Placed and Kantar Release Second Annual Black Friday Report

This post is adapted from analysis written by Jon Swallen, Chief Research Officer, Kantar Media Ad Intelligence.  

Access the full analysis

 

Placed and Kantar once again partnered to deliver the definitive Black Friday study measuring the impact of television advertising on driving customers into stores.  The findings highlight the importance of pre-Thanksgiving advertising spend on generating foot traffic during this critical weekend.

 

As in any contest, some competitors do better than others.  The results of this year’s study are no exception as mega-retailer Walmart used their massive scale to both outspend and outdraw its rivals.  Spending north of $70 million, Walmart not only drew a 38% share of in-store shoppers but did so at the lowest cost per share of any retailer in the study.

 

By contrast, Target spent nearly as much as Walmart but drew nearly 2/3 less visitors over the 4 day period (a 13% share).  It wasn’t all bad news for Target, however, as store traffic was up nearly 22%  vs. the week prior.

 

Download the full report here.

Kantar Whitepaper Graph

Placed Partners with Dstillery to Measure Store Visits Attributable to Cross-Channel Marketing

Following up on the recently announced partnership with Dstillery, Placed is excited to release the first set of performance metrics tied to a desktop campaign for a top 5 department store in the US:

 

  • 5.32% Store Conversion Rate for Desktop Impressions
  • 33.54% Lift in Store Conversion Rate (Exposed vs Unexposed)

In a first for the industry, combining Placed Attribution and Dstillery’s CrossWalk multi-device intelligence technology, this study connects the dots between desktop campaigns and offline behavior. This solution is a significant step forward for clients and the digital advertising industry to quantify desktop impressions to real world store visits.

To learn more about the collaboration, simply reach out to your Dstillery contact, http://www.dstillery.com, or contact Placed at sales@placed.com.

How Location Analytics Can Help Increase Mobile CPMs

Adweek’s recent article, Mo’ Traffic but No Mobile Money, took a look at the mobile CPM challenge plaguing publishers. Even with mobile traffic skyrocketing and smartphone adoption continuing its steady climb, mobile ads still struggle with low engagement, less sophisticated advertising technology and limited screen space, keeping mobile ad prices well below those of their desktop counterparts.

 

Perhaps the biggest hurdle for publishers though is the lack of metrics currently available to make the case for greater mobile CPMs. As the Adweek article states, “For publishers to justify more mobile investment, the industry needs better metrics, most argued.”

 

While on-device metrics are important in moving mobile CPMs higher, many publishers often overlook the value of location context that is inherent and unique to the mobile platform. Try to remember the last time you saw someone pull out their laptop while shopping, now try to remember the last time you DIDN’T see someone browsing on their phone in the same store – get the point?

 

Answering the where in the mobile audience equation has the potential to unlock a wealth of consumer insights to help build the case for greater mobile ad rates. The ability to know and quantify the stores, restaurants, businesses and categories that mobile users are nearby when engaging with publisher content creates a whole new layer of context (and value) for advertisers looking to bridge the gap between the offline and online experience.

 

In a recent case study, we highlighted how one news publisher was able to increase mobile CPM rates using Placed Analytics location data. Here’s a brief recap of the strategies they used to achieve better mobile ad rates:

 

Increase Mobile CPMs with Placed Analytics

  • Identify new categories to prospect:
    The publisher saw that 36% of usage occurred nearby restaurants. However, restaurants made up less than 10% of total ad sales. Using this data point, the sales team was able to identify restaurants as a top prospecting category and use location data to back up their pitches.
  • Optimize ad delivery by day and time:
    The publisher discovered that their users were most often nearby department stores on weekday evenings and weekend afternoons, so they decided to optimize the delivery of retail ads to reach visitors during the times and days when they were most likely shopping.
  • Selling to new advertisers:
    The sales team was able to use location data to secure a new supermarket advertiser. Being able to show that 10% of mobile usage occurred nearby that supermarket’s stores, as well as how much activity occurred near competitors’ stores, and which markets had the most competitive behavior helped justify higher rates for access to its more qualified audience.

As 2013 gets underway, improving mobile monetization is set to be a key theme for publishers and advertisers this year as both seek ways to leverage the small screen for big advertising gains.

 

 

How to Improve Your App with Location Analytics

Location Analytics for Apps You probably already use mobile analytics to understand what people are doing within your app – average session length, daily active users, most popular screens, etc.  But do you think about where people are, or what they are doing in the real world when using your app?  Mobile users can be almost anywhere when using an app or consuming content, which makes mobile different than other types of media.  To truly take advantage of the medium, it’s important to understand the impact that location has on app usage.

 

 

What is Location Analytics?

Understand the Real-World Context of App UsageUntil recently, there wasn’t really an easy way to get location insights for an app.  Google Analytics and Flurry are two excellent mobile analytics solutions, but they will only show location data down to the city level.  That’s why we launched Placed Analytics – a free service – to provide app developers with daily, aggregated reports around the places that users were nearby when interacting with their app.  The service supports Android, iOS and mobile web; the only requirement is that the app or site have permission to collect location data from its users.

 

Use Cases

There are numerous ways that you can use location analytics to better understand the behaviors and preferences of your users, and to shape plans for new features or improvements to your app.

 

Here are some example use cases:

 

App Engagement by MovementUnderstand how often people are moving (and how quickly) when using your app.
Are people usually in transit, walking or standing still?  This may seem obvious, but if they’re often walking or in transit, consider making buttons larger.  Or, you may want to add voice controls to make the app more user-friendly (not to mention safer).

 

 

 

Measure location by in-app activityTrack specific events within your app to identify where people were when they completed important actions.  Where were people when they first registered for your app?  When they upgraded to the paid version?  When they made a purchase or shared something on Facebook?  Using location analytics, you can start to identify relationships between certain types of places and key activities, and adjust your messaging and marketing tactics accordingly.

 

 

Granular Geographic Insights Ensure that your app addresses all the needs of your users.  If your app has a price scanning feature, make sure that you are set up to support all of the various types of products sold in the businesses where people are opening your app most often.  Or, if your app connects people with local services, you can identify which neighborhoods you should expand into next based on the specific areas where people are opening your app.

 

Learn more about your users and their habits.  See if they use your app in urban areas, suburban neighborhoods or rural places.  Determine if they prefer fast food or French restaurants.  Identify whether they shop at Walmart or Nordstrom.  Get a better sense of who your users are and what they like to do.

 

Takeaway

 

Of course, these are just a few general examples.  There are as many use cases as there are types of apps on the market.  If your app or site uses location, you can now access a wealth of valuable data – for free.  Simply implement an SDK, update your app on the market and start discovering new insights about your app and its users the next day.

 

This article originally appeared in MobileDevHQ.