Driving higher value engagement with unified data

Connecting customer and vehicle data

To better compete in a crowded market, an automotive services brand implemented Epsilon’s CDP to unify customer data across in-store, digital and vehicle-level touchpoints.

This created a 360-degree view of each customer, enriched with vehicle data, enabling more precise reach and personalization at the individual level.

With this foundation, the brand could move from generalized campaigns to more data-driven engagement.

A mechanic shows a customer information on a laptop in a car repair shop.

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Driving higher value engagement with unified data

Improving performance with better data

35%

higher exact discount match rate

126%

lift in response rate

increase in margin per delivery

Connecting customer and vehicle data

To better compete in a crowded market, an automotive services brand implemented Epsilon’s CDP to unify customer data across in-store, digital and vehicle-level touchpoints.

This created a 360-degree view of each customer, enriched with vehicle data, enabling more precise reach and personalization at the individual level.

With this foundation, the brand could move from generalized campaigns to more data-driven engagement.

Standing out in a crowded market

The brand needed to deliver more relevant, one-on-one experiences to both new and existing customers while increasing loyalty, retention and overall profitability.

However, disconnected data across channels and touchpoints made it difficult to fully understand customer needs or deliver consistent, personalized interactions.

Smiling woman using a laptop while leaning on a black car.

Increasing relevance and response

By unifying data and applying advanced modeling, the brand significantly improved engagement and performance.

Offers became more relevant by aligning promotions to individual needs
Engagement improved, driving a 126% increase in response rate
Margin improved, with a 2x increase per delivery

These gains reflect more precise targeting and better alignment between offers and customer needs.

A mechanic holds a payment terminal for a customer making a contactless payment in an auto shop.

Applying predictive models and decisioning

With unified data in place, the brand developed advanced models to predict:

Expected customer spend over the next year
Likelihood of reengagement in the near term
Additional services a customer may need

These insights were combined with real-time decisioning to tailor offers, timing and channel selection—helping maximize both customer value and efficiency.

Crucially, customer data was mapped at the individual level, including vehicle identifiers, enabling more accurate targeting and personalization.

A woman talks to a mechanic at a desk in a car repair shop with a car on a lift in the background.

Driving more efficient growth

With a more precise understanding of customer needs, the brand improved how it allocated offers and promotions.

Discounts became more targeted, improving efficiency and reducing unnecessary spend
Engagement strategies became more consistent across channels
Customer experiences became more relevant, supporting loyalty and retention

This shift established a more scalable, data-driven approach to customer engagement.

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