Helsinki, Finland (November 26th, 2024) NinaData, an innovator in contextual advertising solutions, today announced its partnership with VU Compare, the UK’s number one car lease comparison platform. This partnership aims to offer VU Compare unparalleled precision in keyword search to display audience targeting.
NinaData’s unique WordIntent Platform technology addresses the mounting problem of high cost-per-click (CPC) in SEM by harnessing its proprietary Generative AI approach and Large Language Model. Rather than relying on keyword bidding in search engines, WordIntent enables advertisers to reach audiences with high purchase intent by aligning ads with relevant, contextual content across the web. This approach provides a more cost-effective alternative to Google’s search ads, avoiding the limitations and high CPCs associated with traditional SEM.
VU Compare, known for its leading position in the UK car lease comparison space, serves thousands of consumers looking to secure competitive car leasing deals. This partnership gives VU Compare access to NinaData’s unique approach to contextual ad targeting, offering an efficient, lower-cost alternative to traditional search engine marketing.
“It is increasingly challenging to achieve a profitable return on search engine marketing (SEM) investments, especially as competition on high-demand keywords pushes costs ever higher,” says Valtteri Pukander, CEO at NinaData. “Our partnership with VU Compare addresses this head-on, enabling them to benefit from SEM-level precision at a fraction of the cost through contextually targeted display ads.”
Using WordIntent, VU Compare can use their same search ad creative, keyword lists, and valuable keyword intelligence to reach users with high purchase intent outside of the search ecosystem. NinaData leverages search ad creative in display ad inventory for greater visibility and matches ad creative, landing page, and web page for greater relevance and performance.
In early tests with VU, NinaData’s precision targeting demonstrated outstanding results, achieving a tenfold increase in return on investment (ROI) and outperforming traditional display advertising approaches through optimized URL-level targeting powered by semantic search, exact keyword matching, and advanced purchase intent analytics.
“We’re not trying to recreate the specific intent of a search query tied to high cost-per-click (CPC) keywords but to target highly relevant content and display ad inventory at much lower effective CPCs compared to search engines. In effect, VU Compare can spend significantly less on display advertising than they otherwise would in search engine marketing. NinaData enables them to target high purchase-intent content with their most valuable keywords and achieve outsized returns on their marketing spend,” continues Pukander.
“Partnering with NinaData has been a game-changer for our digital advertising strategy. We saw a significant drop in our cost-per-click (CPC) while achieving a much better cost-per-acquisition (CPA). The results speak for themselves – Ninadata has helped us drive more conversions efficiently and effectively. We couldn’t be more thrilled with the performance!” said Hannah Geer, Loud New Media.
NinaData WordIntent has been designed and integrated into its custom-built demand-side platform (DSP) with a number of features and a roadmap for continuous innovation:
– Precise keyword-level page analysis: Continuous page-level analysis of URLs across the web and in programmatic bid requests that exhibit the strongest purchase intent with specific keywords.
– Real-time semantic targeting: Real-time semantic targeting that deconstructs web page “meaning” at the word level to improve performance against display ad inventory based on meaning, sentiment, influence, authority, and emotional connection.
– Exact-match keyword-targeting: Exact-match keyword-targeting, with the strongest semantic disambiguation where multiple meanings exist, on highly relevant web pages.
– Cost-effective and high-quality engagement: High-intent audiences for branding, clicks, or conversions at a fraction of the cost of high-demand keywords in search engine bidding.
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