Performance Analytics
How do you optimize LinkedIn ads?
To optimize LinkedIn ads, work methodically down the funnel starting with your offer and audience. Ensure your offer is compelling to your target audience, then create eye-catching ads that stand out from competitors. Aim for click-through rates of 0.8-1% (above the average 0.4%) and engagement rates above 0.7%. Maintain coherency between your ads and landing pages to provide a seamless user experience. Analyze landing page conversion rates (ideally 1-4%) and implement effective scheduling to increase show-up rates for consultations. Don't immediately blame marketing if leads aren't converting—examine each step of the funnel systematically to identify and fix bottlenecks in sequence.
Watch clip answer (19:07m)
John Stewart Marketing 🚀
00:00 - 19:07
What are the different methods of LinkedIn Ads conversion tracking and their benefits?
LinkedIn Ads offers three main conversion tracking methods. Online conversion tracking uses cookies and third-party data to track website actions, forming the foundation that 90% of advertisers begin with. Offline conversion tracking connects your CRM data to LinkedIn through their conversion API, allowing you to track qualified leads and deal values, though limited to a 90-day window. The new Data Driven Attribution model provides a holistic view of performance across the customer journey, moving beyond just last-click attribution to show how campaigns contribute to conversions at different stages. Each method has complementary strengths for measuring advertising effectiveness.
Watch clip answer (18:26m)
Ben B2B
00:00 - 18:26
What topics were covered in the LinkedIn Ads Radio masterclass series?
The LinkedIn Ads Radio masterclass covered a comprehensive range of topics essential for LinkedIn advertising success. Episodes included an introduction to LinkedIn ads and marketing funnel planning, setting up company profiles, creating first campaigns, mastering targeting, crafting compelling ad copy and design, optimizing campaigns through analytics, and finally scaling strategies. The host emphasizes that this foundation provides advertisers with essential knowledge while future episodes will feature expert interviews and deeper dives into specialized topics like organic LinkedIn, B2B marketing, copywriting, and AI tools.
Watch clip answer (02:16m)
Speedwork Social - LinkedIn Ads Agency
13:31 - 15:47
Why is leveraging analytics important in recruitment?
Leveraging analytics is crucial in recruitment as it enables decision-makers to measure impact and understand what strategies are effective. As one expert notes, "If you can't measure it, you can't manage it," which applies doubly to recruiting. By analyzing data and reviewing reports, recruiters can track performance and make more informed decisions going forward. In today's data age, utilizing analytics allows recruitment professionals to focus resources on successful approaches while eliminating ineffective practices. This data-driven approach forms a key step in optimizing the entire recruiting process and improving hiring outcomes.
Watch clip answer (00:43m)
4 Corner Resources
05:50 - 06:34
What performance management features does Orange HRM offer in its free version?
Orange HRM's free version provides robust performance tracking capabilities that allow managers to monitor employee progress over time, identify top performers, and support underperforming staff. The platform includes a learning management system for training and skill development, along with employee data management that centralizes all information in one location. Additional features include basic reporting tools for analyzing performance trends, organizational charts for understanding team structures, and open-source flexibility for customization to specific business needs. While advanced features like 360-degree feedback are reserved for paid versions, the free offering provides excellent foundational tools for small businesses and startups focused on employee development.
Watch clip answer (01:31m)
HR Toolbox
02:31 - 04:02
What is the difference between field data and lab data in Google PageSpeed Insights?
Field data captures real user experiences by collecting anonymized data from Google Chrome users who visited your site over the past 28 days. It represents actual performance metrics like Largest Contentful Paint and First Input Delay as experienced by your visitors. Lab data (or Lighthouse data), however, simulates a user visiting your page in a controlled environment with specific hardware and network conditions, such as a mid-tier mobile device on a mobile network. While both measure similar metrics, they often show different results because field data reflects real-world usage while lab data provides a standardized testing environment.
Watch clip answer (03:16m)
Rank Math SEO
00:48 - 04:05