce in B2B Sales: Analysis of Digitalization in the Microbiology Division

Bruno Rozetti Cristovão; Natan de Souza Marques

DOI: 10.22167/2675-6528-202602745

Article derived from a Final Course Work (TCC), with content based on the student’s original work and adapted to the editorial format of the E&S Magazine with the support of the ResumeAI tool, an artificial intelligence solution developed by Instituto Pecege for textual synthesis and organization.

Abstract

Digital transformation has led to significant changes in companies’ commercial strategies, especially with the incorporation of digital channels in B2B relationships. In this context, the study analyzed the digitalization profile of e-commerce in the microbiology division of a Life Science unit of the company Lifescience Corporation, a Brazilian multinational, evaluating the growth of the digital channel, its interaction with the traditional channel, and its role in the omnichannel structure. The research was conducted through the analysis of commercial data between 2021 and 2025, considering indicators such as revenue, order volume, average ticket, digital penetration, and customer migration trajectories between channels. The results indicated that the division’s revenue showed a general growth trend over the period, with an atypical peak in 2022 associated with the COVID-19 pandemic, followed by stabilization and a resumption of moderate growth. It was observed that the offline channel remained predominant in transactions, reflecting the consultative and technical characteristics of the B2B Life Science market. However, consistent growth in e-commerce was identified, with an increase in its share of revenue, number of orders, and customer adoption. It was concluded that the analyzed division is in an intermediate stage of digital maturity, in which the digital channel is progressively expanding, acting complementarily to the traditional channel and contributing to the consolidation of a hybrid and omnichannel commercial model.

Keywords: Digital Channel; Commercial Strategy; Life Science; Multichannel; Omnichannel.

1. Introduction

Digital transformation has significantly reshaped companies’ business strategies, especially through the incorporation of digital channels in B2B relationships. This phenomenon represents a current and critical phase for most organizations, directly influencing how they relate to their customers. In the Brazilian context, digitalization is a central factor for innovation, competitiveness, and business productivity, impacting processes, strategies, value generation, and organizational differentiation (OECD, 2020). The use of the internet as a recurring sales channel has driven disruptive changes, consolidating e-commerce as an essential tool that offers accessibility, convenience, and the possibility of price comparison (Borges, 2022).

The COVID-19 pandemic accelerated the digitalization of commerce, affecting both retail and B2B relationships and promoting significant changes in services and products (Veiga, 2024). The inclusion of a digital channel in B2B transactions has shown gains, configuring a rising market with great potential. This scenario demands periodic review so that managers stay updated on the impact of new channels, aiming to strengthen complementarity, optimize performance, efficiency, and consequently, increase revenue, without cannibalization occurring (Abe, 2022).

In this constantly evolving environment, the digitalization of commercial relationships and the integration between traditional and digital channels in the B2B context are crucial (Verhoef et al., 2021; Kannan; Li, 2017; Abe; Ramos, 2022; Veiga, 2024). E-commerce, as part of this transformation, has the potential to optimize transactional processes and expand access to information and products. However, there is still a gap in understanding how the digital channel develops in specific sectors of high complexity, such as microbiology, and how it interacts with traditional channels.

The understanding of these dynamics is fundamental for companies operating in industrial and technological markets, where direct interaction between sellers and customers traditionally plays a central role in complex, high-value-added sales. Thus, the relevance of this study lies in offering evidence on the strategic role of e-commerce in transforming industrial commercialization models for the microbiology sector, which involves the sale of culture media, quantitative strains, filtration equipment, cleaning validation, and sterility and bioburden testing. Given this scenario, the present study aims to analyze the digitalization profile of e-commerce in the microbiology division of a Life Science unit of the company named Lifescience Corporation, a real multinational based in Brazil, seeking to understand whether the digital channel grows together with the division or replaces the traditional channel, whether e-commerce represents a marginal or relevant channel in generating revenue and orders, and how digitalization influences the omnichannel structure, average ticket, and customer channel migration trajectories over time.

2. Material and Methods

This study was characterized as an applied research, with a quantitative approach and descriptive nature. The research strategy adopted was the case study, focusing on the role of e-commerce in the microbiology division of the Lifescience Corporation company. The data used were real, originating from the author’s own organization, with prior authorization for their use, ensuring fidelity to the business context.

