Magnify is an AI-first Customer Growth Automation platform that helps B2B SaaS companies drive retention, expansion, and revenue growth from their existing customer base — automatically and at scale.
Unlike traditional Customer Success platforms that track health scores and manage workflows, Magnify forecasts actual revenue outcomes for the next two quarters, connects signals across your entire post-sales data stack, and automatically executes the right actions across every account. The result is a post-sales motion that operates with the same rigor and predictability as your new business pipeline.
Magnify is designed to complement your existing CRM, CS platform, and data science models — not replace them. It sits as the AI automation and forecasting layer across the systems your team already uses, turning the signals those tools generate into measurable revenue outcomes.
Customer Growth Automation is a software category and operating model designed to help B2B SaaS companies drive retention, expansion, and revenue growth from their existing customer base — automatically and at scale.
Where traditional Customer Success platforms help teams manage customer relationships and track account health, CGA goes a step further: it connects signals across your entire post-sales data stack, uses AI to predict what will happen to each account, and executes the right actions automatically — without requiring manual intervention at every step.
The three pillars of CGA are connected data, AI-driven prediction, and automated execution. When those three things work together as a continuous loop, post-sales teams can move from reactive account management to proactive revenue ownership.
Magnify is purpose-built for this category. It sits as the AI automation and forecasting layer across your existing CRM, CS platform, product analytics, support tools, and engagement systems — turning the signals those tools generate into measurable revenue outcomes.
The simplest way to understand the difference is this: CS platforms help you manage. Customer Growth Automation helps you act.
Traditional CS platforms like Gainsight, ChurnZero, Totango, and Vitally are excellent at organizing the post-sales function. They track health scores, manage playbook execution, run lifecycle programs, and give CSMs a structured way to manage their book of business. For what they were designed to do, they work well.
The gap appears at the execution layer. Most CS platforms surface insights — they show you what's happening across your accounts — but the decision about what to do, and the act of doing it, still falls to a human. That works when account loads are manageable. It breaks down when you're covering hundreds or thousands of accounts simultaneously.
CGA closes that gap by handling the analytical and execution layer automatically: connecting signals across systems, predicting which accounts need attention and why, and triggering the right motions — across email, in-app, CSM task queues, and other channels — without waiting for someone to manually intervene.
Health scores tell you how an account feels. Magnify tells you how much revenue is at risk — or likely to expand — and when.
Rather than producing color-coded statuses, Magnify generates dollar-based revenue forecasts for each account: the specific likelihood of renewal, expansion, or churn, quantified and ranked by financial impact. This shift matters for several reasons.
It moves beyond subjectivity. CFOs and CROs can call their number months in advance based on actual data signals rather than CSM sentiment. It reveals the specific drivers pushing an account toward growth or risk — making it far easier to launch targeted interventions. And it allows teams to focus resources exactly where the financial impact is greatest, rather than spreading attention evenly across a color-coded list.
For finance and RevOps teams accustomed to Salesforce-native forecasting: Magnify's post-sales revenue forecast complements your CRM pipeline view by adding the dimension that CRM forecasting typically lacks — a live, signal-grounded prediction of what the installed base will do — surfaced early enough to act on it.
Magnify describes itself as Customer Growth Automation (CGA) — a category that sits on top of your existing post-sales tech stack and uses AI to automate retention and expansion workflows at scale.
The modern post-sales stack has three layers, and most companies are only running two. Their CRM tracks revenue. Their CS platform tracks customer health. Customer Growth Automation is the missing third layer that connects those systems, reads signals continuously across both, predicts what is going to happen, and drives action automatically at the speed and scale a purely human-touch model cannot match.
No — and in many cases, it shouldn't.
Magnify is designed to work alongside your existing Customer Success platform, not replace it. Platforms like Gainsight, ChurnZero, Totango, and Vitally are effective at relationship management, lifecycle workflows, health scoring, and account visibility. Those capabilities don't go away when you add Magnify.
What Magnify adds is the AI-first automation and forecasting layer those platforms were never designed to provide: cross-system signal connection, predictive churn and expansion modeling, automated multi-channel execution, and continuous closed-loop optimization.
