Every Engagement starts with a question of WHY?
The question of Why is the starting point for what we do. Knowing that no single discipline owns the answer to the question, we embarked on accumulating the most successful techniques of behavior change, regardless of their theoretical point of view. They result is a unified Model of Why that organized data sets that support these tactics and predicts their success.
But First, A Story:
A Tale of Two Millennials
The Model of Why is the starting point to understanding how people that look alike in most ways, do not think alike on the important things.
“The Urban Uptown Young Accumulators”
Same Lifestage / Millennials
Same Media Usage
Same Income Bracket
“What do you think of when you hear the word ‘green'”?
The Other Thinks:
The Lesson: Demographics tell us who and what we are. But demographics don’t explain why we do what we do. For that, we need to look at other data sets.
We have built a working model of what we know works in behavioral sciences.
Our model detects behaviors that can result in universal benefits to all people. Beyond these universal traits, we know that people develop personalized preferences based upon their unique decision-making styles.
Universal Leads are designed to tap into the sentiments of the general market. Populations can reflect how they are impacted by markets in terms of demographics, marketing, current customers, and other observable behaviors. Often they rely on the skillful application of empathy, complexity of systems, psychological safety and the attributes of the products. These leads are very relevant to impulse decisions.
Data Sets Include:
- Population Data
- Regional Data
- Generational Trends
- Customer Data
- Intuitive Factors
- Product Attributes
Personalized Leads rely on preferences fueled by the unique decision-making styles of consumers. We know they respond to personalization with an openness to the appeal of communities, memberships or influencers. We provide data that supplies insights into these subgroups or even whole marketplaces.
Data Sets Include:
- Instinctual Factors
- Reflective Prompts
- Observable Behavior
- Identity Variables
- Lifestyle Attributes
“PathSight didn’t just build a better mousetrap — their approach is revolutionary. I believe it will have a seismic effect on how marketers engage with consumers from today forward.”
The Better Way
People Centric Communications
The first thing the sender of a message does if figure out the value proposition. In a traditional workflow, this consists of how to present the message to the intended target of the communication, and what to say. The PathSight model starts with the reciever of the message. What do we know from our layers of data about this person? What is their Instinctual Pattern? What are the relevant base markers? From there we generate insights about why a person might be interested in our offer and craft a message that focuses on the wisdom of their Instinctual Pattern.
backed by science
A Validated Model
Over the past 10 years PathSight has conducted an array of primary research studies exploring the relationship between one’s biologic instincts and one’s behaviors, attitudes and affinities. These studies have analyzed more than 80,000 people and the findings are the foundation of the PathSight predictive model, which also includes the rigorous application of outcome based measurement and evaluation methods. The underlying science of PathSight has been very well researched. In fact, the psychometric instruments, theoretical constructs and the capacity to influence behavioral outcomes has been investigated and substantiated in many studies from around the world, including those initiated by the PathSight data science team.
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The hospitality market is an extremely competitive marketplace across an array of factors. Competition for customers, revenue, market share, and loyalty are all subjects of public score cards, stock prices and the judgments of the esteemed rating agencies.