The perfect solution is to serve each user individually. The problem? There are 7 billion of them and complete user data with AI can seem hard
Out of the quantitative data providing behavioral, situational, and transactional information, it’s critical to understand the quantitative information including the psychology of individuals. They have intrinsic traits that can be recognized and used to predict future behavior. Collecting user data with AI helps you get the most out of users’ behavior in an ever-changing consumer’s world. Social media becomes a valuable source to find linguistic signals and predict personal traits. Personality Insights enables a deeper understanding of users’ personality characteristics, needs, values, and consumption preferences. With NextUser, it’s now possible to create hyper-personalized marketing campaigns in omnichannel by delivering 1:1 personalized offers & messages. Social media becomes a valuable source to find linguistic signals and predict personal traits. Personality Insights enables a deeper understanding of user’s personality characteristics, needs, values and consumption preferences. With NextUser, it’s now possible to create hyper-personalized marketing campaigns in omnichannel by delivering 1:1 personalized offers & messages.
Someone’s personnality analysis
Tailoring Marketing in 1:1 according to users’ personality traitsTo enhance engagement and conversation rate it’s to reach the right audience at the right time with the right products and messages. In this case, a creative marketing campaign can enable the content to be determined by intrinsic preferences. Here are a few examples of global segments:
- Extraverts are sensitive to rewards and social attention
- Agreeable users value communal goals and interpersonal harmony
- Conscientious users praise achievement, order, and efficiency
- Neurotic users are sensitive to threats and uncertainty
- Open individuals look for intellectual stimulation and creativity
NextUser was a finalist from among 2,000 competitors for the Extreme Tech Challenge. We demonstrated the future of Artificial Intelligence to Sir Richard Branson at Necker Island in February 2015.
From Richard Branson in 2015 to SAP in 2017It all started 3 years ago at the Consumer Electronic Show in Las Vegas, NextUser was a finalist from among 2,000 competitors for the Extreme Tech Challenge to demonstrate the future of Artificial Intelligence to Sir Richard Branson at Necker Island in February 2015.
Alibris was the 1st commercial use worldwide of the new IBM Watson Personality Insights released in June 2015 – please refer to this PR release. NextUser built a database of 1,250 author quotes to submit more than 800 words for each Alibris author to Watson User Modeling API.
NextUser was selected by SAP in France to show their 4th version of Personality Insights. It’s now possible to determine 94 characteristics as you can see in the profile below of the CEO, Bill McDermott. The data visualization demonstrates the importance of each trait and 25 tips are provided associated with each “Big Five” characteristic.
NextUser was selected by SAP in France to show their 4th version of the Personality Insights tool.
Use cases by industry — from Retail to Finance
The most obvious case is customer care and insights by improving client satisfaction, preventing client retention by offering individualized value, reducing churn with real-time assistance, match agent and client for improved service.
Other possible use cases are:
- Brand Analytics to streamline the marketing strategy, design more efficient promotions and campaigns and facilitate the marketing campaign planning.
- Retail to improve customer segmentation and promotions, predict the next best action and identify quality leads.
- Finance to match advisors to investors in wealth management
From Unilever Clear, to MET Gala in New-York including Adecco for recruitment, we have many use cases that would be interesting for you to consider. Feel free to contact us for more information and references.
2015 Personnality insights – Leveraging cognitive computing and social media data to generate customer insights. Source: IBM Watson
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