Which lead sources were automated?

Website forms/VDP, phone-to-text capture, OEM leads, Google Vehicle Ads (VLA), Facebook/Instagram, Marketplace vehicles, third-party marketplaces, and chat.

How fast were replies after automation?

Initial AI reply under 60 seconds 24/7, with human BDC follow-up in under 10 minutes during business hours.

How were leads routed across rooftops?

By ZIP radius, inventory availability, model interest, store hours, and salesperson load balancing.

What compliance measures were used?

Consent capture for SMS, opt-out keywords, audit logs, and template libraries aligned with messaging regulations and platform policies.

Did automation hurt brand voice?

No—templates used plain language with variables (first name, model, VIN, store) and handed off to humans for negotiation.

How were test drives booked?

AI offered two time windows, then sent a calendar link with confirmation and 24h/60m reminders plus easy reschedule.

What about credit pre-qualification?

Optional secure-link pre-qual was offered post-appointment to reduce friction and protect privacy.

How were trade-ins handled?

AI requested mileage, condition, and photos; routed to valuation; delivered ballpark ranges with in-store verification.

What KPIs improved the most?

Response time, appointment set rate, show-up rate, days-to-sale, and gross per rooftop.

Can this work without a complex CRM?

Yes—start with structured sheets and webhooks, then integrate with your CRM/DMS for full pipeline reporting.

How were after-hours leads handled?

AI replied instantly with availability and held times; human BDC confirmed next morning.

What content performed best in replies?

Short, direct answers with one CTA: book a time, request a walkaround video, or confirm store location.

How were no-shows reduced?

Reminders at 24h and 60m, parking directions, and a quick reschedule link; optional refundable deposit for high-demand units.

Did the system handle vehicle holds?

Yes—conditional holds with clear time limits and disclaimers, managed by store policies.

How were inventory changes synced?

Nightly feed + on-demand webhooks updated model/VIN status and removed sold units from automations.

What about service and parts leads?

Separate workflows routed by reason code to the correct department calendars and queues.

How did stores keep messaging consistent?

Central templates with local variables, approved offers, and a change-log with version control.

Was Spanish-language support included?

Yes—auto-detect intent and language, then respond with bilingual templates and bilingual staff routing.

What training was required?

2-hour onboarding for BDC and sales managers, plus a 1-page quick-start and weekly office hours.

How were escalations handled?

Keyword triggers (e.g., finance, price quote) flagged human takeovers and alerted channel leads.

Could stores pause automations?

Yes—per-store toggles by hours, inventory thresholds, or special events.

What’s the rollout timeline?

Pilot in 30 days (2–3 stores), group-wide by 90 days with playbooks and dashboards.

What ROI was achieved?

Illustrative: 3–6× blended ROI within 90 days from faster response and higher show-ups; confirm with your data.

Turn on instant replies for top lead sources and connect a booking link with store-level routing.

Case Study: Multi-Location Auto Group Automated Lead Response — 2025 Playbook

Case Study: Multi-Location Auto Group Automated Lead Response

From web lead to booked test drive in minutes — how automation, routing, and compliance lifted show-ups and monthly gross across rooftops.

Highlights: <60s first reply ZIP + model routing 2-slot booking CTA 24h/60m reminders Dashboards per rooftop

Introduction

Case Study: Multi-Location Auto Group Automated Lead Response chronicles a regional dealer group modernizing its BDC. The mandate: reply instantly, route intelligently, book appointments friction-free, and keep every message policy-safe. The result was a measurable lift in show-ups and a faster path from VDP view to test drive.

1) Group Snapshot & Objectives

Area	Details
Rooftops	8 stores across 3 metros (domestic + import)
Monthly digital leads	~4,500 (web forms, chat, marketplaces, social, OEM)
Objectives	Reply <60s, book more test drives, reduce no-shows, unify reporting

2) Pre-Automation Challenges

Slow first response outside business hours
Manual routing between rooftops caused lead leakage
Inconsistent templates and disclaimers
No unified KPI view; attribution gaps

3) Solution Architecture

Ingest

Website forms & chat
Google Vehicle Ads
Social/Marketplace DMs
OEM & third-party marketplaces

Brain

AI responder (policy-safe templates)
Routing engine (ZIP, model, inventory)
Calendar connector (per store)

Nightly inventory feed + on-demand webhooks ensured VIN status stayed current across automations.

4) Core Flows (Reply → Route → Book)

Instant Reply: AI answers the question and offers two time windows (Today 4–7 / Tomorrow 10–1).
Smart Routing: Assigns by nearest rooftop with unit in stock; fallbacks to sister store within 25 miles.
Booking: Link to store calendar; confirmations + reminders (24h/60m) with parking directions.
After-Hours: Hold times and set expectations; human BDC confirms at open.

5) Messaging Templates (Plain-Language)

First Reply (SMS/Chat)

Hi {{first_name}} — the {{year}} {{make}} {{model}} {{trim}} you asked about is available at our {{store_city}} location.
Two quick options for a visit: Today 4–7pm or Tomorrow 10–1. Which works?

Trade-In Prep

We can ballpark your trade today. Reply with mileage + 3 photos (front/side/interior). Final value confirmed in-store.

Reminder (60m)

We’re set for {{time}} at {{store_name}}. Parking is on {{street}}; ask for {{rep_name}}. Need to reschedule? {{link}}

6) Data & Fields for Routing

Buyer: name, phone/email, ZIP, language
Vehicle: make/model/trim, VIN, new/used, status
Rooftop: radius, hours, inventory depth, queue size
Compliance: consent flag, opt-out state, source tag

7) 30–60–90 Day Rollout

Days 1–30 (Pilot)

Two rooftops, top 5 lead sources, English + Spanish templates
Report on response time, set rate, show-ups

Days 31–60 (Expand)

All rooftops; add trade-in and finance flows
Dashboard per store; weekly stand-ups

Days 61–90 (Optimize)

A/B test CTAs; tune routing weights
Add video walkaround requests; seasonal promos

8) KPIs & Dashboards

Stage	Metric	Target
Speed	First reply time	<60s
Set	Appt set rate	25–45%
Show	Show-up rate	65–80%
Sell	Lead→sale	10–20%
Value	Days-to-sale; gross	-15% cycle; +AOV

9) ROI Math (Illustrative)

Variable	Example
Added monthly sales from faster replies	+18
Avg front/back gross per unit	$1,600
Added gross	$28,800
Tools + ops	$6,000
Monthly ROI	($28,800−$6,000)/$6,000 ≈ 3.8×

Note: Numbers are illustrative; confirm with your store data and policies.

10) Operating Model & Training

BDC owns first reply and calendar; sales owns lot handoff
Weekly 20-minute review: templates, KPIs, inventory hot list
One-pager quick start + video loom for new reps

11) Compliance & Policy Safety

Explicit consent for messaging where required; simple opt-out
Template library with disclosures and store policies
Audit logs for edits, sends, and handoffs

12) Pitfalls & Fixes

Pitfall	Impact	Fix
Over-automating negotiation	Lower trust	Human takeover triggers (price/finance)
Stale inventory in flows	Bad CX	Nightly feed + real-time hooks
Generic CTAs	Low set rate	Two-slot booking CTA with timeboxes

13) Future Enhancements

Personalized payment ranges by credit tier (with privacy safeguards)
AI video walkarounds triggered by model interest
Service retention flows post-sale (first oil change reminder)

14) 25 Frequently Asked Questions

The full 25-question FAQ is embedded in JSON-LD above for rich results. On-page highlights cover routing, consent, booking, trade-ins, and after-hours workflows.