Understanding your guests’ demographics can help when considering site selection, guest engagement, and planning marketing and merchandising in your venues. Placer provides visibility into visitor characteristics including frequency, duration, location, demographics, psychographics, and behavioral shopping patterns to create an unprecedented and constantly evolving view of the consumer at each location and by region.

To better understand your guests and their interests, behaviors, and shopping patterns, it’s best to research guests with relation to their visit patterns and their demographic and psychographic attributes.

You’ll be able to answer these questions after reading this article:

1. How do you view your guests' demographics?
2. How do you view the same POI side-by-side, with different filters in place? 
3. How has your customer profile changed over time?

Get started with the following steps:

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Step 1: Analyze Guest Visit Patterns (loyalty, frequency, dwell time)

Loyalty metrics can be used to better understand customer habits and preferences for your store or competitive locations. Use visit frequency to see how many times customers frequent a location and evaluate your mix of loyal to casual customers. 

Compare Visit Frequency for your venue to other venues of interest

a. Open the Property report page for your POIs^{Points (Locations) of Interest.} (add multiple locations by clicking on the plus icon) and choose your preferred time period. While we use a retail location for this example, the steps are the same for an entertainment or leisure venue.

b. By comparing Visit Frequency^{The number of total visits by unique visitors.} (Metrics), you can see that these 3 home improvement stores in the same market have vastly different metrics. Visitors frequented The Home Depot nearly 4 times in the last 12 months, while Vickery Hardware had less than 2 visits in the same time period. 

Learn about Foot Traffic Metrics

Review additional loyalty data for your venue or your competitors

a. From the Property report page, navigate to the Loyalty section in the left sidebar. 

b. Here, you can view the breakdown between loyal and casual visitors. You determine what a loyal visitor is by setting the minimum number of visits each visitor has to make in your chosen time period to your location to be considered loyal. For example, if you set your minimum number of visits to be 4, the visitors who have visited your location 4 or more times will be counted as loyal visitors. All other visitors will be counted as casual visitors. You can view the data with different filters and easily switch between the Loyal and Loyal vs. Casual visualizations by using the Hide Casual toggle.

c. In the second section, Visits Frequency, each bin in the chart shows the estimated number of unique visitors who visited your store a certain number of times during your chosen time period (choose between Visitors, % of Visitors, Visits, % of Visits).

Learn about Loyalty

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Step 2: Analyze Guest Demographics and Psychographics

Placer’s Audience Profile widget allow you to explore a multitude of consumer attributes so you can identify and describe a brand’s key customer profiles. The Audience Profile widget is available within property reports (Property Audience Profile) – for analysis at a granular, location-specific level – or within chains reports (Chains Audience Profile) for chain-level analysis.

Pro Tip: The insights surfaced in Audience Profile are based on 3rd party datasets that are available on Placer's Marketplace. You may find different datasets in Audience Profile depending on your account’s subscriptions. The Census 2017 and Census 2019 datasets are provided to all users. Most customers also have access to Census 2017 and Census 2019, STI: Popstats, STI: Spending Patterns, STI: Market Outlook, STI: Workplace, Experian Mosaic and AGS: CrimeRisk at no extra cost. A variety of additional datasets are available on Placer's Marketplace at an incremental cost.

Below you’ll find steps walking through specific analyses using just five of the datasets available in Audience Profile: STI’s Popstats, STI’s Spending Patterns, Experian’s Mosaic, AGS Behavior & Attitudes, and Spatial.ai’s PersonaLive.  However, each of these datasets contains much more information than what is highlighted below, and many more data sets are available.  The steps below are simply an introduction to what’s possible with Audience Profile, and we recommend that you spend additional time exploring the data presented throughout each dataset.

Analyze visitor demographics and population demographics using STI Popstats

a. In Audience Profile, under “View”, select “Captured vs. Potential”.  Under “Dataset” select “STI: Popstats”.  STI (Synergos Technologies Inc.) is a market research company, and Popstats offers in-depth demographic, household-level population data collected from several public sources, including the U.S Census, NCHS, NCES, IRS and BEA.

Scroll down to view the table.  Expand “Overview” to see demographic data related to income, wealth, persons in the household, and more.  For both the Captured Market and the Potential Market, you see a list of attributes, the median value of each, and a purple bar graph and index number which shows how this value compares to the national average.  When evaluating the index number, keep in mind that a value of 100 matches the national average, so numbers larger than 100 are proportionally “more likely”, and numbers lower than 100 are proportionally “less likely”.

