Your home-services CRM needs predictive data to predict who will actually book

Who this guide is for

This post is written for marketing and operations leaders in the home-services industry—the people responsible for filling calendars, scheduling appointments, and keeping call centers busy at roofing, solar, and plumbing companies. Whether you’re running campaigns in ServiceTitan, Housecall Pro, Salesforce or HubSpot, your challenge isn’t collecting more leads. It’s figuring out which ones will actually book jobs.

If you’re a CMO, VP of Marketing, or Marketing Ops leads in home services, this piece will show how a predictive data layer can plug into your existing CRM to help your team focus on high-intent prospects—and stop wasting time on leads who were never going to convert.

The problem: Your CRM knows what happened before but not what happens next

Your CRM is great at logging calls, tracking appointments, and storing customer info. But it’s not helping you anticipate what will happen next, who is likely to convert, or how much they might buy. Your team is still guessing who to call first. Campaigns are firing blind. Reps are wasting hours chasing low-quality leads.

The problem isn’t your CRM—it’s what it’s missing: predictive context. You’ve got historical data, but not behavioral or financial signals that show who’s ready to book. That’s where adding data AND predictions comes in.

The solution: The predictive data layer: what it is and why it matters

A predictive data layer adds real-world behavioral and financial signals drawn from verified consumer data to each contact in your CRM. In addition to first party data you collect from web form fills and past interactions, you get third party data points and scores based on how likely each lead is to book right now or in the next 30, 60, or 90 days.

Faraday’s predictive data layer integrates directly into your CRM—no replacement required—and automatically adds key datapoints that reveal intent, readiness, and fit. The result: your reps spend more time on leads that close, not leads that clog up the queue.

What smarter CRMs deliver

Companies that add predictive enrichment to their see immediate results:

• Fewer wasted calls as reps focus on high-intent prospects. If you could sort your call list, why wouldn't you?
• Higher close rates across campaigns. By avoiding bad leads, or leaving them for last, you get better results sooner.
• Cleaner funnels and more predictable revenue forecasting. You can calculate an "estimated value" (EV) for every lead, even if it just appeared in your pipeline.

Faraday has the datapoints that change everything

Most CRMs weren’t designed to predict—they were designed to record. Faraday fills that gap by adding a predictive data layer that plugs directly into your existing tools. You don’t need a data science team, a new platform, or an overhaul. Just a connection to the Faraday Identity Graph, which powers over 1,500 verified consumer datapoints—everything from financial readiness to life-stage signals.

While our platform is chocked full of data that drives value, some are particularly useful for home services brands like yours. Here are the high-impact datapoints Faraday adds to your CRM:

1️⃣ Credit score proxy: Predicts a household’s financial readiness without a hard credit pull. Perfect for screening prospects before offering financing options.

2️⃣ Likelihood-to-Convert: Scores leads based on real behavioral patterns, showing who’s statistically most likely to book a job this week.

3️⃣ Dwelling type: Distinguishes renters from homeowners—critical for knowing whether to push service contracts or new installs.

4️⃣ Household income & equity: Adds key context for premium upsells, like full HVAC replacements or solar upgrades.

So in short, with Faraday’s data, you can:

✅ Predict who can pay
✅ Predict who will book
✅ Predict what to offer next

How to add predictive data to your existing CRM

Adding the datapoints you need to your CRM with Faraday is easy and fast. In a few careful steps, you can turn your existing customer database into a predictive engine that shows you who’s ready to book, who needs nurturing, and who’s not worth chasing—without touching your current workflows.

1. Connect your records. Faraday integrates directly with platforms like ServiceTitan, HubSpot, or your internal CRM through a secure API. Our developer-friendly API and detailed documentation are a good starting point- and we'll give you a hand getting it set up. You can also give it a try using simple CSV uploads and downloads, to get comfortable with the data.
2. Enrich with Faraday’s Identity Graph. We fill in the missing details—household, property, demographic, and behavioral data that CRMs alone can’t provide.
3. Deploy predictive datapoints. Append fields like Credit Score Proxy or Likelihood-to-Convert so your team can instantly see which leads matter most.
4. Automate routing and prioritization. Use these datapoints to filter and prioritize your call queues or lead-routing automations—whether that’s directly inside your CRM or through integrations like ActiveProspect’s LeadConduit. This ensures your highest-value prospects are called first and passed to the right reps in real time, reducing manual triage and wasted dials.

Implementation should take a couple weeks—after that, your CRM doesn’t just record what happened—it starts predicting what’s about to happen next.

FAQ

1. Do I need to replace my current CRM (like ServiceTitan or HubSpot) to use Faraday? No. This is the most common misconception. Faraday is a predictive data layer, not a new CRM. It plugs into your existing system and enriches the customer records you already have. Your team keeps working in the tool they know, but with new, predictive data at their fingertips.

2. What’s the difference between Faraday’s predictive scoring and my CRM's built-in lead scoring? Traditional lead scoring is manual and behavior-based (e.g., "opened email" = +5 points). It only knows what a lead does with you. Faraday’s predictive scoring is AI-driven and market-based. It compares your leads to a massive, verified consumer dataset to find patterns. It answers a different question: not "Is this lead engaged with my marketing?" but "Does this lead look like someone who will actually book a job?"

3. Do I need a data science team or data engineers to implement this? It makes it easier, but not necessarily. Faraday has integrated with hundreds of marketing and operations teams and we can provide more or less help depending on your situation because we connect via pre-built integrations and APIs, you don't need data scientists to build or maintain models. Your ops team can map the new data fields (like Likelihood-to-Convert) into your CRM, and your marketing team can start using them in automated workflows immediately.

4. How does a call center rep actually use a "Likelihood-to-Convert" score? Faraday appends this score directly to each lead record in your CRM or routing system.

• Qualification: The system can filter out bad leads before they ever make it to your call center, if you want.
• Prioritization: Reps can sort call queues by highest Likelihood-to-Convert, so they start with leads most likely to book—no guesswork or manual filtering.
• Routing: Through integrations like LeadConduit, high-scoring leads can be automatically routed to top reps or live-transfer partners, while lower scores move to nurture sequences. The result: reps spend time where it counts—on the leads that actually book.

5. Is Credit Score Proxy compliant? The Credit Score Proxy is a modeled attribute, not actual credit bureau data. It is privacy-safe, does not require a "hard" or "soft" credit pull, and does not use or access any data from credit bureaus, making it fully compliant for marketing and prospecting use cases. More information can be found here.

Putting it all together

So what should you walk away with? Your CRM isn’t broken—it’s just incomplete. By layering in Faraday’s powerful and varied datapoints, you give your team the visibility they’ve always needed: who’s likely to book, who’s financially ready, and who’s worth a follow-up later.

The result? Smarter routing, cleaner funnels, and a marketing team that can finally prove its impact in booked jobs—not dashboards.

If you’re ready to make your CRM predictive, reach out or take a look at our API docs.