Learn how collecting first party data directly from customer interactions builds compliant personalization rules and long term marketing strategy online.
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Start free trial →First-party data is information a brand collects directly from its customers and prospects. It can come from the brand's website, app, email, SMS, loyalty programme, or physical store. Examples include purchase history, browsing behaviour, email activity, account details, support requests, and survey answers. The brand owns this data and collects it with the customer's knowledge. It is often the brand's most accurate source of customer data.
It is distinct from:
Third-party cookies are being phased out, and privacy rules are getting stricter. In India, this includes the Digital Personal Data Protection Act. These changes make third-party tracking less dependable. First-party data gives brands a stronger base for personalisation, retargeting, and customer insight.
First-party data is especially useful for D2C brands. Brands that sell through Amazon, Flipkart, or Myntra do not fully own the customer relationship. A D2C brand does, so it also owns the data from that relationship. More data about purchases, preferences, and behaviour can help the brand better predict what a customer wants and when.
Revenue applications for first-party data in ecommerce include:
Mamaearth has more than five years of customer sales data from its own platform. The data covers product categories, purchase frequency, average basket size, payment choice, and location. The brand uses this data to:
Using first-party data is estimated to improve email revenue per send by 15% to 25% compared with a mass campaign that does not use customer data.
First-party data can divide an A/B test into clear customer groups. A team might test high-value customers, repeat buyers, or people who bought from one category. It can then see how each group responds. CustomFit.ai uses first-party data to build test audiences and show each group a relevant experience.
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