How location based marketers look to the past to predict the future

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How location based marketers look to the past to predict the future
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The iPhone–which is turning ten this month– transformed the way people communicate, shop, and travel. It also transformed the way marketers reach their ideal audiences. For the first time, they could use the smartphone’s location data to find out where consumers were—and buy impressions accordingly.

Today, advertisers continue to use real-time location data to target consumers. But the industry has come a long way since 2007. Advertisers are moving beyond the real-time capabilities of location technology towards more advanced applications. Brands can boost campaign performance and ROI, by using historical data and AI-powered solutions to discover where consumers have been and where they are going.

Back to the Basics, Location 101

Location-based advertising means using real-time location data to reach out to consumers based on where they go. A common example of Location 101 is targeting consumers based on their distance from a given location in real-time, known as proximity targeting. For example, if a pharmacy wants to target young women inclined to purchase its products, they can collect mobile devices seen in similar or related locations. Using location technology, the pharmacy brand can retarget that audience group whenever they come within feet of one of the pharmacies with products they have in stock or specific promotions. The same example applies to many verticals, not just CPG.

But even proximity targeting has matured beyond these basic abilities. More advanced applications involve layering real-time location data with other valuable data for more granular targeting.

Let’s say a high-end retailer on a busy shopping street is using proximity targeting to reach consumers within 100 feet of their store. That brand could be wasting impressions on people who wouldn’t shop at a luxury store in the first place. But how would they know? If the brand pairs its proximity data with consumer information such as shopping histories, demographic and geographic details, they can more accurately target the right person. For instance, they can improve campaign performance by reaching out only to high-income earners who have previously shopped in a different luxury store—individuals who are not just nearby, but also likely to buy.

From Mobile to Mobility

Brands need to remember that they aren’t advertising to a mobile device, rather, they are advertising to a mobile person. Therefore, the importance of looking at historical location data to get to know their consumers and their preferences is paramount. For instance, sports enthusiasts could be identified by the quantity of trips they make to sports fields each month. Their habits can be identified by the types of hotels they stay at while on the road to the games. Based on this historical information, advertisers can utilize this data to target this audience with ads for fan gear when close to sporting goods stores or hotel deals when traveling on the road to games. This type of data builds rich audience targeting segments for marketers so they can advertise based on consumer behaviour.

Places we go over time reveal more than just consumers’ preferences; historical location data can also tell advertisers things like when consumers tend to go to the gym, how often they go shopping, or how frequently they are heading to the airport—from specific location, the day of week, time, to duration of time spent in a location. Such insights can be used to retarget consumers not only at the right place, but also at the right time.

For example, someone who visits the airport monthly is likely a frequent flyer, but that doesn’t mean they’ll be receptive to an airline ad while boarding a competitor’s plane. Instead of using proximity targeting to reach this flyer at the airport, the airline can analyze historical location patterns to reach out after their travel when they are back at work or at home—and before they book their next flight.

AI and Advanced Analytics

While many brands focus on real-time location and historical behavioral patterns, other advertisers are looking into the future. With machine learning and predictive analytics, these advertisers lean on their technology partners’ knowledge of behavioral patterns and advanced algorithms to drive in-store foot traffic.

Brands drive foot traffic by targeting only those with strong purchase intent at exactly the right time and place. Brands can now tell their tech partners how many visitors they need in what locations and buy them on a cost-per-visit model; only being charged once a store visit occurs.

For example, a fast-food chain can identify its ideal audience by looking at individuals who visit this chain a few times a month. Then, they can deliver ads to these individuals at the time and place they are most receptive based on past behavior patterns to drive them in store. Such advanced techniques increase foot traffic as well as in-store sales.

From basic applications to more advanced use cases, location data and technology continue to alter the advertising world. As the industry evolves, brands should look beyond where consumers are in the moment, to where they’ve been and where they’re going in order to improve conversation rates, waste less ad dollars, and increase sales.

View the original article on Digiday by clicking here.

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Partner Spotlight: Q&A with RSi’s Ansa

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Partner Spotlight: Q&A with RSi’s Ansa

Question 1: How long have you been at RSi and what is your role?
For the past three years, I have been responsible for creating and scaling Ansa, a web-based solution from RSi – Retail Solutions, Inc., that has enabled over 75 of the world’s largest CPG companies and their agencies to build, measure and maximize the performance of their shopper marketing campaigns running in support of the nation’s leading retailers. I am responsible for all aspects of business development, partner and agency relationships and the overall revenue growth of Ansa.

Question 2: How does RSi help solve marketer challenges?
Shopper marketers’ biggest challenge is to connect their online campaigns to in-store results. RSi’s Ansa solution provides the intelligence they need, based on daily, store-level POS-data from the largest US retailers in order to plan, target, and measure the impact of their shopper marketing campaigns. Retail Solutions Inc. has partnered with the leading ad networks in Shopper Marketing, such as Blis, to make Ansa’s automated analytics available for the world’s largest CPG companies and their agencies. To measure and maximize their digital ad campaigns, all they need to do is ask for Ansa inside their next campaign.

