Crocs Tops inMarket Back-to-School Foot Traffic Rankings

September 19, 2017 / by Dave Heinzinger posted in retail, inmarket, foot traffic, location data, data, big data, crocs, footwear, mobile location data

Are Crocs cool? According to inMarket Location Data, the answer is... yes.

Crocs has topped inMarket's Back-to-School Retail rankings for 2017, drawing the largest spike in foot traffic of any retailer during the busy July/August shopping period. Aeropostale, Staples, PacSun and Kids Foot Locker also had strong draws druing the 2017 back-to-school rush. 

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Contrarily, Neiman Marcus, Gap and Banana Republic all saw dips in foot traffic this summer. All three have announced store closures in the past 10 days.  

You can download the full report today at www.inmarket.com/insights. If you're interested in learning more about the rankings, just give us a shout over at www.inmarket.com/contact.

 

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How Have Amazon's Price Reductions Impacted Whole Foods’ Foot Traffic?

September 12, 2017 / by Dave Heinzinger posted in mobile, in-store, retail, apps, social, mobile, foot traffic, location data, grocery, amazon, whole foods, stores, consumers, shoppers

At inMarket, we're aggregating and analyzing location data from over 50 million anonymous consumers per month, via hundreds of apps. (Don't take our word for it. Our scale is verified by comScore.)

We use that data to power best-in-class advertising programs for the world’s top brands and retailers. It’s also very useful for predicting business trends, and drawing quality insights on how Americans truly shop in the real world.

This week we’re putting that data to work in a new format, and we're introducing a quick-fire version of our popular inMarket inSights deep-dive category reports: The inMarket inSights Report Card. These one-page analyses will reveal  location data insights and add context to the hottest business trends in real-time.

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Our first edition inMarket inSights Report Card covers Amazon’s impact on foot traffic at Whole Foods since taking control on 8/28 -- with a quick look at competitive grocers as well.

Check out the inMarket inSights Report Card for Amazon's Whole Foods -- live today at www.inmarket.com/insights.

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Retail Watch: Signs Point to Nine West Store Closures

July 21, 2017 / by Dave Heinzinger posted in mobile, in-store, retail, apps, social, mobile, retail, inmarket, location data, store closures

The New York Post is reporting that embattled retailer Nine West is close to shutting down, according to multiple sources.

"Nine West Holdings, owned by private equity firm Sycamore Partners, is mulling an auction proceeding that could spur a liquidation of the chain, according to sources familiar with the situation.

Licensing firms have been approached to determine their interest in the company’s brands, which include Anne Klein, Gloria Vanderbilt, l.e.i., Givenchy Jewelry and 14 others, which are sold in department stores and which have been hit hard by the shopping mall downturn."

The news isn't surprising if you look at the inMarket Location Data: In June, inMarket found that Nine West ranked last for customer loyalty in the non-grocery retail category -- behind failing retailers like Wet Seal and bebe.

While many might take this to be another sign of the retail apocalypse, we see it as a sign that retail is instead undergoing a massive evolution. There's a blend of online and offline happening in both directions. While retailers like Nine West head for closures, e-commerce giants like Amazon are jumping into the real world with their Whole Foods acquisition. There's a ton of value into serving customers in the here-and-now. It's up to the existing brick-and-mortar stores to adopt data-driven, e-commerce style practices that improve the in-store experience and attract customers back to the store. If they don't, the Amazons of the world will. 

E-commerce won't kill brick-and-mortar retail, the same way VHS didn't kill the cinema. But -- offline will have to adapt.

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Bloomberg: Loyalty an Issue for Shake Shack, according to inMarket Location Data

June 22, 2017 / by Dave Heinzinger posted in location, inmarket, adtech, location data, restaurants, data, shake shack, loyalty, customer loyalty, retention, bloomberg, news, inmarket insights, insights

Location data can help us predict business trends -- and sometimes, those trends are quite surprising. This week, Bloomberg has featured inMarket location data in its story about customer loyalty at rapidly growing Shake Shack. 

"As Shake Shack Inc. expands across the U.S. from its New York home base, it’s missing a key ingredient: customer loyalty....

Though the upscale burger chain has more prestige than rivals like Subway and Chick-fil-A, its higher prices may be preventing customers from ordering as often."

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You can read their full story here, or download the full  Loyalty Report for Restaurants at inmarket.com/insights.

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inMarket Location Data Reveals Top, Bottom Restaurants for Customer Loyalty

June 21, 2017 / by Dave Heinzinger posted in inmarket, location data, restaurants

Mobile location data tells the story of the world around us. At inMarket, we use it to power award-winning O2O ad products while analyzing business trends for brick-and-mortar businesses across many categories.

