The Value of Data & Analytics Strategies: A Key to Success in B2B Sectors

Technological integration in B2B sectors has become essential for business survival.

The impact of data monitoring and analysis technologies is crucial for creating personalized, satisfying offerings, optimizing production processes, and eventually staying competitive in the global market.

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Digital transformation has completely reshaped the B2B landscape, bringing about unprecedented change. To stay ahead of the competition, B2B companies need to proactively embrace change and integrate cutting-edge technology tools to ensure long-term growth.

Adopting new data collection and analysis technologies enables companies to swiftly adapt to market changes. These tools are now essential for optimizing production processes and revolutionizing the focus on people and customer relationships.

Delivering customer-centric experiences is closely tied to effective data management.

By collecting, analyzing, and interpreting data, businesses can gain insights into customer preferences and behaviors, as well as evaluate the success of their Customer Experience initiatives. Data management is therefore crucial for maintaining consistent operational efficiency, particularly in anticipating demand spikes and responding to customer feedback.

In competitive B2B markets, customizing services and meeting buyer expectations are key factors in differentiating your offerings and increasing customer loyalty, which significantly impacts your company’s success and profitability.

As highlighted by a Bain & Company study, increasing customer retention by just 5% can boost profits by 25% to 95%.

In highly technical sectors like OT, Mechanical, Engineering, Life Science, Oil and Energy, etc., the application of data monitoring and analysis technologies further enhances production efficiency.

A good example is predictive maintenance, which forecasts equipment failures by analyzing production process data and replacement frequencies. This allows manufacturers to maximize uptime, optimize maintenance schedules, prevent costly downtime, and accurately assess the total cost of equipment ownership.

The introduction of Artificial Intelligence systems, such as AI Engineering, is driving innovation in these fields. Leveraging automated, data-driven approaches based on metadata and data sharing helps maximize the value of data and analytics.

Data sharing is becoming an increasingly important performance indicator, enabling companies to effectively engage stakeholders and generate value not only for their organization but for the digital business ecosystem as a whole.

However, data accuracy remains a challenge, with 84% of B2B companies failing to provide timely updates on pricing, product formula changes, and availability (Source: Deloitte Digital: Customer Experience enters the B2B battlefield. New research shows B2B buyers’ expectations of industrial product companies have changed).

This challenge often stems from the complexity of implementing technological tools and the significant investment required in technology, training, infrastructure, and human resources.

However, the benefits of data analysis can far outweigh the initial costs of implementation.

A data-driven approach is essential for managing ongoing changes.

Big data, in particular, is one of the most transformative, interconnected, and indispensable technologies. Through its analysis, processing, and interpretation, significant trends and patterns can be identified, enabling managers to make informed decisions and explore new growth opportunities for their B2B business.

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Conclusion

The ongoing evolution of digital technologies and the growing availability of data are opening up new opportunities for companies across all B2B sectors.

B2B companies must gather a vast amount of data throughout the customer journey. Trends indicate a growing importance of analytics strategies, not only in business performance but also in understanding customer behavior, particularly what they view, click on, and add to their shopping carts.

This data can later be used to personalize the buying journey based on product interests or user preferences.

The use of data-driven strategies has already shown clear results, as B2B companies that have embraced data have outpaced their competitors.

Top-performing companies that invest in data-driven strategies are 1.5 times more likely to achieve rapid growth, with profit increases of 15-25%. (Source: Jochen Böringer, Alexander Dierks, Isabel Huber, and Dennis Spillecke, “Insights to impact: Creating and sustaining data-driven commercial growth,” McKinsey, January 18, 2022).

For B2B companies, treating data as a true asset—investing in its maintenance, accuracy, and ongoing improvement—is crucial.

Yet, according to a McKinsey & Company study, only 8% of B2B organizations are currently equipped to deliver highly personalized marketing, aimed at capturing customer attention with tailored content, drawing increasingly from the “B2C playbook.”

This represents a significant growth opportunity for many highly technical sectors. Data management strategies promote a more personalized approach, helping companies deliver the right message to the right persona at the right time.

“Today’s buyers are more tech-savvy. They are more digitally engaged. They spend more time on their devices. And they want to engage on their terms, not yours.”

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SOURCES

• McKinsey & Company (2022), Growth, Marketing & Sales Practice | The Future of B2B Sales: The Big Reframe.
• F. d’Agri (A.A. 2022-2023), UniPd Thesis | “LA DIGITAL JOURNEY NELLE IMPRESE B2B E IL SUO IMPATTO SULLA CUSTOMER EXPERIENCE”
• Pivotal Trends and Predictions in B2B Digital Commerce in 2023, in commercetool.com
• Jochen Böringer, Alexander Dierks, Isabel Huber, and Dennis Spillecke (2022) “Insights to impact: Creating and sustaining data-driven commercial growth,” McKinsey, January 18,
• Reicheld, F., Prescription for Cutting Costs, from Bain & Company
• Redazione di ChannelCity (2022), Gartner, gli imperativi per una strategia di Data & Analytics di successo
• Di Marco, E. (2022) in NetworkDigital 360, Analisi dei dati, cos’è e perché è importante nei processi produttivi.
• L’importanza dei Big Data per l’ingegneria meccanica (2019), in Item24.com
• Auschitzky E., Hammer M., Rajagopaul A. (2014), How big data can improve manufacturing, from McKinsey & Company
• "Customer Experience enters the B2B battlefield. New research shows B2B buyers’ expectations of industrial product companies have changed", from Deloitte Digital