Find the business growth hiding in plain sight

Nearly every business has significant opportunities for growth lies hidden in plain sight. These opportunities are waiting to be found within the vast amounts of data your business already generates. 

This data resides in the various systems, devices, and files across a business, and they hold the key to unlocking untapped potential and accelerating earnings. By strategically capturing and leveraging this information, businesses can move beyond intuition and experience to make better informed decisions to bring about higher value results.

The rise of data-driven decisions

In businesses, there's a clear shift away from relying solely on individual experience, and toward strategies grounded in concrete evidence. While experience remains valuable, the complexity of modern markets demands a more objective and comprehensive understanding derived from data analysis. 

Organizations aiming for sustainable growth and a competitive edge increasingly recognize that data-driven insights provide a more reliable foundation for navigating market intricacies and achieving strategic goals.

The impact of this shift is evident in the strong relationship between adopting data-driven practices and improved financial performance. For example, companies that have quantified the benefits of big data analysis report an average 8% increase in revenue and a 10% reduction in costs. The majority (73.5%) of managers and executives in leading data-utilizing companies state that their decision-making is consistently guided by data. 

A composite analysis shows McKinsey found data-driven organizations are 23 times more likely to acquire new customers and 19 times more likely to achieve profitability. This is further supported by PwC, which highlights that companies embracing data outperform competitors by 6% in profitability and 5% in productivity.

The trend towards data-centric business practices is growing rapidly, with projections indicating that data-driven strategies will outperform intuition-based decisions in 65% of B2B sales organizations by 2026. Gartner's assessment shows that 90% of companies now consider information and analytics crucial for their overall business strategy. This growing momentum underscores that data-driven decision-making is not just a competitive advantage but a fundamental necessity for organizations seeking significant revenue growth and a sustainable market position.

Real-world growth through data

The power of data-driven growth becomes clearer when examining real-world successes across various industries:

• Hospitality: MGM Resorts International centralized data from all locations and automated key processes, leading to a unified system with real-time performance data and a $2.4 million increase in annual revenue.
• Finance: American Express analyzed customer behavior and spending habits to predict churn risk, enabling proactive engagement with personalized offers and a notable decrease in customer attrition.
• Software: Corel Software analyzed website data and the customer buying cycle to segment prospective customers and create targeted retargeting campaigns, resulting in a remarkable 106% increase in revenue.
• Travel: Red Roof Inn combined publicly available data on flight cancellations and weather conditions to target stranded airline passengers with mobile advertising, leading to a 10% increase in turnover.

These examples demonstrate the diverse and substantial benefits of applying data analytics strategically, whether it's optimizing operations, enhancing customer loyalty, refining marketing, or capitalizing on market conditions.

Identifying the hidden data assets

The first step to unlocking growth is understanding the data your business already possesses. Valuable information is generated across all departments.

Sales

Analyzing sales data can reveal key metrics like total revenue or profit margins for different customer segments, lifetime customer value, and finding more optimal ways to lower customer acquisition cost.

Where can you find this data?

• Point-of-sale systems, CRM software, e-commerce platforms, customer feedback, sales and customer service interactions, website and app visitor data, lead generation campaigns, customer surveys, email interactions, social media platforms, customer stories, and sales enablement software. 

Marketing

Assessing marketing data allows marketers to know their campaign effectiveness, where the most effective marketing dollars are going, and how to optimize by driving more personalized customer experiences.

Where can you find this marketing data?

• Website analytics, campaign data, social media engagement, comprehensive customer data (demographics, psychographics, behavior), competitor and market data, internal databases, customer feedback, market research, advertising platforms, email marketing software, lead scoring and generation activities, and third-party data. 

Finance

Analyzing financial data is crucial for accurately budgeting, forecasting, and risk management. It’s also the foundation for RevOps (revenue operations) which uses data to view operations in terms of their financial value in order to optimize the business’s key results.

Where can you find this finance data?

• Subscription or transaction management software, accounting software, CRM, marketing platforms (advertising costs), payroll software, expense management software, app stores, banking data, company reports and regulatory filings, financial databases, analyst reports, and even economic data sources. 