Your existing investments are preserved. The systems your CSMs already live in continue to work as they do today. Magnify makes them more actionable by adding the execution layer on top.
For teams evaluating a rip-and-replace: that's not required, and for most mid-market and enterprise organizations with deeply embedded CS platforms, it would be unnecessarily disruptive. The more common — and more successful — path is to deploy Magnify alongside existing tooling, start with one high-impact use case, prove value, and expand from there.
Magnify is not trying to replace your Gainsight investment. What it does is extend what Gainsight can deliver by adding three capabilities Gainsight wasn't designed to own:
First, advanced AI forecasting grounded in cross-system signals — not just the data that lives inside Gainsight, but signals from product analytics, support, billing, and engagement tools unified into a single predictive model. Second, automated multi-channel execution that orchestrates across billing, marketing, in-app, and CRM systems — not just CSM task workflows. Third, dollar-based revenue forecasting that gives CS leaders, CFOs, and CROs the forward-looking visibility they need to call their number with confidence.
The result is a CS function that operates more like a revenue system: Gainsight handles the relationship and workflow layer it was built for, and Magnify handles the AI forecasting and execution layer it wasn't.
Many companies face vendor shifts or sunsetting CS platform tools. Magnify addresses this directly by ensuring you don't lose critical visibility or automation capabilities when a CSP goes away.
Magnify embeds multi-channel insights directly into your Salesforce instance — or any other CRM — so your team can continue managing customers in the system they already use while Magnify handles automation and revenue forecasting in the background. It unifies data that was previously siloed in your CSP — health scores, usage analytics, product telemetry — with your CRM records. And it provides advanced dollar-based forecasting so you don't regress to static or color-coded health indicators when the transition happens.
In short: when a CSP sunsets, most teams worry about losing visibility and automation. Magnify replaces both, while adding predictive and execution capabilities most CSPs never had.
No. Magnify is not a CRM and will not replace Salesforce or HubSpot.
Magnify connects with your CRM to leverage revenue data for forecasting, and pushes insights and signals back into your CRM so your teams can act on them inside the systems they already use. Your CRM remains your system of record. Magnify enriches it with advanced AI forecasts, revenue predictions, and multi-channel automation triggers — without displacing it.
PLG tools like Pocus and Variance are excellent at surfacing product signals — identifying which users are hitting activation milestones, which accounts are showing expansion intent, or which trials are converting. That signal layer is genuinely valuable.
The difference is what happens next. PLG tools surface the signal and stop. Acting on that signal still requires a human to notice it, decide what to do, and do it.
Magnify takes those same product signals — alongside CRM data, support history, billing data, and engagement signals — and does something PLG tools don't: it predicts what those signals mean for revenue, and automatically executes the right motion at the right time. The entire loop, from signal to action to measured outcome, runs without manual intervention at every step.
Yes. Magnify connects with 40+ systems your team already uses, including:
CRM: Salesforce, HubSpot
CS Platforms: Gainsight, ChurnZero, Totango, Vitally, Planhat
Product Analytics: Pendo, Amplitude, Mixpanel
Support: Zendesk, Intercom
Conversation Intelligence: Gong
Data Warehouses: Snowflake, BigQuery
Engagement: Marketo, HubSpot Marketing, Outreach
The goal is not to replace your stack. It is to connect it — so the signals living in each of those systems can work together to drive automated, measurable action across the customer lifecycle. You can view the full and current integrations list here.
Magnify is designed to complement internal data science efforts, not compete with them.
If your team has already built churn or expansion models, Magnify can integrate those models to drive automated actions across your post-sales stack — operationalizing work that might otherwise stay inside a notebook or dashboard. For Revenue Ops, CS, and Sales teams, Magnify makes data science outputs accessible and actionable in the systems they use every day, without requiring them to interpret raw model outputs.
As your data science team refines models over time, those updates can be plugged into Magnify for immediate operational impact — no replatforming or recoding required. The relationship is additive: Magnify provides the execution layer your internal models likely don't have, and your internal models can make Magnify's predictions even more precise.
