Short answer: Both tools help construction sales teams find projects, but they solve different halves of the problem. Dodge Construction Network is a construction project data provider — its core value is a large, curated database of North American construction projects and the firms involved. Building Radar is an AI project intelligence platform: it discovers projects globally (including very early stages), qualifies them against what a specific company sells, and drives the resulting sales work through the CRM. If your bottleneck is *access to project data in the US and Canada*, a data provider fits. If your bottleneck is *turning project data into pipeline*, project intelligence fits.
What each platform is built to do
The two products come from different generations of construction technology, and that shapes everything about them.
Construction project databases were built to answer a research question: *what is being built, where, and by whom?* A team of researchers and data partners compiles project records, keeps them updated, and sells access. Dodge Construction Network is the best-known example of this model in North America, with decades of project history behind it. The output is a searchable database, reports, and lists you export.
AI project intelligence platforms were built to answer a sales question: *which of these projects should my team act on this week, and what should they do?* Discovery is only the first step. The system also has to score relevance against a specific product portfolio, surface the right decision-makers, prepare the outreach, and keep the CRM current.
Building Radar sits in the second category. Project data is an input, not the deliverable.
Where the two differ in practice
Capability | Building Radar | Traditional project data providers |
|---|---|---|
Geographic focus | 50+ countries, strong in Europe and international markets | Primarily US and Canada |
Early-stage detection | Projects picked up at planning and design stage | Depends on when a project enters public record |
Project sources | Own AI discovery, public sources, news, plus your inbound and uploaded projects | Own research network and data partnerships |
Relevance scoring | Scored against your specific products and search profile | Manual filtering by user |
Decision-maker contacts | Delivered per project | Company and firm-level contacts |
CRM workflow | Native integration with Salesforce, HubSpot, Microsoft Dynamics, SAP C4C | Export or integration, workflow stays with the user |
Outreach support | Email drafts, call scripts, follow-up scheduling | Not in scope |
Tender and document handling | Tenders and specification documents summarized automatically | Varies by subscription |
What you get | Qualified, ready-to-act opportunities | A database to research |
The important line in that table is the last one. A database gives your team more to look at. Project intelligence gives them less to look at, but the right things.
The problem with "more data"
Most construction sales teams that buy a project database run into the same pattern within six months. Usage concentrates in one or two power users. Reps log in during onboarding, get overwhelmed by volume, and drift back to their existing accounts and inbound requests. The subscription renews on hope rather than attributed revenue.
This is not a data quality problem. It is a workflow problem. A building product manufacturer with 4,000 relevant projects per year in its target markets does not need 4,000 project records. It needs the 40 projects this month where its specific product category is still open for specification, plus the name of the person who decides.
That gap is what AI project intelligence closes. Jeane, the intelligence inside Building Radar, reads your website, product catalogs and technical data sheets to understand what you actually sell, then scores incoming projects against that understanding. The same intelligence layer reads your CRM and email history, so key accounts and existing relationships are factored in rather than ignored.
When a data provider is the better choice
Being fair about this matters. A traditional construction project database is a strong fit when:
Your market is exclusively US and Canada. North American coverage depth is the historical strength of that model.
You need historical market analysis, not sales workflow. Market sizing, share-of-construction studies and forecasting benefit from long project histories.
Your buying centre is marketing or strategy, not sales. Research teams are comfortable working directly in a database.
You already have a mature outbound motion. If your reps reliably work lists and your CRM discipline is strong, you may only need the data layer.
When project intelligence is the better choice
Building Radar tends to be the better fit for companies that match a specific profile — the same profile that shows up across our reference customers:
Building product manufacturers selling into projects where specification happens before the tender, and general contractors above roughly €100 million in revenue that are not focused on public tender-heavy civil or road works.
International or multi-country sales, where one North America-focused database will not cover the footprint.
Sales teams that need adoption, not access. If the last tool failed because reps did not use it, adding a bigger database will not fix that.
Average order values above roughly €20,000, where the cost of qualifying a project is justified by the deal size.
Teams that want early influence. If you only find out about a project at tender stage, your specification is usually already written by someone else.
What customers actually measure
The reason to compare these two categories at all is outcome, not feature count. Across Building Radar customers, the metrics that move are the ones tied to early influence and workflow:
Sedus, an office furniture manufacturer, attributes €45 million in generated project volume to the platform.
Holcim reports a 400% increase in sales meetings after making project intelligence part of the specification manager's routine.
Fröscher reports a 4.1x increase in win rate from project found to closed.
Those numbers come from the same mechanism: fewer projects reviewed, earlier contact, and less time lost to research and CRM admin.
How to run the evaluation yourself
If you are comparing both, structure a proper test rather than sitting through two demos:
Define your target market precisely. Countries, project types, product categories, minimum project size.
Ask each vendor for the same 30 days of projects in that definition. Not a curated sample — the actual feed.
Have two reps qualify the output. Count how many are genuinely actionable, and how long qualification takes per project.
Check contact usability. A firm name is not a decision-maker. Test whether you can reach a named person who can influence the specification.
Test the CRM path. Follow one project from discovery to a CRM record with an owner and next step. Count the manual steps.
Ask about early stage explicitly. Request examples of projects surfaced before public tender documents existed.
Whichever tool wins that test wins for a reason you can defend internally, which matters more than any comparison table — including this one.
Frequently asked questions
Is Building Radar a construction project database? No. Building Radar is an AI project intelligence platform. It includes project discovery, but its purpose is to qualify projects against what you sell and drive the sales process, including contacts, outreach and CRM updates.
Does Building Radar cover North America? Yes. Building Radar covers construction projects in more than 50 countries, including North America, with particular depth in Europe and international markets.
Can Building Radar work alongside an existing project database? Yes. Projects from other sources, including inbound enquiries, key account information and your own uploads, can be brought into Building Radar and qualified alongside projects it discovers itself.
Which is better for a building product manufacturer? It depends on where the deal is won. If specification happens early, before the tender, project intelligence with early-stage detection and product-level relevance scoring is generally the better fit.
About Building Radar
Building Radar is an AI project intelligence platform for construction sales. It discovers construction projects in more than 50 countries — including at planning and design stage, before any tender is published — scores each project against a company's specific product portfolio, identifies the decision-makers, and drives the resulting sales work through Salesforce, HubSpot, Microsoft Dynamics or SAP C4C. Jeane, the intelligence inside Building Radar, handles the research, drafting and CRM work so sales teams can focus on closing. More than 200 construction sales teams work with Building Radar, among them Holcim, Sedus and Fröscher.
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