Which Source of Fleet Data is Right for Your Business?
If you sell to fleets, it’s exciting see vehicles drive by with logos. It looks like there are prospects all around. But you’ve likely seen a van with a logo, called them, and heard they have a much smaller fleet than your ideal customer.
And what about all the medium-sized fleets that don’t have famous logos? They have enough fleet vehicles to be good prospects for you, but they’re not big enough to be well-known. So you don’t know these fleets exist.
Unless … you have the data to find them.
Here, we’ll share how to choose the right data to find the right fleets for your business.
Fleet Data Sources – Contents
This article is a bit epic, so jump around if you want:
- FMCSA/National Fleet Data
- State/Local Fleet Data
- Inferred Fleet Data
- Business Intelligence Databases
- Other Lists of Fleets
Your Fleet Prospecting Database
Building a profitable prospecting database requires knowing the fleet data sources, and evaluating which sources are right for you.
Ideally you should match data sources with your ideal customer profile (ICP).
Not all fleet data sources are the same. Some are more appropriate for you than others, depending on what you sell and who you target. If this is a surprise, keep reading below!
The knowledge in this article will allow you to increase coverage of your market, reduce data duplication, and decrease obvious and hidden costs. And most important:
You want to ensure your data contains most if not all of the targetable prospects in your total addressable market.
We advocate for a strategic approach to data. A scattershot approach to building a prospecting database will result in missing your intended market significantly, leaving many potential opportunities untouched. This frustrates sales teams as they are flying blind. They are likely calling on many fleets that don’t fit your best customer. Marketing campaigns may under-perform due to loose targeting. You are likely wrestling with a lot of duplication in areas of too much data. While ironically at the same time, insufficient data leaves big holes in knowledge about your market. It’s possible that you don’t know how big these holes are.
When you use strategy for fleet data acquisition, you can avoid or solve these issues.
Your Fleet Data Use Case
The first steps to solving this are:
- Knowing your data use cases
- Matching your data needs to the right sources of fleet data
Companies selling to fleets tend to target two broad categories:
- National: Multi-state, long haul. Medium duty trucks and heavy duty tractor-trailers that often cross state lines for long haul trucking.
- Local: Sedans, pickups, white vans, work trucks and last mile delivery trucks that generally operate within a state or metro area.
These are two major general use cases for fleets. Some companies target both. And some focus on a small slice of the market, such as emergency vehicles, school buses, or utility work trucks.
Which of these use cases fit your business?
To reach fleets, you can acquire data from many sources. These sources vary significantly in coverage of the market and depth of information about vehicles. They also range widely in acquisition and maintenance cost — including both direct and hidden costs.
Let’s dig in to this now …
FMCSA/National Fleet Data
When vehicles are subject to federal regulations, the company operating these vehicles must have a permit from the U.S. Department of Transportation (USDOT or DOT). A USDOT number is assigned. It’s a unique identifier and every regulated vehicle displays this number. The Federal Motor Carrier Safety Administration (FMCSA) registers, inspects and enforces safety standards on these vehicles. These fleets are also called “DOT complaint” because they must comply with federal safety regulations. Drivers are typically required to get training and possess a Commercial Driving License (CDL).
Most vehicles in this data travel across states, so they’re involved in interstate commerce:
- Tractor-trailers or heavy duty “semi trucks” that travel across states, with a gross vehicle weight rating or gross combination weight rating of 10,001 lbs or more
- Vehicles that carry 9-15 passengers for compensation – also called “for hire” – and cross state lines, like tour motor coaches
- Vehicles that carry 15 or more passengers, not for compensation and cross state lines, like sports team buses
- Any size vehicle that carries hazardous materials, anywhere
Instead of being called “vehicles,” they are called “power units” in FMCSA data.
As of September 2021, about 686,000 companies in this data are actively operating.
The vast majority are very small. About half (54%) are single-vehicle “owner-operator” companies. Another 28% have 2-4 power units. If you are seeking owner-operators to carry loads for you, this is okay.
The remaining 18% are trucking fleets with 5 or more power units. Many of our customers are seeking these fleets to sell technology, maintenance, parts, fuel and other services.