In the example below, you can see that visitors to the San Diego Zoo Safari Park have a Household Median Income of $92,557.89, which “over-indexes” (relative to the national average) by 33%, as indicated by the 133 index. You can interpret this as indicating that the Safari Park is currently more likely to reach a higher-income audience.

Of course, the attributes of visitors are very likely to be influenced by the attributes of nearby residents.  Comparing the Captured Market and the Potential Market values and indexes allows you to better understand how visitors to the location differ from individuals that live nearby, within the trade area. The “% difference” column at the right makes this comparison super easy, by showing the percentage difference between two.  For example, the table below reveals that visitors to the San Diego Zoo Safari Park are likely to have higher household incomes, disposable incomes, and discretionary incomes than nearby residents.

b. Now expand “Language Spoken”.  Here you can see that the Safari Park reaches a large number of Spanish speakers, but it actually under-indexes relative to the surrounding population. That is, visitors to the Safari Park are 12.2% less likely than the surrounding population to speak Spanish at home.  

How this insight might be best applied will depend upon the details of an advertiser’s unique marketing objectives, strategies, historical context, and more.  For example, it could suggest that operational enhancements (e.g., Spanish-language signage or more Spanish-speaking staff) are needed before the Park can expect to more effectively convert a Spanish-speaking audience. The Park may then wish to avoid spending additional advertising dollars targeting Spanish speakers in the short-term.    

Alternatively, this insight might suggest the exact opposite: an opportunity for the Safari Park to increase their overall visitation by engaging a somewhat untapped audience of Spanish speakers. Therefore, the San Diego Zoo Safari Park might consider running a Spanish-language advertising campaign in order to better engage the Spanish-speaking population in their trade area.

Analyze visitor and population spending patterns using STI: Spending Patterns

a.In Audience Profile, under “View”, select “Captured vs. Potential”.  Under “Dataset” select “STI: Spending Patterns”. STI’s Spending Patterns sources data from the annual Consumer Expenditure Survey of the Bureau of Labor Statistics to provide insight into weekly spending averages in over 600 products and service categories.

b. Scroll down to view the table.  Under the “Weekly Spending per Person” tab, you see an overview of expenditures by product category.  You may opt to either navigate directly to a category of interest, or browse all categories paying special attention to the “% Difference” column in order to see which categories over- or under-index relative to the population.  

In the example below, you can see that visitors to this Albertsons location over-index slightly in their spending for entertainment-related admissions and fees.

c. To dig deeper, navigate to the “Weekly Entertainment Spending per Person” tab to explore the specific subcategories of Entertainment spending.  Expand the “Fees and Admissions” section and notice that visitors to this Albertsons are more likely than the nearby population to spend on a variety of Entertainment fees and admissions, including movie tickets and participant sports.  

Therefore, Albertsons might consider exploring cinema advertising or sponsorships of local sports teams in this region, in order to reach their target audience.

Analyze visitor and population psychographics using Experian Mosaic

a. In Audience Profile, under “View”, select “Captured vs. Potential”.  Under “Dataset” select “Experian Mosaic”.  Mosaic is a leading consumer lifestyle segmentation system that provides a wide view of consumers’ characteristics and preferences by clustering U.S. households into detailed behavioral segments.  Mosaic segments are widely available for targeting online and offline, within many leading media marketing solutions – including advanced TV providers like Roku, DirectTV, and Samsung, and leading DSPs like The Trade Desk, Viant, and Amazon DSP.

b. Scroll down to view the table.  Examine the “Overview” tab to see the Mosaic groups that describe visitors to the location (Captured Market), residents within the trade area (Potential Market) and the difference between these two (% Difference).  You can hover over the tooltip to read a short description of each Mosaic group. 

In the example below, you can see that almost one-third (32.6%) of the visitors to this Albertsons location are classified as the “A - Power Elite” group.  The purple bar graph and index within it shows how this compares to the national average –– specifically, an index of 389 indicates that visitors to this Albertsons are almost 4x as likely to fall into the Power Elite group. Additionally, the “% Difference” column reveals that this “Captured Market” is almost 15% more likely than the “Potential Market” to fall into the Power Elite group, suggesting that this Albertson’s is especially good at reaching or appealing to “Power Elite” households.

c. To dig deeper, navigate to the “Households” tab to explore how visitors index versus specific segments within each Mosaic group. 

In the example below, expanding the “A - Power Elite” section reveals that visitors to this Albertsons location over-index by 18.5% for the “A03 - Kids and Cabernet” and “A01 - American Royalty” segments, as compared to the “Potential Market”.

