# RevCent Customer Groups Overview This document gives a broad overview of Customer Groups in RevCent, why they matter for ecommerce businesses, how their detailed qualifiers can create highly granular customer segments, and how customer group events can trigger powerful automated workflows. Customer Groups are not just labels. When configured well, they become a customer segmentation, lifecycle, automation, reporting, and engagement layer for an ecommerce business. --- ## What Are Customer Groups? Customer Groups allow customers to be organized into meaningful segments. A basic group might be simple: ```text VIP Customers ``` ```text Wholesale Customers ``` ```text Payment Recovery ``` But Customer Groups can also be much more powerful. A Customer Group can represent a rule-based customer state, such as: ```text Customers with lifetime value over $500 ``` ```text Customers with 2 or more declined sales ``` ```text Customers who bought from a specific product group ``` ```text Customers with metadata affiliate_id = aff_123 ``` ```text Customers with overdue subscriptions ``` ```text Customers who are in VIP but not in Do Not Contact ``` This means Customer Groups can be used to define precise customer segments based on customer behavior, purchase history, metadata, subscriptions, risk signals, and other customer groups. --- # Why Customer Groups Matter for Ecommerce Ecommerce businesses need to understand and act on customer differences. Not every customer should receive the same outreach, same support priority, same offer, same recovery workflow, or same risk treatment. Customer Groups allow a business to organize customers based on what they actually do. Examples: - High-value customers - New prospects - Repeat buyers - Customers who have not purchased recently - Customers with failed payments - Customers with abandoned sales - Subscription customers - Trial customers - Customers with overdue renewals - Customers with refunds or chargebacks - Customers from a specific affiliate or campaign - Customers who bought a specific product group - Customers who should not be contacted - Customers who need manual support review Once customers are grouped correctly, the group can power workflows across email, AI, voice, support, reporting, revenue recovery, and third-party tools. --- # Customer Groups as Business Logic A Customer Group can act like a business rule. Instead of manually remembering: ```text Find customers who bought Product Group A, have LTV over $250, and have not purchased in 90 days. ``` RevCent can represent that segment as a Customer Group. Example group: ```text Product A Winback Candidates ``` Possible meaning: ```text Purchased Product Group A AND lifetime value >= 250 AND days since last sale >= 90 AND not in Do Not Contact ``` This makes the business logic reusable. The group can then be used for: - Email outreach - AI Assistant analysis - AI Voice Agent calls - Customer support priority - BigQuery reporting - Functions - External CRM or marketing automation - Third-party AI Agent workflows --- # Customer Group Qualifier Methods Customer Groups can qualify customers in different ways. The main qualifier methods are: | Qualifier Method | Meaning | |---|---| | `none` | No automatic qualification. Customers are added or removed manually or by workflow. | | `specific_values` | Customers qualify based on detailed values, filters, metadata, and subscription options. | | `customer_group` | Customers qualify based on membership or non-membership in other customer groups. | --- ## No Qualifiers A group with no qualifiers is useful when group membership should be controlled manually or by workflows. Examples: ```text Manual VIP Review Do Not Contact Needs Human Support Approved For Special Offer Escalated Support Manual Risk Review ``` Use this when a human, AI Assistant, Function, external system, or third-party AI Agent should decide whether the customer belongs in the group. --- ## Specific Value Qualifiers Specific value qualifiers allow customer groups to be based on measurable customer behavior. These can include: - Customer account age - Lifetime value - Lifetime refunded amount - Number of sales - Average sale amount - Days since last sale - Number of successful sales - Number of upsell sales - Number of declined sales - Number of abandoned sales - Number of fraud detections - Lifetime chargeback amount - Number of chargebacks - Lifetime PayPal dispute amount - Number of PayPal disputes - Subscription renewal behavior - Subscription status This is where Customer Groups become extremely granular. --- # Available Customer Group Qualifiers The qualifiers below can be used to create very specific segments. --- ## Campaign Filter Customers can qualify based on campaign association. Use cases: ```text Customers from Facebook Campaign A Customers from Affiliate Campaign B Customers from Partner Campaign C ``` This is useful for: - Campaign performance analysis - Campaign-specific follow-up - Affiliate quality tracking - Paid traffic segmentation - Custom winback campaigns --- ## Product Group Filter Customers can qualify based on purchasing products within a product group. Use cases: ```text Customers who bought Skincare Products Customers who bought Subscription Products Customers who bought High Ticket Products Customers who bought Product Group A but not yet Product Group B ``` This is useful for: - Cross-sell campaigns - Reorder reminders - Product-specific support - Warranty follow-up - Customer education - Lifecycle marketing --- ## Third-Party Shop Filter Customers can qualify based on purchases from a specific third-party shop. Use cases: ```text Customers from