This article from Traction Marketing NZ examines the efficacy of manual bidding strategies for LinkedIn advertising. It begins by defining manual bidding, emphasizing the direct control it grants advertisers over their bid amounts for specific ad placements and target audiences. However, the core of the article argues that this granular control often comes at the cost of efficiency and performance when compared to LinkedIn's automated bidding options. The piece elaborates on the advantages of automated bidding, explaining that these strategies utilize machine learning to dynamically adjust bids in real-time, aiming to achieve campaign objectives such as maximizing conversions or clicks. It posits that LinkedIn's sophisticated and constantly evolving algorithm is better leveraged by automated systems, which can adapt to the complexities of the auction environment more effectively than manual adjustments. While acknowledging that manual bidding might have niche applications for highly experienced advertisers with very specific needs or for testing purposes, the article strongly suggests that for the majority of users, automated bidding is the superior choice. This recommendation is based on the potential for automated bidding to deliver better results and greater efficiency by continuously optimizing ad spend in response to market fluctuations and platform learning.