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Why joint data sets are infinitely more valuable

December 21, 2022

This blog was reposted with permission from PredictHQ | Author: Valerie Williams | Original Source

More data = more perspective

Why are joint datasets more valuable? Because they contain information from multiple sources, which provides companies a more comprehensive and nuanced view of the data. For example, a QSR can use their own historical sales data combined with public transport information and census block data to better understand customer trends and patterns that impact their business transaction volumes.

By combining these different perspectives, joint datasets provide a more complete picture of a given phenomenon, which is useful for research and decision-making in multiple ways:

  • Joint datasets help to improve the accuracy of forecasting models by providing a larger and more diverse set of data for the model to work with. Massive data often leads to lower estimation variance, resulting in better predictive performance. More data also increases the chance that it contains useful information.
  • Joint datasets provide a more complete view of the data, which can help to identify trends and patterns that might not be apparent when looking at the data from a single source.
  • Joint datasets also help to identify relationships and connections between different variables, which can be useful for developing more sophisticated forecasting models that take these relationships into account.

Data professionals across many industries have been using the concept of ‘Joins’ in Sql for many years. As more tools, programming languages, and methods become available, the concept of the join needs to evolve to enable various, symbiotic data sets to be easily combined. This will allow data professionals to spend more time analyzing the data and building insights, rather than figuring out how to mesh data sets together.

Let’s take a look at how companies across key industries are using one joint data set in particular to enhance forecasting and drive sales, and you can too.

How joint demand and location intelligence powers deeper business insights

One particularly powerful data combination is demand intelligence and location intelligence, made possible by a partnership between PredictHQ and SafeGraph – a data company that specializes in providing granular location data and insights including point of interest (POI) data and building footprints which businesses use to better understand the physical world.

Leaders in advertising, mapping applications, retail, travel, real estate, and more rely on SafeGraph POI data to reveal the spatial behavior of human beings in relation to physical locations. For example, real estate companies leverage POI data to identify indicators of growth in a specific area based on the presence of certain businesses such as large restaurant chains.

These same industries and many others that PredictHQ works with, including quick service restaurants, accommodation companies, parking companies and more can leverage POI and intelligent event data to get a more holistic picture of locations and their demand.

We join these datasets together using Placekey, a free, universal standard identifier for any physical place. The combined data sets provide even further granularity and precision by clarifying exactly what is driving demand at a location.

Joining these datasets together unlocks local demand insights about holidays, concerts, sports, festivals, and more – each of which impact demand in different ways. With access to accurate POI data and intelligent event data, a variety of industries are gaining greater insight into events tied to unique locations.

How to leverage events + POI data to make data-driven business decisions

Data-savvy companies are boosting customer engagement by aligning their brands with local events, causes, and trends customers care about. When you have insight into all events taking place within walking distance of your stores, you can choose which ones to build campaigns or promotions around.

For example, advance notice of a community breast cancer walk that ends right by one of your store, restaurant, or parking garage locations. PredictHQ provides predicted attendance, exact start times, and accurately predicted end times for attended events – paired with granular location intelligence powered by SafeGraph for unmatched accuracy and detail. Let’s look at a couple of examples of how joint event and POI data powers actionable business insights:

Consumer Packaged Goods (CPGs)

CPG brands often want to know their total addressable market – the total number of businesses that could potentially carry their product. By determining this number and mapping it out geographically, companies can more effectively focus their expansion efforts and target specific areas for growth.

“As the pace of change in shopper demand patterns, market conditions, and supply chain constraints accelerates, demand forecasting AI that uses state-of-the-art models reduces guesswork and gives CPGs a more strategic view,” said PredictHQ CEO Campbell Brown.

For example, a beverage manufacturer that produces a variety of sports drinks. ​​The company can use location data to analyze where their products are currently being sold, as well as where they are not being sold, but have the potential to be successful. Or they could use location-based event data to track local sporting events, such as football games or marathons, where their drinks are likely to be in high demand. They can then reach out to distributors within walking distance of these demand-driving events.

The company could also use event data to identify when and where these events are taking place, and then use this information to target individuals in the surrounding area with targeted advertisements and promotions for their sports drinks. By leveraging joint data, they can boost brand expansion, gain business momentum, and better-than-anticipated earnings year over year.

Out of home advertising

Out of home advertising has been around for decades, with many companies discounting it as a channel for years but it is now experiencing a resurgence. A recent KPMG report pointed out that outdoor advertising has witnessed a 11% annual growth rate over the past five years and we expect to see the upward growth trend in 2023.

Out of home advertising businesses can use the joint dataset for campaign planning through audience segmentation and measure advertising effectiveness based on specific POIs or events that take place. They are using the data to know where and how to interact with certain audiences.

This is a shift from previous strategies of marketing to a person to marketing around an occasion, like a sports game. Occasion-based marketing allows OOH advertising companies to meet their target audiences expectations with context from events and around venues or POI where the events are being held that builds relationships and loyalty.

Occasion-based marketing allows OOH advertising companies to meet their target audiences expectations with context from events and around venues or POI where the events are being held that builds relationships and loyalty.

Mapping products in the geospatial industry

Companies that provide mapping applications such as the ones you use on your phone to find an EV charging station or coffee shop use this joint data to better understand where things are, and update these details to ensure accuracy with the real world. For example, as the names of local stores and venues change, mapping companies need these details to provide the most up-to-date information for end users. Beyond having up-to-date details about a business, it’s important to depict an accurate view of a place’s building footprint, which encompasses a building’s precise parameters or “outlines” of a given structure.

Polygons represent the true shape of a POI, and can help visualize the exact location of a building, the number of buildings, and even buildings hidden in aerial images by trees. For example, POI building footprints can provide context into the restaurants that live within a sports arena and the surrounding surface parking lots. By combining fresh POI and events data, mapping companies can provide their users an accurate depiction of the physical world.


Leading retailers are optimizing their site selection with event and POI data by choosing locations based on demand from nearby venues and areas that have many events – such as severe weather, concerts, sports events, school holidays, and more. Events drive people movement and companies are using event data to determine how many people will be coming to specific locations for events, to better understand the level of competition in the area and the potential growth. This insight helps retailers make more informed decisions about site selection and develop strategies for attracting and retaining customers in the chosen location.

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