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What DOes
stratodem analytics do? 

StratoDem Analytics helps investors, developers and advisory firms in multifamily residential to make investment, development, disposition and marketing decisions faster, earlier and better by building predictive models on massive local-level economic and demographic data.

Why StratoDem Analytics

segmentation GRANULARITY

StratoDem Analytics map showing Millennials households ages 25 to 34 with net worth of $100,000+ in Seattle MSA.png

Examine hyper-localized markets by income, net worth (up to $2.5 million or higher), for age 20-24, 25-29, 30-34 or any other age cohort, which no legacy-generation data provider can generate accurately at our level of granularity.

This granularity and accuracy offers significant analysis advantages for student housing, where the average age of entry is in the twenties, and high-end multifamily, which requires higher levels of net worth and income than tracked by legacy-generation data providers.

Nowcasting VITAL SIGNS

StratoDem Analytics Residential Analyst Memo featuring Millennials fist-time homebuyers, population and income in Denver.png

Get the most accurate and up-to-date economic and demographic forecasts using the StratoDem Analytics engine nowcasts.

When the current generation of data sources provide 2018 demographic estimates, they rely on Census Bureau data that was actually collected on average four years ago. At StratoDem Analytics, data science enables accurate nowcast data as of last month. That typically provides clients one to four years head start in understanding demand shifts in the markets.


StratoDem Analytics heat map showing location quotient of millennials in Seattle.gif

Model back-testing shows that StratoDem Analytics’ forecasts are up to 35% more accurate than legacy-generation data estimates on household wealth, and up to 10x more accurate at forecasting demographic changes.

The StratoDem Analytics engine not only ingests more than 200 data sets from dozens of governmental sources, but it is also the nation’s first and only system that connects all that data to fuel advanced real estate analysis. As a result, only StratoDem Analytics can run massively multivariate analyses, Bayesian hierarchical modeling and other machine-learning techniques to understand where the underlying state of real estate demand factors is today and where it is most likely to shift over the next five years.


StratoDem Analytics Blaise ML analysis of high-income millennials in a multifamily residential portfolio.gif

Meet Blaise ML by StratoDem Analytics, our machine learning analyst that is designed to provide clients desktop access to massive computational analysis for portfolio-level and property-level market analysis and forecasting. On large portfolios with hundreds of properties, Blaise provides clients desktop access to answers for questions about multifamily property investment, development and disposition, predicting which targets will have the strongest or weakest demand-growth outlook.

Answer questions such as:
- Which properties will see the strongest growth in high-income Millennials?
- Which properties will see the largest decline in 25-to-34 population? 
- Where is demand-curve growth most likely to outstrip supply-curve growth?


StratoDem Analytics Market Insights on millennials ages 25-39 with household income of $25,000 to $75,000 in Seattle.gif

Identify what makes submarkets unique. For individual or multiple market areas, Blaise ML by StratoDem Analytics answers questions such as "Which net worth segments of my catchment area are likely to grow faster than the broad metro area?", giving you shareable written analysis, maps, charts and downloadable versions of the underlying data.

Use suggested questions to ask Blaise about markets and customize across segments and time periods, or create new questions. Blaise deployes machine learning and natural language generation to build the answers to questions, leaving StratoDem Analytics clients more time to focus on optimizing deals and strategy.

One platform for Multifamily portfolio analysis

1. Compare future demand growth across all properties

StratoDem Analytics Blaise ML analysis of high-income millennials in a multifamily residential portfolio.gif

Upload a portfolio of property locations and compare historical, current and forecasted market conditions. 

For example: After uploading 700+ apartment community properties, Blaise helps to frame the questions that matter by geographic region or set of properties - dramatically speeding up the research and due diligence process.


2. Identify top growth markets

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Get a deeper analysis of selected set of top- or bottom-performing properties, powered by Blaise and the StratoDem Analytics engine.

For example: Blaise analyzes and ranks your portfolio based on key trends such as:
- Divergence of growth rates for household income or net worth, picking out properties which have the strongest market dynamics
- Shifts in growth, up or down, helping clients to track which markets are likeliest to be undervalued or overvalued

3. Dive deep into top properties

StratoDem Analytics Market Insights on a multifamily residential property.gif

Drill down into the top- or bottom-performing properties you pull with Blaise. 

