Comprehensive, High-Fidelity Data

Replica ingests dozens of input data sources, and transforms them into the calibrated, validated outputs that our customers need. Every day,  we turn billions of data points into a holistic picture of mobility, land use, people, and economic activity — and the ways they interact. This gives our customers unprecedented insights into a world that’s constantly changing.

Insightful, Easy-to-Use Tooling

Having data you can trust is necessary, but it’s not enough. Data is only useful to the extent it turns knowledge into action, and unlocks better decision making. That’s why Replica provides more than just a data table or a static report. The platform offers custom tooling and applications so whether you’re creating a safety action plan or undertaking a corridor analysis, assessing the impact of construction road closures or weighing the equity impact of transit modifications, you can get insights faster.

The Replica Platform provides customers with a single source of data to support a wide range of analyses and use cases.

With hyper-detailed seasonal datasets, near real-time weekly datasets for operational monitoring, and far more than just  traditional mobility metrics, Replica has you covered. See the whole data catalog here.

AADT Origin-Destination flows Vehicle miles traveled (VMTs) Network speeds and volumes Turning-movement counts Work-from home % Weekly ODs and trip volumes    Parcel-level land use    EV Charging demand by neighborhood    Consumer spending by categories like retail and restaurants    Network link volumes overall or for specific modes, trip purposes, and demographics    Disaggregate trip tables with all modes, purposes, and routes    Commercial freight trip data by vehicle type, routes, and time of day    Demand and travel patterns for potential transit corridors    Visitor trip summary statistics and disaggregate data    Changes in visits for specific days and times    Peak hours of travel based on mode, corridor, demographics, and trip types    Vulnerable demographics (age, sex, income) on specific modes across the network    Economic recovery metrics for specific neighborhoods pre-/during-/post- pandemic    Vulnerable community travel patterns for electric charging infrastructure prioritization    Residential VMT based on O/Ds, trip characteristics, and demographics    Mode split by time period, geography, and demographic characteristics    Priority corridors for bike and ped infrastructure    Average trip times and distances for specific populations (e.g. income, sex, race/ethnicity)    Network links with high bike/ped safety risk    Transit profiles based on peak hour flows, trip purposes, and transit rider demographics    Accessibility of land uses within a given geography    Consumer spending O-D flows   Station/development access by mode
AADT Origin-Destination flows Vehicle miles traveled (VMTs) Network speeds and volumes Turning-movement counts Work-from home % Weekly ODs and trip volumes    Parcel-level land use    EV Charging demand by neighborhood    Consumer spending by categories like retail and restaurants    Network link volumes overall or for specific modes, trip purposes, and demographics    Disaggregate trip tables with all modes, purposes, and routes    Commercial freight trip data by vehicle type, routes, and time of day    Demand and travel patterns for potential transit corridors    Visitor trip summary statistics and disaggregate data    Changes in visits for specific days and times    Peak hours of travel based on mode, corridor, demographics, and trip types    Vulnerable demographics (age, sex, income) on specific modes across the network    Economic recovery metrics for specific neighborhoods pre-/during-/post- pandemic    Vulnerable community travel patterns for electric charging infrastructure prioritization    Residential VMT based on O/Ds, trip characteristics, and demographics    Mode split by time period, geography, and demographic characteristics    Priority corridors for bike and ped infrastructure    Average trip times and distances for specific populations (e.g. income, sex, race/ethnicity)    Network links with high bike/ped safety risk    Transit profiles based on peak hour flows, trip purposes, and transit rider demographics    Accessibility of land uses within a given geography    Consumer spending O-D flows   Station/development access by mode

Customers are looking for answers, not just data

We’ve built a suite of tooling and applications that make it easy to derive insight, find the missing variable, and do the analysis needed to make the  right decision. See the full set of applications here.

Changing the Way We Forecast the Future

With Replica Scenario, customers can simulate the impact of changes to the  road network, population growth, employment growth, and land use changes. Unlike traditional models, this self service  approach enables rapid, cost-effective, and iterative forecast planning. With Scenario, you can:

  • Identify Traffic Diversion Patterns: Find alternative routes with ease and understand congestion impacts.
  • Estimate Impacts on Daily Travel: Quantify changes in travel volumes, trip distances, mode split, and more.
  • Identify Future Potential Congestion Points of Failure: Measure changes in network volumes and changes in demand to capacity ratio.
  • Understand Socio-Economic Impacts: Measure how future growth improves  (or hurts) equitable access to jobs and essential services.
  • Quantify Changes in Public Transit Usage: Measure and identify areas  with highest future transit demand.
  • Assess Environmental Impact: Understand changes in vehicle miles traveled (VMT) and emissions.

We’re ready when you are

Replica is a user-friendly web-based platform, with on-demand data covering all 50 states. Reach out today for immediate access.

Learn More?

Contact us to learn how Replica can help bring insights like these to your organization.

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Insights

Replica In Action

Mapping EV VMT by county
Mapping EV VMT by County

Replica data can identify where around the country EV adoption is strongest, and then analyze the characteristics
of EV-specific trips.

The country has only begun to deploy the billions of dollars allocated to investing in EV charging infrastructure across the country, and Replica is helping agencies and private companies around the country figure out how to most effectively deploy those investments to best serve local populations.

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Mapping EV VMT by County

Replica data can identify where around the country EV adoption is strongest, and then analyze the characteristics
of EV-specific trips.

The country has only begun to deploy the billions of dollars allocated to investing in EV charging infrastructure across the country, and Replica is helping agencies and private companies around the country figure out how to most effectively deploy those investments to best serve local populations.

