New Placed Research: Millennials and Auto Shopping

Driving Millennial Shoppers into Car Dealerships

 

The time has come—Millennials are ready for car ownership. They’re past their college years, getting married, earning good salaries, and considering moves outside of urban areas. If you’re an automotive marketer and still think of Millennials as teens who only use ride-sharing services, this Placed Research report is for you.

 

Millennials are actively shopping for vehicles, and using ride-sharing apps as a supplement to car ownership

By integrating Placed’s large-scale business visitation data with 1st-party automotive shopping surveys, we validated that Millennials are shopping at dealerships and taking test drives.

  • Millennials account for 1 in every 5 visits to dealerships.
  • 1 in 3 Millennial dealership visits is a shopping visit.
  • Millennial auto shopping visits over-index for Lyft and Uber app installs.

Although Millennials are ready to buy cars, the study also shows that Millennials shop differently. Fortunately, their real-world behavior—day of the week, time of day, business affinities—follows consistent patterns that can be used for optimizing marketing programs and ad campaigns to drive more Millennials to shop and test drive at dealerships.

Learn more by downloading the report or by contacting sales@placed.com.

Roadtrippers in the Know

Planning a road trip late in the season? Learn from summer road trips by looking at July Placed Insights for Automotive Services and Hotels.

 

Extreme Planners and Road Trips

Experienced roadtrippers make sure that their vehicles are in tip-top shape. They shop for tires before hitting the road, so they can wander without worry. And where do they rest? The most popular lodging for July tire shop visitors are Motel 6, Econo Lodge, and America’s Best Value Inn & Suites.

 

Extreme planners know how to find the shortest oil-change wait times — in July, Sundays and Wednesdays were the best days to visit Oil & Lube shops, with 20-30% less total visitation than Mondays, Tuesdays, and Fridays.

 

And don’t forget about grabbing snacks and fueling up — 7-Eleven had the highest July visit share in the Gas and Convenience Store category, followed closely by Shell.

 

More road trip highlights in the infographic below (click to enlarge).

 

Placed Insights July 2018 – Available Now!

 

Want to learn more about roadtrippers, or a different custom audience? Placed Insights is free and available online – to explore real-world foot traffic data for over 1,900 businesses.

TV Advertising Benchmark Metrics: Infographic from Placed Attribution

Following-up on our recent announcement of a free preview period, here is an infographic that is easy to read and share!

 

Placed Attribution for TV has campaign-level reports for 100 top brands. For a high-level view, we analyzed all the Q12018 campaigns — $3.7B in TV ad spend. The highlights:

 

35% of TV Campaigns Drive Incremental Visits to Businesses
It’s time for a conversion metric for TV. After viewing ads, consumers are taking action in the real-world.

 

Peak Time to Store Visit for Restaurants, Telecom, and Auto
Not all attribution benchmarks are the same — remember to dig down to the industry level.

 

Top Performing TV Networks for Lift in Incremental Visits
Across all campaigns, we identified the top five for driving incremental visits.

 

We hope you enjoy the infographic below (click to enlarge). To learn more about Placed Attribution for TV before the open-access preview period ends on June 29th, visit placed.com/tv and open a free account.

 

Placed TV Ad Benchmarks Infographic Q12018

Hurricane Irma’s Impact on the Location of People and Places

Placed analyzed the location and visitation data generated by residents in the path of Hurricane Irma to gain insights into impacts of what has already proven to be an abnormally active storm season.

 

Foot Traffic to Businesses:  Areas impacted by Hurricane Irma saw quantifiable increases in visitation to grocery stores (2.1x), gas/convenience (1.7x), and pharmacy (1.7x) in the days before expected landfall of Irma. While these visits were expected, unexpectedly visits to Pet Food and Supplies retailers, Diet & Nutritionists businesses, and Sporting Goods stores also saw increased visitation between September 4th through the 7th.

 

Restaurant/QSR locations saw up to 3.7x visitation rates by September 8th as residents began evacuation, or conserved supplies by eating out up until the last minute.  Interestingly, Check Cashing locations saw upwards of 28X the visitation from prior to the hurricane, possibly due to banks being closed and power outages forcing cash only transactions. Wireless retailers also saw significant increases in visitation (1.5x-4x) before, during, and immediately following the storm.

 

Evacuations Before Landfall:  By mapping “away from home” percentages by city by day, we clearly see the alignment to evacuation notices as well as delayed returns for areas where Hurricane Irma caused extended power outages.

 

  • Evacuations Start (Average): 2 days before landfall
  • Population Returns (Average): 3 days after landfall, 5 days after landfall for areas with extended power outages

Distance Traveled:  The metric “distance traveled from home” indicates that the Sept 6th Hurricane Irma path projections, which placed the center of the storm traveling up the Eastern coastline, aligns with the first wave of residents of Miami and Naples opting to leave their home locations and travel distances averaging as much as 260 miles to escape the hurricanes cone of damage.

 

  • Shortest Average Distance Traveled (Pre-Land Fall): 32 miles, Tallahassee Residents
  • Longest Average Distance Traveled (Pre-Land Fall): 295 miles, West Palm Beach Residents

The September 7th announcement of mandatory evacuations for additional cities beginning Sept 8th initiated a second wave of residents departing with Ft Myers-Naples area seeing 73% of residents on the move.

Accurate Location in Limited Supply, Findings from Placed Research

In the same way in which ad viewability was the hot topic issue these past 18 months, Placed anticipates location accuracy to enter into the headlines.  Placed’s research found that on average the accuracy of exchange based locations were on average off by more than 4 city blocks!  Additionally only 1% of bid request are accurate enough to identify store visits.

 

Download Placed’s Accuracy & Bias in Ad Exchange-Derived Location Data White Paper at https://www.placed.com/resources/white-papers/location-accuracy-bias

 

Excerpts from the white paper:

 

Growth in location based advertising is tied to continued growth in mobile usage. Current spend projections for location based targeting are estimated to reach almost $30B by 2020. As spend increases, so will expectations around validating the accuracy of both the location data and the subsequent visitation impact

 

However, there are several well known limitations of exchange-derived location data. First, the

source (e.g., GPS, cell tower, WIFI, IP) and accuracy of a given exchange-derived location data

point is generally unknown without additional validation. Second, given that ad impressions are

served and exchange-derived locations are observed only when the device is in use, there is the

potential for significant measurement bias to exist.

 

High-level results from the location accuracy analysis include:

 

  • The average accuracy of exchange-derived locations is over 4 New York City blocks.
  • After filtering for location accuracy, only 1% of bid requests are useful for in-store measurement (based on a location accuracy < 50 meters).
  • 80% of bid requests are made while people are in between visits—and most of the rest are made at home, limiting viable use of the data for determining store visitation or affinity.

Takeaways from the analysis of bias in exchange-driven location data:

 

  • Exchange-derived locations are only present when the device owner is using the phone and browsing an app that serves ads, thus bid stream data over indexes on location data from Lodging, and Gyms & Fitness Centers– likely due to readily available wifi combined with extended time spent at a given business.
  • Key retail categories such as Fashion, Professional Services (ex. Staples, OfficeMax), Sporting Goods and Computers & Electronics are under-represented in bid data.
  • The skew toward a subset of commercial business categories creates a bias in exchange derived data that requires validation against first party data to ensure corrected weighting.