Using Behavioral Modeling to Engage Customers Throughout the Decision-Making Process

  • Published on
    07-Nov-2014

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DESCRIPTION

Presented at Integrated Marketing Week 2014 Richard Warnaka, manager of UX, Cabela's Shane Johnston, lead experience planner, EffectiveUI As retailers look to understand their customers, they often turn to tools like market segmentation and personas to better understand the different types of user groups within their target market. But this approach often overlooks the different stages a consumer goes through in making purchasing decisions. Behavioral Modeling seeks to construct a universal representation of behavior: information is collected on the context, social structure, previous experience and emotion of a behavior. This session explores why this approach was invaluable for Cabelas, where working together with EffectiveUI the company uncovered the different stages its customers went through as they shopped. By understanding these various phases of decision-making, the company identified some new opportunities to provide meaningful engagement during the process to help guide customers decisions. During the session, we will cover: How to conduct effective behavioral research Turning behavioral models into actionable design Key lessons learned throughout the process

Transcript

1. Behavioral Modeling: Engaging Customers Throughout the Decision-Making Process Rich Warnaka Shane Johnston @IM_WEEK #IMWeek 2. INTRODUCTIONS Shane Johnston Lead Researcher Effective UI Rich Warnaka UX Manager Cabelas 3. OVERVIEW 1 Background and Context 2 Why Behavior? 3 Behavioral Modeling in Practice 4. CABELAS Founded in 1961 Cabelas is the worlds largest direct marketer of hunting, fishing, camping, and related outdoor merchandise. 5. CABELAS : Context Growth of the direct online channel. Total Revenue = $3.6 billion Direct Sales through Cabelas.com and Cabelas.ca = $1 billion (%27.7) Multi-channel experience. 55 Retail Stores throughout North America. Data rich helps explain what happens. Cabelas CLUB = 1.7 million card holders Little understanding of why it happens. 6. CABELAS : Intelligence Gaps The Persona Problem Market Segment Centric Stagnant Artifacts Fluff Factor - Conjecture Requires Organizational Buy-In Behavioral Flexible Factual Intuitive 7. BEHAVIOR & INSIGHT Humans are not (completely) rational actors. 8. BEHAVIOR & INSIGHT Behavioral Determinants Heuristics Either learned or hard-coded rules of thumb. Previous Experience Tacit knowledge gained through practical experience. Emotional Affect The valence, responsiveness to stimuli, and motivational intensity. Context The environmental and situational conditions. 9. BEHAVIOR & INSIGHT Behavioral Modeling A strategic framework for identifying behavioral commonality across customer segments. 10. IN PRACTICE Modeling Objectives 1 Model common behavioral patterns for a given condition (shopping). 2 Map behavioral determinants and customer touchpoints against the model. 3 Identify gaps in the customer experience. 11. IN PRACTICE The Current Model 12. IN PRACTICE Behavioral Model Shopping 13. IN PRACTICE Components Patterns Identifiable regularity in customer behavior. Thresholds The point at which a small change in conditions transitions a person to another stage or model in the shopping/hunting lifecycle. Contexts The environmental and situational conditions (including social structures). Touchpoints Points of interaction with the company/brand. Roles Patterns of behavior across the model. 14. IN PRACTICE Key Learnings 1 Shopping is not a linear process. 2 Design experiences that support our customers behaviors. 3 Segmentation alone provides a one dimensional view of customers. 4 We should recognize that there are different roles throughout the process. 15. IN PRACTICE Paradigm Shift The customer does not live for your company, your company lives for the customer. 16. IN PRACTICE Use within Cabelas Foundational for more traditional types of research, analysis, and strategic efforts: 1Journey Mapping of specific experiences. 2Focus for ethnographic and contextual inquiry research efforts. 3Provides filter for priorities and site architecture. 17. CONCLUSION Thanks! Richard.Warnaker@cabelas.com Cabelas.com Shane.Johnston@effectiveui.com EffectiveUI.com

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