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Mapping EV VMT by county
Measuring the home team’s economic impact
Measuring the home team’s economic impact

With Replica Patterns, it’s possible to quantify the increase in visits due to events, policy changes, and initiatives. We analyzed how Orioles home games impacted the activation of the Inner Harbor shopping + restaurant corridor. We analyzed the activity in Inner Harbor on Summer ‘23 Tuesday and Wednesday nights when the Orioles were home, compared to nights when there wasn’t a game.

We see a 27% increase in shops and restaurants visits to the Inner Harbor on game Tuesdays and Wednesdays. Combining this insight with Replica’s consumer spend data, we can estimate that these games generate hundreds of thousands of dollars of extra spending each game night, in just one square mile.

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Measuring the home team’s economic impact

With Replica Patterns, it’s possible to quantify the increase in visits due to events, policy changes, and initiatives. We analyzed how Orioles home games impacted the activation of the Inner Harbor shopping + restaurant corridor. We analyzed the activity in Inner Harbor on Summer ‘23 Tuesday and Wednesday nights when the Orioles were home, compared to nights when there wasn’t a game.

We see a 27% increase in shops and restaurants visits to the Inner Harbor on game Tuesdays and Wednesdays. Combining this insight with Replica’s consumer spend data, we can estimate that these games generate hundreds of thousands of dollars of extra spending each game night, in just one square mile.

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Measuring the home team’s economic impact
Analyzing a custom walkshed for transit
Analyzing a custom walkshed for transit ridership

Replica data can help draw walksheds for proposed and existing transit routes and stops to identify potential ridership pools and trip characteristics of those within walking distance of the proposed facilities.

METRORapid is Houston Metro’s Bus Rapid Transit system and is planning the University Corridor Project, a key component of the METRONext Plan, which will combine light rail and bus elements along a 25.3 mile corridor. The corridor provides access to four colleges and universities, and Replica data shows how students and others will benefit from this proposed service.

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Analyzing a custom walkshed for transit ridership

Replica data can help draw walksheds for proposed and existing transit routes and stops to identify potential ridership pools and trip characteristics of those within walking distance of the proposed facilities.

METRORapid is Houston Metro’s Bus Rapid Transit system and is planning the University Corridor Project, a key component of the METRONext Plan, which will combine light rail and bus elements along a 25.3 mile corridor. The corridor provides access to four colleges and universities, and Replica data shows how students and others will benefit from this proposed service.

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Analyzing a custom walkshed for transit
TTI validates Replica’s AADT data
Texas A&M Transportation Institute (TTI) validates Replica’s Average Annual Daily Traffic (AADT) data

TTI's compared AADT and hourly volumes estimates from both Replica and Inrix, against observed data collected by TxDOT’s permanent count stations across the state.

The analysis found a high correlation between Replica’s AADT dataset and the observed counts, evidenced by a Mean Absolute Percentage Error (MAPE) of 12.1%. Similarly, the hourly volume estimates showed a strong correlation, with a MAPE of 23.7%.

TTI’s findings underscore the close alignment between Replica's AADT and hourly volume estimates, and TxDOT’s observed data. This level of accuracy is crucial, especially considering the challenges State Departments of Transportation (DOTs) face in counting traffic across every road segment.

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Texas A&M Transportation Institute (TTI) validates Replica’s Average Annual Daily Traffic (AADT) data

TTI's compared AADT and hourly volumes estimates from both Replica and Inrix, against observed data collected by TxDOT’s permanent count stations across the state.

The analysis found a high correlation between Replica’s AADT dataset and the observed counts, evidenced by a Mean Absolute Percentage Error (MAPE) of 12.1%. Similarly, the hourly volume estimates showed a strong correlation, with a MAPE of 23.7%.

TTI’s findings underscore the close alignment between Replica's AADT and hourly volume estimates, and TxDOT’s observed data. This level of accuracy is crucial, especially considering the challenges State Departments of Transportation (DOTs) face in counting traffic across every road segment.

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TTI validates Replica’s AADT data
Just how bad is George Washington Bridge Traffic?
Just how bad is George Washington Bridge traffic?

We’ve visualized typical speeds approaching the George Washington Bridge in New York from both the North and South. Serious congestion in the PM peak is clear in both directions, while not surprisingly, AM traffic is much worse coming into NYC, as commuters stream into Manhattan.

With Replica’s Network Speeds Viewer you can instantly obtain similar data for traffic choke points in your jurisdiction.

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Just how bad is George Washington Bridge traffic?

We’ve visualized typical speeds approaching the George Washington Bridge in New York from both the North and South. Serious congestion in the PM peak is clear in both directions, while not surprisingly, AM traffic is much worse coming into NYC, as commuters stream into Manhattan.

With Replica’s Network Speeds Viewer you can instantly obtain similar data for traffic choke points in your jurisdiction.

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Just how bad is George Washington Bridge Traffic?
Mapping Population Density across the 24 Hour Day
Mapping population density across the 24 hour day

Even in the post-pandemic, work from home world, the flow of commuters have a major impact on our cities.

With Replica’s minute by minute data, we can look at the population density at any specific point in time.

In this visualization, we explored the flow of people in and out of New York City in a typical weekday in 2023.

In NYC, we see a noticeable flattening of the AM/PM peak – people come in later and leave earlier, creating a less extreme, but longer rush hour crush.

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Mapping population density across the 24 hour day

Even in the post-pandemic, work from home world, the flow of commuters have a major impact on our cities.

With Replica’s minute by minute data, we can look at the population density at any specific point in time.

In this visualization, we explored the flow of people in and out of New York City in a typical weekday in 2023.

In NYC, we see a noticeable flattening of the AM/PM peak – people come in later and leave earlier, creating a less extreme, but longer rush hour crush.

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Mapping Population Density across the 24 Hour Day
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