Transforming Retail with Alternative Data

I've always been captivated by the potential of Alternative Data. Back when Power BI was just getting off the ground, I spent years diving into diverse datasets exploring use cases that could give retailers a competitive edge.

Alternative data (What Is Alternative Data? (investopedia.com)), which encompasses non-traditional data sources such as social media activity, geolocation data, and even weather patterns, has revolutionized the retail industry. By leveraging these diverse datasets, retailers can gain deeper insights into consumer behavior, preferences, and trends. This enables them to make more informed decisions, optimize their operations, and ultimately become more competitive in the market. Whether it's identifying the best locations for new stores, tailoring marketing strategies to target specific demographics, or predicting inventory needs, alternative data provides a wealth of information that can drive strategic growth and innovation.

Digging into some of my experiments from over a decade ago

Here is an example of something I pulled together about 11 years ago that sought to analyze information about Emirates , Etihad and SAUDI AIRLINES using information from:

1. Twitter Feed for one week using Twitter Analytics for Excel (amazing work by Patrick Husting ~2013)
2. Google Trends Data
3. Bing Search Data

It was also interesting to connect to the 911 call data for Seattle to get insights on areas with specific types of incidents or areas with the high crime. I correlated this with data from Instagram showing the areas that high concentrations of tourist traffic vs local (using Instagram profiles). This used data from the US Census Bureau, Instagram API, Foursquare API and Real Time 911 Data for Seattle:

Alternative Data and Inference Models

Combining alternative data with inference models creates a powerful synergy that unlocks fascinating insights from non-traditional sources. By integrating data from social media, satellite imagery, and transaction records, businesses can gain a more comprehensive view of market dynamics. For example, social media trends can reveal emerging consumer preferences, while satellite imagery can provide real-time insights into agricultural yields or retail foot traffic. Inference models can then analyze these diverse data sets to predict future trends and behaviors, offering a deeper understanding of market conditions. This combination allows businesses to make more informed decisions, optimize supply chains, and tailor marketing strategies, ultimately providing a significant competitive advantage.

• Uber's vast data repository offers a treasure trove of opportunities for innovative use cases that extend beyond traditional transportation analytics. For instance, a retailer could use anonymized data from a ride-sharing service to understand customer behavior. This data can help identify peak traffic times and adjust staffing to meet demand, improving customer service. They can also use this information to target marketing campaigns more effectively, increasing foot traffic. The use of ride-sharing data provides critical insights that can enhance their business strategy. The NYC Taxi and Limousine Data is a great example.
• Fitbit engineers made an intriguing discovery when they realized that data from Fitbit devices could be used to predict earthquakes. During a 4.4 magnitude quake in Berkeley, California, the engineers noticed a significant spike in the number of Fitbit users who were suddenly awakened by the tremor. By analyzing sleep pattern disruptions and the timing of these awakenings, they were able to infer the quake's impact and even map the epicenter based on the proportion of users affected in various locations. This unexpected use of wearable technology data highlights the potential for innovative applications beyond fitness tracking, offering valuable insights for earthquake detection and early warning system.

Leveraging Digital Exhaust for Business Insights

Digital Exhaust, the trail of data left behind from digital interactions—whether from social media activities, blog posts, IoT devices, or mobile phone usage—offers a goldmine of insights for businesses. By harnessing this data, companies can uncover patterns and trends that were previously hidden, making it possible to infer customer behaviors, preferences, and market dynamics. For example, analyzing social media chatter can reveal emerging consumer trends, while data from IoT sensors can optimize supply chain efficiencies. When businesses tap into the potential of digital exhaust, they gain a deeper understanding of their environment, enabling smarter, data-driven decisions that drive innovation and competitiveness.

The Power of Combining Search and Spend Data

By leveraging Search data, which reveals consumer intent, and Spend Data from credit cards & POS, retailers and brands can gain a comprehensive understanding of consumer behavior at an incredibly granular level. Search data provides a window into what consumers are actively looking for, their interests, and emerging trends, while Spend Data offers tangible insights into their purchasing habits and financial behavior. When combined, these two data sources can uncover patterns across different segments, geographic locations, and specific areas. Retailers and brands can use this rich dataset to optimize their marketing strategies, tailor their product offerings, and enhance customer experiences. By identifying high-demand products and regional preferences, businesses can ensure they stock the right inventory in the right places. Additionally, understanding the correlation between online searches and actual purchases helps in crafting targeted advertising campaigns, leading to higher conversion rates and more effective customer engagement. This powerful synergy of data not only drives better business decisions but also fosters a deeper connection with consumers by meeting their needs more precisely.