The empirical object of the research was the e-commerce channel of Lifescience Corporation, a multinational company based in Brazil, and its interaction with the microbiology division. This division is responsible for the commercialization of materials, supplies, and equipment for quality control analysis, serving pharmaceutical, veterinary, food, beverage, chemical industries, and quality control laboratories.

Data collection was performed from the organization’s internal databases, specifically from a spreadsheet named “Daily Sales”. This spreadsheet contained a macro of essential transactional information, covering data such as customer order, Stock Keeping Unit (SKU), region, total sales (vendas)/ invoicing (emissão de doc) per order, customer name and code, city, and quantity of invoiced items.

For the analysis, all transaction data recorded between the years 2021 and 2025 were considered. Aiming to preserve the confidentiality and ethics of the research, no customer name, city, or region was used. The data were treated in an aggregated manner, focusing only on billing numbers, order quantities, type of channel used by customers, and billing date.

The analyses were conducted at quarterly and annual intervals, seeking a comprehensive understanding of commercial dynamics. The decision not to perform monthly analyses was due to the reality of the microbiology division, where seasonality and import/delivery logistics could generate punctual oscillations and operational noise, making the quarterly analysis more reliable.

Although the digital sales channel, e-commerce, was implemented in 2019, the study period was delimited between 2021 and 2025. This choice aimed to avoid biases related to the initial implementation phases, internal learning, and initial customer adoption, ensuring that the analysis focused on a period of consolidation of e-commerce as an active sales channel.

For standardization purposes in the database, it was considered that each invoice number corresponded to an order. It is important to note that a single invoice could encompass several item lines, but for the order count, the invoice was the unit of measure. The analyses were structured in three main blocks, each with specific objectives.

The first analysis block focused on the evolution of commercial results, seeking to evaluate growth, seasonality, and operational structure. To this end, total revenue per quarter and per year, the average number of lines per order (comparing offline and e-commerce channels), and the volume of orders from each channel, also per quarter and per year, were measured.

In the second block, digital participation and penetration were investigated, with the aim of measuring the relative importance of e-commerce in the microbiology division of Lifescience Corporation. E-commerce participation in total sales and number of orders, by quarter and by year, was analyzed, as well as digital penetration, also by quarter and by year.

The third analysis block addressed the omnichannel structure and digital transformation, aiming to understand customer behavior in relation to channels. Examined were the distribution of customers by channel and by year, the year-over-year (YoY) annual growth rate by channel, the evolution of the average ticket by customer type, and the longitudinal customer digitalization trajectories in the period from 2021 to 2025.

For the analysis of total invoicing, the columns of invoicing and year were extracted from the “Daily Sales” database, summing them up for each year and for each of the twenty quarters (four per year). The average number of lines per order per channel was calculated from the columns “Invoice (Orders)”, “Channel”, “Quarter-Year”, “Year”, and “Product”, using pivot tables to count the orders per channel and a formula to assign the value of lines per order to the corresponding channel.

The volume of orders for each channel was determined using a pivot table, configuring “Year-Quarter” in the rows, “Channel” in the columns, and the distinct count of “Orders” in the values. The e-commerce share of revenue was obtained by dividing the sum of revenue for each channel by the total revenue, after organizing the data into pivot tables with the columns “Quarter-Year”, “E-commerce”, “Offline”, and “Sales EUR”.

The participation of e-commerce in the number of orders was calculated similarly, using the columns “Orders”, “Channel”, and “Quarter-Year” in pivot tables. Digital penetration, defined as the proportion of customers who adopt the online channel (Verhoef et al., 2015), was measured by dividing the number of active customers in e-commerce by the total number of active customers, based on the columns “Quarter-Year”, “Year”, “Channel”, and “Customers” from the “Daily Sales” database.

The distribution of customers by channel and by year was established from the columns “Customers”, “E-commerce” and “Offline” of the “Daily Sales” base. A new column named “Customer Typology” was created with a logical formula to classify customers as “Omnichannel”, “E-commerce”, “Offline” or “No purchase”, according to their interactions with the channels. Then, a pivot table was created to count the proportion of customers in each typology by year.

