A common misconception in the industry is that incrementality only applies to verticals where customers visit the stores frequently (think QSR, gas stations, home DIY improvement, etc.). However, this could not be further from the truth.

Incrementality Is NOT Simply Pre/Post Exposure Testing

Let’s start with understanding what incrementality is NOT.

Many people mistakenly believe that measuring the effect of ad exposure on visitation can be calculated accurately by applying a pre/post-test. In other words, by looking at the number of visits a given person was making before the exposure and comparing that to the number of visits that same person made after exposure, you assume any difference in visits can be attributed to the advertising campaign. 

Pre/post testing has a number of methodological issues, but for a moment let’s only consider the utility of a pre/post-test in determining the effectiveness of ad exposure in verticals with low customer visit frequency (like auto-dealerships, tourist destinations, etc). Since most people do not go on holidays multiple times a month, or to the dealership enough times in a month, comparing visiting behavior before and after exposure might create a situation where we have nothing to compare behavior with! An approach that used pre/post testing would not be useful in these cases.

Cuebiq’s Incrementality Methodology Goes Deeper

In a nutshell, Cuebiq’s incrementality methodology works around this problem as follows: for every device in the exposed group we look at all the brands they visited in the 12 weeks prior to the campaign, and build a visit profile—for which is simply all the brands a person likes to visit. So, for every device that was exposed to the campaign, we have a series of brands that describe that person, creating a “persona”. Personas can vary widely from person to person. For example, think about the difference between people who only visit fast-food restaurants and bars (Persona A) and people who only visit parks and gyms (Persona B).

We then repeat this process to create personas for every device in both the control and exposed groups. From there, we can identify similar personas (Personas A for example) that exist in both groups. That is, we end up with devices in both the control and exposed group that are very similar to each other in terms of what brands they like (and by extension, their interests), except that one set of personas is exposed, and the other ones are not. The only difference between them is the advertising exposure.

See where this is going? By using machine learning we can predict visits to the POI of interest for Personas A in the exposed group, then Personas A in the control group, and link their visit history to their current visiting behavior. We then use sophisticated machine learning to create a mirror version of exposed Persona A that behaves as if they had never been exposed. This goes beyond a mere look-alike logic and even standard control-group methodologies: you’re comparing exposed devices to themselves, unexposed! 

The difference in visiting behavior between Persona A that was exposed and their mirror version had they not been exposed gives you the increase in predicted visits that happened because of the exposure – that is, the incremental visits!

Putting it All Together For Low-Frequency Verticals

Now let’s go back to our use case of verticals with very low visit frequency, like auto-dealerships and hotels. Remember: the problem with these verticals is that very few customers repeatedly visit an auto-dealership or a hotel throughout the duration of a campaign. 

With our methodology, repeated visit frequency by the same device doesn’t matter! Why? Remember that these personas are composed of many different devices. As long as there is at least ONE customer within that persona that visited a location at least ONCE (in both control and exposed groups), we can establish an average baseline of visitation for both control and exposed groups. Then, we use the same mirror technique to understand the average baseline of visits for the exposed group had they not been exposed.

See how this has nothing to do with how many times a specific person visited repeatedly? It’s all about having at least one device in each persona with a visit so we can establish baselines of visitation for both exposed and control groups, measure the difference, and determine incremental visits.

An Auto-Dealership Example

Let’s look at an example that simplifies our methodology for the purpose of illustration: an auto-dealership is running a campaign to promote people to visit their brick-and-mortar stores. You don’t usually visit these stores. However, all we need for our methodology to work is for you to visit sometime during the campaign.

• First, we create a Persona for you: “Persona A”
• Then, we find devices that look like you (Persona A) in our exposed group
• We also find devices that look like you (Persona A) in our control group

Imagine there are 100 devices that look like you in the exposed group, and 100 devices that look like you in the control group. Even though you only visited once during the campaign, we are able to see that, for example:

• Your look-alikes in the exposed group visited 5 times (so 5/100 or .05 visits)
• Your look-alikes in the control group visited only 2 times (so 2/100 or .02 visits). 

We then apply machine learning to create the mirror version of the exposed group (like we mentioned above), to calculate the incremental effect of ad exposure on devices in Persona A. In this case, the calculation would be something similar to .05 - .02 = .03 incremental visits – or, we can attribute 0.3 incremental visits to the auto-dealership to the ad exposed to devices in Persona A.

