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Use Cases provide implementation blueprints for configuring Innkeepr’s signal optimization around specific business objectives. This guide helps you select the use case that aligns with your growth goals and determines how signals flow from your data to your marketing platforms.

Understanding business goals and signal strategies

Innkeepr supports use cases organized into 4 core business objectives:
  • Improve new customer acquisition
  • Suppress spend on unlikely converters
  • Boost retention, upsell, and cross-sell
  • Increase long-term profitability
Each objective requires different signal types, tracking events, and platform configurations. Use cases define these requirements so your signal optimization infrastructure drives the outcomes you need.

Selecting your use case

Follow these steps to identify which use case to implement:
1

Identify your primary objective

from the four business goals above
2

Review associated use cases

evaluating which signal strategy aligns with your specific needs
3

Assess your current tracking

and what additional events you’ll need to collect
4

Consider your platform setup

and which destinations require audience vs. conversion signals
5

Start with your most pressing need

if you’re uncertain—you can expand to additional use cases over time
Your use case selection determines which events to track, how objectives are defined, and which signal types activate in your platforms. Innkeepr’s modular architecture allows you to add use cases as your signal optimization strategy evolves. The following sections detail each business goal and its associated signal strategies.

Improve new customer acquisition

This goal centers on growing your customer base by reaching high-probability new customers. By processing your behavioral data through Innkeepr’s causal engine, you generate audience signals that identify users most likely to deliver incremental acquisition lift—enabling platform algorithms to find similar high-value prospects. Key considerations:
  • Need to lower customer acquisition costs?
  • Want to expand reach into new high-value segments?
  • Looking to drive app installations or signups?
  • Trying to reduce cart abandonment among new users?
Use cases in this category:
Use CaseSignalStrategy
Build seeds based on predicted ad impactAudience signalsGenerate seed audiences from users with high predicted responsiveness to campaigns—creating larger, higher-quality seeds even with limited conversion data
Exclude recent purchasers or convertersAudience signals, ExclusionsSuppress users with recent conversions to reduce overlap and improve seed purity for prospecting campaigns
Tune conversion values based on predicted ad impactConversions signalsWeight conversion values by incremental contribution so platform bidding algorithms optimize for true acquisition impact
Predict signup likelihoods to grow user baseAudience signalsProcess behavioral signals (session depth, engagement) to model signup intent and generate predictive seed audiences
Identify high-value customersAudience signals, Exclusions, Conversion signalsBuild seeds from high-LTV or low-churn segments for lookalike modeling focused on quality acquisition

Suppress spend on unlikely converters

This goal improves efficiency by excluding users with low predicted conversion probability before budget is spent. Exclusion signals reduce wasted impressions, focus spend on high-quality traffic, and lower CAC by refining early-funnel targeting. Key considerations:
  • Seeing high click volume but low conversion rates?
  • Want to avoid paying for low-intent traffic?
  • Looking to improve CAC through better audience filtering?
Use cases in this category:
Use CaseStrategy
Exclude low LTV visitorsIdentify visitors with low predicted monetization potential and suppress them from retargeting before spend occurs
Pre-qualify traffic before retargetingFilter based on session quality or engagement signals to limit retargeting to high-intent visitors only
Suppress low-propensity app installsExclude users with low predicted install likelihood based on behavioral or contextual signals
Filter cart abandoners unlikely to convertSegment cart abandoners by recovery probability and suppress those unlikely to complete purchase
Suppress low signup intentRemove users with weak behavioral indicators from signup-focused campaigns
Suppress churn-prone free usersPrevent remarketing to users showing early churn signals during onboarding or trial periods

Boost retention, upsell, and cross-sell

This goal maximizes value from existing customers by optimizing signals for repeat purchase, product expansion, and long-term engagement. Signals generated for this objective help platforms identify which customers are most likely to respond to retention or expansion offers. Key considerations for this goal:
  • Want to increase purchase frequency from existing customers?
  • Need to prevent churn among high-value segments?
  • Looking to personalize upsell or cross-sell targeting?
  • Want to find new customers who resemble your best repeat buyers?
Use cases in this category:
Use CaseStrategy
Target customers with next-best offerProcess purchase history and product affinity to identify cross-sell or upsell opportunities and generate signals for personalized follow-up campaigns
Accelerate first purchaseOptimize signals for users in early journey stages to drive faster time-to-first-purchase
Promote first-time offersGenerate audience signals for new users most likely to respond to incentives (discounts, free shipping)
Convert browsers to buyersIdentify high-intent product viewers and create signals that prioritize them in retargeting campaigns
Recover abandoned cartsDetect and signal users who abandoned carts with high recovery probability for urgency-based messaging