Operations

In operations, capturing and analyzing system activity helps to understand how users are using their systems, track performance, identify bottlenecks, and optimize processes and workflows to ensure maximum productivity and minimum error.

Where can you find this operational data?

• ERP/CRM systems, transactional data, machine-generated data (sensors, IoT), email marketing metrics, customer profiles, customer interaction records, online activity (shopping carts), spreadsheets, cloud databases, file systems/remote servers, web services, internal CSV files, and organizational data. 

Human Resources

HR data needs to be assessed to understand the overall state of how people are performing in an organization. This is paramount for maximizing workforce retention and employee engagement and acquisition. It’s also necessary for optimizing factors like strategic planning, well-being, and deliverables.

Where can you find this HR data?

• HRIS data, recruiting data, demographic data, compensation and benefits data, turnover data, engagement management systems, succession planning data, exit interviews, employee surveys, absence data, performance reviews, and real-time analytics platforms. 

Customer Service

Customers give more money to businesses that provide them value, and the best way to ensure that value is with customer success processes derived from data. Analyses understanding sentiment and feedback, or for mapping their touchpoints and interactions with your company provide businesses with a wealth of knowledge to ensure optimal customer outcomes.

Where can you find this customer data?

• Demographics, purchase history, customer behavior (website analytics), transactional data (POS), newsletters/blogs (feedback), CRM platforms, customer interaction data (transcripts), behavioral customer data from conversations, social media interactions, surveys and questionnaires, and customer complaint databases. 

By identifying all their data sources, businesses can begin to properly capture that information in a structured way so that it can be examined for insights.

Visualizing insights for realizing action

While collecting and analyzing data are vital, there is a lot of power simply in being able to visualize it effectively. Transforming raw or processed data into visual representations with more easily identifiable metrics makes it easier to understand trends and communicate insights across the organization. 

Visualizations like bar charts, pie charts, line graphs, funnel charts, heat maps, and scatter plots each serve different analytical objectives. They help compare data, illustrate composition, spot trends over time, highlight process bottlenecks, identify correlations, and examine relationships between variables. 

Applying these techniques to sales trends, customer behavior insights, and operational bottlenecks can lead to valuable discoveries and better decision-making.

AI-powered business intelligence is ready for you

Artificial intelligence provides powerful tools for extracting insights, especially from the increasing volume of unstructured data like text, files, conversations, images, and videos. AI techniques like Natural Language Processing, computer vision, and machine learning can analyze this data to identify patterns and provide previously inaccessible insights. 

Natural language processing enables sentiment analysis of customer reviews, entity recognition in documents, and text summarization. Computer vision allows for image and video analysis. Machine learning helps with pattern recognition for finances, fraud detection, and customer churn prediction. 

AI-powered tools can significantly enhance customer feedback analysis, email analysis, and social media analysis, leading to a deeper understanding of complex customer needs for improved efficiency, and better-informed strategies. Better yet, the cost of AI-based tools and compute-power have dropped significantly, lowering the barrier to entry while also raising the bar in ability.

Predicting the future with analytics

Beyond understanding past and present data, predictive analytics, powered by machine learning, allows businesses to anticipate future trends and proactively accelerate revenue growth. 

Machine learning excels at identifying complex patterns of signals in large datasets, leading to more accurate and insightful predictions for sales forecasting, customer churn prediction, and risk prediction. This enables better inventory management, optimized resource allocation, targeted retention strategies, and proactive risk mitigation, ultimately driving financial savings and improved business stability.

Useful insights needs well-structured systems

Successfully implementing data-driven strategies requires a robust and well-maintained data foundation. This involves best practices in structuring databases for simplicity and usability, optimizing digital workflows with strong data naming conventions and a focus on data quality and security, and establishing effective data governance strategies.

By embracing a data-driven mindset and implementing these strategies, businesses across all fields can unlock the hidden growth potential within their existing data, leading to significant revenue acceleration and enhanced overall business performance.