The location space has always been defined by innovation.  It is a complex, yet incredibly powerful data point, and companies like Cuebiq were founded with the mission to help businesses unlock its value to inform decisions across their organization.  This week's partnership announcement with Innovid exemplifies the potential of location to help brands execute more effective media campaigns.   

In its most basic form, location intelligence is simply the understanding of real-world behavior:  Where people go (mobility) and the “stops” they make (visits).  For those unfamiliar with Innovid's DCO product (Dynamic Creative Optimization), it is a powerful technology that helps advertisers generate multiple versions of a creative  (or change the relative allocation of multiple creatives) to more efficiently achieve an outcome.  Brands and publishers have traditionally leveraged optimization tools like Innovid’s DCO to improve media performance metrics (like viewership and engagement), which have proven remarkably effective.  After all, we know advertising works, right?

The integration of Innovid’s Dynamic Creative Optimization (DCO) technology and Cuebiq’s timely, precise visitation metrics, means brands (and publishers) can now optimize their creative messaging to drive more traffic to stores or, even better, more incremental visits using real-world behavior patterns and action.  

The Power of the Partnership

Leveraging opt-in location data, we can now verify the offline customer journey, from the moment people initially see the ad to when they visit the store. These tangible, real-world metrics demonstrate actual human behavior—beyond the digital sphere—and that’s what makes location data so unique, and so powerful. 

For the past two years Cuebiq has been developing our unique definition and methodology for incrementality.  Read this for the long version, but in summary, we project the expected number of visits of an individual (device) based on historical and control group behaviors, isolate variables and compounding factors, and report on the variance to give the industry’s truest understanding of the campaign’s influence at the device level and in aggregate. (apologies if you feel like this was the long version!) 

The ability to optimize to increase incremental foot traffic—to allocate more weight to the creative that does the best job of driving visits that would not otherwise have occurred—means brands and publishers can now maximize ROAS within existing (and often inflexible) campaign elements (ie publishers, inventory mix/type, flighting, etc.).  This is not a subtle or insignificant advancement. This is the manifestation of our industry understanding viewership and engagement metrics only tell part of the story, and recognizing mid or end-of-campaign reporting is woefully insufficient, and demanding the ability to impact real-world behavior in real-time.  

Looking to the Future

This partnership is just scratching the surface of what’s possible.  By testing and optimizing in real-time, we can adjust both the minute and macro elements of a creative, and we can learn what impact every creative decision has on store visits.  This is the realization of the value performance marketing can unlock, and it is incredibly exciting.

Please reach out to your Innovid or Cuebiq representative, or email Jfriedman@cuebiq.com to learn more.

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For years our industry has been talking about the power and promise of location data.  Understanding the real world behavior patterns of a brand’s current and prospective customers enables more efficient targeting, more effective messaging, and (of course) the ability to measure whether a campaign actually had the desired effect of driving people to stores.  

That promise changed a bit over the past year and a half as the pandemic dramatically altered the way people socialized, traveled, and shopped, and the idea of leveraging location to target “in the moment shoppers” or report on the change in visit behavior became less relevant.  Cuebiq and other location intelligence companies quickly pivoted to support efforts by government entities, academic institutions, and news organizations to analyze and navigate the spread of the pandemic.  We also worked with brands to help them understand shelter-in-place, mobility flow, and “social contact” insights as indicators of customers’ likelihood to visit stores or dine at restaurants, and to adjust their strategies accordingly.

How Shopping is Different This Year

Back-to-school season will mark the first real in-person shopping event in more than 18 months.  A survey by Deloitte revealed that parents expect to spend 16% more on back-to-school shopping this year, a drastic increase from the 1-3% growth rate seen in recent years. This won’t just be online—according to the National Retail Federation, 48% of K-12 shoppers will be heading to department stores, 44% to discount stores, 41% to clothing stores, 27% to office supplies stores, and 27% to electronics stores. This back-to-school season will clearly be a success, and though it may seem like those of the past, don’t be fooled—it’s different this year.

It's no secret that a lot has changed as a result of COVID-19. As a recent report from Deloitte puts it, “We saw technological adaptation that would normally have taken years occur in a matter of months. COVID-19’s continued effects will be felt even after the pandemic subsides.”  Business models changed overnight (curbside delivery and “ghost kitchens” to name a few!), and the inability to accurately predict (and plan) challenged every stop along the supply chain.  

