The Uptempo pairing enhances OptiMine’s partnerships, but the combined entity lacks an office in the APAC region, which limits global service capabilities compared to competitors. Capabilities. OptiMine’s calling card is speed to insights, driven by strengths in data ingestion and management. Data ingestion is faster because OptiMine can process highly granular client data without forcing taxonomization.

Accordingly, marketers’ relationships with third-party data are fraught: 64% of marketers would like to reduce their use of third-party data and 68% agree they are reevaluating their third-party data partnerships (see Figure 6). Data Issues Top B2C Marketing Measurement Challenges A bar chart showing respondents’ top challenges that prevent their organizations from making use of measurement and analytics. This graphic has an associated spreadsheet that includes all data presented.

Data governance is effective when it is embedded into operations, supports external data partnerships, and enables data-driven behaviors across the enterprise. Mature organizations link governance efforts to business metrics such as revenue, customer loyalty, and market share, demonstrating that governance is not just a control mechanism but a driver of performance. Operating model. A scalable operating model is essential for consistent governance execution.

In addition to intensive data analysis used to create insights, many providers also supply data hygiene and ingestion services, data partnerships to enhance measurement, measurement education, and change management support to help clients gain internal buy-in and trust in the insights. Marketing professionals engage marketing measurement and optimization services to: Measure incremental marketing effectiveness across channels.

Given the spate of regulatory action around third-party data providers and long-standing quality issues, it’s no surprise that, in 2025, 64% of B2C marketing decision-makers say that they are reevaluating their third-party data partnerships in light of data deprecation. Define Your Firm’s Approach To Evolving Privacy Rules As more jurisdictions introduce new or updated privacy regulations, firms can’t rely on their legal and compliance teams to issue edicts about data processing.

Retailers will continue to invest in machine learning, data partnerships, and new ad formats to improve their retail media offerings and generate an additional revenue stream that helps improve overall profit margins. Global retail media spending will overtake global television ad spending in 2025 and nearly double it by 2030.

Many major AI companies either own social media sites (e.g., Meta, Google) or have data partnerships (e.g., OpenAI with Reddit) that enable access to conversational data. Because genAI is trained on large-scale datasets that include forums and social media discourse, it can reflect and amplify these conversations — making them more visible in AI-generated answers.

Over the next five years, retailers will continue to invest in machine learning, data partnerships, and new ad formats to improve their retail media offerings. Retailers will invest in improving relevance, automation, and self-serve tools — directly or through partnerships — so that brands and agencies can manage onsite campaigns more easily.

Though this has long been Cognism’s core strength, the recency of the changes has contributed to a less developed roadmap than that of most peers and fewer demonstrated areas of data innovation. The company has some valuable strategic data partnerships, but the overall partner ecosystem is not highly developed. Capabilities. In Cognism’s focus areas, its data shines. Superior geographic coverage for contacts and a high volume of email and mobile data are particular strengths.

Scal-e’s understanding of B2B’s critical third-party data enrichment needs shows though its data partnerships and integrations. It has powerful data management capabilities, with out-of-the-box B2B and industry-specific models. Customers can modify these models through a no-code interface. Though the product supports native connectors and customer-specific ML pipelines, the range of its out-of-the-box AI models and workbench capabilities isn’t as expansive as many of its competitors.