The year-over-year (YoY) annual growth rate per channel was calculated based on the results of the customer ratio per channel, applying the percentage change formula between consecutive years (Ross et al., 2016). The evolution of the average ticket per customer type, defined as the average value spent per transaction (Kotler and Keller, 2012), was analyzed using the columns “Customers”, “Sales EUR”, “Year”, “Quarter-Year” and “Customer Typology” in pivot tables to aggregate the values and calculate the averages.

Finally, the longitudinal customer digitization trajectories were constructed from the columns “Year”, “Customers”, and “Type” of the “Daily Sales” database. A score was assigned to each customer type (1 for offline, 2 for omnichannel, and 3 for e-commerce) per year, forming sequences that represented each customer’s trajectory. These trajectories were classified into categories such as “Digital Transformation”, “Digital Churn”, “Customer Churn”, and “Late Digital Transformation”, using a logical formula for categorization.

This study was characterized as an applied research, with a quantitative approach and descriptive nature. The research strategy adopted was the case study, focusing on the role of e-commerce in the microbiology division of the Lifescience Corporation company. The data used were real, originating from the author’s own organization, with prior authorization for their use, ensuring fidelity to the business context.

The empirical object of the research was the e-commerce channel of Lifescience Corporation, a multinational company based in Brazil, and its interaction with the microbiology division. This division is responsible for the commercialization of materials, supplies, and equipment for quality control analysis, serving pharmaceutical, veterinary, food, beverage, chemical industries, and quality control laboratories.

Data collection was performed from the organization’s internal databases, specifically from a spreadsheet named “Daily Sales”. This spreadsheet contained a macro of essential transactional information, covering data such as customer order, Stock Keeping Unit (SKU), region, total sales (vendas)/ invoicing (emissão de doc) per order, customer name and code, city, and quantity of invoiced items.

For the analysis, all transaction data recorded between the years 2021 and 2025 were considered. Aiming to preserve the confidentiality and ethics of the research, no customer name, city, or region was used. The data were treated in an aggregated manner, focusing only on billing numbers, order quantities, type of channel used by customers, and billing date.

The analyses were conducted at quarterly and annual intervals, seeking a comprehensive understanding of commercial dynamics. The decision not to perform monthly analyses was due to the reality of the microbiology division, where seasonality and import/delivery logistics could generate punctual oscillations and operational noise, making the quarterly analysis more reliable.

Although the digital sales channel, e-commerce, was implemented in 2019, the study period was delimited between 2021 and 2025. This choice aimed to avoid biases related to the initial implementation phases, internal learning, and initial customer adoption, ensuring that the analysis focused on a period of consolidation of e-commerce as an active sales channel.

For standardization purposes in the database, it was considered that each invoice number corresponded to an order. It is important to note that a single invoice could encompass several item lines, but for the order count, the invoice was the unit of measure. The analyses were structured in three main blocks, each with specific objectives.

The first analysis block focused on the evolution of commercial results, seeking to evaluate growth, seasonality, and operational structure. To this end, total revenue per quarter and per year, the average number of lines per order (comparing offline and e-commerce channels), and the volume of orders from each channel, also per quarter and per year, were measured.

In the second block, digital participation and penetration were investigated, with the aim of measuring the relative importance of e-commerce in the microbiology division of Lifescience Corporation. E-commerce participation in total sales and number of orders, by quarter and by year, was analyzed, as well as digital penetration, also by quarter and by year.

The third analysis block addressed the omnichannel structure and digital transformation, aiming to understand customer behavior in relation to channels. Examined were the distribution of customers by channel and by year, the year-over-year (YoY) annual growth rate by channel, the evolution of the average ticket by customer type, and the longitudinal customer digitalization trajectories in the period from 2021 to 2025.

For the analysis of total invoicing, the columns of invoicing and year were extracted from the “Daily Sales” database, summing them up for each year and for each of the twenty quarters (four per year). The average number of lines per order per channel was calculated from the columns “Invoice (Orders)”, “Channel”, “Quarter-Year”, “Year”, and “Product”, using pivot tables to count the orders per channel and a formula to assign the value of lines per order to the corresponding channel.

