Commercial Strategic Diagnosis through CRM Data Analysis: a Comparative Study 2024-2025

Thaynara Andrade Silva; Lidiane Mendes Barbosa

DOI: 10.22167/2675-6528-202603510

Article derived from a Course Conclusion 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.

Summary

The growing use of data in commercial management has expanded companies’ ability to identify inefficiencies and align operational strategies. This study aimed to analyze the misalignment between commercial strategy and the operational capacity of a medium-sized company, using CRM data from the years 2024 and 2025. The research was conducted based on a quantitative analysis of registered commercial opportunities, considering indicators such as volume, conversion rate, reasons for losses, and distribution by type of service. An adaptation of the BCG matrix and the SWOT matrix was also applied for strategic analysis. The results showed that, despite the increase in the volume of opportunities, there was no proportional growth in contract conversion, characterizing inefficiencies in the commercial process. A high incidence of losses associated with operational limitations was observed, especially related to meeting deadlines and service capacity, representing 59% of losses in 2024 and 71% in 2025. The analysis by type of service revealed a concentration of commercial efforts on activities with a low conversion rate, reinforcing the strategic misalignment. It was concluded that the use of CRM data can significantly contribute to decision-making, promoting greater alignment between the commercial area and the company’s operational capacity.

Keywords: BCG; CRM; Management; Business; B2B Sales.

1. Introduction

The human factor has always been considered the central element of B2B sales, and interpersonal relationships are often understood as the main driver of business results. This perspective, which values long-term engagement over one-off transactions, was highlighted by Kotler (2011) when discussing relationship marketing. However, the current business landscape has been transformed by increasing digitalization and the availability of large volumes of data.

With technological advancement, commercial management has come to integrate structured decision support tools, such as Customer Relationship Management (CRM) systems. Unlike Enterprise Resource Planning (ERP) systems, which focus on integrating operational and financial information, CRM concentrates data directly related to the commercial process, including opportunity registration, sales funnel tracking, and customer interaction history. The adoption of these solutions allows for greater control and qualification of opportunities, reducing exclusive dependence on intuition and individual experience, as pointed out by Davenport and Harris (2007). The increasing use of data in commercial management has expanded companies’ ability to identify inefficiencies and align their operational strategies.

Despite the recognized importance of data for strategic decision-making, as evidenced by NewVantage Partners (2023) and World Economic Forum (2025), many medium-sized companies still base their business decisions predominantly on intuition. This transition towards data-driven management, although fundamental, requires a structural shift in business practices (Davenport and Harris, 2007). In this context, the use of tools such as CRM is often limited to operational support, without being fully leveraged for in-depth strategic analysis of commercial performance, which hinders the identification of bottlenecks and opportunities for improvement (Solano and Cruz, 2024).

Recent studies reinforce the importance of data analysis for aligning strategy and execution, reducing inefficiencies, and increasing value generation (Hallikainen et al., 2020). Analytical maturity is directly associated with improved quality of strategic decisions (Shanks et al., 2018), and the use of big data analytics positively impacts organizational performance when integrated into business processes (Mikalef et al., 2020). However, it is observed that in medium-sized companies, the expansion of commercial opportunities does not always translate into proportional efficiency in business conversion, indicating a misalignment between prospecting and operational capacity.

The persistence of losses associated with operational limitations, such as meeting deadlines and service capacity, characterizes inefficiencies in the commercial process and reinforces the need for a more in-depth analysis. Given this scenario, this study is justified by the need to diagnose these misalignments and propose data-based strategic guidelines. Thus, this study aims to analyze the CRM system of a medium-sized company in the years 2024 and 2025, seeking to identify patterns of losses, strategic misalignments, and opportunities for improvement. From this diagnosis, it is intended to propose strategic guidelines for commercial direction in the year 2026 with the structured use of data to overcome the exclusive dependence on the human factor in commercial strategy.

2. Material and Methods

The present study was characterized as a research of an analytical-descriptive and applied nature, adopting a quantitative and descriptive methodological approach. The investigation was based on documentary analysis, with the central objective of diagnosing possible strategic misalignments in the commercial area. To this end, a structured analysis of historical records of commercial opportunities of a medium-sized company was carried out.