For example: After Blaise identifies a top-ranking property, it can direct you to the StratoDem Analytics Market Insights application, where you can break down the market further into granular submarkets or segments by age, household income, net worth, home value, educational attainment, etc.
Blaise uses maps, charts, heatmaps and written analysis to transform raw data from the StratoDem Analytics engine into easy-to-share content (and data exports) for segments such as households 20 to 34 years old with household income between $25,000 and $75,000.


Portfolio Insights ranking of markets across the US with the highest median household income in 2018

Upload your investment portfolio and create reports. Download the data in Excel format and use it in your presentation.

Compare your investment portfolio markets performance with

  • The US as a whole

  • The largest private equity homeowner portfolio

  • The largest private equity home builder portfolio

  • The largest senior living operator portfolio

  • The largest senior living REIT portfolio

  • The largest private equity senior living portfolio

and many other real estate portfolios that StratoDem Analytics now tracks.

Ready to get in touch?  

What Our clients say

StratoDem Analytics client: Real estate private equity
StratoDem Analytics client - National Real Estate Developer
StratoDem Analytics client - Real Estate Investment Trust
StratoDem Analytics client - Residential Builder

Let's get started


What core services does StratoDem Analytics provide?

The core StratoDem Analytics product is organization-wide access to a powerful data-science platform that allows clients to analyze historical trends, track current developments with our nowcasts, and build confidence in future market performance with forecasts of demographics and economics for any market or submarket across the US.

We offer access to an ecosystem of data science products including:

  • Portfolio Analysis Engine to power national- and portfolio-level analysis for questions such as "Which market areas will see the strongest growth of income-qualified Millennials over the next three years?"
  • Market Insights, a hyper-granular segmentation analysis tool to dive deep into household dynamics for submarkets
  • Residential Developer Analyst, Blaise ML, our Machine Learning analyst system to write demand-side housing market analyses for first-time, trade-up and empty-nester homebuyers for every market and submarket across the US
  • Seniors Housing Analyst, Blaise ML, our Machine Learning analyst system to write demand-side and supply-side senior housing market analyses for 20 to 34 Millennials product for every market and submarket across the US

Let's take the question from above to demonstrate the power of the ecosystem:

  • Ask the Portfolio Analysis Engine by typing in the question, "Which market areas will see the strongest growth of income-qualified senior households over the next three years?"
  • The StratoDem Analytics analyst will analyze all properties or markets in the portfolio definition and return an answer like "Your property to the north of Boston, MA will add 5,320 young adults ages 20 to 39 with at least $100,000 in household net worth over the next five years, good for a +17.8% growth rate."
  • Then, dive deeper into that market in the Market Insights application and analyze submarket-level demographics and economics for detailed analysis of segment growth rates between 2005 and 2025.
  • To finish the analysis, open an analytical memo written by Blaise ML in the Residential Developer Analyst application.

How do I use the StratoDem Analytics Platform?

StratoDem Analytics has developed multiple independent applications, in addition to client-specific semi-custom deliveries:

  • Market Insights. Report covering vital economic and demographic metrics using the most current market analysis and our industry-leading forecast
  • Residential Developer Analyst. StratoDem Analytics Blaise ML, a Machine Learning analyst system writes a demand-side analysis covering crucial economic and demographic forces shaping a market area, specific to homebuilding and residential development
  • Senior Housing Analyst. Blaise ML analyzes supply-side and demand-side dynamics for senior housing across a national portfolio
  • Portfolio Analysis Engine. The engine can assess the current/past/future market condition for properties in your portfolio, and your competitors' portfolios, identify the best performing and the worst performing properties based on the market five-year outlook

Included with access to each of our platforms are the following complimentary services:

  • Data download. Download data on a single market or a portfolio of markets (bulk download) in a single Excel file
  • Data Upload. Work with us on the type of data you would like to integrate (supply-side metrics, for example) and we will analyze and map competitor locations against demand-side factors
  • Onboarding for your whole team. Our team will walk through example use cases during an initial onboarding period for all users. We also open up access to our knowledge base for tutorials and hints.
  • Technical support throughout your subscription period.

What can you tell me about pricing?

Pricing depends on a number of factors, including geographic coverage, level of customization/build time, license terms, and segment coverage.

Please use this page to learn more about pricing.

Can StratoDem Analytics develop additional analyses or applications that meet my needs?

