Third-party data is no longer optional. Data that originates outside of the confines of your organization represents a rich source of insight for nearly any business process or decision. Whether it’s using external information to identify new customer preferences or assessing the impact of existing vendor partnerships, third-party data helps organizations make better business decisions and strengthen relationships with key stakeholders.
A recent report by MIT Sloan Management found that analytical innovators are five times more likely to use data from multiple external sources than laggards are.
It’s easy to see why. Organizations that do not leverage third-party data are at risk of:
- Failing to grasp how external events impact their customers, partner networks, and supply chains.
- Missing critical signals from their customers and other external stakeholders, leading to lost opportunities.
- Falling behind competitors who leverage a more robust set of data to inform their strategic and tactical decisions.
In short, without third-party data, organizations lack the “big picture view” that is critical for making smarter, faster strategic decisions. They miss opportunities to improve the accuracy of their existing analytics and develop new insights, correlations, and predictive capabilities.
In this blog, we’ll share all there is to know about third-party data and help you understand how much of a potential goldmine it can be for your organization.
Defining Third-Party Data
“Third-party data” refers to any data that organizations do not generate internally. There are a variety of sources for acquiring third-party data, including:
- Paid Sources
- Events Databases (i.e., concerts, sports, conventions)
- Customer Demographics
- Market Trends
- Public Sources
- Weather and Environment
- Online Customer Reviews
- Economic and Census Data
These examples just scratch the surface.
Third-party data is everywhere, and providers have the potential to help your organization generate tremendous value. Utilizing third-party data can save you time and effort by helping your organization fill in knowledge gaps and provide insight into customer preferences, all while reducing your costs along the way.
Despite its many benefits, third-party data also presents several challenges that must be addressed to make the most of your efforts. To start, because third-party data is growing in scope and volume, it can be difficult to know which data sets to integrate and which to ignore. Compounding this challenge is the simple fact that third-party data initiatives often require significant investments to develop, launch, and derive value – even when the data sources driving the initiatives are free. To ensure your organization extracts meaningful value from third-party data initiatives, you must allocate time upfront to tie the initiatives into your overall business strategy and goals. Importantly, you must attach your third-party data initiatives to a clearly defined business case with meaningful potential ROI.
Identifying Use Cases for Third-Party Data
Different organizations have different opportunities to derive value from third-party data. Consider one of our clients, a large hospitality group. This company knew that high-impact events—such as concerts, festivals, and conferences—had a significant impact on their occupancy rates and customer demand. However, they did not understand how they might leverage these events to optimize their rates, inventory, and guest experiences.
That’s where we stepped in. Together, we worked with our client to integrate external events data to optimize their rates, inventory, and guest experiences during high-impact events. We then developed more sophisticated third-party data initiatives to optimize revenue from smaller, more localized events. Additionally, we:
- Assessed multiple external data providers and selected a vendor.
- Built an automated data pipeline that incorporated this data into the client’s cloud environment.
- Created a flexible and dynamic tool to monitor upcoming events and correlate them to hotel demand.
- Enhanced multiple business use cases and developed a strategy to optimize rates during high impact events
By leveraging third-party data, this organization is projected to generate an additional $90 million annually in revenue.
In another example, we partnered with a leading mass retail organization to combine proprietary data and third-party data to improve demand forecasting before and after major weather events. The purpose was to enable the company to respond to emergency weather events more effectively and more cost-efficiently, thereby increasing top-line revenue growth. This process, called data monetization, involved operationalizing the latest machine learning techniques to build predictive models using 73 billion historical weather observations from National Oceanic and Atmospheric Administration (NOAA) with 10 years of the retailer’s sales and inventory history. By using the data available, the retailer enhanced its home improvement demand forecasting before and after major weather events, identified opportunities to add $30 million to its bottom-line during significant events, and boosted customer loyalty by continuing to deliver necessary goods and services during emergency events.
These are just two examples of how organizations can drive important business decisions through third-party data. Other potential use cases include:
- Dynamic Pricing Optimization
- Product Assortment and Localization
- Weather Driven Product or Experience Adjustments
- Customer Experience Measurement and Improvement
- Competitive Analytics (Pricing, Product Assortment, Offers)
- Development of New Product Roadmaps
Once an organization defines the business cases that apply to their third-party data initiative, it must develop a practical strategy to operationalize it.
Following Four Steps to Maximize Third-Party Data Outcomes
We guide our clients through four simple steps to develop, launch, and derive value from their third-party data projects.
Step One: Select Appropriate Data Sources: To drive business outcomes, organizations must define use cases and determine how data can be used to improve decision making. This step includes identifying potentially valuable data sources, performing a gap analysis of existing data sources, determining what information is missing, and assigning these missing data sources an ROI value. It’s important to procure worthwhile data sources with appropriate costs, terms, and limitations.
Step Two: Integrate the New Data Sources: Next, feed these data sources into existing analytics capabilities and any relevant internal data. Be sure to cleanse, format, catalog, store, and secure the data to operate in a cohesive manner within the existing data environment. Develop an automated pipeline connecting all sources.
Step Three: Perform Enhanced Data Science: Step three is all about identifying and deploying the appropriate data science tools, techniques, and solutions for the new data sets. Once established, it’s time to design, build, and test these new data models.
Step Four: Promote Data Socialization and Utilization: In the final step of our process, we work with organizations to plug new data sources into existing models. From there, we develop and share new dashboards, build reporting structures and cadence, and establish governance and oversight to ensure new data sources are leveraged in the organization’s day-to-day operations and decision-making processes.
The result: A stream of new insights that internal data cannot deliver on its own, and a strategy for transforming these insights into meaningful actions that will position your company to achieve its desired outcomes.
Third-party data is a goldmine of information that can dramatically improve your organization’s ability to make smarter, faster decisions. Among its many uses, data from third parties can help you uncover new business opportunities, discover customer pain points that must be addressed, and improve your overall operations. Although your company may have a significant amount of proprietary data that can support deeper customer insights and more targeted revenue growth, third-party data sources fill important gaps that are likely not available in your own data sets.
If you haven’t been involved in the third-party data space before – either by integrating external data into your own organization or monetizing your existing data for others – today’s rapidly changing, increasingly interconnected environment makes a great case for getting started. It can be the essential ingredient you need to stay ahead of your competitors.