The unit of analysis consisted of commercial opportunity records, and the empirical object was the company’s Customer Relationship Management (CRM) system. The institution studied is a medium-sized organization operating in the telecommunications service sector, focusing on infrastructure solutions, installation, and specialized technical services. The company was chosen due to direct access to operational and commercial data, as well as the sector’s relevance.

The researcher worked in the organization from 2021 to 2026 as a commercial analyst, being responsible for registering and monitoring opportunities in the CRM system. This involvement enabled access to the data used in the research. The study was conducted with the company’s knowledge and authorization, formalized through an agreement document, ensuring compliance with ethical principles in the use of organizational information and the confidentiality of the analyzed data.

The database used was exclusively the company’s Customer Relationship Management (CRM) system, covering the complete record of open commercial opportunities in the years 2024 and 2025. All opportunities registered in the period were extracted, regardless of their final status, ensuring comprehensiveness and consistency for the analysis. The exclusive use of the CRM ensured that the analyses were based on formal records of the commercial operation.

The data were consolidated through pivot tables, allowing comparative segmentations between the two years analyzed. The variables considered in the study included: opportunity opening year, final status (won, lost, declined, suspended), reason for loss, service type, estimated opportunity value, sales representative, and opening and closing dates.

For the descriptive analysis of the sales funnel, the total volume of opportunities was consolidated by year, as well as the distribution by status (won, lost, declined, and suspended). From this data, metrics such as the overall conversion rate, the loss rate, and the percentage variation between the years 2024 and 2025 were calculated.

An internal data triangulation strategy was adopted, through the cross-referencing of multiple analytical variables. This included the type of service, reasons for loss, volume of opportunities, conversion rate, and the temporal evolution of the data. This approach allowed for the analysis of the phenomenon from different perspectives, enhancing the interpretive robustness of the results and reducing limitations associated with the use of a single database.

The triangulation was carried out from the integration between descriptive, comparative, and relational analyses, aiming to identify consistent patterns and validate the findings under different dimensions of the commercial process. Opportunities classified as lost were segmented according to the reason recorded in the CRM, being grouped into categories such as Lack of labor, Scope error or technical qualification, Price, Suspension by the client, and Others.

For the analysis of the causes of loss, the absolute volume per reason, the percentage of total losses, the distribution by type of service, and the associated potential revenue were considered. This stage aimed to distinguish internal factors, related to the company’s structure and capacity, from external factors, related to the market or the customer.

The opportunities were segmented by service type for comparative analysis, allowing for the evaluation of opportunity volume per service, specific conversion rate, loss concentration by category, and total estimated value per service. This analysis sought to identify recurring patterns of misalignment between commercial effort and operational capacity.

As management tools, an adaptation of the BCG Matrix was applied based on CRM data. The criteria used for classifying services were: the horizontal axis, representing the relative volume of opportunities by service type in relation to the overall average, and the vertical axis, indicating the conversion rate by service type compared to the global average rate.

The classification of services in the quadrants (Star, Cash Cow, Question Mark, and Dog) allowed for the identification of the distribution of commercial effort and the evaluation of its coherence with the obtained results. Additionally, the SWOT matrix (Strengths, Weaknesses, Opportunities and Threats) was applied as a complementary strategic analysis tool.

The use of SWOT aimed to consolidate the main findings of the study, integrating internal factors, identified from CRM data, and external factors related to the company’s competitive context. The matrix construction was based on the interpretation of the results obtained in the descriptive, comparative, and triangulated analyses, allowing for the structuring of a synthetic view of strengths, weaknesses, opportunities, and threats, and supporting the development of a strategic action plan.

3. Results and Discussion

The analysis of data extracted from the company’s Customer Relationship Management (CRM) system, referring to the years 2024 and 2025, allowed for an in-depth diagnosis of commercial performance and the identification of strategic misalignments. This section presents the results obtained, starting with an overview of commercial opportunities and their distribution by status. Next, the causes of losses and the analysis of suspended and declined opportunities are detailed. Subsequently, the distribution and performance of services by category are discussed, culminating in the identification of misalignments between commercial strategy and operational capacity, and in the application of strategic tools such as the BCG and SWOT matrices to consolidate the interpretations.