This week, we're using inMarket Location Data to rank the top and bottom Full Service Restaurants (FSRs) and Quick Service Restaurants (QSRs) for customer loyalty. It’s the second installment in our inSights program that looks at loyalty across various categories (like retail). We use repeat device visitation from over 50 million anonymous consumers to determine which businesses are performing better (or worse) than average.

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In general, the higher a business ranks for customer loyalty, the more likely it is to be thriving and expanding. Contrarily, many of the businesses toward the bottom of the rankings are struggling with bankruptcy, closures and poor sales.

The full report is available at inmarket.com/insights today. Feel free to contact us with any questions.

 

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Ranking Retailers from Top to Bottom on Customer Loyalty; inMarket Utilizes its Industry Leading Location Data to Project Growth and Closures

June 7, 2017 / by Dave Heinzinger posted in location, mobile, in-store, retail, advertising, location data, data, trends

Customer loyalty is vital to business health. Today, thanks to mobile location data, we can quantify customer loyalty and its impact on a business. In this report, we’re looking specifically at the retail industry, where each week it seems like there’s another round of mass store closures. But despite the “retail-pocolypse,” there are a few retailers that are expanding and thriving. What do they have in common? Loyal customers.

In our latest inSights report, we identify the top 10 and bottom 10 retailers for customer loyalty, based on inMarket location data. This first in a series of reports across brick and mortar verticals uses mobile location data from spring 2017 to identify customer loyalty at major U.S. retailers. The full report is available today at www.inmarket.com/insights. 

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The findings from inMarket’s Spring 2017 data show a clear correlation between low customer loyalty and announcements of store closings, while high-loyalty retailers are actually expanding in the face of the predicted “retail apocalypse.” Thus far in 2017, five out of the top 10 retailers for customer loyalty have announced store expansions. Contrarily, eight out of the bottom 10 retailers for customer loyalty are either closing stores, laying off employees or freezing growth in 2017. 

inMarket uses machine learning in order to analyze billions of data points and paint a picture of consumer behavior’s influence on business. This retail loyalty ranking is based on inMarket location data from over 50 million anonymous consumers -- focusing specifically on repeat device visitation as an indicator of customer engagement, loyalty and retention.  

In addition to predicting market trends, inMarket uses location data to power its suite of industry-leading ad products such as its Lapsed Shopper Program -- which launched in March as an equalizer for brick and mortar retail against e-commerce. Retailers are recovering over 40% of their lapsed shoppers with the program, which capitalizes on store visit data the same way online retailers uses web visit data to retarget shoppers. 

For more information on these rankings or to find out your business's loyalty score, contact us today. 

 

 

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How To Use Location To Power Smarter Mobile Moments

April 20, 2017 / by Dave Heinzinger posted in mobile, in-store, retail, apps, social, location, location-based advertising, in-store, adtech, location data, data, mobile marketing

As marketers, we’re always looking for ways to keep up with rapidly evolving consumer behavior. Social, mobile and location have created new windows into the most important moments in a shopper’s purchase cycle.

But as soon as you have the game figured out, the rules change.

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This is particularly true for social, where the largest players have focused on monetization strategies and are charging for what used to be free. Facebook is probably the best-known example: throttling organic reach for business pages while charging to promote content to the page’s earned audience. The result? Diminishing returns for advertisers in a crowded newsfeed.

But these challenges create opportunities, and the savviest marketers are exploring new, tech-forward ways to influence shoppers when it matters most. Location has matured to become arguably the most important piece of the mobile marketing puzzle. It’s no longer an innovation concept — it’s a critical marketing ingredient.

At inMarket, we help brands lift sales through cutting-edge location strategy. Here are a few exciting ways that we’ve seen marketers use location to create smarter mobile moments:

Augment Customers’ Reality

Pokemon Go, the summer’s biggest mobile fad, leaves us with a few key takeaways, the biggest being that the masses are willing to seek out great location-based content. In Pokemon Go’s case, it was the hunt for special characters, plus a healthy dose of nostalgia, that appealed to users. 

Augmented reality content, particularly with an air of exclusivity, is here to stay. Snapchat is a great example, having developed a geofilter product that bridges the online/offline worlds, providing specialized content based on where you are. The magic in these geofilters is that, by nature, you literally have to be there.

Marketers should ask themselves a few questions before jumping into location-based AR. How can it help the customer or improve their experience? Is the content designed for a smaller, more loyal audience within a brand’s app, or for a wider audience via third-party apps? Does it necessitate the micro-location of beacons, or can it be triggered by wider geofences?

