// data strategy

All signals tagged with this topic

Sep 3

Roku Prioritizes Data Quality Over Volume in CTV Advertising Push

Source: Beet

Roku is explicitly rejecting the industry's signal-maximization playbook by constraining data inputs to improve ad targeting and performance measurement. The move amounts to an admission that data abundance in CTV has created more noise than signal for advertisers trying to justify spend. If the market leader in connected TV is saying "fewer is better," it's because current attribution and targeting frameworks are failing to prove ROI to brand marketers—a gap that directly threatens the premium CPM gains CTV has relied on. The shift consolidates around proprietary first-party data rather than third-party signal abundance, moving CTV ad platforms away from data aggregation toward data refinement.

theme-commerce retail media programmatic advertising data strategy

Jun 23

Retail Media Networks Face Data Fragmentation Problem

Source: Beet

Retail media networks have aggregated impressive ad inventory, but remain operationally fragmented. Amazon, Walmart, and Target each control their own data and refuse meaningful interoperability, forcing brands to rebuild campaigns separately. The economics only work if retailers can prove coordinated insights across channels improve performance—a requirement that demands breaking down the walled gardens protecting their highest-margin ad businesses. Without standardization, retail media risks becoming a channel tax rather than a data-enabled competitive advantage.

theme-brand ai adoption data strategy organizational readiness

May 19

Mid-market companies face AI adoption bottleneck without data foundation

Source: SiliconANGLE

Mid-market businesses—the economic backbone between small firms and enterprises—are hitting a critical juncture. AI adoption requires clean, governed data infrastructure they often lack. While large enterprises have invested years in data architecture and small companies experiment cheaply, mid-market firms face worse timing: pressed to deploy AI now but without foundational work that makes deployment profitable rather than loss-creating. Mid-market productivity gains or losses directly affect regional GDP growth and employment in ways enterprise AI wins don't.