If we add all the incremental visits for all personas in the exposed groups across the whole campaign, we get the total number of incremental visits for all of the exposed groups!

So, as long as there are people in both the control and exposed groups that look like you (in terms of which brands you like to visit), we are perfectly able to determine incrementality by roughly following the logic we described above, even for verticals with very low visit frequency such as hotels, auto-dealerships, etc.

Pretty powerful isn’t it?

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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.

When it comes to location intelligence for the auto enterprise, there are countless ways to enhance your dealership at every level and knock out the competition.

In 2018, we commissioned a paper with 451 Research—Location Intelligence for Auto Marketers—in which we discovered that marketers in the automotive sector are more sensitive to the moves their competitors are making than any other vertical surveyed. In fact, 58% of those who said they are likely to increase their use of mobility data for marketing cited “pressure from competitors” as a driver. Mobility data can help auto marketers not only better their own marketing strategies, but also ensure the competition does not steal their thunder.

Mobility data can be applied across many departments within an auto enterprise, including corporate marketing, media and agency partners, dealership operations and service, sales and business development, and finance/operations/strategy. With the help of our platform, Cuebiq Workbench, each of these auto enterprise departments can leverage data-driven insights to seamlessly map consumers’ offline car-shopping journey. Equipped with these insights, companies can provide better customer experiences, improve media and marketing performance, increase revenue, and boost efficiencies. So what are you waiting for?

Corporate Marketing

Without marketing, your product has zero chance of being discovered and desired. Location intelligence can help marketing departments engage auto consumers in a variety of strategic ways.

Co-Branding + Sponsorship Opportunities

Auto marketers can analyze offline consumer behaviors, visitation patterns, and purchase intent to evaluate new partnership opportunities by leveraging location analytics to see the relationship between their visitors and other brands. This can help them identify opportunities that resonate with their target audience.

Loyalty Program Development

Through the use of mobility data, marketers can gain a window into their consumers’ cross-shopping activities including brand affinity, visit frequency, dwell time, and more. Not only can this help them improve their loyalty programs, but it can also guide segmentation strategies.

Consumer Persona Building

By analyzing offline consumer behaviors such as brand affinity and loyalty, auto marketers can more effectively build their buyer personas and improve their marketing strategies and communication efforts.

Competitive Intelligence

Moving on to analyzing the competition — marketers can build conquesting and day-parting communication efforts based on consumer footfall to grow market share and marketing ROI.

Media / Agency Partners

Media and agency partners can help brands take their marketing to the next level through data-driven and consumer-centric insights.

Strategic Planning

Strategy is the key to success! Media and agency partners can identify and test new audiences and media-planning strategies to evaluate publishers, creative messaging, content platforms, media mix, and cross-channel investments.

Audience Targeting

After mapping consumers’ offline journey and path to purchase, these partners can activate geo-behavioral audience segments like branded audiences, predictive audiences (based on churn), seasonal, lifestyle, and more.

Cross-Channel Spend Optimization

They can leverage real-time, daily visit, and uplift metrics to optimize their media spend by creative, publisher, and geo for campaigns already in-flight. This will result in better media decisions and investments.

Cross-Channel Measurement

To prove ROI, media and agency partners can measure cross-channel advertising performance on digital, TV, OOH, and radio.

Dealership Operations & Services

It’s essential to understand how vendors and consumers are engaging at the dealership level to improve dealership operations strategies and keep customers happy.

Enhanced Dealership & Service Experience

To ensure the most optimal consumer experience, dealership operations and service professionals need to understand the busiest time of day for their dealerships, the time of day consumers prefer to visit locations, and how much time they actually spend “on lot.” These location-based data points will prove instrumental in enhancing service center experiences.

Model Demand Forecasting

In addition, footfall trends can help with building proactive models and service part demand infrastructures & forecasts.

Finance / Operations / Strategy

Finance, operations, and strategy departments can accelerate growth and reduce costs by optimizing operations with real-time, data-driven decisions.

Trade & Market Area Analysis

They can analyze state, DMA, and dealership-level performance by a variety of location-powered KPIs unique to location intelligence.

Revenue Forecasting

Real-time consumer footfall data can help with forecasting brand sales, revenue, foot traffic, visitation trends, and more. These revenue predictions are key to staying one step ahead.

Sales / Business Development

Finally, sales and business development teams can efficiently pinpoint undiscovered sales opportunities using location intelligence.

