Logic: Weighted Distribution

Weighted Distribution Settings offer a flexible and probabilistic approach to funnel design, allowing you to route contacts across multiple branches based on assigned "weights" rather than strict conditions or random A/B splits. In a system like Groundhogg CRM, this type of logic lets you control the likelihood of a contact following a specific path, with each branch’s weight determining its proportional share of traffic. Unlike Split Path Settings (first-match priority) or A/B Testing (equal or defined splits for comparison), Weighted Distribution introduces a customizable, percentage-like allocation that doesn’t require the weights to sum to 100—though doing so simplifies interpretation. Let’s break it down.

How Weighted Distribution Settings Work

Weighted Distribution operates like a weighted lottery:

• Multiple Branches: You define as many branches as needed—e.g., Branch A, Branch B, Branch C, etc.
• Assign Weights: Each branch gets a numerical "weight" reflecting its relative importance or desired traffic share. For example, Branch A: 50, Branch B: 30, Branch C: 20.
• Proportional Routing: Contacts are distributed across branches based on the weights’ proportions. If the total weight is 100 (50 + 30 + 20), Branch A gets 50% of the traffic, Branch B gets 30%, and Branch C gets 20%. If the total isn’t 100—say, 80 (40 + 30 + 10)—the proportions adjust accordingly (50%, 37.5%, 12.5%).
• Randomized Assignment: Unlike condition-based routing, the distribution is probabilistic, with higher-weighted branches receiving more contacts over time.

In Groundhogg, this might appear as a Weighted Split or custom distribution step, where you input weights and let the system handle the proportional allocation.

Example in Groundhogg CRM

Here’s how you might configure Weighted Distribution Settings:

1. Setup: Add a Weighted Distribution step in your funnel.
2. Define Branches and Weights:
   • Branch A: "Premium Offer Email" – Weight: 50
   • Branch B: "Standard Offer Email" – Weight: 30
   • Branch C: "Educational Content Email" – Weight: 20
3. Total Weight: 100 (for simplicity), so Branch A gets 50% of contacts, Branch B gets 30%, and Branch C gets 20%.
4. Execution: As contacts enter the funnel, they’re randomly assigned based on these weights—over time, roughly half will receive the premium offer, 30% the standard offer, and 20% the educational content.

If the weights were 40, 30, and 10 (total 80), the distribution would adjust to 50%, 37.5%, and 12.5%, respectively.

Benefits of Weighted Distribution Settings

• Customizable Control: You decide the exact proportion of traffic each branch receives, unlike A/B’s fixed splits or condition-based routing.
• Scalability: Add as many branches as needed without worrying about complex condition logic.
• Balanced Experimentation: Test multiple strategies simultaneously with intentional emphasis on certain paths (e.g., favoring a proven winner).
• Simplicity: No need for intricate conditions—just set weights and let probability do the work.

Practical Use Cases

1. Offer Distribution: Send 60% of contacts a high-value offer (Weight: 60), 30% a mid-tier offer (Weight: 30), and 10% a low-tier offer (Weight: 10).
2. Content Variety: Distribute blog subscribers across topics—50% product updates (Weight: 50), 30% tutorials (Weight: 30), 20% industry news (Weight: 20).
3. Support Routing: Assign support tickets—50% to Team A (Weight: 50), 30% to Team B (Weight: 30), 20% to Team C (Weight: 20)—based on capacity.
4. Gradual Rollouts: Test a new campaign on 10% of contacts (Weight: 10) while 90% follow the existing flow (Weight: 90).

Tips for Effective Weighted Distribution

• Use 100 for Clarity: While the total weight doesn’t need to be 100, summing to 100 makes percentages intuitive (e.g., Weight 25 = 25%).
• Align Weights with Goals: Assign higher weights to branches you want to prioritize, like a high-converting offer or a critical funnel step.
• Monitor Distribution: Check Groundhogg’s analytics to ensure the actual split matches your intended proportions over time.
• Start Simple: Begin with 2-3 branches and refine weights based on performance before scaling up.
• Adjust Dynamically: If one branch underperforms, tweak its weight to redirect traffic elsewhere.

Challenges to Watch For

• Randomness Variability: With small sample sizes, the actual distribution might not perfectly match the weights (e.g., 10 contacts with weights 50/30/20 might not split 5/3/2 exactly).
• Lack of Conditions: Since it’s probabilistic, it doesn’t account for contact-specific data like Yes/No or Split Path logic does.
• Analysis Complexity: Tracking performance across multiple weighted branches requires clear metrics and patience for trends to emerge.
• Over-Weighting: Too many branches with small weights can dilute focus—keep the setup purposeful.

Comparison to Other Logic Types

• Vs. Yes/No Logic: Yes/No uses conditions for binary routing; Weighted Distribution uses weights for proportional randomness.
• Vs. Split Path Settings: Split Paths assign based on the first matching condition; Weighted Distribution splits traffic probabilistically across all branches.
• Vs. Split (A/B) Test: A/B Testing compares two branches with a win condition; Weighted Distribution allocates traffic without a specific “winner” in mind, though you could analyze results post-hoc.

In summary, Weighted Distribution Settings in Groundhogg CRM give you a dynamic way to allocate contacts across multiple branches using customizable weights. Whether you set the total to 100 for simplicity or let the system calculate proportions from any sum, this approach excels at balancing traffic, testing variations, or prioritizing paths without rigid rules. Want to design a Weighted Distribution setup? Tell me your branches and goals, and I’ll help you assign the perfect weights!