The factors causing so much change are ultimately irrelevant—the bottom line is the change has happened. Traditionally, marketers could target a general audience, like people with kids for back-to-school campaigns, because they never had to think about individual (or regional) behaviors based on external factors like a pandemic. The US has always been a complicated network of different ecosystems.  The difference now: approaching key initiatives such as “back-to-school” as a national event with singular messaging and tactics is demonstrably inefficient at best and a guaranteed recipe for failure at worst.  

How Location Data Can Help

With the realization that individual communities are behaving vastly differently from one another comes the recognition that location as a data point is uniquely positioned to help brands make better decisions across the organization.  Real-time analysis of how people are moving around can indicate a “return to normal” mindset and willingness to “physically” engage with a brand. General mobility coupled with category and competitive visit trends, can help inform site-planning, product tests and offers, and marketing strategies.  

If leveraged properly, location can help individual brands understand their current and prospective customers better, and action more effectively as a result.  Think of it as the bridge between analysis and activation enabling regionalized strategy and activation previously thought of as inefficient by national advertisers spending big money on big reach.  

Contact us to learn more about how you can leverage location data.

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Want to understand how Mobility Insights can help your business during and after the pandemic? It’s easy. Through location data, you can understand how people are moving in the offline world and use those insights to fuel your strategies moving forward. Learn more about Cuebiq Mobility Insights in our video!

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It’s that time of year again: flu season. As you may have read, it’s more important than ever that consumers receive flu shots this year, to avoid being double impacted by the flu and COVID-19.

Widespread adoption of flu shots as well as increased COVID-19 testing are proven public-health measures to mediate the negative health and economic impacts of COVID-19. Pharmacies and retail testing centers can increase foot traffic to retail locations that offer flu shots and COVID-19 testing through targeted advertising campaigns based on consumer behaviors in the offline world.

Reach Consumers With Targeted Messaging

It all starts with reaching the right consumers. With location data, pharmacies can identify specific segments of consumers to target with flu shot or COVID-19 testing messaging.

For example, a pharmacy could use Cuebiq’s Traveler Analysis to identify groups of consumers who are traveling from out-of-state hot spots and are not sheltering in place upon arrival. These segments might be considered “high-risk” for contracting COVID-19, and would make sense to serve with ads promoting COVID-19 testing. Other prime segments for such ad targeting would be frequent bar visitors and essential workers.

Measure and Optimize Campaigns With Incremental Visits

Next, it’s important for pharmacies to be able to tell how effective their targeted advertising is. With offline measurement, they can measure the effectiveness of messaging in driving in-store visits. Then, they can use those insights to fine-tune their campaigns during dynamic crises such as COVID-19. Specifically, they can determine whether their campaigns are driving incremental visits to pharmacies from customers who would not have otherwise visited, and then optimize their campaigns accordingly.

For example, a pharmacy brand could determine whether an ad campaign promoting COVID-19 testing resulted in an uptick of visitors to their pharmacies. Using incrementality at the consumer level, they can also understand whether their campaign was effective in driving new visitors to store. With this information, they can determine how each channel they’re running media on is affecting consumers differently, segment consumers based on campaign influence, allocate their media spend for each segment, and finally target those segments. Over time, these tactics could increase their share of COVID-19 testing and flu vaccinations.

Use Mobility Insights for Campaign Planning

Once a safe COVID-19 vaccine is publicly available, these strategies may also serve as the foundation for driving vaccination adoption. Using Mobility Insights, retail testing centers can monitor consumer mobility and store visit patterns and plan accordingly. Specifically, they can use location data to inform when to send what messaging to whom.

For example, retail testing centers might want to deploy a phased campaign once a COVID-19 vaccine is available. With the first round of vaccinations likely going to essential workers such as teachers, retail testing centers could target this segment with ads for the vaccine in November. In the new year, they could expand their targeting to all demographics, once the vaccine becomes publicly available. With a dynamic rollout, they can better reach the right consumers at the right time with messaging that resonates.

In these ways, location data can drive not only flu vaccinations and COVID-19 testing, but also ultimately COVID-19 vaccination adoption.

To get started, check out Cuebiq’s robust location-based segments available for targeting, or search for Cuebiq audiences on your favorite DSP!

The post How To Spur COVID-19 Testing and Vaccination With Location Data appeared first on Cuebiq.