WooCommerce Shop A Customers from Shopify Store B Customers from Marketplace Channel C ``` This is useful when one RevCent account handles customers from multiple stores, brands, or commerce channels. --- ## Metadata Filter Customers can qualify based on metadata name/value pairs. Examples: ```text affiliate_id = aff_123 lead_source = google_ads customer_tier = gold sales_rep = alex crm_id exists preferred_language = es risk_score = high ``` Metadata is extremely powerful because it lets businesses define their own custom customer dimensions. A user may say: ```text Group customers by affiliate. ``` Technically, that may mean: ```text Use customer metadata where name = affiliate_id. ``` Metadata qualifiers allow Customer Groups to reflect business-specific logic that does not fit into standard fields. --- ## Metadata Exists Qualifier Metadata qualifiers can also check whether a metadata name exists. Example: ```text crm_id exists ``` This is useful for: - Customers synced to CRM - Customers missing enrichment - Customers with assigned sales reps - Customers with risk flags - Customers with external IDs - Customers with loyalty records --- ## Has No Sales Customers can qualify if they have no sales on record. Use cases: ```text Prospects Leads Signups who have not purchased Customers created before checkout but never converted ``` This is useful for: - Lead nurture - First purchase offers - AI qualification - Email onboarding - Sales follow-up --- ## Days Since Created Customers can qualify based on how long ago the customer was created. Use cases: ```text New customers created in last 7 days Customers created over 30 days ago with no sales Old leads Recently created prospects ``` This is useful for: - Welcome flows - New lead follow-up - Trial onboarding - Dormant lead campaigns --- ## Lifetime Value Customers can qualify based on lifetime value. Use cases: ```text Lifetime value over $500 Lifetime value between $100 and $500 Zero lifetime value High-LTV customers Low-LTV customers ``` This is useful for: - VIP programs - Support priority - Retention campaigns - High-value payment recovery - Customer success routing - Offer personalization --- ## Lifetime Refunded Customers can qualify based on lifetime refunded amount. Use cases: ```text Customers with refunds over $100 Customers with no refunds Customers with high refund rate ``` This is useful for: - Refund risk review - Support escalation - Customer quality analysis - Fraud/risk workflows --- ## Number of Sales Customers can qualify based on total sale count. Use cases: ```text First-time buyers Repeat buyers Customers with 3+ purchases Customers with no purchases ``` This is useful for: - Repeat buyer programs - Loyalty tiers - Reorder campaigns - Customer lifecycle segmentation --- ## Average Sale Amount Customers can qualify based on average sale amount. Use cases: ```text High average order value customers Low average order value customers Customers who usually buy premium products ``` This is useful for: - Premium support - Upsell strategy - Offer selection - High-ticket customer segmentation --- ## Days Since Last Sale Customers can qualify based on how long it has been since their last sale. Use cases: ```text No purchase in 30 days No purchase in 90 days Recently active buyers Dormant buyers ``` This is useful for: - Winback campaigns - Reorder reminders - Customer reactivation - Churn prevention --- ## Number of Successful Sales Customers can qualify based on successful sales. Use cases: ```text Customers with 1 successful sale Customers with 5+ successful sales Customers with no successful sales ``` This helps distinguish customers who attempted payment from customers who actually completed purchases. --- ## Number of Upsell Sales Customers can qualify based on upsell sales. Use cases: ```text Customers who accepted upsells Customers who never accepted upsells High upsell engagement customers ``` This is useful for: - Upsell targeting - Offer testing - Funnel optimization - Customer value analysis --- ## Number of Pending Declined Sales Customers can qualify based on declined sales. Use cases: ```text Customers with at least 1 declined sale Customers with multiple declined attempts Customers who need payment recovery ``` This is useful for: - Decline salvage - Payment update outreach - AI Voice Agent recovery calls - Support-assisted sale recovery --- ## Number of Pending Abandoned Sales Customers can qualify based on abandoned sales. Use cases: ```text Customers who abandoned checkout Customers with multiple abandoned sales High-intent customers who did not complete purchase ``` This is useful for: - Abandoned sale recovery - Email reminders - AI Voice Agent follow-up - Offer testing - Customer support outreach --- ## Number of Fraud Detections Customers can qualify based on fraud detection count. Use cases: ```text Customers with fraud detections Customers requiring manual review Customers excluded from automated outreach ``` This is useful for: - Fraud review - Risk workflows - Support caution - Manual approval queues --- ## Lifetime Chargeback Customers can qualify based on chargeback amount. Use cases: ```text Customers with chargeback amount over threshold Customers with no chargebacks Customers with high risk history ``` This is useful for: - Chargeback review - Risk monitoring - Support escalation - Fraud/risk workflows --- ## Number of Chargebacks Customers can qualify based on chargeback count. Use cases: ```text Customers with one or more chargebacks Repeat chargeback customers ``` This is useful for: - Risk review - Manual support handling - Suppression from certain offers - Chargeback mitigation workflows --- ## Lifetime PayPal Dispute Customers can qualify based on lifetime PayPal dispute amount. Use cases: ```text Customers with PayPal disputes Customers with high PayPal dispute amount ``` This is useful for: - PayPal dispute review - Payment method risk analysis - Support escalation --- ## Number of PayPal Disputes Customers can qualify based on PayPal dispute count. Use cases: ```text Customers with multiple PayPal disputes Customers with no PayPal disputes ``` This is useful for: - Risk scoring - Manual review - Dispute prevention workflows --- # Subscription Qualifiers Customer Groups can include subscription-specific qualifiers. These are valuable for businesses with recurring revenue, trials, renewals, or subscription products. --- ## Days Since Last Renewal Customers can qualify based on how long it has been since their last subscription renewal. Use cases: ```text Recently renewed customers Customers due for engagement after renewal Customers with no renewal in a long time ``` This is useful for: - Subscription lifecycle engagement - Renewal follow-up - Churn analysis - Customer success outreach --- ## Number of Renewals Customers can qualify based on renewal count. Use cases: ```text Customers with 1 renewal Customers with 3+ renewals Long-term subscribers New subscribers ``` This is useful for: - Loyalty tiers - Long-term subscriber rewards - Retention analysis - Subscription lifecycle reporting --- ## Number of Successful Renewals Customers can qualify based on successful renewal count. Use cases: ```text Reliable subscribers High-retention customers Customers with no successful renewals ``` This helps identify subscription quality and retention strength. --- ## Number of Overdue Renewals Customers can qualify based on overdue renewal count. Use cases: ```text Customers with overdue renewals Customers with multiple overdue renewals Customers needing payment recovery ``` This is useful for: - Subscription save workflows - Payment recovery - AI Voice Agent outreach - High-value recovery prioritization --- ## Subscription Status Customers can qualify based on subscription status. Possible statuses include: ```text active trial overdue occurrence_limit suspended cancelled ``` Use cases: ```text Active subscribers Trial customers Overdue customers Suspended customers Cancelled customers ``` This is useful for: - Subscription lifecycle marketing - Trial conversion - Cancellation winback - Retention workflows - Payment recovery - Customer support priority --- # Customer Group-Based Qualifiers Customer Groups can qualify customers based on other groups. This allows layered segmentation. Available relationship types include: | Group Qualifier | Meaning | |---|---| | `in_any_customer_group` | Customer must be in at least one of the selected groups. | | `in_all_customer_group` | Customer must be in all selected groups. | | `not_in_customer_group` | Customer must not be in at least one selected group. | Examples: ```text Customer must be in VIP ``` ```text Customer must be in High LTV and Active Subscriber ``` ```text Customer must not be in Do Not Contact ``` ```text Customer must be in Winback Candidate but not in Manual Review ``` This allows powerful composite segments. --- # Ecommerce Benefits of Well-Configured Customer Groups Customer Groups benefit ecommerce businesses when they are designed around real business outcomes. --- ## Better Segmentation Customer Groups let businesses segment customers by: - Value - Activity - Product interest - Purchase behavior - Campaign source - Subscription status - Payment problems - Refund behavior - Risk signals - Metadata - Lifecycle stage This makes messaging, support, reporting, and automation more precise. --- ## Better Personalization A customer in a group can receive more relevant experiences. Examples: ```text VIP customers receive premium support. Winback customers receive reactivation offers. Trial customers receive conversion education. Payment recovery customers receive update-payment outreach. Wholesale customers receive business-specific messaging. ``` Personalization becomes easier because the customer’s current group describes their business context. --- ## Better Revenue Recovery Groups can identify customers who are likely recoverable. Examples: ```text Failed Payment Recovery Overdue Renewal Abandoned Sale Recovery Trial Conversion Recovery High Value Recovery Card Update Needed ``` These groups can trigger workflows to recover revenue. Possible actions: - Send payment update email - Trigger AI Voice Agent call - Trigger AI Assistant review - Create support note - Add CRM task - Notify customer success - Trigger external AI Agent analysis --- ## Better Customer Support Support teams can use groups to understand customer context immediately. Examples: ```text VIP Manual Review Fraud Review Escalated Support Subscription Save Do Not Contact High Refund Risk ``` This helps support teams know: - How important the customer is - Whether special handling is needed - Whether outreach is allowed - Whether the customer has risk history - Whether the customer is in a recovery or retention workflow --- ## Better Reporting Customer Groups make reports easier to understand. Examples: ```text Revenue by Customer Group LTV by Customer Group Refund rate by Customer Group Chargeback rate by Customer Group Subscription renewal success by Customer Group Recovery success by Customer Group ``` A well-defined group turns raw data into business categories. --- ## Better AI and Automation AI Assistants, AI Voice Agents, Functions, and external tools can use Customer Groups as signals. Examples: ```text If customer enters High Value Recovery, trigger