Loyalty opportunities hidden in today’s affordability environment: What automotive analytics reveal 

Manufacturer loyalty is defined as the percentage of RTM households that acquire a new vehicle from the same manufacturer as the vehicle in the garage.

Manufacturer loyalty varies significantly across the 11 largest multi-brand manufacturers, from a high of 66.6% down to 37.3%. That is almost a two-to-one spread and represents vastly different conquest exposure and defensive requirements. 

Loyalty behavior also varies within brands based on the financial profile of the household. Analysis of loyalty by credit score reveals important nuance for OEMs’ incentive strategies.

Some brands, like Nissan, show a positive correlation between credit score and loyalty: higher-credit households are more loyal. Others, like Land Rover, show the inverse: low-credit households are more loyal. This information has direct implications for how auto dealer incentives and financing offers should be deployed.

Rate subsidies and APR offers are most powerful for credit-sensitive buyers. Cash-back incentives may be better suited for high-credit households who are less influenced by financing terms but more responsive to total cost of ownership. Layering automotive loyalty data with credit-tier analysis allows teams to match the right financial lever to the right household.

Layering loyalty data with auto finance analytics allows OEMs to match the right incentive strategy to the right household segment.

According to automotive market data, propulsion type has become one of the strongest predictors of future purchase behavior in the US—and the patterns vary significantly by geography.

EV households in the West are substantially more committed to staying in electric than EV owners in any other region. In markets like Denver, Seattle, and Portland, the gap between EV fuel-type loyalty and brand loyalty is striking—reaching as high as 20 points. That means EV owners in these DMAs are more loyal to the propulsion type than to the brand that delivered it.

For conquest teams, this is an explicit signal: households in these markets will consider switching brands as long as the alternative is also electric.

Hybrid owners nationally present a different dynamic, being more likely to acquire another hybrid or a gasoline vehicle than an EV. Still, in the West, hybrid-to-EV migration runs higher than average. Conquest campaigns targeting hybrid owners in Western markets can be structured around range, charging access, and payment comparisons that bridge from hybrid economics to EV ownership.

Further loyalty automotive analytics at the trim level reveals details that bulk brand data obscures.

For a single compact crossover model with 18 to 19 trim configurations, brand loyalty can vary by nearly 16 percentage points from the highest-loyalty trim to the lowest. A comparable model shows a gap approaching 17 points. 

The practical implication is significant. Conquest campaigns targeting “a model” are leaving precision on the table. The trim levels with the lowest loyalty represent the most accessible households for competitive offers—and the most cost-efficient use of marketing spend. Incentive dollars applied at the trim level, rather than the model level, can achieve better conquest conversion with less waste.

Local supply dynamics also create conquest windows that are invisible to teams working from national data. When a competitive model runs low in a specific DMA, households in market have fewer choices. Brands with strong availability in that market can capture incremental conquest sales.

The same principle applies during model changeovers. When manufacturers transition to a new model year, the outgoing version often accumulates excess inventory. Elevated incentive spend to clear that inventory can increase the product’s conquest appeal and pull customers away from competitors.

Monitoring these dynamics—model, trim, DMA, and inventory depth—in close to real time is what separates responsive marketing from reactive marketing.

With the automotive analytics capabilities available at S&P Global Mobility, including loyalty metrics, OEMs and dealers can identify numerous conquest opportunities, using real-time automotive market data. These metrics offer insights by manufacturer, brand, segment, model, and trim, but they also go deeper, providing analyses by fuel type, body style, demographic cohorts, and ZIP-Code level geographic areas.

This is vital information not just for loyalty and incentive teams, but OEM pricing teams as well. 

For loyalty teams that must master timing, data, and relevance, success starts with understanding why customers leave and reaching them well before they are back in the market. Incentives need to be targeted at genuine defection risks, not applied broadly.

When loyalty metrics shift, it's often a sign that customers don't think the vehicle is worth the price. That's directly actionable for pricing teams. Retention data reveals which segments have pricing headroom, where incentives are failing to hold customers, and how payment sensitivity is driving defection. Simply put, loyalty metrics tell pricing teams where value perception is breaking down—and where there's room to hold the line.

Pricing teams and loyalty teams are solving adjacent problems, and when they work together and not in silos, both can improve outcomes.

Success in a high-defection environment requires a disciplined framework. These five pillars can help ensure the data you leverage will translate into strategically sound decisions:

• Strengthen relationships with existing owners to minimize defection before it happens. Proactive outreach—including targeted payment relief offers, loyalty cash, or rate subsidies—can keep at-risk households engaged well before they begin shopping.
• Identify and target low-loyalty competitors. Manufacturer loyalty varies nearly two-to-one across major OEMs, creating clear conquest windows. Where a competitor’s loyalty falls below 45%, that’s a population actively receptive to alternatives.
• Align conquest strategies with propulsion system migration patterns. Matching conquest messaging to fuel-type intent—not just brand—dramatically improves targeting efficiency.
• Monitor competitor inventory levels in real time. When a rival model runs short in a specific DMA, consumers have fewer choices. Brands with strong availability in those moments can capture sales that would otherwise be unavailable.
• Match incentive spend to competitive inventory and pricing conditions. Model changeovers, excess inventory, and regional supply gaps all create temporary pricing windows. Responsive incentive deployment—rather than static national programs—captures those opportunities before competitors do.