The customer data profile is the collection of multiple data sources into one clear asset. This profile tells why customers buy, their behavioral data around those purchases, and more. With customer data profiles in hand, organizations can better understand what the customer needs to deliver more insights-driven experiences.
Staying relevant today requires this level of understanding of the customer. Organizations can leverage these profiles to aggregate multiple data points into one cohesive view. This unified view allows teams to gain access to a more firm foundation to examine and understand the ultimate question behind revenue operations — why do customers buy, and how do you keep those customers for longer?
A Unified View of Customer Behavior
The proliferation of technology has shifted the customer journey. No longer is it as predictable of a process. Today’s customers are far more complex with how they move from email to social media, online advertising, and numerous other digital touchpoints.
Navigating these touchpoints requires a sound strategy as customers decide on their purchase. With a customer data profile, organizations can bring all of this scattered data into one unified view to draw behavioral insights into why consumers buy and engage with a brand.
Aggregating the data into one customer data warehouse is only the first step. Pulling first, second, and third-party data streams together to extract insights allows teams to create a more organized, dynamic view. That view can then be used alongside a strategic framework to infuse a human touch and generate a lasting impact.
Getting to the “Why”
Quantitative metrics only tell part of the story about why your customers decide to buy. Qualitative data paired with deep-rooted empathy, multiparty data, and path-to-purchase data are all required to uncover specific gaps in the buyer’s experience. With this data, organizations are more equipped to make strategic decisions that will stir the pot emotionally and logically within their customers.
Empathy mapping exercises can be backed into a customer data profile to uncover what’s driving customer behaviors and motivations. This asset helps simplify the complex through a more intimate understanding of your customer personas. Supplementing quantitative data with qualitative findings allows companies to approach problem-solving more empathetic and customer-centric manner.
In turn, organizations become equipped to create more sustainable revenue streams.
Applying Your Findings to a Framework
Customer experience cannot be treated as a one-off initiative. Knowing why customers choose one brand over another and why they stay is one thing. Executing those insights requires a framework to solve specific initiatives within the larger context of your business. Here’s why we choose StoryVesting for this framework.
The brand’s story, or why they get started, must align with the customer’s data profile findings to generate a corresponding emotion. When there’s an emotional response to a brand, it’s easier for a company to meet customer expectations and build strong cognitive associations. Brand stories create customer certainty in purchase decisions, which translates to a healthier bottom line overall.
A customer data profile gives organizations the insights to lift those brand experiences. When paired with a strategic framework like StoryVesting, companies can keep the guardrails up as changes get implemented, keeping the business on course and moving in the right direction.
Reaching for Brand Euphoria Through CX Led Growth
The further apart the brand’s experience is from the customer’s, the further into No Man’s Land organizations get. It’s here where businesses slip backwards, ultimately losing touch with the market and causing growth to suffer. The closer the two circles align, the more euphoric that customer experience becomes, building immersive experiences that inspire deep emotive and cognitive associations, as well as pivotal triggers at each stage of the journey.
Customer Experience (CX) Terms
- 360° Degree View of the Customer
- AI Ops
- Barlow Bands
- Behavioral Triggers
- Bow Tie Funnel
- Brick-to-Click
- Business Impact Analysis (BIA)
- Cognitive Computing
- Cohort Analytics
- Content Mapping
- Conversational User Guidance
- Customer Data Profile
- Customer Experience (CX)
- Customer Friction
- Customer Insights Map
- Customer Journey
- Customer Journey Mapping
- Customer Satisfaction (CSAT)
- Customized Ratios
- CX Intelligence
- CX Led Growth
- CX Metrics
- Data as a Product (DaaP)
- Data as a Service (DaaS)
- Data Culture
- Data Driven
- Data Engineering
- Data Fabric
- Data Governance
- Data Humanization
- Data Hygiene
- Data Looping
- Data Mapping
- Data Mining
- Data Modeling
- Data Monetization
- Data Swamp
- Data Visualization
- Data Warehouse
- Data-Centric
- Descriptive Analytics
- Diagnostic Analytics
- Digital Asset Management (DAM)
- Digital Transformation
- Dirty Data In Dirty Data Out
- Embedded Intelligence
- Empathy Mapping
- Employee Data Profile
- Employee Experience (EX)
- EX to CX Data Mapping
- EX to CX Mapping
- Experience Management (XM)
- Gap Analysis
- Generative AI
- Human-Centered Design (HCD)
- Journey Analytics
- Machine Learning (ML)
- Managed Agile Services on Demand
- Modified Hoshin
- North Star Metric
- Party Data
- Pathway to Purchase
- Predictive Analytics
- Product-Market Fit Mapping
- Real Time Design Looping
- Revenue Acceleration
- RevOps
- S Curve of Growth
- Stack Impact Analysis
- StoryVesting
- Table Stakes Testing
- The 3 P’s
- User Experience (UX)
- User Insights Map
- User Interface (UI)
- Voice of the Customer (VoC)
- Voice of the Employee (VoE)
- World Cloud Generator Sentiment Mining
- X Analytics