AI Assistant analysis. If customer enters Subscription Save, trigger AI Voice Agent. If customer enters Fraud Review, trigger Function to notify risk team. If customer leaves Payment Recovery, close external CRM task. ``` The group becomes an automation switch. --- # Customer Group Events Customer group membership changes can trigger event-driven workflows. Important event notations include: ```text customer.updated.customer_group.added customer.updated.customer_group.removed ``` These events represent meaningful changes in a customer’s state. --- ## `customer.updated.customer_group.added` This event occurs when a customer is added to a group. Examples: ```text Customer added to VIP Customer added to Payment Recovery Customer added to Trial Conversion Customer added to Fraud Review Customer added to Winback Candidate ``` This event is useful because entering a group often means the customer now qualifies for a new action. --- ## `customer.updated.customer_group.removed` This event occurs when a customer is removed from a group. Examples: ```text Customer removed from Payment Recovery Customer removed from Trial Conversion Customer removed from Manual Review Customer removed from Winback Candidate Customer removed from Do Not Contact ``` This event is useful because leaving a group can also require action. For example: ```text Removed from Payment Recovery ↓ Mark recovery workflow complete ``` ```text Removed from Do Not Contact ↓ Customer becomes eligible for outreach again ``` ```text Removed from Trial Conversion ↓ Customer may have converted or become ineligible ``` --- # Automated Workflows From Customer Group Events Customer group events can trigger many types of automation. Conceptual flow: ```text Customer qualifies for group ↓ Customer group added or removed ↓ customer.updated.customer_group.added or customer.updated.customer_group.removed event fires ↓ Automation runs ↓ Outcome is stored as note, metadata, group change, external task, email, call, or report ``` --- ## AI Assistant Workflows AI Assistants can be triggered by customer group events when the next step requires reasoning, summarization, classification, or decision-making. Examples: ### High Value Recovery ```text customer.updated.customer_group.added: High Value Recovery ↓ AI Assistant reviews customer lifetime value, payment history, notes, subscriptions, and failed payments ↓ AI recommends recovery strategy ↓ AI triggers email, voice call, support note, or Function ``` ### Winback Candidate ```text customer.updated.customer_group.added: Winback Candidate ↓ AI Assistant reviews purchase history and product preferences ↓ AI recommends best offer and channel ↓ Email or AI Voice Agent outreach is triggered ``` ### Risk Review ```text customer.updated.customer_group.added: Fraud Review ↓ AI Assistant summarizes customer history, refunds, chargebacks, and fraud detections ↓ Internal memo or note is created for human review ``` ### Group Removed ```text customer.updated.customer_group.removed: Payment Recovery ↓ AI Assistant checks whether payment was recovered ↓ AI summarizes outcome and updates note or metadata ``` AI Assistants are powerful when a group change means “decide what should happen next.” --- ## AI Voice Agent Workflows AI Voice Agents can be triggered when a group event means a customer should receive a phone call. Examples: ### Payment Recovery Call ```text Customer added to Payment Recovery ↓ AI Voice Agent calls customer about payment issue ↓ Customer is guided to secure payment update process ↓ Call outcome is saved as note or metadata ``` ### Subscription Save Call ```text Customer added to Subscription Save ↓ AI Voice Agent calls customer with retention-focused script ↓ Customer accepts offer, asks questions, or requests cancellation ↓ Outcome is saved ``` ### Trial Conversion Call ```text Customer added to Trial Conversion ↓ AI Voice Agent calls customer before or after trial expiration ↓ Agent explains value and next steps ↓ Customer converts or follow-up is scheduled ``` ### VIP Follow-Up Call ```text Customer added to VIP Follow-Up ↓ AI Voice Agent places personalized check-in call ↓ Outcome updates notes/customer metadata ``` AI Voice Agents are useful when the group event is time-sensitive or high-value. --- ## Function Workflows Functions can run custom code after a customer group event. Examples: ```text Customer added to VIP ↓ Function posts Slack alert to customer success ``` ```text Customer added to Fraud Review ↓ Function sends customer details to external risk API ``` ```text Customer removed from Payment Recovery ↓ Function closes CRM recovery task ``` ```text Customer added to Abandoned Sale Recovery ↓ Function sends customer to external marketing platform ``` Functions are useful when the group event needs to connect RevCent to external systems or perform deterministic custom logic. --- ## Email Template Workflows Customer group events can trigger customer-facing email communication. Examples: ```text Customer added to Winback Candidate ↓ Send winback offer ``` ```text Customer added to VIP ↓ Send VIP thank-you message ``` ```text Customer added to Payment Recovery ↓ Send payment update email ``` ```text Customer removed from Payment Recovery ↓ Send payment resolved confirmation ``` Email Templates are useful for branded, repeatable messaging based on customer lifecycle state. --- ## External Tools and Third-Party AI Agents Customer group events can also trigger external tools, including third-party AI Agents. These workflows can be connected through Functions, webhooks, APIs, or other integration mechanisms. Examples: ### External CRM ```text Customer added to High Value