Adobe Experience Platform (AEP) for a Global Automotive Company​

Solution Overview

​​Step 1: Setting Up Adobe Experience Platform

• Environment Configuration:

We began by setting up the AEP environment, including configuring data sources and destinations. This setup allowed the company to ingest data from various channels and distribute it to relevant marketing tools.

# Initialize AEP environment

adobe-aep --init --env=production

• Data Schema Creation:

AEP’s data schema was configured to handle various types of customer data, such as demographic information, purchase history, and interaction logs. This schema was essential for creating unified customer profiles.

{

    "schema": "customer_profile",

    "fields": [

        {"name": "customer_id", "type": "string"},

        {"name": "first_name", "type": "string"},

        {"name": "last_name", "type": "string"},

        {"name": "email", "type": "string"},

        {"name": "purchase_history", "type": "array"}

    ]

Step 2: Real-Time Data Streaming and Integration

• Ingesting Data from Multiple Sources:

We set up data ingestion pipelines to pull data from the client’s website, mobile apps, dealerships, and call centers. This data was streamed in real-time to AEP, ensuring that customer profiles were always up-to-date.

 @Component(immediate = true)

public class DataIngestionService {

  public void ingestData(CustomerData data) {

        // Stream data to AEP

        aepClient.streamData("customer_profile", data);

    }

}

• Real-Time CDP Integration:

AEP was integrated with the Real-Time Customer Data Platform (RTCDP) to enable real-time data activation and segmentation. This allowed the client to deliver personalized content and offers based on the most current customer data.

public class RTCDPService {

public void activateSegment(Customer customer) {

        Segment segment = rtcdpClient.getSegmentForCustomer(customer.getId());

        rtcdpClient.activateSegment(segment);

    }

}

Step 3: Creating Unified Customer Profiles

• Profile Unification:

The customer data from various channels was unified into a single profile in AEP. This profile included detailed information about each customer’s interactions, preferences, and purchase history.

{

    "customer_id": "12345",

    "first_name": "John",

    "last_name": "Doe",

    "email": "john.doe@example.com",

    "purchase_history": [

        {"vehicle": "Sedan", "purchase_date": "2023-06-01"},

        {"vehicle": "SUV", "purchase_date": "2024-01-15"}

    ]

}              

• Segment Creation:

Using AEP’s segmentation capabilities, we created dynamic customer segments based on real-time data. For example, we segmented customers who had recently visited a dealership but had not yet made a purchase, enabling targeted follow-up campaigns.

var recentDealershipVisitors = {

    "segmentId": "seg_recent_dealership_visitors",

    "criteria": {

        "lastDealershipVisit": ">=2024-08-01"

    }

};

adobe.aep.getSegments().then(segments => {

    segments.push(recentDealershipVisitors);

})

Step 4: Personalized Marketing Campaigns

• Integrating with Adobe Target:

We integrated AEP with Adobe Target to deliver personalized content and offers across the client’s website and mobile apps. This integration allowed the client to leverage unified customer profiles for real-time personalization.

 adobe.target.applyOffer({

    "mbox": "homepage-banner",

    "params": {

        "customerSegment": "seg_recent_dealership_visitors"

    },

    "offer": {

        "content": "Exclusive offer for your next vehicle purchase!"

    }

});

• Multi-Channel Campaign Execution:

Personalized marketing campaigns were executed across multiple channels, including email, SMS, and in-app messages. These campaigns were tailored to each customer segment, ensuring relevant and timely communication.

public class CampaignService {

    public void executeCampaign(Segment segment) {

        campaignClient.sendEmail(segment, "Exclusive Vehicle Offer", "Check out our latest vehicles just for you!");

    }

}

​Step 5: Data Analytics and Insights

Analyzing Customer Data:

Adobe Analytics was used to analyze customer behavior and campaign performance. We examined metrics such as conversion rates, customer lifetime value, and engagement across different channels.

 public class AnalyticsService {

​ public void analyzeCustomerData(String customerId) {

        Report report = adobeAnalytics.getCustomerReport(customerId);

        report.getMetrics().forEach(metric -> {

            System.out.println(metric.getName() + ": " + metric.getValue());

        });

    }

}

• Optimizing Marketing Strategies:

The insights gained from data analysis were used to refine the client’s marketing strategies. For example, we identified high-value customers who were more likely to purchase premium vehicles and tailored campaigns specifically for them.

 adobe.target.optimizeOffer({

    "mbox": "premium-vehicle-banner",

    "params": {

        "customerSegment": "high_value_customers"

    },

    "offer": {

        "content": "Upgrade to a premium vehicle with exclusive benefits!"

    }

});