Yes. StratoDem Analytics frequently builds what we call semi-custom deliveries, where we do some of the following for our clients:

  • Build custom dashboards to track an existing portfolio of properties for investors or developers
  • Create new data and forecasts for topics ranging from insurance coverage to household income broken down by source of income
  • Rebuild already existing analysis pipelines and technological stacks of advisory services firms to replace them with faster deliveries, better design, and more accurate data

Which markets does StratoDem Analytics cover?

StratoDem Analytics provides complete coverage for the entire US (except some remote regions of Alaska), including:

  • 400+ metros and metropolitan divisions
  • 3,000+ counties
  • 30,000+ zip codes
  • 70,000+ census tracts; for example, Boston, MSA has over 900 census tracts that we track.

Which metrics does StratoDem Analytics forecast?

StratoDem Analytics provides nowcasts and forecasts for critical economic and demographic metrics, including:

  • Local market economic growth (think GDP for counties and metros)
  • Alpha and beta, our proprietary estimates breaking down the sustainability and volatility of growth patterns for markets and industry segments
  • Population by age, race or ethnicity, educational attainment level
  • Household income by age, broken down by the source of income, such as:
    • Wage and salary income
    • Income from interest, dividends and rental income
    • Income from retirement savings, including pensions and annuities
    • Social security
  • Household net worth by age
  • Home values by age and/or by household income
  • Homeownership rates by age of householder
  • Housing costs for homeowners and renters
  • Insurance coverage by age of householder

This is just a starting point for what StratoDem Analytics provides for clients, and we also frequently add, build, or integrate new data sets for clients during the initial on-boarding process or as more comprehensive semi-custom builds.

Don't see something you need on the list above?

We may already have it, but we also frequently add, build, or integrate new data sets for clients during the initial onboarding process.

Can StratoDem Analytics analyze all markets at once?

Yes. Our Portfolio Analysis Engine can answer questions about metros or rank performance across all properties in a portfolio. Our machine-learning-powered analysts provide desktop access for you to ask questions or pull market scorecards for any market of interest.

How does StratoDem Analytics handle segmentation?

StratoDem Analytics can help clients slice and dice by age, income, net worth, and a number of other factors in combination with each other (e.g., households age 80+ meeting specific levels of retirement income, net worth, home value, insurance coverage, etc.). Then StratoDem Analytics can map them by Census tract or generate segmentation heatmaps to quickly identify segments with higher or lower concentration than the US or a comparison market. One way we analyze the data is through a location quotient.

A location quotient is the relative index of a segment's concentration in one market compared to another market. (For example, if households 20 to 34 years old with $200,000 or more in household income living in Dallas-Plano-Irving, TX MSA have a location quotient of 6.65 relative to the U.S., then the percentage of households in that segment in Dallas-Plano-Irving, TX MSA is 6.65 times greater than the percentage of households in that segment nationally.)

What is "nowcasting"?

Nowcasting is the prediction of the present state of data before it is released by the Federal governmental statistical agencies.

Example: StratoDem Analytics can predict 2017 regional GDP numbers (Gross Metropolitan Product or GMP) in January 2018, when the Bureau of Economic Analysis will not release the 2017 data until November 2018. The Goldman Sachs Growth Tracker and the Federal Reserve Bank of Atlanta GDPNow deploy similar methods for national growth estimates, although only StratoDem Analytics can release this data at local-market level instead of national level.

Why does it matter?

Every data set is released on a lag. For example: The 2016 American Community Survey population data is released by the US Census Bureau at the end of 2017. 2016 county-level income data is released by the US Bureau of Labor Statistics at the end of 2017. Household net worth data is released by the Federal Reserve Bank once every three years. Nowcasting creates accurate estimates of where that data will be before it is released, giving clients dramatic leads in understanding local market conditions before competitors—providing true competitive advantage.

What is Bayesian statistics?

Bayesian modeling is an approach to statistics that uses the mathematics of probability to combine data with prior information.

Why use Bayesian modeling? Bayesian models drive inferences which are more precise than would be obtained by either of those sources of information alone. StratoDem Analytics uses Bayesian modeling to combine hundreds of data sets at varying frequencies and geographic levels in a statistically rigorous, robust way.

As one example, the StratoDem Analytics engine builds its core population forecasts using hierarchical Bayesian time-series modeling with data from national, state, metro, county, census tract data (and more!).

The downside of Bayesian modeling? The models typically come at extremely high computational cost, which is why complex implementations are only now becoming possible in this era of scalable data science.