Are these numbers different than you expected?
Clearly, larger fleets are a finite market. Only 2% of fleets in FMCSA data have 50 or more power units (about 12,600 fleets).
Source: Vehicle/power unit registrations with FMCSA
Company Profile: Interstate operations, carrying cargo or passengers, hazmat carriers
Fleet Profile: Half are single vehicle owner operator; 82% have less than 5 vehicles, mostly heavy duty trucking
Typical Industries: Long-distance trucking, multi-modal transportation, hazardous waste, motor coach tours
Uses: Compliance, training and safety offerings; shippers and 3PL logistics seeking motor carriers
Pros: Because the vehicles are federally regulated, this data is centrally available. It’s public information to download from the FMCSA website. Data includes age of vehicles, power units, number of drivers, miles driven, safety scores, inspection and crash information, compliance status, insurance carried. This info is good for companies that sell federal regulation compliance products, such as electronic logging devices (ELD), hours of service (HOS) tracking, CDL driver training and medical exams, alcohol and other drug testing, trucking insurance, repair and maintenance. It’s good for selling useful products for interstate trucking like toll passes and fuel cards. Freight brokers can find motor carriers.
Cons: Most vehicles in fleet operations do not require federal oversight. In fact, federal data represents only one-tenth of all fleet vehicles! If your business isn’t completely focused on federally-regulated vehicles, it’s important to know that the federal data is an incomplete picture when you’re seeking to understand the Total Addressable Market. Fleets with USDOT-registered trucks and buses often also have light duty vehicles. But you don’t get visibility into these vehicles like sedans, pickups, SUVs, vans and small trucks. Fleets that don’t have any USDOT-registered vehicles will not be in the FMCSA data. And this is, actually, most business fleets in the U.S.
Regarding contacts, because the information is public, FMCSA contacts have been bombarded with marketing messages for years, and may not be as responsive. For larger prospects, you often need multiple contacts across departments: fleet, maintenance, finance, procurement, safety, risk management, IT, operations, etc. The FMCSA contact may not be the right one for your business.
Bottom Line: You will still have to invest in other sources of fleet information if you target non-USDOT fleets. You may still need to invest in contact data.
Federal data represents only one-tenth of all fleet vehicles.
If your business isn’t completely focused on federally-regulated vehicles, it’s important to know that the federal data is an incomplete picture when you’re seeking to understand the Total Addressable Market.
State/Local Fleet Data
State and local fleet data can be compiled through many public sources of information. A more reliable source is vehicle registrations. Every vehicle on the road needs a license plate, and this is handled by the states. Vehicles operated by businesses must have state commercial vehicle registrations.
This includes passenger cars, SUVs, pickups, vans, local delivery trucks, work trucks, emergency like police cars and ambulances, school buses, airport shuttles, taxis – basically, everything. And, the federally-registered heavy-duty tractor-trailers must also have state registrations. So they are in both federal and state data.
Most companies with fleets of vehicles are local, in industries like construction and contractors, utilities, last mile delivery. Local fleets include governments, schools, colleges and universities. Think of all the companies that travel to homes and businesses with services: landscaping, pest control, janitorial, technicians … it’s a very long list of industries!
Now, one way that federal FMCSA data and state data are similar is that the vast majority of fleets are very small, less than 4 vehicles. In this way, state data looks a lot like the federal data. But there’s a key difference – and a big difference! – between these two sources:
* Based on 40 states
For fleets with 5 or more vehicles, states have 573,900 more fleets than federal data.
While the chart above shows 699,296 companies with 5+ vehicles, if you also count fleets with 1-4 vehicles, there are 6.2 million fleets in 40 states.
As you can see, the big difference is, there is much more data available at the state and local level. This is because all companies with any kind of fleet vehicle are included.
