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A number of catalysts can trigger social media channels to change algorithms. These include evolving consumer behavior, new buying trends and fresh platform features. These data-driven adjustments may take the form of small refinements or sweeping overhauls. And they can confound brand marketers’ plans, especially since the nature of the changes can’t be predicted and the timing remains equally hard to forecast. The best hope for marketers: Remaining informed about algorithm revisions. This allows them to modify their content strategies and continue to effectively reach their prime targets.
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Social media platform algorithms rank marketing content according to relevancy, personalization, interactivity and freshness, among other criteria. Changes in those rankings could result in any number of negative impacts on marketing efforts. A brand’s organic reach might decline, leaving posts much less visible. Information may be prioritized differently, spurring users to interact differently with brand content. Focus could be shifted from one kind of content to another, such as from pictures to videos, inflicting a setback on brand marketing dependent on still images.
Let’s now turn to specific examples of how and why certain social media channels changed their algorithms, demonstrating the unpredictability of such actions.
- Facebook facts. Confronted with decreasing organic reach, Facebook recently responded with changes that ensure its new feed displays greater numbers of updates from friends and family, as opposed to Facebook ads or pages followed by visitors.
- Google guide. Recent Google algorithm updates focused on ensuring visitors connect to increasingly “high-quality sites,” among them small or independent sites with useful, original content. Updates also aimed to better capture improvements in these sites.
- YouTube yields. Giving in to trends, the YouTube algorithm started with prioritizing clicks before switching to prizing video watch time. After loopholes were exposed in each algorithm, the site settled on gathering data from users and suggesting videos.
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