Compare Data Across Functional Modules: Within social media platforms, utilize different functional modules for data verification. For instance, on YouTube, compare the "Number of Subscribers" displayed on the channel homepage with the subscriber data available in the "Audience Insights" module. This includes metrics like subscriber growth trends and geographical distribution. If discrepancies arise between the two sources, further investigation is warranted.
Correlate Content and Audience Data: Analyze the relationship between content engagement metrics (such as video views, likes, and comments) and fan data. For example, on Instagram, if an influencer experiences rapid fan growth but shows low average engagement on posts, this could indicate potential issues, such as the presence of fake followers or other factors leading to data inconsistencies.
Verify Time Series Data: Assess whether data changes over time are logical. On Facebook, examine the correlation between fan growth and content release timing. If there is a substantial increase or decrease in followers during periods without new content or promotional activities, this may suggest data errors or unusual activity, such as account hacking or the purchase of followers.
2. Cross-Platform Data Comparison
Analyze Fan Demographics Across Platforms: Compare the demographic profiles of an influencer's audience on different social media platforms. For instance, if Instagram fans are predominantly women aged 30-40, while TikTok fans are mostly men aged 15-20, such stark differences may raise questions about data accuracy or reflect varying strategies employed by the influencer on each platform.
Evaluate Content Performance Across Platforms: Assess how the same content performs on different platforms. For example, if a product promotional video shows excellent engagement on YouTube but underperforms on Facebook, investigate potential reasons such as audience differences, content format adaptability (e.g., video length and format), or data collection issues.
Compare Promotional Link Metrics: When influencers promote products across multiple platforms using trackable links, analyze traffic and conversion rates directed to product pages. If one platform shows exceptionally high traffic but a low conversion rate, consider whether the issue lies with user quality, link functionality, or data collection inaccuracies.
3. Benchmark Against Industry Data and Competitors
Compare Against Industry Averages: Familiarize yourself with industry data standards and compare influencer metrics accordingly. For example, in the beauty sector, the average conversion rate for product recommendation videos typically falls between 5% and 10%. If an influencer's conversion rate deviates significantly from this range, further verification of the data's authenticity is necessary. Industry benchmarks can be sourced from professional reports and research institutions.
Analyze Competitor Data: Select competitors within the same niche for comparative analysis. In the fashion industry, assess similar influencers based on metrics such as follower count, engagement rates, and content reach. If an influencer's metrics significantly outperform those of competitors, it is essential to investigate the reasons behind this, which could indicate either a unique strategy or potential data anomalies.
Assess Market Trends in Context: Consider how market trends affect influencer data and analyze fluctuations in their metrics in relation to industry developments. For example, in a rapidly growing technology product sector, you would expect an upward trend in both follower counts and conversion rates for relevant influencers. If an influencer's data contradicts these trends—such as stagnation amidst rising market demand—deeper analysis is required to uncover the underlying causes.