A day in the life of a QSR marketer is a bit different from that of a marketer in other retail sectors, such as auto or apparel — due to a specific reason. For consumers, choosing a quick-service restaurant is more likely to be based on impulse and circumstance than for other types of retail purchases, due to the costs of fast food being much lower. This makes a QSR marketer’s job more difficult because the stakes of each brand interaction are lower, but the benefits of loyalty and repeat business are crucial. 

Location data has become a key element for QSR brands, both in planning and buying strategies, giving marketers the tools and insights they need to properly take advantage of the consumer journey. According to 451 Research, location data ranks near the top in importance for QSR marketers because of the complex challenges it solves. 97% of QSR marketers surveyed said they will increase their usage of location data over the next two years. And they aren’t just looking to increase usage to solve the same old problems; they are looking to enhance the way they plan, buy, and measure their advertising dollars.

57% of QSR marketers plan on using location data to improve attribution and to better understand consumer behavior, suggesting that marketers are significantly investing in location data applications beyond more traditional use cases like geo-fenced triggered promotions. With increased usage and confidence in location data, QSR marketers are gaining new insights into the consumer journey, which support and help guide their media planning and buying decisions.

Download Study

QSR Marketers Are Becoming Proficient With Location Data

451 Research asked QSR marketers to rate their companies’ maturity levels in using location data for various purposes, from geo-fencing to attribution. The five maturity levels ranged from the early stages of planning (level 1) to more advanced or best-in-class programs (level 5), which are well-organized and integrate location data into day-to-day planning.

Most QSR marketers rated their companies somewhat in the middle stages (levels 3 to 4), indicating that they have formal programs with managed processes but are reluctant to describe what they do as best-in-class … yet! However, it's clear that the majority of QSR marketers are way past the initial stages of planning, with 76% of marketers rating their companies at level 3 or above!

The big takeaway here is that QSR marketers are moving fast and aren’t just using location data to solve simple problems, but rather they are using it for advanced uses cases like attribution and analytics.

[video width="1920" height="1080" mp4="https://www.cuebiq.com/wp-content/uploads/2020/03/451-qsr-2020-3.mp4"][/video]

QSR Marketers Want More Location Data

It makes sense that 97% of marketers are planning to increase their usage of location data — as marketers tackle more advanced use cases, it's easier to see the value of location data. One of those values that is crucial for every marketer is “incrementality,” a game-changing metric that helps brands understand if their advertising is actually changing consumer behavior (for example, driving new consumers or increased visits to store).

Incrementality is even more important for QSR marketers because it provides a true look at campaign performance, offering insights beyond campaign uplift around incremental visits. With incrementality, QSR marketers can now understand which of their media tactics is influencing new visits or driving additional visits from already loyal consumers. Incrementality gives marketers the tools they need to get the most out of their ad dollars.

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Want to learn more about the 451 Study or how Cuebiq can help you? Connect with an expert on our team today!

The post QSR Marketers Consider Location Data “A Must-Have” According to 451 Research appeared first on Cuebiq.

Published 1/3/2020

2019 was a year of abundant growth and innovation in the MarTech industry, and we are confident that 2020 will continue on this trajectory. We got the opportunity to sit down with Cuebiq’s EVP of Growth, Valentina Marastoni-Bieser, to hear her take on the new year’s upcoming trends. Having been in the industry for over 15 years, she has had a front seat watching the space evolve. Read on to find out Valentina’s predictions for the most significant topics and trends in the MarTech industry for 2020.

1. Artificial Intelligence

Her first prediction centers around a highly buzzed-about term: artificial intelligence. While you are probably familiar with popular applications of AI such as Alexa, you might not know that AI has numerous applications for the MarTech industry as well. From chatbots that allow brands to offer 24/7 customer support to hyper-targeted advertising, AI has the power to make marketers’ lives easier.

“What we’re seeing is that companies are really using it to bring to life powerful use cases. So, we are going beyond the buzz and finding real applications for marketers, and an example is predictive and prescriptive analytics,” said Valentina. 

2. Incrementality

Incrementality, which is made possible by AI, is a metric that gives brands a deeper understanding of campaign performance. As a refresher, uplift measures the impact of ad exposure in driving in-store visits. However, it doesn’t tell the complete consumer story — and that’s where incrementality comes in. Incrementality shows whether a campaign actually changed consumer behavior, by illustrating whether it drove incremental store visits from new customers.