Overview of business opportunities

The evaluation of the overall landscape of commercial opportunities registered in the CRM revealed an expansion in prospecting volume between the analyzed years. In 2024, 223 opportunities were registered, of which 44 were won, 167 lost, and 12 suspended. In the following year, 2025, the total volume of opportunities increased to 296, with 80 won, 151 lost, and 65 suspended. This growth represents an increase of 73 opportunities, or approximately 32.7%, in the total sales funnel volume. Although the number of won opportunities grew from 44 to 80, and the absolute volume of losses decreased from 167 to 151, the evolution of results was not entirely proportional to the increase in prospecting.

The company’s overall conversion rate, which was approximately 19.7% in 2024, improved to about 27.0% in 2025. However, the number of lost opportunities remained high in both years, indicating a possible inefficiency in the alignment between prospecting and operational service capacity. A relevant aspect was the significant increase in opportunities classified as suspended, which went from 12 in 2024 to 65 in 2025. Although these occurrences do not constitute definitive losses, their growth signals interrupted commercial processes or postponed decisions, either by the client or by the company itself, which demands managerial attention to transform data into effective decisions (Petrescu; Krishen, 2024). This finding reinforces the importance of analyzing the causes of losses and the strategic adherence of what is being prospected.

Classification of Opportunities

To deepen the analysis of opportunities and their outcomes, the classifications recorded in the CRM were interpreted according to the established definitions. The “Canceled” status refers to situations where the client opted to discontinue the quote or quotation request, often motivated by factors such as budgetary unavailability or a change in internal priority. The “Declined” status corresponds to opportunities rejected by the company itself after a preliminary scope assessment, generally due to technical incapacity or lack of specialized knowledge. The “Deadline” classification is assigned to opportunities lost due to the company’s inability to present a proposal or execute the service within the client’s required timeline. Finally, “Awarded” indicates the success of the negotiation, resulting in the effective contracting of the service. These categorizations allowed for a precise analysis of the factors that influenced the results and the misalignments between the demands captured and the operational capacity.

Analysis of the causes of lost opportunities

The investigation of loss causes revealed that the “Deadline” factor has consolidated as the main reason for failure in commercial negotiations, with a growing and proportional incidence between the analyzed years. In 2024, out of 167 lost opportunities, 99 were attributed to deadline-related limitations, representing approximately 59% of the total. The remaining 68 losses, about 41%, were associated with the price factor. In 2025, the pattern intensified: out of 151 lost opportunities, 108, or approximately 71%, were due to deadline issues, while 43, about 29%, were due to price. This deadline predominance suggests that the company’s main challenge is not just the financial competitiveness of proposals, but rather the ability to meet demands within the schedules required by clients.

The recurrence and increase in losses due to deadlines indicate structural limitations in labor availability or in the capacity to mobilize resources necessary for the execution of activities. This scenario points to a difficulty in aligning the company’s operational capacity with customer time expectations. Additionally, it may reflect failures in the qualification process of opportunities registered in the CRM, suggesting that the demands captured by the commercial area are not always aligned with the operational capacity available at the time of the request. Cross-analysis of the data shows that deadline-related losses are not homogeneously distributed among services, concentrating mainly in categories with a higher volume of opportunities, such as Infrastructure and Street Level Solutions (SLS), evidencing a structural problem in specific operational fronts.

Analysis of suspended and declined opportunities

Beyond the lost opportunities, the CRM recorded suspended or declined negotiations, providing additional indications about the alignment between commercial demands and the company’s focus. In 2024, 12 suspended opportunities were identified, with eight canceled by the client and four declined by the company after preliminary scope assessment. In 2025, there was a significant increase in this type of record, totaling 65 suspended opportunities, of which 27 were classified as canceled by the client and 38 were declined by the company. This sharp growth suggests increasing complexity in the commercial process and expectation management, indicating that a relevant portion of opportunities does not advance to the proposal or effective contracting phases.