The volume of orders for each channel was determined using a pivot table, configuring “Year-Quarter” in the rows, “Channel” in the columns, and the distinct count of “Orders” in the values. The e-commerce share of revenue was obtained by dividing the sum of revenue for each channel by the total revenue, after organizing the data into pivot tables with the columns “Quarter-Year”, “E-commerce”, “Offline”, and “Sales EUR”.

The participation of e-commerce in the number of orders was calculated similarly, using the columns “Orders”, “Channel”, and “Quarter-Year” in pivot tables. Digital penetration, defined as the proportion of customers who adopt the online channel (Verhoef et al., 2015), was measured by dividing the number of active customers in e-commerce by the total number of active customers, based on the columns “Quarter-Year”, “Year”, “Channel”, and “Customers” from the “Daily Sales” database.

The distribution of customers by channel and by year was established from the columns “Customers”, “E-commerce” and “Offline” of the “Daily Sales” base. A new column named “Customer Typology” was created with a logical formula to classify customers as “Omnichannel”, “E-commerce”, “Offline” or “No purchase”, according to their interactions with the channels. Then, a pivot table was created to count the proportion of customers in each typology by year.

The year-over-year (YoY) annual growth rate per channel was calculated based on the results of the customer ratio per channel, applying the percentage change formula between consecutive years (Ross et al., 2016). The evolution of the average ticket per customer type, defined as the average value spent per transaction (Kotler and Keller, 2012), was analyzed using the columns “Customers”, “Sales EUR”, “Year”, “Quarter-Year” and “Customer Typology” in pivot tables to aggregate the values and calculate the averages.

Finally, the longitudinal customer digitization trajectories were constructed from the columns “Year”, “Customers”, and “Type” of the “Daily Sales” database. A score was assigned to each customer type (1 for offline, 2 for omnichannel, and 3 for e-commerce) per year, forming sequences that represented each customer’s trajectory. These trajectories were classified into categories such as “Digital Transformation”, “Digital Churn”, “Customer Churn”, and “Late Digital Transformation”, using a logical formula for categorization.

3. Results and Discussion

The analysis of the commercial data of the microbiology division of Lifescience Corporation, covering the period from 2021 to 2025, revealed a detailed panorama of the evolution of e-commerce and its interaction with the traditional channel. The results indicated a general trend of growth in the division’s revenue, albeit with particularities that reflect the dynamics of the B2B market and the impact of external events, such as the COVID-19 pandemic. Digitalization, in this context, proved to be a continuous and complementary process, not replacing, but enhancing the existing commercial model.

The division’s total revenue showed a growth trajectory throughout the studied period, increasing from 11.98 million Euros in 2021 to 16.05 million Euros in 2025. An atypical peak was observed in 2022, with 15.15 million Euros, which can be associated with increased demands resulting from the COVID-19 pandemic, especially due to the race for vaccine inputs and intense activity in the healthcare market (Cornish et al., 2023). The microbiology division, by commercializing equipment and supplies for pharmaceutical analyses, was directly impacted by this scenario.

After the 2022 peak, 2023 registered a normalization of billing levels, with 13.81 million Euros, returning to a trajectory more aligned with the pattern observed in 2021. In subsequent years, moderate and consistent growth was observed, indicating a sustained expansion of the division in the post-pandemic period. The quarterly analysis, in turn, revealed a tendency towards seasonality of purchases, a common phenomenon in industrial markets, where the demand for products presents specific patterns of rise, plateau, and decline throughout the year, as pointed out by Borucka (2023).

Evolution of commercial results: average lines per order (Offline vs E-commerce)

Regarding the average lines per order, an interesting dynamic was observed between the channels. The e-commerce channel, in general, presented an average of lines per order slightly higher or comparable to the offline channel in several quarters, such as in the first quarter of 2021, with 1.46 lines for e-commerce and 1.39 for offline. However, a significant peak was noted in the offline channel between the second quarter of 2022 and the third quarter of 2023, where the average lines per order for offline considerably surpassed that of e-commerce, reaching 3.26 in the fourth quarter of 2022, while e-commerce registered 1.48.