Extracting Data from Radio Waves

In the age of digital transformation, extracting data from radio waves is revolutionizing industries. Technologies like AIS (Automatic Identification System) and ADSB (Automatic Dependent Surveillance-Broadcast) are pivotal in tracking maritime and aviation movements, respectively. Satellite data from entities such as NOAA and INMARSAT provide invaluable information for weather forecasting, climate monitoring, and global communication. By integrating these diverse datasets, businesses can gain real-time insights and predictive analytics that enhance operational efficiencies, safety measures, and strategic decision-making. This innovative approach to data collection is unlocking new potentials across sectors, turning the airwaves into a treasure trove of actionable intelligence.

Check out my experiments with harvesting data from the air: Harvesting Data From The Air (substack.com)

Unlocking Business Insights with Open Data

Open data is a goldmine for businesses aiming to extract actionable insights. By analyzing datasets like NYC taxi data, companies can identify peak restaurant traffic on Friday nights, optimizing staffing and inventory. Similarly, demographic datasets provide valuable information about foot traffic in specific areas, helping retailers strategically position stores and tailor marketing campaigns to local populations.

Microsoft's Azure Open Datasets further enhance this potential. These curated, open data sources are designed to streamline machine learning and AI applications. With Azure Open Datasets, businesses can easily access and leverage high-quality data for predictive analytics, driving smarter, data-informed decisions that fuel growth and innovation. By tapping into these resources, companies can unlock new opportunities and refine their strategies to better meet market demands.?

Unlocking the Power of Public Knowledge

The internet holds a wealth of data that can drive business innovation and accelerate AI utilization, yet it has long been seen as too chaotic and unreliable for AI and BI pipelines. Nimble, a Microsoft for Startups Pegasus partner, has revolutionized this perception. Nimble's advanced AI-driven technologies automate the collection of web data, ensuring high accuracy and compliance. By integrating intelligent proxies and optimizing workflows with AI, Nimble makes large-scale data collection effortless, removing the need for manual intervention. The true game-changer is Nimble's interface for AI agents to search and interact with the data, paving the way for unprecedented reliability and usability in AI and BI applications.

Microsoft Azure has partnered with Nimble to natively incorporate advanced data capabilities into Azure, unlocking significant value for its customers. With this partnership, Azure customers can now leverage real-time and unstructured data at granular levels to gain deeper insights, increase velocity, and improve operational efficiencies. Azure’s AI and machine learning services, enhanced by Nimble's technology, provide an ideal platform for processing and analyzing large datasets from the web. This collaboration enables transforming vast amounts of data into actionable knowledge.

Join us at Discovery Day Chicago (Oct 15-16)

Discovery Day Chicago is where cutting-edge Artificial Intelligence & Alternative Data providers showcase the latest datasets to Financial Services (Hedge Funds, PE, VC and Asset Managers) and Corporate Data Users (Brands, Retailers, eCommerce..). I will be speaking on Alternative Data and how Retail and CPG companies can harness the untapped potential of web data for business innovation and strategic decision-making. This data can be used to gain deeper insights into consumer behavior, industry trends, and competitive landscapes, ultimately improving operational efficiencies and driving growth

Details: Battlefin Chicago Registration (nimbleway.com)

Partner with Innovative Startups:

Besides partnering with Nimble, Microsoft for Startups also collaborates with various other innovative startups to automate data collection and ingestion from both structured and unstructured sources. Notable partners include Unstructured, Osmos, Dataloop, and others.

To remain competitive and meet the demands of their customers, retailers are actively innovating. Utilizing startup solutions can enhance and expedite this process. The Microsoft for Startups Pegasus ecosystem can help augment in-house innovation for brands and retailers. Please reach out to me if you'd like to meet with startups and/or explore our startup portfolio.