Recovery ↓ CRM task is created for account manager ``` ### Helpdesk ```text Customer added to Escalated Support ↓ Helpdesk ticket is created ``` ### Third-Party AI Agent ```text Customer added to Winback Candidate ↓ Third-party AI Agent reviews CRM history and prior offers ↓ Agent recommends best outreach strategy ``` ### External Risk AI ```text Customer added to Fraud Review ↓ External AI risk system analyzes behavior ↓ Risk recommendation is sent back to RevCent ``` ### Marketing Platform ```text Customer added to Reorder Candidate ↓ Customer is synced to marketing automation platform ``` These integrations let Customer Groups act as bridges between RevCent and the broader business technology stack. --- # Group-Driven Customer Journeys Customer Groups can define entire customer journeys. --- ## Prospect to First Purchase ```text Prospect ↓ Welcome email ↓ AI Assistant qualification ↓ First purchase offer ↓ Customer moves to First-Time Buyer ``` --- ## First-Time Buyer to Repeat Buyer ```text First-Time Buyer ↓ Post-purchase education ↓ Product reorder reminder ↓ Cross-sell offer ↓ Customer moves to Repeat Buyer ``` --- ## Active Subscriber to Payment Recovery ```text Active Subscriber ↓ Renewal fails ↓ Customer enters Payment Recovery ↓ Email + AI Voice Agent outreach ↓ Payment recovered ↓ Customer leaves Payment Recovery ``` --- ## Trial User to Paid Customer ```text Trial User ↓ Trial Conversion group ↓ Email or AI Voice Agent outreach ↓ Trial payment succeeds ↓ Customer moves to Paid Customer ``` --- ## High Value Customer to VIP ```text High lifetime value threshold reached ↓ Customer enters VIP ↓ AI Assistant summarizes customer history ↓ Customer success team receives notification ↓ VIP outreach begins ``` --- # Practical Customer Group Examples ## VIP Group Possible qualifiers: ```text Lifetime value >= 1000 AND chargeback count = 0 AND not in Manual Review ``` Possible automation: ```text customer.updated.customer_group.added ↓ AI Assistant creates customer summary ↓ Function notifies customer success ↓ Email Template sends VIP message ``` --- ## Payment Recovery Group Possible qualifiers: ```text Declined sales >= 1 OR overdue renewals >= 1 ``` Possible automation: ```text customer.updated.customer_group.added ↓ AI Assistant evaluates recovery priority ↓ Email Template sends payment update email ↓ AI Voice Agent calls high-value customers ``` --- ## Winback Candidate Group Possible qualifiers: ```text Days since last sale >= 90 AND lifetime value >= 250 AND not in Do Not Contact ``` Possible automation: ```text customer.updated.customer_group.added ↓ AI Assistant selects offer ↓ Email Template sends winback campaign ↓ Third-party AI Agent evaluates additional outreach if no response ``` --- ## Trial Conversion Group Possible qualifiers: ```text Subscription status = trial OR trial-related metadata exists ``` Possible automation: ```text customer.updated.customer_group.added ↓ Email Template sends trial education ↓ AI Voice Agent calls high-value trial customers ``` --- ## Fraud Review Group Possible qualifiers: ```text Fraud detection count >= 1 OR chargeback count >= 1 OR risk metadata exists ``` Possible automation: ```text customer.updated.customer_group.added ↓ Function sends data to risk platform ↓ AI Assistant creates internal risk memo ↓ Human review is triggered ``` --- ## Reorder Candidate Group Possible qualifiers: ```text Purchased specific product group AND days since last sale is within expected reorder window ``` Possible automation: ```text customer.updated.customer_group.added ↓ Email Template sends reorder reminder ↓ AI Assistant selects related upsell ``` --- # Customer Groups for Filtering Customers Customer Groups are one of the easiest ways to filter customers into meaningful, reusable segments. Instead of repeatedly rebuilding complex filters every time a business wants to find a certain kind of customer, the business can define the group once and then use the group as a reusable filter. Example: ```text High Value Customers = lifetime value >= 500 ``` Once this group exists, the business can use it to filter customers for: - Support priority - Email campaigns - AI Voice Agent outreach - AI Assistant analysis - BigQuery reporting - Customer success workflows - Revenue recovery - Risk review - Manual review - Export or sync to external systems The Customer Group becomes a saved customer segment. --- ## Filtering Customers by Business Meaning Customer Groups are powerful because they let businesses filter customers by business meaning, not just raw fields. Raw filter: ```text lifetime_value >= 500 AND days_since_last_sale >= 90 AND not in do_not_contact ``` Business meaning: ```text Winback Candidate ``` Raw filter: ```text num_overdue_renewal >= 1 AND lifetime_value >= 250 ``` Business meaning: ```text High Value Payment Recovery ``` Raw filter: ```text metadata affiliate_id = aff_123 AND num_sale >= 1 ``` Business meaning: ```text Affiliate 123 Buyers ``` This makes customer data easier for humans, AI tools, and automations to understand. --- ## Examples of Customer Filtering With Groups | Customer Group | What It Filters For | Common Use | |---|---|---| | `VIP Customers` | High lifetime value, strong purchase history, low risk. | Priority support, loyalty offers, customer success. | | `Winback Candidates` | Valuable customers who have not purchased recently. | Re-engagement campaigns. | | `Payment Recovery` | Customers with declined sales or overdue renewals. | Decline salvage and recovery workflows. | | `Trial Conversion` | Customers currently in trial or recently expired trial. | Trial-to-paid conversion outreach. | | `Abandoned Sale