The Competitive Edge in Any Business is Custom Data. Here’s How to Harness it.

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Generative AI and other analytics makes this possible to extract intelligence automatically from an SMB’s own custom data of historical transactions and customer engagements.

Every business accumulates vast troves of data through daily operations – customer transactions, inventory logs, accounting records, supplier info, and more. This “custom data” offers immense analytical potential to guide strategic decisions and drive competitive advantage. 

However, realizing this potential has long been a challenge. While large enterprises employ teams of data scientists to mine such insights, small to midsize businesses (SMBs) lack the expertise and resources to tap the value hidden within their data.

The costs of building advanced analytics infrastructure and machine learning capabilities have put these out of reach for most SMBs. As a result, their exclusive data, representing a goldmine of business intelligence, remains largely untapped.

This is now changing as new generative AI solutions bring enterprise-level analytics capabilities to organizations of any size. These technologies finally make it possible for SMBs to extract powerful insights from their data to accelerate growth and performance.

See also: Putting More Intelligence into Business Intelligence

Democratizing Business Intelligence

Generative AI solutions democratize access to strategic business insights that were previously attainable only with specialized skills. These tools automate the complexity of data science and machine learning behind the scenes.

Users simply describe what they want to learn from their data. The AI handles parsing the raw data, identifying meaningful patterns and relationships, and distilling insights.

This augments human intuition with hard evidence drawn straight from an organization’s own unique data. Leaders gain an unprecedented vantage into customer behaviors, operational drivers, emerging trends, and indicators of risk or opportunity. The guesswork is eliminated.

A natural language interface allows users to explore data just through conversation. Simply ask questions like “Which customers are most likely to churn?” or “What drives repeat purchases?” Plain language queries are interpreted and translated to analyze the underlying data.

Automated data wrangling resolves duplication issues, missing values, and other imperfections common in real-world data. Advanced statistical algorithms rapidly uncover hidden correlations. Organizational data of any type can be ingested, cleaned, and structured for analysis within minutes.

These capabilities not only surface insights faster but also make the process accessible to business teams without technical expertise. Specialized data science skills or complex Excel formulas are no longer required. Generative AI solutions turn raw data into strategic intelligence for any employee to utilize.

A Competitive Edge for SMBs

This democratization of data analytics provides a key competitive advantage for SMBs. Their sharp focus on serving niche audiences generates highly differentiated transactional data. Previously, transforming this data into unique business insights required scarce and expensive data science resources.

Generative AI unlocks these exclusive insights for any SMB by automating the entire data-to-intelligence pipeline. No data infrastructure or specialized skills are required. SMBs can finally tap the value of their #1 asset – tailored, proprietary data from running their specific business.

The AI rapidly learns subtle patterns, customer behaviors, and market dynamics that are unique to an SMB’s niche. These rare and valuable insights are unattainable through general market research. But they can provide a tremendous competitive advantage if harnessed properly.

Generative AI makes this possible by extracting intelligence automatically from an SMB’s own historical transactions and customer engagements. The technology surfaces correlations, predicts outcomes, and quantifies the business impact of various factors specific to their market.

Leaders gain granular clarity into what drives customer satisfaction, lifetime value, and referrals. Key metrics are forecasted based on detected trends and relationships in the data. The AI reveals optimization opportunities and surfaces emerging risks before they become issues. All of this is powered by the business’s own proprietary data.

Turning Insights into Action

But analysis alone creates little value. The defining characteristic of generative AI is its ability to prescribe actions based on data insights to achieve business objectives.

Users simply define a goal – for example, improving customer retention. The system reviews all available customer, transaction, and interaction data. It identifies factors correlated with retention and surfaces that present the greatest optimization opportunities.

The AI then provides tactical recommendations tailored to the organization’s specifics to improve retention. This can include adjusting pricing and promotions, introducing loyalty programs, or modifying engagement channels.

By continuously learning from new data on the business impact of those initiatives, the system refines its recommendations over time. It becomes an intelligent optimization engine driven by the company’s own data.

This creates a positive feedback loop where data insights trigger concrete actions, generating new data and leading to smarter recommendations. Generative AI drives rapid business acceleration powered by this cycle.

Data-Driven Decisions at Scale

This combination of data-driven strategic insights and prescriptive recommendations fundamentally enables better decision-making across the organization. With generative AI systems, every employee can leverage the full power of the company’s data to drive outcomes.

Frontline staff are empowered with data-backed guidance to handle diverse customer situations. Marketers can tailor messaging and offerings precisely to customer segments based on granular behavioral data. Supply chain managers have visibility to mitigate emerging fulfillment risks learned from trends in order data.

Better decisions at scale are no longer only for data-rich giants. Generative AI solutions finally give SMBs the capabilities to become truly data-driven organizations. They democratize access to data intelligence for employees at all levels to utilize.

The New Strategic Imperative

The implications of this technological revolution are profound. Extracting valuable intelligence from data is no longer a “nice-to-have” capability reserved only for large enterprises. It is now a strategic imperative for any SMB looking to compete and thrive in the modern era.

Possessing niche datasets is table stakes – what matters is the ability to harness insights to direct strategy and operations. Generative AI provides the means to realize this advantage. SMBs that fail to take advantage risk extinction in hyper-competitive markets.

However, adopting this new analytics capability is insufficient alone. It must be accompanied by a cultural shift to become truly data-driven organizations. From the frontlines to the C-suite, gut feel must give way to decisions founded on data-based evidence and insight.

The businesses that successfully navigate this transition will gain an edge that rapidly converts to market share and profits. Combining unmatched proprietary data with AI-driven intelligence creates a defensible competitive advantage that rivals will struggle to replicate. The future belongs to SMBs who recognize data as their greatest asset and act to unlock its full potential.

Jon Reilly

About Jon Reilly

Jon Reilly is co-founder and CEO of Akkio, where he focuses on driving the company's product-led growth (PLG) mission of democratizing AI. Prior to Akkio, Reilly was VP of Product and Marketing at Markforged and led the Music Player product management team at Sonos. Reilly holds an MBA from Babson and a BSEE from Gonzaga University.

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