The increase in opportunities declined by the company itself, from four to 38, suggests that part of the demands captured by the commercial process is not aligned with the organization’s technical competencies or operational availability. This behavior points to possible failures in the initial opportunity qualification process, resulting in the registration of requests that are subsequently identified as unfeasible for execution. Similarly, the growth in opportunities canceled by clients, from eight to 27, may reflect changes in priority or budgetary limitations of the contractors. However, it may also be associated with delays in the company’s response process or the inability to present proposals within the expected timeframe, reinforcing the strategic misalignment with operations.

Distribution of opportunities by type of service (2024-2025)

The distribution of commercial opportunities by type of service, analyzed for the years 2024 and 2025, allowed for an understanding of the direction of commercial efforts and changes in the demand profile. In 2024, a strong concentration of opportunities was observed in the Infrastructure and Civil Works service, which totaled 87 records, representing the largest volume among all categories. Subsequently, Street Level Solutions (SLS) services stood out, with 64 opportunities, and Installation: Activation/Configuration/Migration/Adaptation, with 24 records. Other services, such as DAS (Distributed Antenna System) and DROP and Network Construction, showed intermediate volumes, while activities like Access 5G and Microwave had a reduced participation in the total opportunities.

In the year 2025, a redistribution of the volume of opportunities among services was observed. Although Infrastructure and Civil Works remained as one of the main categories, its volume was reduced to 70 opportunities, indicating a possible adjustment in commercial focus or market demand. In contrast, the service of Logical Services for Activation, Configuration, Migration, and Adaptation showed expressive growth, going from eight opportunities in 2024 to 65 in 2025, becoming one of the main categories in volume. The Street Level Solutions (SLS) service registered a reduction from 64 to 42 opportunities, and Installation had a slight drop from 24 to 22 opportunities.

Additionally, 2025 marked the emergence or increased relevance of new services, such as Digital Services, Off Grid, and Rural Schools, which, despite relatively low participation in the total volume, indicate a diversification of the commercial portfolio. This comparison between periods highlights a shift in the direction of opportunities, with less concentration on services traditionally more infrastructure-intensive and greater participation of services with a specialized technical and operational component, such as logical services. This movement aligns with the concept of strategic positioning proposed by Porter (1985), which emphasizes the choice of activities that reflect the organization’s internal capabilities. However, the isolated analysis of the volume of opportunities does not allow for an evaluation of the effectiveness of this change, requiring an assessment of performance in terms of converting opportunities into effective contracts.

Comparative analysis of service performance (2024-2025)

The comparative analysis of service performance between 2024 and 2025 revealed crucial patterns of efficiency and misalignment, reinforcing that effectiveness in B2B sales depends on the qualification of opportunities and the ability to deliver solutions (Rackham, 1988). Services with high demand volume and low conversion consistently showed a higher incidence of losses due to deadlines, evidencing a misalignment between commercial strategy and operational capacity. In 2024, the Infrastructure and Civil Works service, with 87 opportunities, awarded only seven contracts and registered a significant volume of losses due to deadlines (41 occurrences) and price (37 occurrences), indicating low conversion efficiency despite high commercial demand.

In 2025, the Infrastructure and Civil Works service, with 70 opportunities, presented 17 awards, with a reduction in losses due to price to four, but losses due to deadlines remained high, with 30 occurrences. This behavior suggests an improvement in commercial competitiveness, but a maintenance of operational limitations. In contrast, the Activation, Configuration, Migration, and Adaptation Logical Services presented an expressive evolution, going from one award in eight opportunities in 2024 to 21 awards in 65 opportunities in 2025. This significant improvement in conversion capacity and greater adherence between commercial demand and operational execution are consistent with the literature that points to the alignment between demand and capacity as a critical success factor (Rainy; Rahman; Mou, 2024).