Recovery` | Customers with abandoned or failed sales. | Cart/sale recovery emails or calls. | | `Fraud Review` | Customers with fraud detections, chargebacks, or risk metadata. | Manual review and risk workflows. | | `Reorder Candidate` | Customers due for a repeat purchase. | Replenishment campaigns. | | `Affiliate Segment` | Customers tied to a specific affiliate or source metadata. | Affiliate performance reporting. | | `Do Not Contact` | Customers suppressed from outreach. | Compliance and suppression logic. | | `Subscription Save` | Customers with cancelled, overdue, or at-risk subscriptions. | Retention workflows. | --- ## Filtering Customer Lists Customer Groups can be used to quickly view or work with specific customers. Examples: ```text Show customers in Payment Recovery. ``` ```text Find VIP customers who have not purchased recently. ``` ```text List customers in Trial Conversion group. ``` ```text Find customers in Fraud Review who also have chargebacks. ``` ```text Show customers in Affiliate 123 Buyers. ``` Filtering by Customer Group is useful when the goal is to identify actual customers who belong to a segment. This can support: - Human review queues - Support queues - Sales outreach lists - Retention call lists - Payment recovery lists - Customer success task lists - Manual export workflows - AI Assistant analysis - AI Voice Agent call targeting --- ## Combining Customer Groups With Other Filters Customer Groups are even more useful when combined with other filters. Examples: ```text Customers in VIP group with no purchase in 90 days ``` ```text Customers in Payment Recovery group with lifetime value over $500 ``` ```text Customers in Trial Conversion group from a specific campaign ``` ```text Customers in Winback group who purchased Product Group A ``` ```text Customers in Subscription Save group who are not in Do Not Contact ``` This allows a business to start with a meaningful segment and then narrow it further. --- # Customer Groups for Reporting on Segments Customer Groups are also extremely useful for reporting. A report is more useful when it answers questions in business language. Instead of asking only: ```text What is total revenue? ``` a business can ask: ```text What is total revenue by Customer Group? ``` Instead of asking: ```text How many customers have refunds? ``` a business can ask: ```text What is the refund rate for VIP Customers vs Winback Candidates vs Affiliate Buyers? ``` Customer Groups turn reports into segment-based business intelligence. --- ## Segment Reporting Examples Customer Groups can support reporting such as: | Report | Why It Matters | |---|---| | Revenue by Customer Group | Shows which segments produce the most revenue. | | Lifetime value by Customer Group | Identifies the most valuable customer segments. | | Net revenue by Customer Group | Accounts for refunds, discounts, and other reductions. | | Refund rate by Customer Group | Shows which segments have refund risk. | | Chargeback rate by Customer Group | Shows which groups have dispute/risk problems. | | Subscription renewal success by Customer Group | Shows which segments retain best. | | Trial conversion by Customer Group | Shows which trial segments convert to paid customers. | | Payment recovery success by Customer Group | Shows which recovery workflows are working. | | Average order value by Customer Group | Shows which segments buy more per order. | | Repeat purchase rate by Customer Group | Shows which groups are more loyal. | | Product purchases by Customer Group | Shows product interest by segment. | | Campaign performance by Customer Group | Shows whether campaigns produce high-quality customers. | | AI Voice Agent outcome by Customer Group | Shows which segments respond to voice outreach. | | Email engagement by Customer Group | Shows which segments respond to email campaigns. | --- ## BigQuery Reporting With Customer Groups For reporting, aggregations, metrics, and trends, Google BigQuery is usually the right tool. Customer Groups can be combined with customer, sale, subscription, renewal, product, refund, chargeback, metadata, and lifetime value data. Example business questions: ```text Which Customer Groups generate the highest lifetime value? ``` ```text Which Customer Groups have the highest subscription renewal success? ``` ```text Which Customer Groups produce the most refunds or chargebacks? ``` ```text Which recovery group has the highest salvage success rate? ``` ```text Which affiliate-based customer group creates the best repeat buyers? ``` ```text Which product-based customer group has the best reorder rate? ``` ```text Which Customer Groups should receive AI Voice Agent follow-up? ``` ```text Which Customer Groups are declining in revenue over time? ``` Because Customer Groups are attached to customers, and customers are connected to purchases, subscriptions, renewals, trials, transactions, chargebacks, refunds, and metadata, Customer Group reporting can become a complete view of segment performance. --- ## Reporting on Customer Lifetime Value by Group Lifetime value is one of the most important measures for ecommerce businesses. Customer Groups make lifetime value easier to understand. Examples: ```text Average lifetime value by Customer Group ``` ```text Total lifetime value by Customer Group ``` ```text Median lifetime value by Customer Group ``` ```text Lifetime value by campaign-based Customer Group ``` ```text Lifetime value by affiliate Customer Group ``` ```text Lifetime value by subscription status group ``` This can answer important questions: ```text Are VIP Customers really more valuable? ``` ```text Do customers from Affiliate A have better