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Your A-Z guide to customer-led growth terminology. 60+ terms defined with practical examples.
Personalization that grounds AI-generated recommendations, messages, and conversations in current, approved customer and business data at runtime.
Personalization that uses multiple input and output modalities such as text, images, audio, video, and behavior signals instead of relying on text-based targeting alone.
Measurement that quantifies the causal lift created by a marketing action by comparing what happened with what would have happened without it.
A customer-data architecture in which storage, identity, modeling, and activation are assembled from modular components rather than from one monolithic suite.
A decision-support form of personalization that intervenes helpfully at key journey moments rather than passively tailoring content everywhere.
Data that is representative, governed, and fit for a specific AI use case rather than merely clean in a generic analytics sense.
A marketing operating model in which AI agents plan, execute, and optimize customer-facing work against business goals under human-defined guardrails.
Workflows that run end to end without human intervention, used for high-volume, low-risk customer marketing motions where speed and consistency outweigh the need for review.
Data customers intentionally and proactively share with a company: preferences, goals, context, feedback. More reliable than inferred behavioral data because it's declared, not deduced.
The category of software and practice for automating end-to-end business workflows across teams, tools, and systems, replacing handoffs and manual steps with orchestrated execution.
A program that systematically captures, synthesizes, and routes customer feedback into product, marketing, and CS decisions.
A blend of product, marketing, and community behavior that reliably predicts B2B SaaS retention and expansion before financial metrics catch up.
An AI design pattern where humans review, correct, or approve AI decisions at specific checkpoints, improving accuracy, trust, and responsibility for sensitive work.
Moving an existing customer up to a more expensive tier, edition, or capability level of the product they already use.
The end-to-end process of sourcing, capturing, approving, and deploying customer testimonials as continuously refreshed sales and marketing content.
The automated triggering, distribution, collection, and routing of customer surveys across the lifecycle, from NPS to product feedback to advocacy invitations.
Automation that scales the customer success function: health scoring, at-risk outreach, milestone tracking, QBR prep, and adoption nudges, freeing CSMs for high-judgment work.
The collective customer signal (reviews, testimonials, case studies, logos, awards, peer mentions) that shapes how prospects evaluate a B2B purchase decision.
The capture, scoring, and routing of individual behavioral, sentiment, and commercial signals that feed customer decisions in real time.
The automated interpretation of tone, emotion, and intent in customer text (support tickets, reviews, community posts, surveys) to inform CS, marketing, and product decisions.
Grouping customers or prospects by shared characteristics or behaviors to enable relevant targeting, content, and program design at scale.
The automated delivery of rewards, recognition, gifts, and incentives triggered by customer behavior, program participation, or lifecycle events.
The discipline of sourcing, curating, responding to, and amplifying customer reviews on G2, TrustRadius, Gartner Peer Insights, Capterra, and other B2B review platforms.
The total revenue growth from existing customers through upsell, cross-sell, seat growth, and add-ons. Expressed as NRR, GRR plus expansion.
Automated workflows that trigger retention interventions based on customer behavior, health signals, or lifecycle stage.
A marketing approach focused on long-term customer relationships rather than transactional outcomes, with retention, expansion, advocacy, and loyalty as the central goals.
The marketing programs that run in the lead-up to a contract renewal to make the renewal conversation a formality, not a negotiation.
A structured program that rewards existing customers for introducing new qualified buyers to your product, with tracked attribution, rewards, and conversion.
A coordinated series of touchpoints that keep prospects, leads, or customers progressing toward a specific outcome (next stage, expansion, renewal, advocacy) at their own pace.
Using behavioral signals and ML models to forecast churn risk before it shows up in renewal numbers, so teams can intervene early.
An AI assistant embedded in marketing workflows that helps humans draft, analyze, decide, and execute faster, while leaving final judgment with the human operator.
Small, low-commitment advocacy actions (a reaction, a short review, a quick quote, a public like) that compound into meaningful signal.
Marketing automation infrastructure (email, triggers, workflows) configured specifically for reducing churn and driving engagement.