This variation can be explained by the nature of the initial e-commerce implementation, which was primarily directed at distributors. These clients already possessed technical knowledge of the products and fixed pricing agreements, not requiring personalized service or consultative selling. The temporary migration of these distributors to the offline channel during the peak period, with many of their orders being processed through this channel, suggests instability or specific demand for one-off projects, driven by external factors that impacted commercial dynamics (Verhoef et al., 2021).

Despite this specific migration, the channels demonstrated functional complementarity regarding the number of lines per order, a behavior aligned with omnichannel strategies (Herhausen et al., 2015; Verhoef; Kannan; Inman, 2015). E-commerce, due to its ease of adding different products in the same order, tends to have a higher number of lines, a characteristic associated with the convenience and efficiency of digital channels in B2B environments (Kannan; Li, 2017). Both channels, however, remained constant over time, with the exception of the peak period.

Evolution of commercial results: order volume from each channel by quarter and by year

The volume of orders per quarter showed the continued predominance of the offline channel in terms of transaction quantity throughout the entire analyzed period. In 2021, the offline channel registered 11,540 orders, while e-commerce totaled 4,340. In 2025, offline maintained the lead with 10,685 orders, and e-commerce reached 5,459. This pattern suggests that, despite the expansion of the digital channel, the consultative and relational sales model, with direct interaction between seller and customer, remains the main channel for order acquisition and execution in the microbiology division, given the technical complexity of the marketed materials (Porter; Heppelmann, 2014).

Quarterly seasonality was also observed in both channels, with fluctuations that can be attributed to budgetary cycles, laboratory projects, and institutional purchases. These variations are likely related to annual laboratory qualifications and clients’ internal technical and documentary validations, which are intrinsic characteristics of companies that perform microbiological quality control. This behavior is consistent with the literature on digitalization in B2B contexts, which indicates a preference for digital channels for routine and less complex transactions, while traditional channels are maintained for complex, consultative, and high-value-added sales (Porter & Heppelmann, 2014; Verhoef et al., 2015).

Channel participation and digital penetration: E-commerce share of revenue by quarter and by year

The participation of e-commerce in the division’s total sales demonstrated a clear trend of structural growth over the period. In 2021, the average participation of e-commerce in total sales was 18.46%, while the offline channel represented 81.54%. Progressively, e-commerce participation increased, reaching 28.56% in 2023 and 27.67% in 2025, with offline participation decreasing to 71.44% and 72.33%, respectively. This upward trajectory indicates that the digital channel is not merely marginal but captures a relevant and growing share of the division’s total sales.

This behavior is an indicator that the digital channel acts in a complementary way to the traditional channel, contributing to transactional efficiency without replacing it, a pattern aligned with the concept of omnichannelity (Anderson et al., 2006; Verhoef et al., 2015). The quarterly analysis also revealed fluctuations in e-commerce participation, with peaks such as 34.54% in the fourth quarter of 2023, suggesting that digital adoption may vary seasonally or in response to specific campaigns, but the general trend is expansion.

Channel participation and digital penetration: E-commerce participation in number of orders (%) by quarter and by year

The participation of e-commerce in the number of orders also showed a consistent growth trend. In 2021, the average e-commerce participation was 27%, rising to 30% in 2022, 31% in 2023, and remaining at 34% in 2024 and 2025. This evolution demonstrates that the digital channel is increasingly being used for routine and recurring transactions, consolidating itself as a channel of operational convenience. The stability of this growth, compared to the variations observed in total sales, corroborates the hypothesis that e-commerce is preferred for more basic and less complex orders.

The digital channel, by its nature, facilitates faster purchase processes with agile confirmation, from cart to order processing, without the need for manual intervention. This ensures customer satisfaction and encourages repeat purchases of the same type. This behavior is consistent with literature suggesting that smaller, lower-value purchases are more likely to be made online, while more complex transactions requiring negotiation remain in the offline channel (Verhoef et al., 2015).

Channel participation and digital penetration: digital penetration by quarter and by year

Digital penetration, which measures the proportion of customers adopting the online channel, showed continuous growth over the period. The average digital penetration increased from 20% in 2021 to 32% in 2024 and 2025. This increase indicates that the expansion of orders in the digital channel is not restricted only to already digitized customers, but also includes adoption by new customers who previously did not use e-commerce. This corroborates the progressive incorporation of new customers into the digital channel, reflecting structural digital adoption and the diffusion of innovation (Venkatesh et al., 2012).

