Lookalike Audience Data Audit
Liability Check
Your customer data, fed into lookalike audience tools, needs a lawful basis under DPDP. Without it, you're not just targeting new customers, you're targeting ₹250 Crore penalties.
Why Lookalike Audience Data Audit is at Risk
Many growth teams in Bengaluru's tech parks or Mumbai's startup hubs routinely use customer lists on platforms like Meta or Google to find similar users. Under DPDP, this data transfer and processing for advertising purposes requires a **specific and clear consent**, separate from service usage. The **original purpose** for collecting the data (e.g., fulfilling an order) does not automatically extend to marketing or lookalike generation. Failing to ensure your seed audience data is **lawfully acquired, current, and purpose-specific** exposes your company to significant fines and reputational damage.
Common Violations
- 1.Uploading your full customer database to Meta/Google for lookalikes without explicit, separate marketing consent.
- 2.Failing to regularly refresh or purge outdated customer data used as seed audiences for lookalike models.
- 3.Mixing customer service data with marketing data, making it impossible to separate lawful bases for processing.
The Immediate Fix
Audit your current lookalike audience generation process. Immediately separate customer data collected solely for service fulfillment from data explicitly consented for marketing and audience expansion. Implement a data minimisation strategy before uploading any list.
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Projected Compliance Deadline: Immediate