The use of ML models to predict customer behavior, score accounts, personalize content, and optimize spend in ways that improve with every interaction rather than staying static.
A structured program that recognizes and rewards long-term customers for engagement, advocacy, expansion, and renewal across the full relationship, not just at purchase.
The total revenue a customer is expected to generate across the full length of the relationship, net of the cost to serve them.
The end-to-end customer journey that starts with acquisition and ends with the customer actively advocating for the brand.
Marketing strategy and execution focused on a small set of named, high-value accounts, with deep personalization, multi-stakeholder engagement, and tight CS-sales-marketing alignment.
A centralized, searchable repository of product documentation, customer guides, community-generated content, and advocacy assets that customers and prospects actually use.
Behavioral data that indicates a buyer or customer is researching a specific category, product, or problem area, captured from first-party and third-party sources.
Automation that orchestrates a customer's path through a defined journey (onboarding, expansion, renewal) with branching logic driven by real behavior, not linear cadence.
Partnering with industry experts, practitioners, and community voices to influence B2B purchase decisions through their trusted audience relationships.
A composite score that predicts a customer's likelihood to renew, churn, or expand, built from behavioral, sentiment, and relational signals.
The practice of coordinating marketing, sales, and customer success around a shared signal layer and a sequenced motion instead of siloed campaigns.
A self-reinforcing system where one customer action produces data, advocacy, or reach that fuels the next stage of growth.
Advocacy program design that removes every unnecessary step for the customer, so participation costs minutes not hours.
The discipline of marketing specifically to existing customers to drive upsell, cross-sell, and account growth.
The capture, synthesis, and routing of all customer feedback (surveys, tickets, reviews, community, sales calls) into decisions that shape product, marketing, and CS.
Automated, signal-triggered touchpoints that keep customers active in product, community, and content without sending the same drip to everyone on the same day.
The practice of using behavioral, engagement, sentiment, and outcome data to drive every marketing decision, from targeting to creative to channel mix.
The discipline of using marketing programs to keep existing customers engaged, renewing, and growing instead of churning.
The discipline of synthesizing customer data into decisions, turning behavioral and sentiment signals into routable insights for marketing, CS, and sales.
A growth strategy that treats existing customers as the primary engine of new revenue through retention, expansion, and advocacy, not just as an installed base to maintain.
The system that manages a curated pool of customers willing to speak to prospects, routes reference requests, and tracks utilization and fatigue.
A unified view of every customer that blends product usage, marketing engagement, support history, commercial data, and sentiment into one record.
Selling a different, complementary product to an existing customer. Distinct from upsell, which upgrades the product they already have.
Purpose-built software that runs the end-to-end advocacy program: identifying advocates, automating requests, capturing artifacts, and measuring impact.
End-to-end automation of post-sale lifecycle work (onboarding, adoption, expansion, advocacy, retention) triggered by signal rather than calendar.
Software for running customer communities at scale: discussions, events, programs, member intelligence, and the integration into the broader customer marketing motion.
Advocacy expressed through behaviors buyers look for: reviews, references, recommendations, and public endorsements that influence purchase decisions.
The marketing discipline that designs, runs, and measures referral programs as a scalable B2B growth channel, treating advocates as a pipeline source.
A purpose-built software category for running AI-powered customer marketing end to end: signals, intelligence, agents, plays, and measurement in one layer instead of stitched tools.
Growing revenue inside an existing customer account through more seats, more usage, more tiers, or additional products.
A defined, multi-step sequence of automated actions triggered by a specific event or signal: the building block of every automated marketing or CS motion.
The discipline of turning existing customers into active promoters through structured programs for reviews, references, content, and referrals.
An autonomous or semi-autonomous AI system that executes customer marketing work end to end, from signal detection through message delivery, under defined guardrails.
Using AI to orchestrate marketing across the full post-sale lifecycle (onboarding, adoption, expansion, advocacy, retention) with personalized, signal-driven plays instead of static cadences.