The trend line of digital penetration corroborates the rise of digital incorporation in customers who already purchased through offline channels, indicating that e-commerce is no longer a marginal channel and is in a state of progression towards a plateau, which suggests a consolidated digital maturity in the customer base. Although there are quarterly variations, which can be explained by seasonality and occasional changes in the active customer base, the general trend is one of growth and consolidation of digital presence.

Omnichannel structure and digital transformation: customer distribution by channel and by year (%)

The distribution of customers by channel revealed a significant transition. In 2021, 75% of customers were “offline-only”, 21% “e-commerce-only”, and 4% “omnichannel”. In 2025, the proportion of “offline-only” customers decreased to 62%, while “e-commerce-only” customers increased to 29% and “omnichannel” to 9%. This visualization indicates a migration of the customer base to digital channels, with those who were previously only offline now adopting the digital channel. This suggests that e-commerce functions as an entry point for new customers, especially for less complex purchases (Verhoef et al., 2015).

Omnichannel structure and digital transformation: annual growth rate by channel (YoY by channel – %)

The Year-over-Year (YoY) assessment complemented the results, highlighting the relative reduction of the offline channel and the expansion of e-commerce and omnichannel channels. The biggest leap in digital adoption occurred in the post-pandemic period, especially from 2022 onwards, with e-commerce registering 3% YoY growth in 2022, 14% in 2023, and 21% in 2024. The omnichannel channel saw remarkable growth of 129% in 2023, indicating an acceleration of customers’ digital maturity and greater confidence in using the electronic channel for purchases.

The growth peak observed in 2022 may also be associated with operational improvements in the digital channel, as e-commerce platforms are frequently updated and enhanced, which can increase the efficiency of the purchasing process and encourage adoption. Starting in 2024, a reduction in growth rates was observed, with e-commerce showing -4% in 2025, and omnichannel 10%, indicating a possible stabilization after the period of accelerated expansion. This slowdown may reflect a return to growth levels closer to the market’s structural pattern, but the continuous increase in the participation of omnichannel customers suggests the consolidation of a hybrid purchasing model (Verhoef et al., 2021).

Omnichannel structure and digital transformation: evolution of average ticket by customer type

The evolution of the annual average ticket by customer type revealed that the total sales of omnichannel customers are becoming increasingly larger. The omnichannel customer’s average ticket grew from 11,147.68 Euros in 2021 to 19,289.41 Euros in 2025. In contrast, the e-commerce average ticket was significantly lower, at 1,059.83 Euros in 2021, falling to 386.49 Euros in 2025, while the offline average ticket remained high, at 10,530.30 Euros in 2021 and 11,720.87 Euros in 2025.

This disparity suggests that omnichannelity is an indicator of a customer profile with greater complexity and value, who makes recurring purchases through digital channels and complex purchases with consultative sellers. More sophisticated customers tend to adopt multiple channels, while less sophisticated customers remain “digital-only” or “offline-only” (Herhausen et al., 2015). The low average ticket of e-commerce justifies routine and operationally simple purchases, while offline remains the channel for negotiations and customized sales that depend on a salesperson (Verhoef et al., 2015).

The analysis also indicated that omnichannel customers may be purchasing a wider variety of products, categories, and services (Herhausen et al., 2015). A relevant strategic point is the trend of a plateau in recent years in the omnichannel average ticket, which may indicate a possible saturation of the monetization of these customers. This suggests that, in the future, a greater expansion of the omnichannel customer base may be necessary, rather than focusing solely on increasing the average ticket per customer.

Omnichannel structure and digital transformation: longitudinal trajectories of customer digitalization (2021 – 2025)

The analysis of longitudinal customer digitalization trajectories (2021-2025) classified customers into different types. The “Customer Churn” category represented the largest proportion, with 40.81% (1436 customers), followed by “Others” with 38.79% (1365 customers). “Digital Transformation” accounted for 6.79% (239 customers), and “Late Digital Transformation” for 13.61% (479 customers). No cases of “Digital Churn” were observed in the analyzed database.