On the other hand, the Street Level Solutions (SLS) service showed an inverse behavior. In 2024, it registered 20 awards in 64 opportunities, being one of the main responsible for the positive commercial result. However, in 2025, there was a reduction to seven awards in 42 opportunities, accompanied by a relevant increase in losses due to deadlines (21 occurrences) and maintenance of losses due to price (11 occurrences), indicating a deterioration in the performance of this segment. Other services, such as Installation and DROP and Network Construction, maintained a relatively stable performance, with moderate improvement in conversion and reduction of losses due to external factors. In general, the company’s commercial performance evolved heterogeneously among the different types of services, with some segments showing efficiency gains while others demonstrate signs of deterioration or persistent operational limitations, a characteristic behavior of data-oriented organizations (Davenport and Harris, 2007).

Identification of misalignments between commercial strategy and operational capacity

The integrated analysis of data over time, combining distribution by service type and loss causes, allowed for the consolidation of the identification of structural misalignments. The persistence of loss patterns over time, especially in services with a high volume of opportunities, indicates that the misalignment between commercial strategy and operational capacity is not an isolated event, but a recurring characteristic of the company’s operating model. For example, the Infrastructure and Civil Works service, which maintained the highest volume of demands in the two years analyzed, continued to show high levels of loss over time, with 41 occurrences in 2024 and 30 in 2025, evidencing a structural limitation in service capacity.

A similar situation was observed in the DAS (Distributed Antenna System) service, which showed an increase in overdue losses, rising from eight in 2024 to 16 in 2025, even with the growth in the volume of opportunities. This behavior suggests an expansion of demand that was not matched by a corresponding increase in operational capacity. The case of Street Level Solutions (SLS) also highlighted a relevant misalignment, with a significant reduction in awards in 2025 and an increase in overdue losses, signaling a possible deterioration in execution capacity in the face of captured demand. In contrast, the Logical Services service demonstrated a positive alignment scenario between commercial strategy and operation, with significant growth in awards and a proportional reduction in operational losses, indicating greater maturity and execution capacity.

A triangulated analysis, which consolidated the volume of opportunities, the conversion rate, and the incidence of deadline losses by service type, reinforced these findings. Services such as Infrastructure and Civil Works, with 157 opportunities, 15% conversion, and 71 deadline losses, and SLS, with 106 opportunities, 25% conversion, and 34 deadline losses, were diagnosed with high volume and low conversion or performance drop, indicating structural misalignment and operational risk. On the other hand, Logical Services, with 73 opportunities, 30% conversion, and 10 deadline losses, demonstrated high alignment. This data indicates that the commercial strategy is not fully aligned with the available operational capacity, resulting in the capture of opportunities that cannot be met within the conditions required by clients, a critical factor for organizational performance (Kaplan and Norton, 1997). The identified misalignment suggests that information collection, although structured, does not yet translate into effective strategic decisions (Solano and Cruz, 2024).

Application of the BCG matrix to the service portfolio (2024-2025)

The application of an adapted BCG matrix, using the volume of opportunities as the horizontal axis and conversion capacity as the vertical axis, allowed for a strategic interpretation of the company’s service portfolio, according to the methodology originally proposed by the Boston Consulting Group (1970). This tool classified the services into different quadrants based on data from 2024 and 2025. In the “Stars” category, characterized by high volume of opportunities and high conversion, the Logical Services were identified in 2025, showing a strong alignment between demand and operational capacity, evidencing a robust and promising performance for the company.

In the “Question Marks” category, which groups services with high demand volume but low conversion capacity, Infrastructure and Civil Works and Street Level Solutions (SLS) were classified in 2025. These services, despite presenting high commercial demand, are marked by significant operational limitations, mainly evidenced by high losses associated with deadlines. They represent strategic opportunities that, to have their full potential exploited, require substantial investments in operational capacity to improve performance and conversion efficiency. The identification of these points is crucial for the reorientation of investments and development strategies.

As “Cash Cows”, characterized by low volume of opportunities and high conversion, were identified the Installation and DROP services and Network Construction, the latter with moderate performance. These services, despite a smaller prospecting volume, demonstrate good conversion capacity, potentially representing stable sources of revenue and cash flow for the company. Finally, in the “Pineapples” category, which encompasses services with low volume of opportunities and low conversion, Access 5G, Digital Services, and Microwave were classified. These services show low relevance in both volume of opportunities and conversion rate, suggesting low adherence to the company’s strategic focus or a need to re-evaluate their viability and market potential.

