Consumers have changed. It’s time for your audience segmentation and studies to change too.
Before Marketers, Customer Insights, Strategy, or other digital decision-makers would rely on traditional panel studies to portray their audience.
The demographic data is limited, consumption trends constantly change (specifically after COVID-19), and the client’s behavior is an emotionally driven decision.
Now, Artificial Intelligence (AI) unveils a 360-degree view of your consumers to:
- Understand your market, sub-segments, and audiences.
- Target a specific audience based on 300+ data points.
- Provide custom advertising and content based on each cluster.
- Acquire these prospects and drive conversions to your ecosystem.
By adding multiple layers and facets to the demographic data you historically relied on, you can bridge the gap between your panel and your online consumers.
How does it work?
1- Triangulation for influencers, VIP, relationship strength and communities
You collect online data and extrapolate all your audiences with the triangulation methodology. The purpose is to increase the study’s accuracy by cross-checking data from multiple sources and social networks.
Triangulation process for social networks (Twitter example)
For influencers, the triangulation technique identifies them because they are following the targeted social accounts. Taking influencer one and two, and comparing their followers allow us to identify influencer three, and so forth.
The VIPs or brand ambassadors will be identified with the same mechanism by looking at the social accounts following them.
Quick overview of the information for any social profile user (Instagram example)
You also qualify the relationship strength and the proximity between your consumers with triangulation.
Then, you can regroup your consumers into thematic communities they belong to (based on topics discussed, hashtags, images, etc.) with the consolidation of insights coming from social data, semantics, sentiment, and visual analysis.
2- Augmented Research with AI
300+ data points for each consumer
AI will reveal consumers’ behaviors, personalities, habits, needs, and lifestyles (…) using 9 AI services. You will be able to answer your key questions with 300+ data points per digital user:
- Who are your consumers?
- What do they love, and how to connect with them?
- What resonates with them?
- What are their buying behaviors?
- What drives their buying decisions?
- What are their interests and brands?
Multi-dimensional consumer insights at scale complementing your traditional studies
Personality Insights
You can analyze millions of online users and text inputs from social media, websites, blogs, forums, reviews, and customer support conversations with big data.
Consumer behaviors are identified at scale with psycholinguistic analysis anticipating 142 traits from the individual’s written language.
You get a deeper understanding of people’s personality characteristics, big five, needs, values, and consumption preferences to help engage online users on their own terms. This powerful psychologic study enriches your group and segment analysis.
Moreover, it will support your client acquisition by designing more efficient campaigns, your retention by offering a personalized message, your marketing agility by deciding on your Next Best Action…
Anticipate 142 personality traits from millions of online users at scale in every language
Demographic data
Quantitative insights from social media lack a formal methodology identifying the traditional demographic variables: age, sex, job, education, location, and more!
AI associated with Human Intelligence and the power of the Internet can reliably assist you in deducing all these consumer variables.
You can easily determine all your segments and groups with a smart combination of different technologies: text analysis, visual recognition, social verification, and manual curation…
Demographic data analysis on sex, age, and location from a smart combination of technologies
3- Clusters and personas
To gather similar consumers into logical groups, you classify them into 4 to 7 clusters. The users with identical key characteristics will be placed into the same cluster.
By doing this, you quickly limit the number of content variations you will build for your advertising campaigns, landing pages, and other assets.
Classify similar consumers into logical groups called “clusters”
In the example above, five personas were built from the clusters, including the following:
- Full social media profile analysis (social statistics, audience, location, paid vs. organic, most relevant tags, hashtags, interests, brands).
- Personality analysis (big 5, basic, human values, fundamentals need, consumption preferences).
- Semantic, visual, and sentiment analysis reflecting the consumer’s mindset.
- Demographic data (age, sex, job, education, location) to grasp the user’s context.
Build your data-driven personas from 300+ variables from each consumer.
You now understand how to target your audience and boost conversions with the personas.
From the initial research to the final activation in your conversion funnel, you follow and measure the performance with identified metrics and KPIs. Intrigued? Let’s get started with NextUser!