Question 3: What benefits does the partnership with Blis bring to buyers as well as the adtech ecosystem?
With RSi’s Ansa solution, building, dynamically optimizing, and reviewing attribution measures for every digital ad campaign has never been so simple. Here is how it works:
1. STORE-LEVEL TARGETING: automatically get from Ansa your store targeting data as store addresses, lat/longs or by Ansa Digital ZIPs to identify stores with the greatest sales potential prior to launching hyper-local media.
2. IN-FLIGHT OPTIMIZATION: see in real-time how sales are trending in your targeted stores vs. a 52-week historical average, and get access to dynamic optimization lists that can guide budget reallocation.
3. MEASUREMENT & INSIGHTS: get access via the online portal to end of campaign analysis just days after the media campaign is over. Visualizations give you a standardized set of analytics, such as sales lift, incremental dollars and units, confidence level, weekly lift, characteristics of high performing stores, etc. Prove and improve your media to help you fine-tune strategies for your future campaigns.

Question 4: What are use cases for the Blis + RSi partnership? (Please provide a few examples from different verticals).
If you are a shopper marketer, maximizing your budgets, understanding performance of your marketing tactics and generating key learnings from those marketing tactics are tasks that are essential to your business.

Running a digital marketing campaign with Blis, and Ansa’s daily, store-level sales intelligence helps make that extremely for the CPG community and shopper marketers specifically.

For existing products, Blis campaigns using Ansa targeting can reach a targeting efficiency of 2:1 vs. campaigns that do not use Ansa store-level targeting thereby ensuring that every dollar is spent driving sales to your most important retailer locations.

Blis campaigns optimized with Ansa typically identify and heavy up investment around 16% of stores that are trending significantly ahead of the average store during a campaign and identify and decrease investment around 14% of stores that are trending significantly behind the average store, therefore ensuring that your budget is being optimized surrounding stores that are over-performing during a given campaign.

After each Blis campaign, Ansa automatically generates measurement of Featured Item Lift and Halo Item Lift at both the total event and week levels. Results are completed 5 business days after the end of each campaign and allow you to learn quickly and improve continuously, all at an amazingly affordable price.

Question 5: What shopper marketing measurement trends do you predict for 2018?
Optimization in-flight based on store sales trends during campaign. Optimizing on engagement, intent and / or clicks may be ok for some campaigns but more and more frequently shopper marketers are tasked with driving sales at their most important retailers. And understanding how their marketing tactics performed 5-6 weeks after a campaign has finished is just not fast enough anymore in today’s fast paced world and puts media providers at a severe disadvantage. By utilizing automated reporting that allows Ansa partners like Blis to understand and optimize their media in-flight based on daily, store-level POS sales data you now empower your media partner to act on supporting the stores that are driving your product sales which can ultimately provide a powerful boost to a shopper marketing campaign.

Question 6: If there was one piece of content you think every marketer should read, what is it?
(Other than this blog post of course!)

Think with Google and Facebook IQ are two fantastic sources of resources. Articles, trends, case studies, POVs, insights, etc… pretty much everything you need to read to keep you up-to-speed in this very fast-paced environment.

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Meet, Greet and Keep: How Mobile Can Help Brands Throughout the Sales Funnel

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Meet, Greet and Keep: How Mobile Can Help Brands...

Our mobile devices give us more than just a way to call or text friends and family: Today, they are our maps, books, radios, and miniature shopping malls. We turn to them for news, entertainment and answers. And from dawn till dusk, we keep them at our sides like our most faithful companions.

So it’s no wonder mobile devices have become integral to an advertiser’s ability to reach their ideal audiences at every stage of the sales funnel. Here’s how brands can employ effective mobile advertising strategies to acquire, engage and retain customers.

Win Over New Customers

One of the best ways for advertisers to identify new audiences is to see where they shop. But without access to a competitor’s first-party purchase data or information about their website traffic, how can advertisers find this out?

Mobile devices provide the answer. By revealing where consumers go, mobile location data can tell brands which consumers spend their time browsing similar products at a competitor’s store. Let’s say Target wants to reach out to consumers who usually shop at Walmart. They can use location data to identify—then target—those who frequently visit the competitor yet still live near a Target store.

But brands need to be careful before jumping to conclusions about consumers. Real-time location data provides important insights, but they can be strengthened when paired with historical location data.

For example, just because someone visits a high-end boutique like Chanel, it doesn’t mean that person has the budget to shop there—they could just be browsing. How can an upscale fashion brand find out which of those Chanel visitors are actually potential shoppers? Here, historical location data can help. It can reveal, for instance, which of those visitors go to private airports a few times a month or regularly visit Giorgio Armani or Versace stores. Chances are, these consumers will be a better bet for the fashion brand seeking to acquire new customers.

