Auto dealers are sitting on mountains of untapped data across DMS, CRM, and marketing platforms. We unify it all into a single intelligence layer that drives lead conversion, optimises inventory, and keeps customers coming back.
The Reality
Dealerships aren't failing because they lack data. They're failing because the data is trapped in DMS silos, disconnected CRMs, and spreadsheet reports that arrive too late to act on. These problems compound — and they're costing you sales, service revenue, and customer loyalty.
Your BDC treats every lead the same. Without AI-powered scoring, high-intent buyers wait in queue behind tire-kickers — and by the time you call, they've gone to a competitor.
You don't have real-time visibility into what's sitting on each lot. Aging units pile up, popular models sell out, and pricing decisions are made on gut feel, not market data.
After the warranty expires, customers vanish. You have no predictive model to identify at-risk service customers or trigger retention outreach before they leave for an independent shop.
Your DMS holds years of sales, service, and parts data — but it's locked in proprietary formats. Getting a simple cross-department report takes days of manual extraction.
If you operate multiple rooftops, you can't compare performance across stores. Each location runs its own reports, with different definitions and different timelines.
Your team spends more time pulling data into spreadsheets and formatting monthly reports than actually analysing performance or finding growth opportunities.
OEM program requirements are getting more complex. Without automated compliance tracking and reporting, you risk losing incentives and program eligibility.
You're spending on Google, social, third-party leads, and traditional media — but you can't tell which channels actually drive showroom visits and closed deals.
Our Expertise
AI-powered lead scoring that ranks every prospect by purchase intent, sales funnel analytics that expose bottlenecks, and BDC optimisation that turns more calls into appointments.
Real-time inventory visibility across every rooftop, dynamic pricing recommendations based on market demand, and days-on-lot optimisation that keeps capital turning.
Service appointment analytics that predict no-shows, customer lifecycle tracking that drives repeat visits, and warranty analytics that protect margins.
Multi-rooftop dashboards that benchmark every store, group-level analytics for dealer principals, and OEM compliance reporting that keeps you in good standing.
AI-Powered
Go beyond dashboards. Our AI models continuously score leads, optimise pricing, and predict service demand — turning your dealership data into decisions before your team even opens a report.
AI-Powered Intent Detection
An AI model that scores every inbound lead by purchase probability — factoring in browsing behaviour, trade-in signals, and engagement patterns — so your BDC focuses on the hottest prospects first.
Market-Driven Price Optimisation
An AI agent that monitors market listings, days-on-lot, and local demand signals to recommend optimal pricing — maximising gross profit while maintaining competitive turn rates.
Retention & Fixed Ops AI
A predictive model that identifies customers due for service, predicts no-show risk, and triggers personalised outreach — keeping your service bays full and retention rates high.
Our Process
A proven 5-step methodology that takes you from fragmented dealership data to unified, AI-powered analytics — with measurable results at every stage.
We map your entire dealership data ecosystem — DMS, CRM, lead sources, service systems, and marketing platforms — to identify gaps, quality issues, and quick wins.
We connect and unify your data sources into a single, governed analytics layer — normalising taxonomy, resolving identity, and building the foundation for every downstream use case.
We build role-specific dashboards for sales managers, service directors, and dealer principals — with lead scoring, inventory analytics, and service retention models baked in.
We deploy predictive models for lead scoring, dynamic pricing, and service demand — each calibrated to your specific market, inventory mix, and customer base.
We continuously monitor model accuracy, recalibrate against actuals, and evolve your analytics as your dealership group grows — adding rooftops, brands, and use cases over time.
Auto Tech Stack
We don't force you onto a single platform. We orchestrate the right combination of DMS, CRM, analytics, and data tools to build your unified dealership intelligence layer.
Salesforce Automotive Cloud
CDK Global
DealerSocket
Snowflake
Tableau
Power BI
Google Analytics
Databricks
+ native connectors to all major DMS & CRM platforms
How We Work
Pick the engagement model that fits where you are. All engagements include a dedicated automotive analytics lead and a clear outcome definition.
