Location data can differentiate companies looking to stand out in a very crowded advertising space. The use of consumer data in advertising has grown exponentially in the last decade. Data on demographics, online activity, purchasing trends, geography, and various other factors have revolutionized how companies get closer to their target audiences and make more strategic bets for driving and improving advertising performance.
To stay competitive, brands are leveraging additional data in their audience analysis to ensure they are targeting the right people at the right time. Places data is a particularly powerful supplemental dataset in this effort. Enriching privacy compliant consumer data with the context of physical places provides marketers a new level of sophistication in planning, buying, optimizing, and measuring programmatic campaigns, especially in online-to-offline attribution.
We wrote about the rise of location-based marketing previously. Here, we elaborate on the importance of location for building audiences. The information in this guide will help marketers and ad specialists use Places data to enhance audiences, and enable you to increase ROI by incorporating geographic data in your ad strategy.
In this guide, we will cover:
To stay competitive in today’s market, brands need to carefully curate the end-to-end customer journey. There are many ingredients that can be used to optimize this experience, all relating to what the consumer prefers, how they behave, where they go, and other details that enable personalization. However, consumer data without offline behavior is extremely limited in providing this necessary insight.
Census block group (CBG) level data and generalized household demographics may adequately describe who a target consumer is, but they fall short in providing the reasons, locations, and relevancy required to target them effectively in a manner that is well received by that consumer. Mobility data combined with places data blends well with digital signals to give a more well-rounded picture of the target consumer and improves return on ad spend (ROAS).
For example, consider car enthusiasts who routinely browse websites without actual purchase intent. They often look at car models they never plan to buy. Places data can be used to cross reference online signals with their physical movements, identifying whether they have recently toured an auto dealership (a much more likely signal of intent to purchase) or better yet, entered the actual showroom (an even higher converting signal). By understanding whether these consumers are “window-shoppers'' or potential buyers, a whole audience segment can be ruled out of ad targeting, saving a lot of money and increasing ROAS.
Here are just a few examples of companies leveraging places data really well to provide advertising value to their customers:
Each of these companies share a competitive edge that cannot be achieved without the use of clean, accurate places-based insights.
In today’s omnichannel world, consumers are interacting with brands both online and offline. It’s important to bridge both the physical and digital world by using a mix of data sources for a more holistic view of audience profiles.
Combining data such as foot traffic, browsing behavior, and purchase history provides better insight on how an audience interacts with brands across different channels. These insights explain why individuals are engaging with a brand in a certain way, ultimately helping derive consumer affinity for brands and products. This enables marketing teams to create more effective campaigns that can reach audiences wherever they are.
Diverse data sources also simplify the ability to personalize messaging to audience segments. Personalization hones in on specific audience needs and can lead to higher conversion rates and better brand engagement, plus happier customers. For example, research by McKinsey shows that personalizing the customer experience results in a 20% higher customer-satisfaction rate and a 10-15% increase in sales-conversion rates.
Points of interest (POI) or Places data is important because it offers marketers a geospatial perspective for understanding their target audiences and where they might visit. Bad data will only lead to audience inaccuracies and misleading indicators.
The physical world undergoes constant transformations with places opening, closing, and operational hours shifting. It is crucial not to settle for POI data sources that update annually or even quarterly. Instead, investing in POI datasets that refresh monthly, like SafeGraph Places, will ensure access to the most reliable information.
POI polygons add an extra layer of detail to enrich your audience profile. Polygon data takes POI data a step further by providing the building footprints, estimated sizes, and where possible, actual tenant splits so you can create more specific location-informed audiences.
Incorporating POI polygons aids in discerning whether someone actually visited a POI - and is therefore a part of a target audience - or if someone simply walked past it. This level of specificity allows you to precisely identify who in an audience has visited a POI, and offers a more reliable means to confirm campaign performance than relying on estimates or projections.
Context is critical when utilizing mobility data for audience profiling. Simply clustering individuals based on their proximity to certain POI is not enough. To gain deeper insights, you must derive context on how these places relate to behavior. For instance, it’s important to recognize that a consumer may act drastically different in two different cafe settings (say, one serving strictly espresso versus one offering wine late into the evening). Accounting for this will help you develop stronger, more targeted audiences. Make sure to consider what hours are typically most popular and what times places open and close for business. This way your algorithm can make sure to attribute those late night pings to the bar that is still open and not the bagel shop next door that closed at noon.
Cross-referencing visits to other POI can also unlock patterns and preferences of certain audiences. For example, it can show if an individual frequents Target and a specific restaurant, say Chipotle, in the same trip. Without factoring in contextual nuances from POI data, mobility data alone may yield incomplete or even misleading insights into audience behavior and preferences.
The significance of POI data in crafting precise and strategic audience profiles is undeniable, playing a pivotal role in optimizing the return on investment for advertising by understanding your audiences at a deeper level.
At SafeGraph, we understand the importance of data quantity and quality. That’s why we publicly track our accuracy efforts. Our team can help you uncover how leveraging accurate POI and polygon data will elevate your audience-building strategies, supercharge your campaigns, and ultimately grow your return on ad spend. Get in touch here.