In the world of digital marketing, few expressions generate as much controversy as vanity metrics. These are indicators that measure the superficial popularity of content or profiles on social media, such as the number of followers, views or likes. At first glance, they seem like great achievements. However, their true value in social media data analysis is often called into question.
What are vanity metrics?
By definition, vanity metrics are easy to measure but not very useful for understanding the real impact of content on the business. These include:
- Number of followers on social media.
- Number of visits to a website.
- Video views.
- Likes or reactions to a post.
This data is ubiquitous because any digital platform offers it free of charge and in real time. Its appeal is immediate: it allows us to show what we would call ‘quick wins’ in our client reports. However, the problem arises when it is confused with strategic indicators.
Why are they raising doubts?
The main reason is that they are not usually directly related to sales, business objectives or reputation goals. There are many examples: influencers with millions of followers who cannot sell even a few T-shirts, brands that accumulate likes without converting their followers into customers, or companies that achieve very large communities and high interaction, but are mostly criticised by those followers.
Vanity metrics have other drawbacks:
- They are ambiguous: they do not mean the same thing on all networks. A comment on TikTok does not have the same value as on LinkedIn, where identity is verified and exposure is professional.
- They can be easily inflated: the purchase of fake followers or bots remains a widespread practice.
- They hide what is important: while likes are celebrated, critical metrics such as ROI, customer acquisition cost (CAC) and lifetime value (LTV) are overlooked.
Are they useful?
Despite the criticism, it is not advisable to dismiss them entirely. Some experts prefer to call them optimisation metrics, because they serve to improve the optimisation of content and campaigns.
A thorough analysis of these metrics can reveal, for example:
- What type of posts generate the most interest among the audience.
- What formats drive interaction (short video, carousel, stories, reels)?
- At what times of day is your community most active?
- Which messages generate conversation, although not necessarily sales.
In this way, vanity metrics function as a gauge of superficial engagement which, when used correctly, helps to make tactical decisions.
The impact of generative artificial intelligence on vanity metrics
Over the past two years, the emergence of generative artificial intelligence (AI), with tools such as ChatGPT, Midjourney, and Sora, has changed the landscape of vanity metrics. Why not?
- Mass content production: thanks to AI, it is now easier to generate videos, posts, or images in large quantities. This increases competition on social media, and therefore likes or views become an even more inflated resource.
- Artificial engagement: profiles that use automatically generated content to attract followers and increase interactions are proliferating, often without a clear commercial purpose.
- Greater need for quality metrics: faced with the noise generated by AI, brands are forced to look beyond the number of likes. It is essential to measure the quality of interaction (relevant comments, mentions, qualitative shares) and, above all, the impact on sales or reputation.
- Predictive personalisation: on the positive side, AI allows for smarter analysis of vanity metrics. For example, machine learning models can be used to identify which superficial interaction patterns anticipate actual purchasing behaviour.
In short, generative AI is putting pressure on the value of vanity metrics, forcing us to separate digital noise from data that really contributes to business.
How to integrate them into your strategy without falling into the trap
The key is not to ignore vanity metrics, but to put them into context. Some practical recommendations:
- Define clear business KPIs before looking at likes.
- Use them as secondary data to help you understand the behaviour of your community.
- Analyse trends, not absolute values: evolution is more important than a static number.
- Contrast with qualitative metrics: review the quality of comments, the source of traffic, or interaction on professional channels.
- Integrate advanced analytics tools (with AI) to detect correlations between superficial interactions and actual conversions.
And if in doubt, call us!
