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What is Data Aggregation? Examples by Industry

Data aggregation is quickly becoming one of the most important tools available to boost business performance and competitiveness. The process of compiling and analyzing information from multiple sources can unlock game-changing insights and enable more informed strategy. Across industries, companies are realizing the immense potential of aggregated data.

Automated Data Collection

According to surveys, over 85% of companies now use some form of data aggregation. But effectively combining vast amounts of information from hundreds of sources would be impossible without automation.

Sophisticated tools like web scrapers, scripts, and APIs now allow for continuous real-time aggregation of data across the web and internal systems. For example, specially programmed bots can scrape pricing information from competitor websites every hour. Other scripts extract sales data from various business applications to a central data warehouse.

Proprietary algorithms clean and normalize this raw data from diverse formats into consistent datasets ready for analysis. The whole process of large-scale data aggregation is managed and automated in the cloud – enabling scalability and efficiency impossible with manual approaches.

Why Aggregated Data Provides Unique Value

Industry research suggests that businesses using data aggregation grow revenue over 25% faster than competitors. But why is aggregated data so invaluable?

Holistic View – Compiling data from multiple sources, departments, and third-parties provides a comprehensive perspective that cannot be obtained otherwise. This full view reduces blindspots.

Cross-linking – Combining different datasets reveals correlations, trends and insights that would remain hidden when analyzing data in silos. This cross-context analysis powers better decision making.

Timeliness – Automated aggregation means up-to-the-minute data is available for real-time monitoring and response. Outdated data leads to flawed choices.

Precision – Data anomalies, inconsistencies, and gaps are minimized when aggregating from hundreds of sources. Aggregation distills data down to its most accurate form.

Flexibility – Custom aggregation strategies can be developed to focus on specific business needs. The questions asked of data determine the value extracted from aggregation.

Applications in Finance and Investing

Financial data aggregation has become integral to capital markets and investment practices. By combining current pricing data, historical time-series data, alternative data like web traffic or satellite imagery, research, news, filings, and more, analysts gain an information advantage.

Hedge funds use aggregated data flows to quickly detect events and market movements that present trading opportunities, then execute strategies through automated trading systems. The speed and comprehensiveness of aggregated data allows maximum agility.

Wealth management firms combine economic indicators, sentiment signals, earnings reports, client portfolios, and other data sources to optimize investment plans. Aggregated data helps portfolio managers match assets and strategies to changing macro conditions and individual needs.

Travel Industry Uses

Data aggregation has transformed the travel sector, enabling companies to tailor offers, manage inventory and staffing, personalize suggestions, target marketing, and develop competitive pricing strategies.

OTA‘s like Expedia aggregate flight options across airlines and use past booking data to recommend packages and deals to users. Travel review sites like TripAdvisor aggregate ratings and comments from multiple providers to give travelers a single comprehensive information source when planning trips.

Hotels use revenue management systems that aggregate bookings data, local events, competitor rates, demand forecasts, and other inputs to optimize pricing. Adjusting rates based on aggregated data has boosted hotel revenue by over 5% across the industry.

Retail Applications

Progressive retailers rely on real-time aggregated data to drive decisions on pricing, promotions, inventory, hiring, product assortment, and more.

Ecommerce leaders like Amazon use aggregated web traffic, sales, and customer data to personalize recommendations and deliver customized shopping experiences. Retailers also aggregate panel data on purchase behavior to improve merchandising and marketing.

Brick-and-mortar retailers use POS data aggregated across locations to right-size staffing schedules. Foot traffic data aggregated from security cameras, wifi signals or other sensors help stores optimize operations.

Best Practices for Data Aggregation

While aggregation provides impactful insights, proper governance and security controls must be in place. Companies should inform customers how data is being collected and aggregated. Consent should be obtained where applicable.

Aggregated data stored in repositories should only be accessible to authorized employees, with protections against unauthorized use or leakage. Data should be aggregated using transparent and ethical methods.

Used responsibly, data aggregation is a valuable tool for boosting performance. Leveraging it fully while respecting customer privacy is in the best interests of both businesses and consumers. The opportunities it unlocks are too powerful to ignore.

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