Many retailers with limited budgets often find variants of their SKU have less conversion data. Machine learning algorithms struggle with SKUs with sparse data - they can't make valid changes to your bids.
We've found a way around this stumbling block. Our Product Data Scientists have developed 'search term sharing' to enhance our existing machine learning technology.
Search term sharing enables you to 'share' converting search terms from similar or identical products from your own catalogue with their own wealth of performance data.
Dr Matthew Dale explains the technology in more detail below.
The search term sharing feature marks a significant advancement in Bidnamic’s Google Shopping Ads product. By facilitating the sharing of successful search terms across products and breaking language barriers, it offers retailers a robust tool to optimise their advertising strategies.
The results obtained from implementing our product underscore its capability to optimise Google Shopping strategies, maximise revenue, enhance conversions, and significantly increase product visibility - all while maintaining a cost-effective approach.
This holistic approach ensures that our clients achieve optimal performance across key metrics, solidifying their success in the competitive global online marketplace.