Corporate Social Responsibility

These departments can leverage location data to support nonprofit organizations and universities in their efforts to drive innovation around the globe by solving real-world problems such as natural disaster evacuation planning.

Differentiate Dealership Brands

Sales teams can also use location data to enhance their dealership sales strategies at the geographic and demographic consumer level.

As evident, location data can help solve many automotive organizational needs. Applying the strategies we discussed across an auto enterprise will lead to better, more data-driven decisions that will strengthen the organization’s retention rate and help them beat the competition.

To learn how location intelligence can be applied further, download our Location Intelligence for the Auto Enterprise infographic.

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Automotive marketers are constantly looking for new ways to break down some of the most frustrating barriers to buying a car. Reducing consumer friction is vital,  and location data can help tackle this problem, as it provides insights about consumer behaviors, competitive intelligence, and market trends.

Here are four key takeaways for automotive marketers using location data:

1. Gain Visibility into Campaigns Through Location Data

In 2018, we commissioned a study with 451 Research on automotive marketers and found that just under half (45%) of automotive respondents cited lack of data or visibility into campaigns as a key challenge in executing on their priorities. This suggests there is a strong need for insights into performance, in order to have an edge over competitors.

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Fortunately, location data can provide these insights by enabling marketers to understand which aspects of their marketing and promotion actually drive real-world behaviors, like store or dealership visits.

For example, an auto marketer can use footfall attribution to understand whether a certain addressable TV campaign actually drove consumers to their dealership or not, and then refine that campaign accordingly.

2. Analyze Consumer Behavior Using Footfall Trends

Location data can also help marketers glean critical insights about their target consumers. Our study found that 61% of automotive marketers are likely to use location data to analyze customer behavior at dealerships. Without understanding exactly who your buyers are, you can’t sell cars to them, which is why understanding customer behavior is a top priority.

It’s essential to be aware of how long consumers spend in your dealership, where they go before or after, and what you can do to reel them into your dealership. By measuring these footfall trends, automotive marketers can use location data to win over customers and beat the competition.

3. Establish Brand Loyalty and Activate Audiences

A majority of automotive respondents (55%) cited brand loyalty as a key metric for their marketing departments, higher than any other KPI. For purchases that are as personal, expensive, and long-term as a car, understanding how to influence brand loyalty is essential.

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Location intelligence not only gives insight into how consumer brand loyalty differs within a vertical, but it can also reveal directly actionable audiences marketers can target within a campaign. In this way, marketers can activate audiences based on loyalty levels to build a more targeted strategy against specific competitors.

4. Apply Location Intelligence to Marketing Strategies

Finally, while automotive marketers may be tempted to apply location intelligence to a range of problems, they would be better off starting with a single application and expanding gradually. Demonstrable results could make it easier for marketers to pull in resources to support programs that use data in more contexts.

Location data can drastically change marketing strategies and executions for automotive marketers sealing the deal in car sales. By focusing on one single aspect, marketers can successfully see improvement in that area before applying the value of location data to other sectors of their company.

To learn how to further use location intelligence, download the full 451 Research report or book a demo.

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Just like buying a house, buying a car is one of the most important decisions a person will make — not to mention a very expensive one. Much like how customers weigh their options when it comes to a car brand, features, and type of vehicle, automotive marketers must do the same when researching and challenging their competition. While there are many factors that can make a huge difference in strengthening automotive marketing, it ultimately comes down to one thing: the power of location data.

Our recent study with 451 Research found that automotive firms are beginning to leverage location intelligence to understand real-world consumer behavior. Through location intelligence, automotive marketers can work toward building brand loyalty, increasing customer engagement, and ultimately boosting revenue by connecting online with offline.

Here are three daring ways to drive customers straight to your dealership:

Crush the Competition

According to our study, marketers in the automotive sector are more sensitive to the moves their competitors are making than any other vertical surveyed. In other words, leveraging competitive intelligence is key in the automotive vertical.

To crush the competition, auto marketers can leverage aggregated anonymous data to understand overlaps between fans of particular car brands and other kinds of retailers, financial services providers, or gasoline brands, among others. This opens the door to pairing proximity marketing to visitors of those kinds of outlets that are near competitive dealerships.

Competitive analysis and location intelligence go hand in hand because when you continuously keep tabs on who sells a similar product to yours and where your customers are gravitating, you will always stay one step ahead of the game.