Experian provides robust profiles describing each group and segment, including demographics, family structure, media consumption, technology adoption, and much more.  You can explore these in the Mosaic Handbook, which is linked within the Mosaic page in the Placer Marketplace.

This is immensely valuable information to consider when crafting messaging, planning promotions, or defining your media strategy. 

Analyze visitor and population psychographics using AGS Behavior & Attitudes

a. In Audience Profile, under “View”, select “Captured vs. Potential”.  Under “Dataset” select “AGS Behavior & Attitudes”.  Applied Geographic Solutions (AGS) is a leading supplier of marketing data. Behavior & Attitudes allows you to examine over 400 psychographic segments to reveal consumers’ lifestyles and preferences – from favorite types of products to individual views and travel habits – built on consumer insights from the MRI-Simmons study along with additional AGS data.

b. Scroll down to view the table.  Expand the “Media” group to explore attributes related to media consumption that can inform media planning.  

In the example below, we’re analyzing visitors to a 24 Hour Fitness location in Southern California, and we can see that they over-index as talk radio and especially NPR listeners.  The index of 201 conveys that they are more than twice as likely to listen to NPR than the US average. The “% Difference” column indicates that this is 6.7% higher than the trade area population.

c. Expand the “Modern Technology” group to explore attributes related to technology use and digital media behaviors that can inform digital media planning.

In the example below, we can see that visitors to the same 24 Hour Fitness over-index for Yelp (254), LinkedIn (181) and Twitter (136) usage.

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c. Next expand the “Health And Fitness” group to explore related behavioral and psychographic characteristics that might inform creative strategy.

In this example, visitors over-index as “weight satisfied” (110), “yoga enthusiasts” (163) and “pilates people” (182) – even more than the trade area population. This insight could be used to inform or substantiate creative messaging and visuals that highlight happy, fit yogis (as opposed to, say, power lifters).

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Step 3: Analyze visitor and population social media activity using Spatial.ai PersonaLive

a. In Audience Profile, under “View”, select “Captured vs. Potential”.   Under “Dataset” select “Spatial.ai PersonaLive”.  PersonaLive is a geosocial application that combines store visitation with digital behavior from social & web interactions to classify households into 80 segments that encapsulate behavioral and demographic traits. Since it incorporates digital behavior, many advertisers find PersonaLive especially helpful when planning targeted digital marketing campaigns.

b. Scroll down to view the table.  Examine the “Overview” tab to see the PersonaLive groups that describe visitors to the location (Captured Market), residents within the trade area (Potential Market) and the difference between these two (% Difference).  You can hover over the tooltip to read a short description of each PersonaLive group.

In the example below, you can see that over one-fifth (20.9%) of the visitors to this BMW dealership are classified within the “B - Wealthy Suburban Families” group.  The purple bar graph and index within it shows how this compares to the national average – specifically, an index of 292 indicates that visitors to this BMW location are almost 3x as likely to fall into the Wealthy Suburban Families group. Additionally, the “% Difference” column reveals that this “Captured Market” is over 45% more likely than the “Potential Market” to fall into the Wealthy Suburban Families group, suggesting that this location is especially good at reaching or appealing to Wealthy Suburban Families households.  

Conversely, this location is not particularly good at reaching the group “H - Young Professionals”, as the “% Difference” between Captured and Potential markets is -10%.

c. To dig deeper, navigate to the “Segment Families” tab to explore how visitors index versus specific segments within each PersonaLive group.

In the example below, expanding the “B - Wealthy Suburban Families” group reveals that both the Captured and Potential markets are classified as only two of the four possible segments: “B02 - #SatelliteScions” and “B01 - #FusianFamilies”.

d. Now select “Advanced Reports” in the main navigation. Within the “Advanced Reports” menu on the left, select “Spatial.ai PersonaLive”.

e. Click on “#FusianFamilies” in the FAMILY B: Wealthy Suburban Families” box.  Once the page loads, you’ll see an in-depth overview of the place visitation, web visitation, media channel preferences, demographics, and recent social media hashtags popular among individuals classified in this segment.

f. Click on “Channels” in the left-hand menu to see this segment’s media channel and publisher preferences, including preferred magazines, TV channels, TV shows, and top websites.

g. Click on “Social Topics” in the left-hand menu to see the topics and hashtags commonly mentioned by this segment in social media.  Click on “Influencers” to view this segment’s top influencers, with an index noting their propensity to follow each account (relative to the national average).

These highly-specific behavioral insights are incredibly useful in planning digital media advertising campaigns.