lifetime value than Affiliate B? ``` ```text Do customers in Reorder Candidate group eventually reorder? ``` ```text Are Trial Conversion customers becoming long-term subscribers? ``` ```text Which groups deserve more marketing spend? ``` --- ## Reporting on Revenue Recovery by Group Customer Groups are especially useful for recovery reporting. Examples: ```text Payment Recovery group revenue recovered ``` ```text High Value Recovery group recovery rate ``` ```text Abandoned Sale Recovery group completed sales ``` ```text Trial Conversion Recovery group paid conversions ``` ```text Subscription Save group retained subscriptions ``` ```text Card Update Needed group recovered renewals ``` This helps a business measure whether its recovery workflows actually increase revenue. Example: ```text Customers entered Payment Recovery ↓ Email, AI Assistant, AI Voice Agent, or support follow-up occurred ↓ Some customers recovered ↓ BigQuery reports recovered amount by group ``` This turns customer groups into measurable revenue pipelines. --- ## Reporting on Customer Risk by Group Customer Groups can also help report on customer risk. Examples: ```text Refund rate by Customer Group ``` ```text Chargeback rate by Customer Group ``` ```text Fraud detections by Customer Group ``` ```text PayPal disputes by Customer Group ``` ```text Net revenue after refunds/chargebacks by Customer Group ``` This helps the business understand whether certain segments generate high revenue but also high risk. Examples: ```text Affiliate A generates high sales but high chargebacks. ``` ```text Product Group B customers have high refund rates. ``` ```text High Value group has low refund risk and should receive more retention effort. ``` This supports better marketing, support, and risk decisions. --- ## Reporting on Engagement by Group Customer Groups can be used to measure engagement outcomes. Examples: ```text Email open/click or response by Customer Group ``` ```text AI Voice Agent call outcome by Customer Group ``` ```text Support escalation rate by Customer Group ``` ```text Winback offer acceptance by Customer Group ``` ```text Trial conversion outreach success by Customer Group ``` ```text Subscription save call success by Customer Group ``` This helps answer: ```text Which segments respond best to email? ``` ```text Which segments should receive AI Voice Agent calls? ``` ```text Which segments need human support instead of automation? ``` ```text Which outreach channel works best for high-value customers? ``` --- ## Reporting on Group Movement Customer Groups can also be reported on as lifecycle movement. Examples: ```text How many customers entered Payment Recovery this week? ``` ```text How many customers left Payment Recovery after successful recovery? ``` ```text How many customers moved from Trial User to Paid Customer? ``` ```text How many customers moved from First-Time Buyer to Repeat Buyer? ``` ```text How many customers entered VIP this month? ``` ```text How many customers entered Do Not Contact? ``` This is valuable because group membership changes can represent lifecycle transitions. Group movement reporting helps businesses understand how customers flow through lifecycle stages. --- ## Customer Group Reporting as a Feedback Loop Customer Group reporting should feed back into business decisions. Example: ```text Report shows Winback Candidate group has low conversion ↓ Change offer or outreach channel ↓ Measure again ``` Example: ```text Report shows High Value Recovery group responds well to AI Voice Agent calls ↓ Expand AI Voice Agent recovery strategy ↓ Measure recovered revenue ``` Example: ```text Report shows Affiliate Segment has high chargebacks ↓ Adjust affiliate strategy or review traffic quality ↓ Monitor future group performance ``` This creates a continuous improvement loop: ```text Define group ↓ Use group for workflow ↓ Measure group performance ↓ Improve qualifier or workflow ↓ Repeat ``` --- ## Filtering vs Reporting Filtering and reporting are related but different. | Use | Purpose | Example | |---|---|---| | Filtering | Find specific customers in a segment. | “Show customers in Payment Recovery.” | | Reporting | Measure performance of a segment. | “How much revenue did Payment Recovery recover?” | Filtering helps identify who should be acted on. Reporting helps determine whether the segment and workflows are working. A strong ecommerce strategy uses both. --- ## Practical Examples ### Example: Payment Recovery Segment Filter: ```text Show all customers in Payment Recovery group with lifetime value above $250. ``` Report: ```text How much revenue was recovered from Payment Recovery group this month? ``` Action: ```text Trigger AI Voice Agent for high-value customers and send Email Template to the rest. ``` --- ### Example: Winback Segment Filter: ```text Show customers in Winback Candidate group who purchased Product Group A. ``` Report: ```text What percentage of Winback Candidate customers purchased again after outreach? ``` Action: ```text AI Assistant chooses personalized offer and Email Template sends campaign. ``` --- ### Example: VIP Segment Filter: ```text Show VIP customers with unresolved support notes. ``` Report: ```text What is the average lifetime value and refund rate of VIP customers? ``` Action: ```text Customer success team receives notification or AI Assistant creates summary. ``` --- ### Example: Affiliate Segment Filter: ```text Show customers in Affiliate 123 group with chargebacks. ``` Report: ```text What is lifetime value, refund rate, and chargeback rate for Affiliate 123 customers? ``` Action: ```text External AI Agent reviews affiliate quality and