> ## Documentation Index > Fetch the complete documentation index at: https://docs.innkeepr.ai/llms.txt > Use this file to discover all available pages before exploring further. # Choosing a Use Case 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: from the four business goals above evaluating which signal strategy aligns with your specific needs and what additional events you'll need to collect and which destinations require audience vs. conversion signals 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 Case | Signal | Strategy | | :------------------------------------------------------ | :----------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------- | | **Build seeds based on predicted ad impact** | Audience signals | Generate seed audiences from users with high predicted responsiveness to campaigns—creating larger, higher-quality seeds even with limited conversion data | | **Exclude recent purchasers or converters** | Audience signals, Exclusions | Suppress users with recent conversions to reduce overlap and improve seed purity for prospecting campaigns | | **Tune conversion values based on predicted ad impact** | Conversions signals | Weight conversion values by incremental contribution so platform bidding algorithms optimize for true acquisition impact | | **Predict signup likelihoods to grow user base** | Audience signals | Process behavioral signals (session depth, engagement) to model signup intent and generate predictive seed audiences | | **Identify high-value customers** | Audience signals, Exclusions, Conversion signals | Build 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 Case | Strategy | | :--------------------------------------------- | :----------------------------------------------------------------------------------------------------------------- | | **Exclude low LTV visitors** | Identify visitors with low predicted monetization potential and suppress them from retargeting before spend occurs | | **Pre-qualify traffic before retargeting** | Filter based on session quality or engagement signals to limit retargeting to high-intent visitors only | | **Suppress low-propensity app installs** | Exclude users with low predicted install likelihood based on behavioral or contextual signals | | **Filter cart abandoners unlikely to convert** | Segment cart abandoners by recovery probability and suppress those unlikely to complete purchase | | **Suppress low signup intent** | Remove users with weak behavioral indicators from signup-focused campaigns | | **Suppress churn-prone free users** | Prevent 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 Case | Strategy | | :---------------------------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------- | | **Target customers with next-best offer** | Process purchase history and product affinity to identify cross-sell or upsell opportunities and generate signals for personalized follow-up campaigns | | **Accelerate first purchase** | Optimize signals for users in early journey stages to drive faster time-to-first-purchase | | **Promote first-time offers** | Generate audience signals for new users most likely to respond to incentives (discounts, free shipping) | | **Convert browsers to buyers** | Identify high-intent product viewers and create signals that prioritize them in retargeting campaigns | | **Recover abandoned carts** | Detect and signal users who abandoned carts with high recovery probability for urgency-based messaging |