Why 40 and not 50 states? See below, a discussion about the remaining 10 states …
Sources: Currently 40 states provide this information, available through approved partners
Company Profile: About 6.2 million local operations, mostly private (own use) fleets
Fleet Profile: 89% have less than 5 vehicles; due to larger quantity of data available, about 700,000 have more than 5 vehicles
Typical Industries: Construction, contractors, field services, last mile delivery, rental & more
Uses: Offerings for the entire fleet life cycle for all vehicle types: purchase, operate, maintain, dispose
Pros: If you wish to understand the whole comprehensive fleet market, this larger dataset is critical to see the full picture and target a much larger universe. The data can be extracted from VIN information like weight (used to calculate Class 1-8), body type, manufacturer, fuel type, engine type and chassis/axles. This breadth of data provides a more accurate portrait or footprint of a fleet: age of the fleet, ownership, brand mix and other operating characteristics. Most vehicles operate within a state or local area, so accurate geo-targeting is possible.
You can also get data on all locations where a company or government has vehicles.
If you sell products or services that could be used by any business vehicles, then the state data will give you the biggest pool of prospects.
Cons: This data comes from many dozens of sources that all operate on different data reporting timelines. And it’s only available through select providers, so there is latency in capturing, standardizing data, and making it available. For the same reasons, it is much more expensive to compile and validate than the federal data.
As of September 2021, ten states (we call them “restricted states”) do not release information about commercial fleet vehicle registrations. This results in a gap of about 20% of companies with fleets. Inferred fleet data can fill this gap, as discussed below.
The Bottom Line: Unlike the federal data, state data is not free or cheap. It has strong advantages that can be worth the investment. It is the only way to reach local and intrastate fleets in most industries, and also the only way to get a true picture of the fleet market including all vehicles.
Inferred Fleet Data
Federal and state data do not capture every commercial fleet on the road. Reasons include: lack of fleet registration info from the ten restricted states, business vehicles registered under personal names and home addresses, businesses that relocated and did not re-register.
So, data providers such as Valgen model the presence of fleets with known fleet variables like company size, industry, location type, and other factors. This data is often a range, instead of a specific number of vehicles. Inferred fleet data plays a valuable role. It fills the gaps in federal and state registration info, so you get complete coverage of the US market.
Source: Analytics & data providers with modeling expertise and fleet domain knowledge; available for all states, but focus on restricted states to “fill-in” gaps
Company Profile: 2M companies (in restricted & non-restricted states), similar in firmographic and industry profile to companies with state registered fleets
Fleet Profile: Representative of the known fleet market, in areas where fleet data is not available
Typical Industries: Construction, contractors, field services, last mile delivery, rental & more
Uses: Offerings for all aspects of the fleet life cycle: purchase, operate, maintain, dispose
Pros: Inferred data is the only way to get local fleet information in the 10 restricted states, where data is not available from the states. It can help give a more complete picture for national fleets that operate in states where data is both available and not available.
Cons: Accuracy of the fleet estimates depends on accuracy of the firmographic data. This data can vary.
The Bottom Line: This can be a great way to fill in companies in certain markets, where otherwise data is not available.
Business Intelligence Databases
Many companies selling to fleets use B2B intelligence software. Dozens of business data compilers have rich company firmographics, industry and contact data. But they don’t have data about fleet vehicles. It’s possible to find fleets in their data by using keywords and industry filters, or searching for fleet-related job titles. But these methods won’t turn up all fleets.
And ultimately fleet size and vehicle information – which is a core need if you’re selling to fleets – is not available.
Source: Dozens of lead generation and prospecting apps, social networking like LinkedIn
Company Profile: B2B data software tends to focus more on desirable heavily-prospected companies, so there may be less information about very small companies
Fleet Profile: Not available
Typical Industries: All industries, though various B2B data software tend to have strengths in certain industries and weaknesses in others
Uses: General purpose sales and marketing outreach, building a core dataset of all relevant companies, appending fleet data with contacts
Pros: Business intelligence software that is rich with direct contact information like direct dials, mobile numbers and validated emails can be a good supplement to sources of fleet data.
If you are already using software like ZoomInfo, Clearbit, Seamless.ai, RocketReach, Lusha, LeadIQ, etc., you can append your prospect/lead gen database with fleet data. The results are often surprising! This will help you focus resources on your fleet ICP.