recommends changes. ``` --- ### Example: Subscription Segment Filter: ```text Show customers in Overdue Renewal group. ``` Report: ```text What percentage of Overdue Renewal customers were recovered after AI Voice Agent outreach? ``` Action: ```text Send payment update email, trigger AI Voice Agent, or escalate high-LTV customers. ``` --- ## Why This Matters Customer Groups let ecommerce businesses move from raw customer data to actionable customer intelligence. They answer: ```text Who belongs to this segment? ``` and: ```text How is this segment performing? ``` This makes Customer Groups valuable for both operations and strategy. They can help a business: - Find the right customers to contact. - Understand which segments generate revenue. - Measure which workflows recover revenue. - Identify risk-heavy customer segments. - Compare customer quality across campaigns or affiliates. - Improve personalization. - Improve support prioritization. - Decide where to spend marketing effort. - Decide where automation should be expanded or reduced. Customer Groups are therefore both a filtering tool and a reporting dimension. # Customer Groups and BigQuery Reporting Customer Groups also make reporting more meaningful. They can be used as a reporting dimension to measure revenue, lifetime value, refunds, chargebacks, recovery performance, subscription behavior, engagement outcomes, and customer lifecycle movement. Reports can group customers by business-defined categories rather than only raw fields. Examples: ```text Revenue by customer group Lifetime value by customer group Refund rate by customer group Chargeback rate by customer group Subscription renewal success by group Payment recovery success by group Winback conversion by group Trial conversion by group Average order value by group ``` This helps the business understand whether a group is actually valuable. For example: ```text Does the Winback Candidate group generate recovered revenue? ``` ```text Do VIP customers have lower refund rates? ``` ```text Which customer groups produce the highest lifetime value? ``` ```text Which campaign-based customer group creates the best subscribers? ``` BigQuery reporting can turn Customer Groups into measurable business strategy. --- # Customer Groups, Notes, and Metadata Customer Groups work well with notes and metadata. Examples: ```text Customer added to Manual Review ↓ Note is created explaining why ``` ```text Customer added to Payment Recovery ↓ metadata: recovery_status = active ``` ```text Customer removed from Payment Recovery ↓ metadata: recovery_status = recovered ↓ Note summarizes outcome ``` This creates a feedback loop where group membership triggers action, and action results are stored back on the customer. --- # Guardrails for Customer Group Automation Customer Groups can trigger powerful workflows, so they should be configured carefully. Recommended guardrails: - Give each group a clear name. - Write a detailed description explaining the group’s business purpose. - Clearly define the qualifiers. - Avoid vague or overlapping groups unless intentional. - Use suppression groups such as Do Not Contact where appropriate. - Avoid circular automation where group changes repeatedly trigger each other. - Add cooldowns for repeated outreach. - Use human review for sensitive groups such as fraud, chargeback, legal, or angry customers. - Test qualifiers before connecting them to live outreach. - Use notes and metadata to record automation outcomes. - Use BigQuery to verify that the group is producing useful results. --- # Why Customer Groups Are Powerful Customer Groups combine four major capabilities: ```text Granular customer qualification + customer lifecycle state + event-driven automation + measurable reporting ``` This means Customer Groups can be used to identify the right customer, at the right moment, and trigger the right next action. Examples: ```text Customer becomes high value ↓ VIP workflow starts ``` ```text Customer has overdue renewal ↓ Payment recovery workflow starts ``` ```text Customer becomes winback candidate ↓ Retention workflow starts ``` ```text Customer enters fraud review ↓ Risk workflow starts ``` When configured correctly, Customer Groups help ecommerce businesses: - Segment customers precisely - Personalize engagement - Recover revenue - Improve customer support - Automate customer journeys - Trigger AI workflows - Connect to external tools - Improve reporting and segment-level analysis - Increase lifetime value --- # Summary Customer Groups are one of the most important customer capabilities in RevCent. They allow ecommerce businesses to define precise customer segments using detailed qualifiers such as purchase behavior, lifetime value, refunds, chargebacks, sales counts, subscription status, metadata, campaign, product group, third-party shop, and membership in other groups. Even more importantly, Customer Group events such as: ```text customer.updated.customer_group.added customer.updated.customer_group.removed ``` can trigger automated workflows across: - AI Assistants - AI Voice Agents - Functions - Email Templates - External tools - Third-party AI Agents - CRM systems - Helpdesk systems - Marketing platforms - Risk systems - Customer success workflows The key concept is: ```text A well-configured Customer Group is not just a segment. It is a reusable customer filter, a reporting dimension, and a business signal that can trigger the next best action for the customer. ``` --- Document Parent Directory * [Operations](https://revcent.com/documentation/markdown/mcp/operation/index.md) - AI/MCP details and overviews for operations available within the RevCent MCP.