Valentina predicts we will see a large shift from focusing solely on uplift to also focusing on incrementality at the consumer level, which Cuebiq now offers in its state-of-the-art enhanced platform. Moreover, she predicts it’s going to be the hottest topic for 2020 since it solves a problem many marketers face in the B2CB world: understanding the true impact of their campaigns. 

3. Personalization

Personalization is, as Valentina puts it, “the holy grail of marketing.” The key to gaining a consumer’s loyalty is through personalized messaging. While this isn’t a new concept, what will make it a trending topic in 2020 is how brands will go about such personalization. Like incrementality, personalization is made possible by AI. “If you understand incrementality on consumer level, then you can segment and personalize your message to the consumer based on what you learned.”

4. Conversational Sales & Marketing

A term coined by Drift, conversational marketing allows consumers to easily engage with a brand by having access to real-time conversations through targeted messaging and chatbots. While this customer centricity is already apparent in the B2C world, brands have traditionally driven the conversation in the B2B world. 

As predicted by Valentina, 2020 will be the year of conversational marketing, and it will change the B2B landscape to be more consumer-centric. As marketers continue to work with tighter budgets, prove campaign ROI, and shorten the buying cycle, it is imperative to adjust tactics to be more customer-focused. “Direct-to-consumer brands have been succeeding because they have done this the best. So B2B has to come around because we’re marketers but we’re also consumers. We want the same type of buying experience.”

5. Connected TVs, OTT, and Data Privacy

In addition to the four topics discussed above, Valentina is quick to point out that some of the biggest trends and hot topics of 2019, like data privacy and connected TVs and OTT, are not going anywhere anytime soon.

With CCPA now in effect, data privacy will become an even bigger topic of discussion and regulation. Privacy will be a key differentiator for companies, such as Cuebiq, which remains at the forefront of global industry standards when it comes to data privacy.

Additionally, connected TVs and OTT will continue to be a prominent topic. With ongoing advancements in the space, like interactive ads on TV and mobile, there will be even more need for measurement and personalization.

It's never too late for marketers to prepare for what’s to come. Valentina’s advice is to focus on putting the customer first. “Look at everything through the lens of ‘what does my customer need’ or ‘how is my customer buying’ or ‘what are their challenges,’ and make sure your strategies and tactics are tailored toward this.”

Want to know if Valentina’s predictions for 2020 will prove to be true? Stay up-to-date with the industry's latest trends, topics, and news by following Cuebiq’s blog.

The post 5 MarTech Predictions for the New Year appeared first on Cuebiq.

While it’s hard to believe, Q4 is quickly coming to an end. With the end of the year also comes time for reflection — time to look back on the past year’s successes and begin preparing for the year to come.

In the spirit of reflection, the Cuebiq marketing team took stock of all major trends and hot topics in offline intelligence from this past year. Ultimately, we concluded that the biggest trends of the year were data privacy, brand safety, the merging of online and offline, incrementality, and predictive analytics. So let’s recap on why each of these were important and how they affected the advertising industry as a whole.

1. Data Privacy

It goes without saying that data privacy has been a very hot topic of conversation in 2019. For companies collecting location data, it’s essential that they do so in a fully privacy-compliant and transparent manner that puts the consumer first. 

With regulations like GDPR having been in place for over a year now, we have witnessed firsthand the effects they’ve had on how European businesses operate and handle data. This past year, brands started vetting potential future partners more rigorously, and they will continue to do so in the future. As the landscape evolves and more regulations such as CCPA come into effect, privacy will play an increasing role.

2. Brand Safety

Going hand in hand with data privacy is brand safety — which hinges on data security. While it is imperative that companies collect data in a privacy-compliant manner, it is just as important that once said data is in their hands, they do everything possible to keep it safe and secure.

Over the past year, companies across all industries have invested in secure practices for using consumer data. Those that haven’t have faced dire consequences, such as massive data breaches that are detrimental to their brand reputation.

The biggest lesson the industry has learned from this is that security teams should be routinely testing security products to uncover possible flaws. In fact, here at Cuebiq, we recently put our security tools and frameworks through rigorous testing.

3. Merging of Online and Offline

The intersection of online and offline is a familiar concept for marketers, especially when it comes to retail. With the rise of e-commerce, brick-and-mortar retailers must quickly learn how to compete by connecting clicks and bricks. In other words, they need to integrate online data from their consumers with offline data.

