Welcome to the StratoDem Analytics Frequently Asked Questions page. After working through issues with many of the largest private equity funds, REITs, operators and developers, we've noticed that some questions just come up repeatedly!
Here you can find answers to the most frequently asked questions about StratoDem Analytics, data science and our services. Questions are grouped by topic area, from general questions about the company and our clients to more specific questions about methodologies and products.
If we missed including your question, please feel to ask your question on contact us page, and we'll typically send an answer to your question within 24 hours.
What is StratoDem Analytics?
StratoDem Analytics is a Boston-based data science firm deploying advanced statistical methodology and machine learning to deliver geographic market intelligence for investors, developers, operators and advisory services clients in the real estate sector.
What does StratoDem Analytics do?
StratoDem Analytics helps clients to prepare for economic and demographic forces shaping market outcomes by building predictive models on massive economic and demographic data.
We’re partnering with industry leaders, investors and real estate developers to help them make decisions faster, earlier and better.
How does StratoDem Analytics do its analysis?
After 15 years of strategy, research and predictive analytics work, the StratoDem Analytics founders StratoDem Analytics spent 18 months painstakingly engineering data pipelines for 200+ governmental data feeds, deploying machine learning to identify patterns that humans simply cannot see, developing statistically rigorous models and algorithms that recalculate instantaneously with every new data feed, then testing and back-testing the outputs.
We rely on three pillars for modeling and analysis:
- Bayesian hierarchical modeling, which allows us to integrate more data, more accurately, and build never-before-created data, like household net worth for wealthy households or ages 85+
- Continuous back-testing, so that each new data or model update is rigorously validated out of sample before we push our industry-leading economic and demographic nowcasts and forecasts to our clients
- Data pipeline engineering, giving the StratoDem Analytics team the ability to deploy semi-custom data science deliveries to clients better and faster than anyone else on the market
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 senior households 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 55+ active adult and senior living 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 machine-learning-powered 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 1,322 adults ages 80+ with at least $25,000 in household income 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 Senior Housing 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
Who are your clients?
We have served a wide range of clients including:
- Large seniors housing operators
- Investment firms backed by one of the leading global private equity firms
- National market research and consulting firms
- Real Estate Investment Trusts in multifamily and seniors housing
- National and regional residential developers and homebuilders
Can we have a trial period?
Yes, please reach out to the sales team to set up the trail. Use contact us page to send a request.
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.
Is bulk analysis an option? Can a series of addresses be batched into a single output?
Yes. Our large investment clients use our bulk analysis tools to create portfolio definitions to ask the engine questions about acquisition and disposition decisions.
How does StratoDem Analytics calculate household net worth? What is included in net worth?
StratoDem Analytics uses the same definition for household net worth as used by the Federal Reserve: total household assets less total household liabilities.
Households are composed of all individuals living at an address who consider it their usual place of residence.
Total assets are broken up into financial and nonfinancial assets.
Financial assets include checking accounts; savings accounts; money market accounts; call accounts at brokerages; certificates of deposit; directly-held mutual funds, excluding money market mutual funds; equities; government bonds, excluding bond funds and savings bonds; IRAs; thrift accounts; future pensions, including currently received benefits; savings bonds; cash value of whole life insurance; trusts; annuities; managed investment accounts in which the household has equity interest; loans from the household to someone else; future proceeds; royalties; futures; non-public stock; deferred compensation; oil, gas or mineral investments; and cash.
Nonfinancial assets include vehicles; principal residence; land contracts the household has made; properties other than a principal residence; timeshares; vacation homes; current value less tax basis of active and non-active businesses; luxury and household items (gold, silver, other metals, jewelry, gemstones, cars (antique or classic), antiques, furniture, art, photographs, rare books, collectibles, musical instruments, livestock, horses, crops, wine, computers, equipment, and tools).
Total debts include mortgages; home equity loans; home equity lines of credit (HELOCs); land contracts; debt for other residential or vacation properties; other lines of credit; credit card debt; vehicle loans; education loans; other installment loans; loans against pensions; loans against life insurance; margin loans; and miscellaneous other debts.
How does StratoDem Analytics calculate home values?
Home values are based on machine learning models with data from multiple open sources, including Census Bureau microdata and FHFA hyper-local home price indexes. We also use some other third-party non-governmental open data sources to improve and validate our housing machine learning models.
Are forecast metrics broken out by age?
Nearly all of our households metrics are broken out by age, including:
- Household income
- Household net worth
- Educational attainment
- Insurance coverage
- Home value
- Housing costs for homeowners and renters
Does StratoDem Analytics also provide historical data?
Yes. Many of our demographic metrics range back to 2000, with nearly all available from at least 2005.
Which data is only available from StratoDem Analytics?
Only StratoDem Analytics can calculate current market depth accurately by zip code/radius/drive-time, age, income, net worth, home value, among other factors in combination with each other. (For example, while most legacy-generation data providers cannot identify net worth beyond $500,000, StratoDem Analytics calculates the actual market depth for specific segments most likely to move into higher-end communities. Some legacy-generation data providers cannot generate counts of households beyond age 75, but for senior housing developers, StratoDem Analytics calculates market depth for the specific segments most likely to move.)
Only StratoDem Analytics has the data granularity and models to calculate local-market alphas and betas to determine how much of a region’s growth is driven by structural factors versus cyclical factors, which regions will most likely sustain or compress in a downturn, and which of the larger employment sectors in the region are more likely to grow, contract, or remain stable in a downturn.
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 80 to 84 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.