In a previous article, we explored the art of customer curation, detailing a strategic approach that allows companies to identify and cultivate relationships with those customers who truly drive growth. Now, we will expand this perspective to address the concept of audience curation. While customer curation focuses on optimizing existing relationships with customers for whom we have some type of registered and manageable data through a database, audience curation encompasses a broader spectrum, from identifying potential customers to creating engaged communities around a brand. Today, AI plays a fundamental role in this process, allowing companies to understand and connect with their audiences in a deeper and more personalized way. In this article, we will delve into the power of AI to drive audience curation, exploring how new technologies can transform the way companies interact with their target audience.
Vanity metrics: The mirage of success
In the world of audience campaigns, vanity metrics are like a mirage in the desert: some results data may seem impressive at first glance. These are superficial indicators that, while they may generate a sense of satisfaction for the Marketing leader, do not necessarily translate into tangible results for the business. Some examples that can be mentioned are the following:
Paid ads: Impressions, reach, clicks, video views.
Organic Search Engine Optimization (SEO): Organic traffic, search result rankings, number of keywords ranked.
Social media: Followers, likes, comments, shares.
These metrics can be useful for measuring the reach and visibility of a campaign, but they do not offer a complete view of its real impact nor do they confirm that we are impacting the right audience according to business objectives. For example, an ad can generate thousands of impressions, but if it does not translate into conversions (sales, registrations, downloads, etc.), its value to the company is limited.
Therefore, it is essential to go beyond vanity metrics and use AI-powered tools to curate audiences accurately and efficiently, an art that is based on value criteria that drive tangible results.
MQL and SQL: Key criteria for B2B Inbound Marketing
In the context of B2B Inbound Marketing strategies, which is not entirely applicable to audience management due to lack of data, the criteria for identifying and qualifying leads are as follows:
MQL (Marketing Qualified Lead): AI analyzes users' online behavior, such as website visits, content downloads, or social media interaction, to determine their level of interest and engagement.
SQL (Sales Qualified Lead): AI evaluates demographic and firmographic characteristics, such as company size, industry, or job title, to identify those leads with the highest conversion potential.
While the concepts of MQL and SQL originated in B2B Inbound Marketing, their essence can be adapted and applied to audience management in paid campaigns, social media, and SEO, leveraging the power of AI to optimize results.
Trust or engagement (MQL) could be assessed in AI-powered audience management by evaluating audience engagement across different channels:
Paid ads: AI analyzes clicks, video view time, form interactions, and other actions that indicate interest in the product or service.
Social media: AI evaluates likes, comments, shares, link clicks, and other interactions that show affinity with the brand or content.
SEO: AI analyzes user behavior on search engine results pages (SERPs), such as clicks on organic results, time on page, and bounce rate, to identify those users most likely to become potential customers.
The same approach used for SQLs could be applied in audience management to leverage demographic and interest information available on advertising platforms and social media to identify those users who fit the ideal customer profile:
Paid ads: AI uses demographic data (age, gender, location) and interests to segment the audience and show relevant ads to those users with the highest conversion probability.
Social media: AI analyzes users' profile data, such as interests, groups they belong to, and pages they follow, to identify those with the highest purchase potential.
SEO: While demographic information is not directly available on SERPs, AI can analyze user behavior on the website (pages visited, time spent, etc.) to infer their interests and demographic characteristics.
By combining this data, it is easier to optimize campaigns in real-time, adjusting segmentation, messaging, and offers to maximize ROI. For example, AI can identify that users who interact with certain types of content on social media have a higher conversion probability and adjust the content strategy accordingly.
The future of audience curation with AI
Artificial intelligence is redefining the marketing landscape, allowing companies to go beyond superficial metrics and delve into the essence of their audiences. AI's ability to analyze customer behavior across multiple touchpoints, from ad clicks to social media interactions, provides unprecedented insight into their preferences, needs, and motivations.
With this information, AI can create incredibly accurate audience segments, grouping users based on shared characteristics and behavior patterns. This allows companies to design highly personalized campaigns that resonate with each individual, maximizing impact and return on investment.
But personalization doesn't stop there. AI can also automate the delivery of personalized messages across different channels with automated communication platforms, ensuring that each user receives the right content at the right time. Whether it's an email with product recommendations based on purchase history, a social media ad highlighting the most relevant features for a specific segment, or a personalized offer on the website, AI enables the creation of unique and relevant experiences for each user.
This advanced personalization not only improves customer satisfaction but also drives loyalty and long-term engagement. By feeling understood and valued, customers are more likely to interact with the brand, make repeat purchases, and recommend it to others.
In summary, AI-based audience curation is the future of marketing. Those companies that adopt this technology will be better positioned to build strong and lasting relationships with their customers, drive growth, and achieve success in the competitive digital world.
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