This past year, brands found that the key to merging online with offline lies in one thing: leveraging location data. Thus, brands are increasingly partnering with offline intelligence companies in order to close the loop on the consumer journey. By using offline measurement, brands can measure their online and offline campaigns’ success in driving consumers to store.

4. Incrementality

The concept of incrementality has become more popular with marketers over the past couple years, but it really rose to prominence this year. Simply put, incrementality is a metric that gives brands a deeper understanding of campaign performance. 

As it relates to offline measurement, incrementality builds on the industry standard of uplift, going one step further to reveal whether a campaign actually changed consumer behavior. We expect incrementality at the consumer level to be a major hot topic for next year as well. 

5. Predictive Analytics

Like incrementality, predictive analytics is a topic that really started to gain momentum this past year. As a refresher, predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. In other words, we can predict consumer behavior by finding patterns and relationships within the data we already have.

We’re excited that Cuebiq’s enhanced platform offers solutions that rely on both predictive as well as prescriptive analytics. Going one step further than predictive, prescriptive analytics find the best course of action for a given situation and then issue specific recommendations. 

Now that we have delved into the offline intelligence industry trends of this year, it’s time to start looking ahead to next year. Stay tuned for the next blog in this series, which will feature predictions from our internal experts on what the hottest topics for next year will be. 

In the meantime, you can stay up-to-date on all offline intelligence trends by following our blog.

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We have a controversial statement to make: MAUs are out. While measuring scale in terms of monthly active users has been the prevailing method of recent years, location data has advanced such that this metric is no longer good enough. As with bidstream data, which was once so popular but was ultimately proven inadequate to be the industry standard in terms of accuracy and privacy, MAUs are now insufficient in producing high-quality location data.

So, MAUs are out — and DAUs are in. Our reasoning is pretty simple: Offline analytics and attribution need to be based on daily measurement. This means you should have the ability to see the behavior of your opted-in users every day, not only a few days a month. After all, if you don’t see your users every day, then what exactly are you measuring?

DAUs: The Key to Measuring the Complete Consumer Journey

Let’s consider the consumer journey. Mapping daily consumer patterns with a future-proof privacy approach is the only safe way to measure the consumer journey effectively. If you’re not able to see consumers every day, then you do not necessarily know if they indeed visited a store after being exposed to an ad. This means you might not be accurately measuring store visits. Also, you may be missing out on a huge part of their buying journey — such as brand affinity, brand loyalty, churn, purchase intent, and more. By understanding the complete journey, you can activate against these insights to target more effective audiences that are more likely to convert, thus driving better-performing ads and an increase in ROAS.

Whether you’re a brand, agency, or publisher, it’s imperative to partner with a company that leverages first-party data, collected on a daily basis — this is the only way to gain meaningful data and insights. Having a panel of DAUs is the best practice for getting data regularly, because it reveals where users shopped before as well as after seeing an ad. This paints a complete picture of the consumer journey — not just a part of it.

New iOS Updates Require a New KPI

What’s more, the iOS updates that went into effect in September give users more control over their data sharing frequency, rendering MAUs no longer a good measure of panel scale and quality. Since MAUs could include users that are only seen once, this KPI is no longer effective.

As follows, it’s important to ask existing and potential partners what their DAU count is. Collecting sparse data points (from MAUs) is no longer enough; location data companies need to be collecting data on a daily basis. Frequent data is more telling than sporadic data, and it leads to better insights.

Looking Ahead: Future-Proof Privacy & Data Quality

We recognize that changing the industry metric for scale is a tall order, but it’s an important one. And our industry is no stranger to change. Let’s consider, for example, that bidstream comparison we made earlier.

Collecting location data via bidstream used to be the norm. When we at Cuebiq introduced our first-party data collection methodology via app-direct relationships, it allowed us to be the first to accurately measure dwell time and collect high-quality location data at the same time — challenging the status quo. Now, it is widely accepted that bidstream data is deeply problematic for both brand safety and privacy compliance. While bidstream data sources enable massive scale, they sacrifice quality and trust in doing so. Bidstream data collection does not allow the end user to provide consent, have control over how the data is used, or even know who it is sold to. In all of these respects, bidstream data lacks transparency and is a major threat to brand safety.

Just as bidstream data went from au courant to passé, MAUs are failing to provide the information we need them to in order to keep up with the times. As follows, we at Cuebiq are now only measuring scale in terms of our DAUs. We embrace collecting location data on a daily basis as the future of measurement, as it provides data that is truly meaningful.