The high percentage of “Customer Churn” can be attributed to factors such as purchases by different CNPJs from the same customer, interruption of the business relationship with the microbiology division, migration to distributors (already included in the analysis), incorporation by other customers, or change of CNPJ. This indicates a significant structural turnover in the microbiology market, where total sales (vendas)/ Invoicing (emissão de doc) is influenced by equipment validation cycles, capital expenditure (CAPEX) studies, research and funding cycles, impacting purchase recurrence (Anderson et al., 2006).

The offline channel remains dominant, not only due to product complexity but also due to the traditional sales method. The gradual digital shift is still under development, and although growing, it does not constitute the majority, characterizing a state of intermediate digital maturity (Verhoef et al., 2021). The presence of a significant portion of “Late Digital Transformation” corroborates this transitional state, indicating a gradual digitalization of customers, often reactivating them, suggesting that e-commerce can serve as a reactivation channel (Venkatesh et al., 2012).

In summary, the microbiology division of Lifescience Corporation demonstrates an intermediate stage of digital maturity. The digital channel shows consistent growth and increasing customer adoption, acting complementarily to the traditional channel. This scenario indicates the consolidation of a hybrid and omnichannel commercial model, where different channels meet distinct needs in the purchasing journey, contributing to efficiency and deepening customer relationship, without the digital channel replacing the traditional salesperson.

4. Conclusion

The present study analyzed the digitalization profile of e-commerce in the microbiology division of a Life Science unit at Lifescience Corporation, seeking to understand the dynamics between digital and traditional channels. It was found that the division’s total sales showed a general growth trend between 2021 and 2025, with an atypical peak in 2022 associated with the COVID-19 pandemic, followed by stabilization and moderate recovery. The continuous predominance of the offline channel in order volume and total sales was observed, reflecting the consultative and technical nature of the B2B Life Science market. However, consistent growth in e-commerce was identified, with an increase in its share of total sales and order volume, as well as an increase in digital penetration, indicating the progressive adoption of the online channel by customers. The analysis of the omnichannel structure revealed that customers using multiple channels presented the highest average ticket value, suggesting a profile of greater complexity and value. These findings characterize the division as being in an intermediate stage of digital maturity, where e-commerce acts complementarily to the traditional channel, consolidating a hybrid commercial model.

The main contribution of this study lies in offering evidence on the strategic role of e-commerce in transforming industrial commercialization models for the microbiology sector, a segment of high complexity. Although the research focused on a case study, which limits generalization, the results point to the consolidation of a commercial model that enhances transactional efficiency and deepens customer relationship. One identified limitation was the high customer turnover, which reflects the structural dynamics of the microbiology market, influenced by validation and funding cycles. For future studies, it is recommended to broaden the analysis to other B2B contexts and explore more deeply the impacts of digitalization on commercial performance, customer retention, and the evolution of purchasing behavior in business environments, especially in Life Science sales, in addition to investigating strategies to expand the omnichannel customer base, considering the possible plateau in monetization.

Bibliographic References

Abe, C. F. J.; Ramos, C. S. D. M. O impacto da adoção de canais de vendas digitais em vendas B2B. 2022. Disponível em: https://repositorio.insper.edu.br/handle/11224/6488. Acesso em: 10 fev. 2026.

Borges, G. Os desafios do marketing omnichannel: a “omnicanalidade” é simples na teoria e difícil na implementação. GV-Executivo, v. 21, n. 1, p. 34–39, 2022.

OCDE. E-commerce in the time of COVID-19. Paris: OECD Publishing, 2020. Acesso em 16 Fev. 2026

Veiga, C. P. de; Veiga, C. R. P. de; Michel, J. de S. S.; Di Iorio, L. F.; SU, Z. E-commerce in Brazil: an in-depth analysis of digital growth and strategic approaches for online retail. Journal of Theoretical and Applied Electronic Commerce Research, v. 19, n. 2, p. 1559–1579, 2024.

Verhoef, P. C. et al. Digital transformation: a multidisciplinary reflection and research agenda. Journal of Business Research, v. 122,

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