Ideal for: Dealers needing clarity on their data landscape
A 2-week deep-dive into your dealership data ecosystem — DMS connectors, CRM data quality, lead source gaps, and reporting bottlenecks — with a prioritised remediation roadmap.
Ideal for: Dealer groups ready to consolidate and unify
A full analytics build — from DMS data ingestion and unification through to lead scoring, inventory dashboards, and service retention analytics — delivered in 8–12 weeks with a dedicated automotive analytics team.
Ideal for: Dealer groups that want ongoing expert analytics
We embed as your analytics Centre of Excellence — continuous optimisation, AI model management, dashboard evolution, and a dedicated automotive analytics partner on call.
Case Study
a multi-rooftop dealer group had no cross-store visibility. Each location ran its own DMS reports, lead scoring was non-existent, and service retention was below 60%. We unified their data, deployed AI lead scoring, and built group-wide dashboards — lifting lead conversion by 25% and service retention to 90%.
25%
Lead conversion lift
12→1
Unified dashboard
90%
Service retention
Lead conversion lift
Unified · AI-Scored · Automated
Real Results
1000+
Projects
600+
Customers
20+
Years of Enterprise Expertise
4.5
Customer Satisfaction Score
Connected Services
Dealership intelligence doesn't exist in isolation. These foundational services underpin every automotive analytics and AI solution we deliver.
Unify, cleanse, and activate your dealership data across platforms — building the foundation every automotive analytics stack depends on.
Data EngineeringConnect Salesforce Automotive Cloud to your unified data layer — for cross-dealership analytics that actually work.
Technology ServicesBuild the data infrastructure that powers dealership intelligence — from ingestion pipelines and semantic layers to governed data products.
Data DashboardingCommon Questions
Four core workstreams. (1) Lead scoring & sales intelligence (predictive lead scoring, AI-powered intent detection). (2) Inventory & pricing analytics (dynamic pricing engine, market-driven price optimisation). (3) Service retention & fixed ops. (4) Dealer performance & group analytics. Cross-stack credentials across Salesforce Sales / Service / Marketing Clouds, MCI, Tableau, Snowflake, Databricks.
Both, with the deepest work at dealer-group level (multi-rooftop, multi-brand groups). Dealer-group economics — shared infrastructure cost across rooftops, cross-rooftop inventory transparency, group-level performance benchmarking — make the data investment ROI clearer than at individual dealer level. We also work with OEMs and aftermarket service networks.
Yes. Common patterns: extracting DMS data (CDK, Reynolds & Reynolds, DealerTrack) into Snowflake / Databricks for analytics; integrating CRM (VinSolutions, Salesforce Automotive Cloud, ELEAD) for lead-to-sale tracking; pulling inventory feeds for pricing optimisation; combining service appointment data for retention modelling.
ML models trained on your historical lead-to-sale conversion data, identifying patterns that indicate buying intent — vehicle interest, time-on-site, return visits, finance pre-qualification, trade-in valuations. Models surface high-intent leads to your sales floor in priority order. We typically deliver this on Databricks with MLflow for model lifecycle management; ongoing model refresh is built into the engagement.
A focused engagement (lead scoring model, inventory pricing optimisation, or retention analytics) typically runs 2–4 months. Enterprise programs (group-wide data foundation + multiple workstreams + AI activation) run 6–12 months. We time go-lives around model-year transitions and OEM reporting cycles, not against them.
Cross-stack credentials applicable to dealer economics — Salesforce SELECT (Automotive / Sales / Service Clouds), Snowflake Select Partner, Databricks Premier (for predictive lead scoring + dynamic pricing ML). Plus delivery experience with dealer groups and OEMs across the US. Most automotive consultancies are CRM-only; we're cross-stack.