Check out our blog “6 Truths About Location Data” for more insights about location data quality.

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You’ve probably heard a lot about offline intelligence, but you might not be sure how to tell what actually constitutes high-quality location data. Not all location data is created the same, and if you’re evaluating potential providers, there are several key factors that should be on your radar. Read on for six truths about location data to learn how to choose the right partners to maximize your marketing efforts.

1. Privacy Compliance Is Everything

When it comes to data, privacy has been the topic of the year. In this day and age, it’s absolutely paramount that the location data you use be privacy-compliant. This means it needs to adhere to current privacy regulations, such as GDPR. If not, you risk winding up embroiled in a privacy scandal.

In order to avoid this, you should go one step further and partner with a location data company that exhibits a future-proof approach to privacy. With more stringent privacy laws coming to the US, it’s important to stay ahead of the curve in terms of privacy compliance. You want potential partners to not only meet existing privacy regulations, but also be focused on setting higher privacy standards and industry best practices, and ultimately preparing for future regulations that will come to the US such as CCPA.

2. High Scale = Meaningful Insights

The next truth is that in order for location data to yield meaningful and actionable insights for your local-to-national marketing efforts, it needs to be representative of the US population at large. This means that the data set needs to be diversified and have high scale.

Imagine that you’re in charge of optimizing media dollars against performance. In this case, performance = in-store visits based on ad exposure. If you’re leveraging offline measurement to measure in-store visits, it’s vital that your decisions be based on meaningful insights. For example, 200 visits is quite different from 2,000 visits — and you do not want to be wasting ad impressions and media dollars on low-scale insights. At the same time, you do not want to sacrifice scale for accuracy, which brings us to our next point.

3. Accuracy Goes Hand In Hand With Precision

Location data must be accurate. With regard to location, accuracy is the degree of certainty of how close the data provided is to the actual point of interest (or retail location). But what if the data is accurate for a certain location — say for example, the Bed Bath & Beyond store in Wynnewood, PA — but not precise? Precision means exactness on a map, and it is expressed using lat-long coordinates. The more decimal places that exist, the more precise the location is. So in our example, precision would be how many feet the location data is from Bed Bath & Beyond. In this way, accuracy and precision go hand in hand; they are both necessary qualities for the location data to be valid.

4. Not All “Visits” Are Real

It’s a common misconception that every location data company can provide data on store visits. In order for a location data company to be able to determine whether an actual consumer visit took place, it needs to measure time spent in store. This is a metric known as “dwell time,” which measures how much time consumers spend in store. It is used to verify a consumer visit by distinguishing actual visits from non-relevant data points, or as we call them at Cuebiq, “fake visits.”

Let’s consider an example. Just because a user gives off a momentary location ping near a hockey stadium does not mean they actually saw a game — they could have been just walking by. In order to determine whether they attended the game or not, you need to consider how long they spent at that location. In this way, dwell time is an essential metric to consider in evaluating location data providers, as it parses real visits from fake visits. Just like in truth No. 1, the numbers matter — 200 pings does not equal 200 visits. Location data can be layered onto almost every aspect of your marketing efforts, but if you’re choosing the wrong partners, you will not see the ROI.

5. First-Party Data Rules

How is the data collected? You want first-party location data to ensure the data is high-quality and can be trusted. When the data is collected directly by the provider from consumers, it means that there are no intermediaries collecting the data. First-party data is also important with regard to user privacy, as it ensures that users have the opportunity to opt-in to data collection. This is key to making sure your brand maintains a positive relationship with consumers, and you are adhering to existing privacy regulations.

6. Security Is the Secret Make-Or-Break

Finally, I want to mention a less buzz-worthy topic: security. As you evaluate new and current partners on privacy, it’s also important to understand how well they are equipped to protect their data. Partnering with a company that has its own internal security team and protocol is a great place to start. Using security as an evaluation metric will not only help protect brand and consumer privacy, but it will also reduce your risk of partnering with the wrong provider.   

To learn more about what to consider when evaluating a location data provider, chat with an expert.

The post 6 Truths About Location Data: How to Choose the Right Data to Maximize Your Marketing Efforts appeared first on Cuebiq.

This article was written before Cuebiq deprecated our SDK, which you can learn more about in this blog. We've left the following information up as it may offer offer additional insights and context.