Four areas where Magnify consistently outperforms internal builds:
Speed. Magnify's pre-built connectors and AI models deliver actionable insights within weeks. Internal builds typically take months to reach comparable capability — and longer to reach production reliability.
Ongoing maintenance. Magnify continuously refines its platform and releases new integrations, removing the engineering overhead that in-house solutions require to stay current. AI models are reviewed and updated quarterly to maintain accuracy.
Multi-channel execution. Internal solutions often do a reasonable job of tracking and predicting — but most lack robust, production-ready multi-channel automation. Knowing what to do and being able to do it automatically at scale are different problems.
ROI measurement. Magnify is built from the ground up to prove the value of every initiative — tracking which Motions are working, which aren't, and what the measurable impact is on retention and expansion. Most in-house solutions treat reporting as an afterthought.
Magnify ingests data from your existing tech stack — product analytics, CRM, CS platform, support, billing, marketing automation — and runs proprietary AI models trained on your historical revenue outcomes. Rather than producing color-coded health scores, Magnify predicts the exact revenue each account is likely to renew or expand, up to two quarters ahead.
Predictive factors include product adoption trends, support ticket frequency, user login patterns, contract history, billing details, feature utilization, and marketing engagement signals. Accounts are grouped by churn risk, neutral, or expansion potential — each with dollar-based revenue projections rather than subjective status labels. This lets teams prioritize interventions by financial impact rather than by gut feel.
When Magnify is connected to your CRM, CS platform, support, and product data, our AI models typically reach a 90% confidence interval.
For organizations with less complete data connectivity, accuracy generally remains at or above 80%. As additional data sources are connected and more historical revenue outcomes accumulate, the models continue to refine — accuracy improves over time, not just at the point of deployment.
For finance and RevOps leaders accustomed to evaluating forecast tools: Magnify's models are trained on your company's actual historical outcomes, not generic industry benchmarks. This means the predictions reflect the specific signals that actually drive churn and expansion at your business — not a generalized model applied uniformly across all customers.
Motions are Magnify's automated action layer — targeted, multi-channel programs that execute the right engagement at the right time, without requiring manual intervention for every account.
Motions are triggered by the AI signals Magnify detects and are fully customizable based on your data, your team's workflows, and the outcomes you are trying to drive. Two common examples:
A growth Motion for an account showing expansion signals might: flag the opportunity in Salesforce or Gainsight with revenue context, ping your Slack upsell channel with account details, and launch in-app tutorials or email campaigns to encourage deeper product adoption — all automatically, at the moment the signal appears.
A churn-risk Motion for an at-risk account might: identify underutilized features and trigger step-by-step in-app walkthroughs via Pendo or Gainsight PX, create a CSM task in Salesforce to prompt a follow-up conversation, and initiate a targeted re-engagement email sequence — before the account reaches a point of no return.
Every Motion includes defined success metrics — retention rate, usage lift, expansion conversion — so you can track ROI for each initiative and continuously optimize which plays are working.
Unified Data and Single Customer View. Magnify connects the platforms you use post-sale — CRM, support, product telemetry, billing, marketing automation — into one streamlined data pipeline. This creates a real-time, unified view of every account that updates continuously as signals change, rather than relying on manual data pulls or weekly snapshots.
AI and Machine Learning Insights. Magnify's models find the leading indicators of churn and expansion specific to your customer base and project actual dollar amounts at risk or available for upsell. Rather than a generic health score, you see the specific drivers behind each account's trajectory — the factors that are actually causing an account to move toward growth or risk — giving your team actionable context rather than a status label.
Omni-Channel Automation via Motions. Motions are targeted campaigns or triggers that execute at scale — email sequences, in-app walkthroughs, Slack alerts, billing nudges, CSM task creation, and more. You define the success metrics for each Motion and track progress in Magnify's reporting dashboards, creating a closed loop between prediction, action, and measured outcome.
No. Magnify supports both digital-scale motions and high-touch enterprise programs — and many customers run both simultaneously.
For digital and tech-touch segments, Magnify enables true at-scale coverage: personalized automated outreach, closed-loop NPS programs, onboarding acceleration, and churn prevention across large books of business that a purely human-touch model could not cover cost-effectively.