Answering these questions upfront will help you wow shoppers while deploying the most effective AR strategy for your brand.

Hit The In-Store Bullseye

“Location” is a big word, and it often doesn’t say what we need it to. Location targeting shoppers in New York is distinctly different than location targeting shoppers when they walk into Rite Aid. And yet they’re often lumped together, creating confusion for everyone.

If we think about location targeting like a concentric circle (i.e. a dartboard), we can understand how different technologies get us closer to the bullseye. We might use IP data to geotarget people on a wide scale. This works well if you’re a footwear brand advertising snow boots in New York and flip flops in Florida.

Closer to the center, we might use geofencing to create a virtual boundary around a particular retailer. For example, if you walk by a department store in New York, you could receive a personalized ad for snow boots.

But most brands want to hit the bullseye. That’s where we rely on cutting-edge technology like beacons, where IOT infrastructure creates the most precise targeting available to influence in-store decisions. Beacons allow marketers to trigger contextual experiences through an app on a shopper’s phone at the exact moment the shopper walks into a store or an aisle within that store.

When you’re this close to the end of the funnel, you want to remind shoppers why they’ve come so far. Great content examples include using a fashion app to deliver key design details about a brand of snow boots, or showcasing someone wearing the boots on a key Instagram account.

When you combine bullseye targeting with hyper-relevant content, the conversation gets really exciting. We expect the award-winning mobile campaigns of 2017 to incorporate bullseye targeting with exclusive AR experiences.

Target By Actual Need

Demographics have always been used to guide targeting. But the places people go are a better indicator of who they are and what they need. Today, we can aggregate location data to understand consumer patterns and determine actual need versus likelihood of need.

For example, a major car manufacturer might target men ages 34 to 45. They might even geotarget “men 34 to 45 in northeast cities” with region-specific creative. But they have no way of knowing who in that audience actually needs a new car.

What if they could target people who have been to an auto repair shop multiple times that month? Or better yet, to a car dealership? Both of these behaviors better indicate that the shopper is a hot lead, as opposed to any demographic qualifier.

Today, targeting by need is a practical concept. Location companies have already put the infrastructure in place to accurately understand individual consumer trends, creating a tremendous opportunity for impactful mobile moments. 

Predict Shopper Cycles

If we can tell when shoppers actually need a product based on their location history, you can look at those visits over time to determine their purchase cycle and when they’re “due” for a store visit. For example, if data indicates you grocery shop every Thursday, you’re more receptive to brand messaging on Wednesday when you’re actively planning to go, versus Friday after you’ve already shopped.

Modern targeting will focus on shoppers who “pre-qualify” themselves through offline behaviors and location visits. In other words, the data point of “Joe went to a car dealership” is just as actionable from a marketer’s standpoint as if Joe had searched for “new cars” online.

We’re at an exciting point in the evolution of mobile location where real, sophisticated campaigns are resonating positively with consumers at scale. Reaching shoppers when they’re most receptive to brand messaging is paying off for marketers in the form of foot traffic and sales. The next 18 months will provide fast-moving marketers with an opportunity to own the mobile/location ecosystem while the competition plays catch-up.

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Mobile Location Data Reveals Restaurant Chain Winners, Losers of Spring Training in AZ and FL

April 17, 2017 / by Dave Heinzinger posted in location, location-based advertising, foot traffic, location data, restaurants, spring training, baseball, arizona, casual dining, qsr, mlb, florida

Spring Training is big business for many cities in Florida and Arizona, as teams and their fans make the annual pilgrimage out of the cold to celebrate baseball and sunshine. The Baltimore Orioles, for example, generated over $89MM in economic output for their winter home of Sarasota, FL. The state as a whole drew over 1.5MM fans in 2016 -- setting a 100-year high, according to Gov. Rick Scott.

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While teams like the Orioles measure their economic output through official sporting + cultural events and its promotion of Sarasota tourism, they (and other teams) might actually be selling themselves short. There’s a nice side effect that happens when you’re drawing tourists from all over the U.S.: They spend lots of money at in-state and in-city businesses -- specifically restaurants.  

At inMarket, we use first-party, full cycle location data from over 50 million anonymous consumers to understand foot traffic patterns at retail, restaurants, airports, salons and more. Based on that data, we’ve ranked all of the Florida and Arizona restaurant chains based on their share of visits (SOV) during spring training. A positive (+) number indicates the SOV is higher than average, while a negative (-) number indicates that the SOV is below average. This helps us to understand how restaurants are performing relative to their size and number of locations.

Check out the full report below -- or give us a shout directly here


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