Episode 27: From Online Discovery to Booking: Tracking the Offline Journey That Starts Online

Key Takeaways

• Quality-scored leads are replacing raw call counts as the standard for measuring local marketing ROI
• AI-powered conversation intelligence can automatically tag, score, and surface insights from every call at scale
• Multi-location brands should match their CTAs to audience preferences rather than assuming everyone converts the same way
• Voice AI agents are emerging as an always-available first responder for local businesses, reducing missed calls and speeding up routing
• Call recordings and AI transcriptions are a goldmine for content strategy, product development, and sales coaching

For multi-location brands, the customer journey rarely starts and ends in the same channel. A prospect discovers a business through search, lands on a local page, and then picks up the phone, sends a text, or walks into the store. The gap between that online discovery and the offline conversion is where revenue is won or lost — and where most brands lose visibility.

In this episode of the Local Marketing Beat podcast, host Christian Hustle sits down with Chris Todd, Sr. Principal of Marketing Operations at CallTrackingMetrics, to explore how brands can connect online discovery to offline actions, why lead quality matters more than lead volume, how AI is transforming call intelligence, and what multi-location marketers should be testing right now.

Timestamps

00:00 Introduction and CallTrackingMetrics overview

02:48 Trends in consumer journeys and lead quality

04:55 Industry use cases: home services, addiction treatment, and beyond

06:56 AI-powered call scoring and conversation intelligence

08:41 Turning call insights into content and product strategy

10:26 Multi-location routing and regional reporting

12:55 Best practices for tracking offline conversions

14:27 The biggest mistake: treating all leads the same

16:14 Voice AI agents and the future of local call handling

18:55 Key takeaway: data-informed decisions and quality measures

Lead Quality Is Replacing Lead Volume as the Standard

“It’s a lot more value to a client for an agency to say we generated basically 30 qualified leads last month, which maybe they were reporting 50 leads before, but it’s really 30 qualified. That value measure is something that I’m seeing a lot more of our customers start to add on.” — Chris Todd

Chris identifies a fundamental shift in how local marketing performance is measured. The old model — counting raw phone calls or form submissions — is giving way to quality-scored leads that distinguish genuine prospects from spam, misdials, and unqualified inquiries.

This matters especially for multi-location brands feeding conversion data back to ad platforms like Google Ads, where machine learning algorithms optimize for whatever signal you send them. As Chris explains, sending junk data back to your ad platforms means their AI will find more junk for you.

For brands using analytics and reporting tools to measure location performance, this reinforces the importance of the conversion pillar: It is not enough to drive visibility and engagement if the leads those interactions produce are not being qualified and measured accurately. Chris recommends layering a scoring system on top of every conversion channel so that reporting reflects business reality, not vanity metrics.

AI Call Intelligence: From Manual Listening to Automatic Scoring

“The AI will basically do that listening for you at scale. Every single call that you’ve transcribed can go through that AI process — ask whatever question you want. Is it qualified? Is it not qualified? Likely to buy, what product were they looking for?” — Chris Todd

One of the most practical innovations Chris describes is CallTrackingMetrics’ “Ask AI” feature, which applies conversation intelligence to every transcribed call automatically.

Instead of manually listening to hundreds of recordings — something Chris still recommends doing selectively for strategic insight — the AI tags each call with custom criteria: Whether the caller was qualified, what product or service they asked about, whether they booked an appointment, and more.

This has direct implications for brands managing review management and customer feedback at scale. The same AI-driven analysis that identifies qualified leads can also surface recurring customer complaints, frequently asked questions, and messaging gaps — insights that feed directly into content strategy.

Chris shares an example of a home services client that discovered demand for landscaping through call analysis and expanded into that service line as a result. For brands already investing in local SEO, call intelligence adds a layer of customer voice data that no keyword tool can replicate.

Match Your CTAs to Your Audience, Not the Other Way Around

“The mistake that any marketer makes is that everybody they think that everybody’s the same. Their ideal persona is the same person that calls is the same person that texts is the same person that submits a form.” — Chris Todd

Chris identifies the most common conversion mistake for local brands: assuming all customers want to interact the same way. Some people prefer to call. Others want to text. Some will only fill out a form.

And as Christian points out from his own experience buying cars, some will simply show up at the location without any prior digital interaction at all. The problem arises when brands optimize for one conversion path and neglect the others.

For multi-location brands building local landing pages, this means testing different CTAs across locations and segments rather than defaulting to a single form. Chris recommends regularly testing which conversion methods work best for each audience and not assuming those preferences will remain static — he suggests revisiting CTA performance every six months at minimum. Brands using messaging and chatbot tools alongside traditional phone and form options are better positioned to capture the full spectrum of customer intent.

Voice AI Agents Are Becoming the Always-On Front Door

“I see voice AI agents being really prevalent especially with local marketing, local services where even now Google’s adding that thing where AI will basically call the business for you and be like, are you open? You’re open. Cool. Let me tell them.” — Chris Todd

Chris sees voice AI agents as the next major shift in local customer engagement. The use case is straightforward: When a local business receives a call outside of hours or when all agents are busy, a voice AI agent answers, qualifies the caller, asks relevant questions, and can even book an appointment through a calendar integration — all before a human ever gets involved.

For industries where missed calls have serious consequences (Chris cites addiction treatment as a life-or-death example, and home services where a single missed call can mean losing a $12,000 roof job), this always-on capability is transformative.

This aligns with the broader trend toward AI-powered customer engagement across the local marketing stack. Whether it is Uberall’s UB-I managing location data and insights or CallTrackingMetrics routing and qualifying inbound calls, the pattern is the same: AI handles the repetitive, time-sensitive work so that human teams can focus on closing deals and building relationships.

Multi-Location Routing and Regional Reporting Under One Roof

“If you have multi-location that can maybe service giant regions and you want to make sure that when a phone call comes in, it goes to the right office, you can just quickly set up that routing.” — Chris Todd

For franchise and multi-location brands, Chris highlights two operational use cases beyond attribution.

The first is intelligent call routing: When a call comes in, the system identifies the caller’s region and sends the call directly to the right location’s queue, eliminating transfers and reducing wait times. The second is consolidated reporting: All locations live under one account with subaccounts that can be rolled up by region, territory, or brand — giving headquarters a unified view while preserving location-level detail.

This mirrors what brands achieve with location data management platforms — centralized control with local flexibility. When call routing and listings management are aligned, the customer experience is seamless from online discovery through to the first human interaction. Chris also notes that call data can reveal targeting problems: If ads for one region are consistently generating calls from a different region, that is an immediate signal to fix targeting or listing accuracy.