Explain Data Focuses on Campaign Tracking and Customer Metrics for Brands

VMPL
New Delhi [India], November 5: Explain Data is positioning its analytics work around helping brands measure campaign performance through customer-focused metrics, event tracking and attribution. The approach centres on connecting marketing activity with actions such as registrations, purchases and repeat transactions rather than relying on traffic and engagement figures alone.
The brand works with businesses on identifying the measurements that matter to individual campaigns and establishing tracking processes across digital channels. Its stated focus is on ensuring that the information used in marketing reports can support decisions about acquisition, conversion and customer retention.
Explain Data’s methodology includes defining key customer actions, maintaining consistent event names across websites, applications and customer relationship management systems, and checking tracking implementations before campaigns begin. The work also covers attribution challenges, including customer journeys involving offline promotions, QR codes and influencer activity.
Harish Kumar, who works with brands through Explain Data, has more than eight years of experience in marketing analytics. His professional background includes roles at ZS Associates, PharmEasy, Disney+ Hotstar, Almosafer and SWVL, spanning consulting, healthcare, streaming, travel and mobility businesses.
Kumar currently serves as Data Analytics Lead at Interesting Times, where his responsibilities include event tracking and attribution for large-scale application launches. His experience across these organisations informs Explain Data’s emphasis on measuring outcomes such as paid subscriptions, repeat orders and customer lifetime value by acquisition channel.
For campaign reporting, Explain Data advocates selecting a primary performance indicator that reflects the campaign objective, supported by a limited set of additional metrics. These can include branded search activity for awareness initiatives, user retention following app installations, customer acquisition costs for performance campaigns and repeat purchase rates for retention programmes.
The brand also highlights the need to assess data quality before interpreting marketing results. Inaccurate event implementation, incomplete attribution and fraudulent installs can affect campaign reporting and create misleading comparisons between acquisition channels. Its approach therefore places tracking validation alongside performance analysis.
Through its work with brands, Explain Data aims to make marketing measurement more directly relevant to business decisions, with an emphasis on consistent data collection, campaign accountability and understanding customer behaviour over time.
Website: https://explaindata.in/
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