Cons: For companies offering solutions to fleets, prospecting only with B2B intelligence data is like casting a small net in a huge ocean. The amount of data found may not justify the combined cost of data acquisition and time spent building filters. And worse, too much prospect data that doesn’t fit your fleet-specific ICP is unproductive for sales’ selling time.
For example, the need for fleet size is especially true if your ICP is fleets with as few as 5+ vehicles. Believe it or not, about 85% of all commercial fleets have less than 5 vehicles. So if you’re searching with industries, keywords and job titles, it’s possible that 8 out of 10 companies won’t fit your ICP. Only 2% of fleets have 50+ vehicles, so it’s a shot in the dark to look for these companies without fleet data.
Many B2B prospecting databases are stronger for midmarket and enterprise in popular heavily-prospected industries: technology, SaaS, finance, health care. There is less coverage of manufacturing, industrial and contractor markets with fleet vehicles, particularly for small business fleets (SMB).
Bottom Line: Vendors that focus deeply on contact data will obviously be stronger in that area. You will likely still need to invest in appending with fleet data. So consider that when setting your data budget. To offset this, you will likely see ROI.
Other Lists of Fleets
This includes conference, meeting, webinar and other event attendees, lead gen activities like white paper downloads, trade media subscribers, association and professional membership rosters of companies that have interests in owning and operating a fleet. These are grassroots, bootstrap ways to gather lists.
Source: Fleet event attendees list, magazine subscriptions, trade association lists, etc.
Company Profile: Depends on the source; national conferences and trade media can have bigger fleets though most fleets are smaller companies operating locally
Fleet Profile: Varies considerably, likely less than 20 vehicles
Typical Industries: Specific to the lists obtained
Uses: Can be limited to the services offered to fleets through the event, magazine, association, etc.
Pros: People and organizations on these lists have an affiliation with fleets. They have vehicles, have an interest, or are a vendor to fleets. The data is compiled through your internal efforts and investment in content and events, so you may get data that competitors do not have. This data sourcing can fill gaps in geographic regions or fleet use cases, such as a meeting roster of trucking companies around San Antonio, Texas. Webinars and content marketing with very targeted content could uncover buyer intent such as middle- or bottom-of-funnel interest in electric vehicles.
Cons: None of these sources give you a comprehensive picture of the fleet market. Conference data includes only attendees and exhibitors at conferences. Association data includes only members of the association. Trade media subscriber lists include only subscribers. None of them, alone, cover a large percentage of the overall market of businesses and governments with fleet vehicles.
The cost of building a database as measured by “cost per lead” metric can be very high, depending on the initial quality of the data and your staff effort required to make the data usable. You will often have to cleanse, dedupe, and fill in vehicle data through follow-up research. Combining multiple sources of disparate data and creating a single view is an enormous undertaking for many companies, with significant technology, time and cost. These are hidden costs. So approach this with caution.
There can be inconsistencies between the information obtained here and federal and state registration data, for a lot of reasons. One of them is the inaccuracy of self-reported data. Because this data is often self-reported, your follow-up research may reveal very different fleet sizes. For example, a regional fleet manager of a very large decentralized national fleet may report the local vehicle size under her management, not a national number. Or she may do the opposite, reporting a national number that would be inaccurate for a local fleet vendor.
Because of its very nature of limited quantities, it is difficult to scale to the volume needed to serve larger SDR and BDR teams. Further, this data is not truly representative of the market, which means you could be using valuable marketing and sales resources to target segments that may not be the most profitable or scalable, increasing your cost of customer acquisition.
Bottom Line: You may be collecting leads from association events, online form fills, badge scans at trade show booths. We find once this lead gen data is appended with more accurate fleet data, only about 20-40% fits the ICP. You may want to set a budget to append these lists with fleet data.
Consider yourself now graduated from a course on fleet data!
You’ll be able to evaluate different types of data, and know which is best for your needs.
We work with all sources of data in our ProsperFleet database of companies with fleet vehicles. Contact us if you have questions or would like to explore data, or analytics like addressable market and segmentation.
President & CEO at Valgen
Rainmaker extraordinaire for our clients. Turns databases into gold. Analytics executive and entrepreneur with a track record of producing significant and sustained revenue gains for sales teams in fleet, transportation, high tech & financial services.