The analysis of the adapted BCG matrix shows that a significant part of the company’s commercial effort is concentrated in activities classified as “Question Marks”, that is, services with high demand volume but low conversion capacity. This scenario reinforces the urgent need to review the strategic direction of the commercial area. Such a review can be implemented by strengthening operational capacity in segments with higher demand or by reorienting commercial efforts towards services that demonstrate greater adherence to the existing structure. According to Mintzberg (2000), strategy must be continuously adjusted based on observed results in organizational practice, ensuring that resources are allocated more efficiently and aligned with the company’s objectives.

Application of the SWOT matrix with a strategic action plan

To complement the strategic analysis of the service portfolio and consolidate the main findings of the study, the SWOT matrix (Strengths, Weaknesses, Opportunities and Threats) was applied, a tool widely used for integrated evaluation of the organization’s internal and external environments. Among the identified strengths, the structured use of CRM, the growth in the volume of opportunities, the improvement in the overall conversion rate, and the good performance of Logical Services, especially in 2025, stand out. These strengths indicate a solid foundation for data management and a potential for commercial growth, which can be leveraged to optimize the company’s overall performance.

The identified weaknesses include low operational capacity in high-volume services, high losses due to deadlines, misalignment between commercial and operational areas, and concentration of efforts on inefficient services. These weaknesses directly impact the company’s ability to convert opportunities into contracts and maintain customer satisfaction, representing bottlenecks that need to be addressed. The opportunities point to the reorientation of the commercial portfolio, the expansion of high-conversion services, the strategic use of data for decision-making, and the optimization of operational capacity, suggesting paths for future development and improved competitiveness.

The threats, in turn, include loss of competitiveness, customer dissatisfaction, more efficient competition, and loss of opportunities due to internal failures. These external and internal factors can compromise the sustainability of the company’s growth and market position if the identified misalignments are not proactively addressed. Based on this analysis, a detailed strategic action plan was proposed. For high losses due to deadlines, the recommended action is to review operational capacity and team sizing, aiming to reduce operational losses and increase the conversion rate, promoting greater efficiency in project execution.

To address the misalignment between the commercial and operational areas, the proposal is to implement rigorous opportunity qualification criteria, especially in technical pre-sales. The objective is to improve proposal adherence and reduce the capture of unviable opportunities, optimizing the sales funnel from the initial stages. The concentration of efforts on inefficient services will be combatted by redirecting to services with higher conversion rates, such as Logical Services, aiming to optimize the portfolio and increase the company’s overall commercial efficiency. These actions seek to align the commercial area’s resources with the operation’s delivery capabilities.

The low utilization of data will be addressed by creating a routine for periodic analysis of CRM indicators, supporting decision-making and promoting greater strategic assertiveness in all areas of operation. Finally, to address the disordered growth of demand due to the high volume of unqualified opportunities, an integrated planning between the commercial and operational areas is proposed. The objective is to balance demand and execution capacity, ensuring the sustainability of the company’s long-term growth. The SWOT matrix, therefore, not only consolidates the critical factors identified but also serves as a fundamental basis for formulating concrete and targeted strategic recommendations, essential for the continuous improvement of organizational performance.

In summary, the research results evidenced a persistent misalignment between the company’s commercial strategy and operational capacity, manifested by the increase in the volume of opportunities that did not translate into proportional growth in contract conversion. Losses due to time, which represented 59% in 2024 and 71% in 2025, were identified as the main bottleneck, indicating structural limitations in the execution and qualification of demands. The analysis by service type and the application of the BCG matrix revealed a concentration of commercial efforts in segments with low conversion efficiency, while the SWOT matrix consolidated strengths, weaknesses, opportunities, and threats, providing a robust basis for proposing strategic guidelines aimed at improving operational alignment and efficiency.

