Now Reading: Netcore.ai bets on outcome-based pricing for agentic marketing era
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Netcore.ai bets on outcome-based pricing for agentic marketing era
Netcore.ai bets on outcome-based pricing for agentic marketing era
The Story in Brief
Netcore Cloud has rebranded as Netcore.ai and repositioned itself as an 'agentic marketing platform', shifting from tool-based pricing to outcome-based compensation. Founder Rajesh Jain said the company is now willing to link part of its fees to customer retention, transaction growth, and customer lifetime value improvements.
Jain argued that traditional MarTech is labour-intensive, forcing marketers to create limited segments and campaigns manually. An agentic platform uses AI agents to handle segmentation, content creation, and channel decisions at scale, freeing human marketers to focus on strategy.
The company is targeting what Jain calls the 'reacquisition tax', the heavy cost brands incur to win back customers they already have. In Indian commerce, 60-65% of customers make only one purchase. Netcore.ai plans to turn this retention gap into an arbitrage opportunity by delivering measurable outcomes rather than selling message volumes.
Indian Opinion Analysis
Netcore.ai is betting on a structural shift already visible in Indian SaaS: vendors taking outcome-linked fees rather than charging for volume. This model, common in performance marketing, is rare in retention and CRM software, where platforms typically earn per user or per message. The real test will be adoption among large Indian retailers and ecommerce firms, where customer churn runs at 60-65% and marketing heads are wary of handing control to an algorithm. If Netcore.ai delivers measurable retention lifts, it could force competitors like MoEngage and WebEngage to rethink pricing. The next signal to watch is whether the company signs multi-year outcome-based contracts with at least two top-50 Indian ecommerce brands within the next financial year.
Source: brandequity.economictimes.indiatimes.com
This story was synthesised by AI from the source linked above. Methodology and corrections.