Keep Them Interested

What’s the first thing you do when you wake up in the morning? For most of us, it’s look at our phones to turn off our alarms before checking the weather and scrolling through our Twitter feeds. And throughout the day, we continue to stare down into the faces of our mobile devices: checking the news on the train, sending an email between meetings, or watching videos from our living room sofas.

In order to engage consumers on the devices we use day in and day out, advertisers will need to serve ads that make sense for the consumer depending on where they are during the day. To do this, advertisers must first ask the question: What do consumers want to see on their mobile devices and when? Consumers spend a third of their time online watching videos, for instance, but they aren’t going to watch a 30-second video ad while walking down the street.

To boost engagement, brands can use knowledge about a consumer’s historical and real-time whereabouts to reach out at the time and place that will produce the greatest level of engagement. To effectively grab the attention of a consumer that’s out and about, a banner ad may work best. Later that evening, when the consumer is at home using a tablet or laptop, a longer video on a larger screen may work well.

Inspire Loyalty

How can brands make sure they retain the new and existing customers they’ve worked so hard to gain? They must first recognize and show appreciation for their most loyal customers.

Most advertisers identify loyal customers by looking at newsletter subscriptions and online purchase histories, but they may be missing other valuable customers who prefer to shop in stores. By identifying devices that frequently visit a brand’s store location, advertisers can make sure they are recognizing—and thanking—all their biggest fans. When an existing customer comes into a store a certain number of times, for example, advertisers can deliver a thank-you message—perhaps offering the loyal customer a generous coupon to redeem in-store.

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Retailers’ Golden Ticket to Reviving Brick and Mortar Stores

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Retailers’ Golden Ticket to Reviving Brick and Mortar Stores

Interested in understanding how to connect mobile experiences to physical stores? Or how mobile can be the extension of a retailer’s store? Maybe you’ve wondered about the new Cost-Per-Visit metric? Look no further. Blis’ location data experts will be answering these questions on a weekly basis over the next few months in our ‘Retail Series’ which aims to equip retail marketers with the right insights and top tips to stay ahead of the game.

Following its decision to buy e-commerce company Jet.com last year, Walmart recently agreed to acquire Bonobos, a retailer with a strong online presence and generous shipping policies. If these moves weren’t sign enough that the physical and digital retail worlds are merging, Amazon’s acquisition of Whole Foods is the ultimate wake-up call.

Retailers everywhere are realizing that while brick and mortar stores are still critical, they’ll need a strong digital strategy to keep them filled with happy customers. Mobile devices are retailers’ golden ticket to connecting with consumers and reviving in-store shopping.

Understanding Consumers though Mobile

Whether they are going to work or going shopping, consumers carry their phones with them wherever they go. As a result, mobile devices provide retailers with a constant stream of valuable consumer insights. GPS and Wi-Fi data can tell retailers, for instance, whether a consumer is at a desktop at work, connected to Wi-Fi at home, or walking past a retailer’s store.

Beyond real-time location data, retailers can use historical location data to understand a consumer’s habits. For example, some consumers might visit a luxury jewelry brand on Fifth Avenue just to browse, even if they have no intention (or monetary means!) of buying. Thus, for that specific retailer, in-store visits may not indicate ideal customers. Instead, that luxury retailer can look at historical location data to identify their ideal consumers: perhaps individuals who frequently stay at the Four Seasons Hotel or regularly check in to exclusive country clubs.

But retailers shouldn’t rely on mobile data alone. By layering mobile insights with other valuable sources of data, advertisers can gain a holistic picture of their perfect audiences. Data collected from laptops, for instance, can reveal browsing histories and online shopping patterns; however, consumers won’t be opening up their laptops while shopping in stores. The trick is for retailers to match the data across devices to unique mobile device IDs. Only then will they gain a more holistic understanding of consumers and will be able to target or retarget them with products they are likely to go buy.

Driving Foot Traffic Creatively

Once they’ve gotten a clear and thorough understanding of their ideal audiences, how can retailers use mobile devices to drive foot traffic? Proximity targeting—delivering ads to consumers when they come within a certain distance of a store location—is a common approach. Retailers can maximize the power of proximity targeting by crafting unique and imaginative creatives.

For instance, advertisers can deliver ads to shoppers already in the area to tell them about an in-store sale, or offer them a coupon they can only redeem in person. Retailers can also deliver ads that feature a handy map telling consumers how to find their store.

Sometimes, targeting consumers when they are walking by a store may be a little too late. A QSR wanting to boost its 10 am breakfast crowd, for instance, may want to target consumers when they wake up around 7a and begin planning their day. Otherwise, the consumer has most likely already made their breakfast choice.

While there is no one-size-fits-all solution for retailers looking to connect with consumers and drive in-store sales, a strong mobile strategy is key. As the digital and physical worlds continue to blend, retailers must harness the insights and capabilities of mobile to reach their unique brand objectives.

Tune in next week to read all about how mobile is fast becoming the extension of a retailer’s store.

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