Below is a Q&A between Viant and Cuebiq's Lawrence Chan, which was originally posted by Viant on 1/21 here.

Today’s Q&A is with Lawrence Chan, EVP, Data Ecosystem at Cuebiq, a location intelligence and measurement company that specializes in offline consumer behaviors.

A 10-year veteran of mobile advertising and marketing, Chan focuses on identifying innovative opportunities and strategic partnerships to drive Cuebiq’s expansion.

Q: There have been numerous advancements in location data quality in recent years. What stands out most?

Marketers are now able to leverage location data that is much higher quality than what was available even just a few years ago. That’s due in large part to the development of new data collection methodologies, such as Cuebiq’s proprietary location-based SDK (software development kit), which brings marketers location data that is both accurate and high-scale and collected with a forward-thinking privacy framework. The combination of these three factors is critical for location data to be representative of the population and lead to meaningful insights.

Q: The phrase “SDK data,” which you mentioned above, is significant when it comes to evaluating the quality of location data. What exactly does it refer to and why is it important to understand?

Location data can be collected in several ways, one of which is through a software development kit – an SDK. In layman’s terms, Cuebiq’s SDK is a line of code that our mobile app partners embed in their apps, which collects first-party data from anonymous users who opted-in to the location data collection. Through an SDK like Cuebiq’s, you know exactly where the data is coming from and can ensure users are providing consent to data collection. This is why SDKs are the recommended methodology to collect data that is high-scale, accurate and dense, and follows a forward-thinking privacy framework — all of which are necessary for quality location data.

Q: Measuring travelers’ physical visits seems to be the best way to close the loop for marketers in the travel vertical. Is that the case, and if so, how does dwell time factor in?

Yes, measuring visits is the best way for travel marketers to close the loop, since it enables them to understand whether their campaigns are actually driving consumers to locations or not. Dwell time is key for marketers to consider, since it tells the difference between real versus fake visits to a location. For example, one user location data point (or as we call it a “ping”) near a hotel does not mean that users actually vacationed there — they could have been just walking by. In order to determine whether or not anonymous users spent time at any given location, you need to consider how long they spent there. At Cuebiq, we verify all visits to locations using dwell time, to distinguish actual visits from non-relevant data points.

Q: User privacy is extremely important for brands and agencies, especially when it comes to leveraging location-based data. What should marketers keep in mind as they evaluate different location data partners?

User privacy has moral and ethical implications, which should be key drivers for all players in the ecosystem. But user privacy is also a business imperative for brands and agencies as they identify the data sets and data partners for their stacks. In fact, in today’s data-driven landscape, brand safety is no longer just about the environment in which ads run, it is also tied to the origin of the data that brands use for their initiatives. For this reason, it is vital that both brands and agencies be aware of and screen their partners’ data collection practices to ensure that they themselves are in a safe position.

When evaluating potential partners, marketers need to consider their approach to user privacy. Does the partner require user consent to collect location data, and enable users to opt out if they so choose? Is the partner transparent in how they’re using the data? Has the partner been certified by industry privacy organizations? These are some important questions to ask.

Q: How does the value of location data differ for brands who have physical locations versus those that do not?

Brands with a physical presence typically use location analytics to map and measure the real-world behaviors of their consumers and understand whether their campaigns are working. Take, for example, a grocery chain that runs an OOH campaign to drive consumers to their stores. Location data will enable them to measure if the consumers who saw those ads actually visited the stores.

For brands that don’t have a physical presence, location data can still provide a trove of insights. On a tactical level, it allows them to target consumers based on intent. For example, an online retailer can target consumers who shop at a brick-and-mortar competitor of theirs.  On a strategic level it can shed a light on consumers’ behaviors for a specific vertical or a set of competitors. Think of direct-to-consumer brands that may want to expand from e-commerce to a mixed model including brick and mortar, a trend that we see more and more today. By understanding offline consumer behaviors for their vertical or a specific set of competitors, these brands can expand their consumer knowledge beyond what happens online.

Q: What stands out about Cuebiq’s integration with Adelphic?

Viant and Cuebiq’s partnership is rooted in Viant’s commitment to bring clients the best solutions to drive their marketing efforts. Both Viant and Cuebiq are equipped to deliver actionable insights and measurement leveraging high-quality data. Additionally, Cuebiq’s forward-thinking privacy approach to collecting location insights provides clients with the precision and safeguards they desire as key integration benefits from our two worlds at their fingertips.

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