Use Footfall Patterns and Promotions to Your Advantage

Automotive marketers differ from their peers in other retail environments in several key respects. Many automotive sellers face the hurdle of getting customers to travel physically to their dealership locations before making a sale, which explains the need and emphasis on in-store visits.

In the automotive industry, seeing a car in person is what seals the deal. As follows, 61% of auto marketers cite the need for integrating online and offline promotions, while 52% are significantly more likely to be sending promotions when customers enter a geofence.

In the same vein, 53% are highly familiar with using footfall trends to understand visits compared to competitors. These insights further highlight how invaluable location intelligence is in learning both how to reel in customers, as well as how to engage them to beat out the competition.

Make Your Marketing Matter

Using location intelligence to inform your marketing strategies can help you not only reach your target audience, but ensure your messaging resonates with them. Auto dealers are finding that location data can help maximize the chances that marketing messages will get through to the right potential buyers, pulling them in with relevant pitches and allowing them to stand out from their competitors.

Location data can also help you measure your marketing campaigns. In our study, auto marketers gave high scores for location data applications such as optimizing multichannel campaigns while in flight and integrating outdoor advertising with mobile and email programs to drive visits.

Overall, as an auto marketer, you are not just selling a car; you are selling a brand. You need to establish strong branding and loyalty in your marketing campaigns to distinguish yourself from competitors.

Finally, automotive marketers see efforts in employing location data as part of a journey that is ongoing, and they’re looking to increase usage of location data. 84% expect the role of competitive intelligence in their marketing strategies to increase over the next two years. This survey suggests that within the automotive vertical, location intelligence will soon become instrumental in measuring how well marketing drives people into dealerships.

To continue staying ahead of the curve when it comes to location intelligence, download the full 451 Research report.

The post 3 Ways Auto Marketers Can Drive Consumers Straight to the Dealership appeared first on Cuebiq.

“Your brand is what people say about you when you are not in the room.” - Jeff Bezos

The marketers and advertisers that attended JD Power AMR this year were in for a serious treat. JD Power put together a stellar lineup of speakers and an interesting array of content. From artificial intelligence and messaging techniques to in-store experience and the changes the industry needs to make moving forward, JD Power was full of powerful thought leadership. Here are a few key takeaways:

1. Marketers Need to Close the Online-Offline Loop

With the ability to search any topic from their pockets, consumers are taking their time researching purchases online. On average, auto consumers spend 16 weeks researching a car purchase before setting foot in a dealership. Coupled with the increasing adoption of ad blockers, marketers have a large obstacle to overcome to close the online to offline loop. Marketers must figure out when someone is in-market without much knowledge about them. To come out on top brands must find the tools that fit their marketing strategies, and provide the most accurate campaign reporting to garner ROI and revenue.

2. Marketers Must Learn to Engage Consumers With No Brand Loyalty

Younger generations are not brand loyal, they take months to do research, they are averse to advertising, they use ad blockers and incognito settings, and they typically begin their car search with no more than two cars in mind. Because of this, auto marketers have an interesting challenge in front of them: figuring out how to place relevant advertisements in front of these consumers without much insight.

To get on the “short list” of these younger generation consumers, brands must own their voices, be insightful by leading messaging with value and insights, and be anticipatory but unselfish. These younger generations abhore “fake”, “self-serving” advertisements and they will not give them any attention. Thoughtful, targeted advertisements and accurate campaign measurement have never been more important.

3. Brands Must Update the In-Store Experience

The auto in-store experience has remained relatively unchanged for far too long and it needs to innovate now. Incredibly, the in-store experience in the auto industry can last up to 5.5 hours, 1.5 of them spent solely filling out paperwork. AI and AR experiences could change the face of the in-store experience.

What if you could answer a few questions about style and preferences and a computer showed you side-by-side comparisons of cars you would like? What if you could personalize a car from top to bottom in 3D? The brands that innovate and gear in-store experiences to customer satisfaction by anticipating frustration points and customer needs will be the brands that succeed.

At the conclusion of the discussions and presentations, it was clear the auto industry has a lot of room for growth. It was also clear, however, that with the use of new technologies and creative innovation the industry can thrive. As the auto marketers search for revenue among a tech-savvy and advertising averse audience strong branding, thoughtful messaging, and quality insights will generate coveted ROI.

Read more insights and recommendations from the Cuebiq team. Visit our blog for the latest updates.

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