4. Conclusion

The study sought to analyze the CRM system of a medium-sized company in the years 2024 and 2025, with the objective of identifying patterns of losses, strategic misalignments, and improvement opportunities. It was verified that, despite the increase in the volume of commercial opportunities, this growth did not translate into a proportional increase in contract conversion. It was observed that losses due to deadlines constituted the main bottleneck, representing 59% of losses in 2024 and 71% in 2025, which indicated structural limitations in operational capacity and demand qualification. The analysis by service type, complemented by the application of the adapted BCG matrix, revealed a concentration of commercial efforts in segments with low conversion efficiency, such as Infrastructure and Civil Works and Street Level Solutions (SLS), classified as “Question Marks”. In contrast, the Logical Services offering showed a positive alignment between demand and execution, positioning itself as a “Star”. The SWOT matrix consolidated these findings, highlighting low operational capacity and misalignment between the commercial and operational areas as central weaknesses, while the structured use of CRM and the potential for portfolio reorientation were identified as strengths and opportunities.

The main contribution of this study lies in demonstrating that data-driven management, through the systematic analysis of CRM information, is a determining factor in improving commercial efficiency and strategic alignment in medium-sized companies. The detailed diagnosis allowed for the proposal of strategic guidelines for commercial direction in 2026, focusing on reviewing operational capacity, qualifying opportunities, and optimizing the service portfolio. However, the study has limitations, such as exclusive reliance on the company’s CRM records, not incorporating other sources of evidence, such as interviews or external financial data, which prevents a more comprehensive analysis of the competitive context. It is suggested for future studies to expand the methodological approach by including qualitative data and market information, in addition to continuing the application of strategic management tools to deepen practical recommendations and strengthen organizational decision-making.

Bibliographic References

BOSTON CONSULTING GROUP. The product portfolio. Boston: BCG, 1970.

Davenport, Thomas H.; Jeanne G. Harris. Competing on analytics. Boston: Harvard Business School Press, 2007.

Hallikainen, H. et al. Data-driven decision-making in organizations. 2020.

Kaplan, Robert S.; Norton, David P. A estratégia em ação: balanced scorecard. Rio de Janeiro: Campus, 1997.

Kotler, Philip; Keller, Kevin Lane. Administração de marketing. 14. ed. São Paulo: Pearson, 2012.

Mikalef, P. et al. Big data analytics capabilities and firm performance. 2020.

Mintzberg, Henry. Safári de estratégia. Porto Alegre: Bookman, 2000.

NEVANTAGE PARTNERS (WAVESTONE). New Vantage Partners Releases 2023: Data and Analytics Leadership Executive Survey. 2023. Disponível em: https://www.prnewswire.com/news-releases/newvantage-partners-a-wavestone-company-releases-2023-data-and-analytics-leadership-executive-survey-301711081.html. Acesso em: 11 fev. 2026.

Petrescu, Maria; Krishen, Anjala S. Marketing analytics in 2024 conferences: Al and data-driven decision-making. Journal of Marketing Analytics, v. 12, 2024.

Porter, Michael E. Estratégia competitiva: técnicas para análise de indústrias e da concorrência. Rio de Janeiro: Elsevier, 1985.

Rackham, Neil. SPIN Selling. New York: McGraw-Hill, 1988.

Rainy, Tahmina Akter; Rahman, Md Arifur; Mou, Anika Jahan. Customer relationship management and data-driven decision-making in modern enterprises: a systematic literature review. American Journal of Advanced Technology and Engineering Solutions, v. 4, n. 4, p. 57–82, 2024.

Shanks, Graeme; Belo, Orlando; Barlow, Jordan; Crawford, Lindsay; Inderpal, Singh. Achieving benefits from big data analytics. 2018.

Solano, Maria C.; Cruz, Juan C. Integrating analytics in enterprise systems: a systematic literature review of impacts and innovations. Administrative Sciences, v. 14, n. 7, 2024.

World Economic Forum (2025). Future of Jobs Report 2025. Geneva: WEF, 2025. Available at: www.weforum.org. Accessed on: 12 Feb. 2026.

Article originating from the Final Course Work of the Specialization in Business Management of the MBA USP/Esalq

To learn more about the course, click here and access the MBX Academy platform