Sales Plays and Patterns

Owner: Field Enablement / Sales Strategy

App Archetypes Seeing Traction

Three distinct patterns of apps are gaining adoption:

flowchart LR
    subgraph Archetypes["APP ARCHETYPES"]
        BC["🎯 BUSINESS COCKPIT<br/>Full analytics stack<br/>for executives"]
        DV["🔬 DEEPLY VERTICAL<br/>Industry-specific<br/>AI-powered"]
        HZ["🛠️ HORIZONTAL<br/>Platform productivity<br/>tools"]
    end
    
    BC --> BusBuyer["Business Exec Buyer"]
    DV --> DomainBuyer["Domain Specialist Buyer"]
    HZ --> PlatformBuyer["Platform Team Buyer"]

Archetype 1: Business Cockpit Apps

Definition

An application that gives business persons a clear understanding of their business across the analytics maturity spectrum.

The Analytics Maturity Stack

flowchart TB
    subgraph Cockpit["🎯 BUSINESS COCKPIT APP"]
        P["PRESCRIPTIVE: What should be done?"]
        S["SIMULATIONS: Plan for scenarios?"]
        PR["PREDICTIVE: Where is business going?"]
        C["CAUSAL: What is causing current state?"]
        D["DESCRIPTIVE: Where is business now?"]
        
        P --> S --> PR --> C --> D
    end
    
    Cockpit --> Value["Business users get FULL VISIBILITY<br/>without SQL skills"]

Characteristics

Example Use Cases

• Executive dashboard with scenario planning
• Operations command center with anomaly detection
• Sales forecasting with prescription recommendations
• Supply chain visibility with risk simulation

Archetype 2: Deeply Vertical Apps

Definition

Applications that address a deep pain point for a customer or completely disrupt a process for specific industry tasks.

Characteristics

Example Use Cases

Archetype 3: Horizontal Apps

Definition

Applications that improve productivity within the platform for existing users OR reduce the barrier of entry for new user segments.

Characteristics

Example Use Cases

Guided Selling Triggers

Why Guided Selling Matters

FE often doesn’t recognize Apps opportunities even when present. These triggers help identify when to bring Apps into the conversation.

Conversation Triggers by Archetype

Account Signals to Watch

Sales Objection Framework

Objection 1: Money

“Will this product make money for me?”

Objection 2: Mindshare

“Too many products to position—why lead with Apps?”

Objection 3: Maturity

“My customer isn’t ready, or the product doesn’t fit.”

Objection 4: Product Limitations

“The product has gaps that block my customer’s use case.”

When to Walk Away (For Now):

• Customer needs external-facing apps with internet exposure
• Customer needs horizontal auto-scaling for burst traffic
• Customer is highly cost-sensitive with variable workloads

Use Case Qualification Framework

Fit Assessment Questions

1. Is the use case net-new or migration?
   • Net-new → Good fit
   • Legacy migration → Not ready yet
2. Does it leverage Databricks data gravity?
   • Data already in Lakehouse → Strong fit
   • Requires new data onboarding → Okay fit
   • Data in competitor platform → Weak fit
3. Does it require AI/ML?
   • Yes, AI-powered → Differentiator
   • No AI needed → Still fits, but weaker moat
4. Who is the end user?
   • Business users → Good (expands addressable market)
   • Technical users only → Okay (platform extension)
5. What’s the governance requirement?
   • Strict governance needed → Strong fit (moat)
   • Loose governance → Less differentiated

Actions for Field Enablement

Last Updated: January 2026