For enterprise and high-touch accounts, Magnify provides CSMs with an AI-powered intelligence layer: weekly action plans that surface recommended next steps across their entire book of business, early risk signals before they become visible problems, expansion opportunities identified from behavioral data, and competitive intelligence surfaced on demand. The goal is not to automate the enterprise relationship — it is to make the humans managing those relationships better informed and more effective.
Many Magnify customers start with their digital and long-tail segments as a low-disruption pilot, demonstrate clear ROI, and then extend Magnify's capabilities to their strategic account motion.
Yes — and this is one of the areas where Magnify most meaningfully differentiates from both traditional CS platforms and CRM-native forecasting.
Magnify forecasts churn risk, renewal likelihood, and expansion potential up to two quarters ahead, grounded in actual behavioral signals across your customer base rather than static health scores or subjective CSM input. Leadership gains earlier, more reliable visibility into GRR and NRR trends — with enough lead time to intervene before outcomes are already decided.
Magnify's post-sales revenue forecast is designed to complement your CRM pipeline view, not replace it. It adds the dimension that Salesforce-only forecasting typically lacks: a live, signal-grounded prediction of what your installed base is likely to do. This gives CFOs and CROs a complete revenue picture — new business pipeline on one side, installed base forecast on the other — and the confidence to present both to the board.
Magnify's AI operates across three distinct functions:
Signal detection. Magnify continuously reads signals across all connected systems — product usage patterns, support ticket frequency and sentiment, login activity, feature utilization, billing history, engagement data, and more — identifying meaningful changes that predict risk or opportunity at the account and user level, across your entire customer base, in real time.
Revenue prediction. Rather than producing health scores, Magnify produces revenue predictions: the likelihood each account will renew, expand, or churn, quantified in dollar terms and ranked by financial impact. These predictions are trained on your actual historical outcomes — what actually predicted churn or expansion at your company — not a generic industry benchmark.
Automated execution. When the system identifies that an account needs a specific action, it triggers that action automatically across the right channel. CSMs receive weekly AI-generated action plans surfacing recommended next steps across their book of business — replacing the manual analysis and guesswork that typically consumes CS capacity and letting them focus on the conversations that genuinely require a human.
Magnify is purpose-built for B2B SaaS and software companies that need to drive post-sales revenue growth without linearly scaling headcount. It is particularly well-suited to organizations with large customer bases, meaningful product usage data, and expansion revenue as a material part of their growth model.
The teams that use Magnify span multiple functions: Customer Success for account coverage and motion execution, Revenue Operations for forecasting and reporting, Growth and Product for PLG signal activation, Sales leadership for expansion and competitive intelligence, and Finance for revenue visibility and planning.
In terms of company profile, Magnify delivers the most immediate value for mid-market and enterprise SaaS companies with established data infrastructure — CRM, product analytics, and ideally a CS platform already in place. For companies earlier in their data maturity journey, Magnify can still deliver value from a minimal starting integration set, with accuracy and coverage improving as more data sources are connected over time.
Most teams start seeing measurable impact within weeks, not quarters. Implementation typically follows two phases:
Initial integration (approximately one month). Magnify connects your core data sources — CRM, support, product usage, billing — building a unified pipeline for AI modeling. Most deployments start with a minimal integration set (typically CRM plus product analytics) and expand progressively as additional use cases are activated.
First Motions (approximately one additional month). Your team designs and launches its first automated plays — churn risk prioritization, renewal motion automation, expansion opportunity surfacing, or NPS closed-loop programs. By the end of month two, most teams have measurable early results: churn risk identified and actioned, expansions triggered, CSM time shifted toward higher-value work.
Because Magnify layers onto existing systems rather than requiring a platform migration, there is no extended implementation runway before value begins to appear.
Not perfect data — but some data maturity matters for getting the most from Magnify's predictive capabilities.
At minimum, Magnify needs product usage signals and CRM data to begin building meaningful predictions. From there, each additional data source — support history, billing, engagement signals, NPS data — makes the models more accurate and the predictions more actionable.
If your data is fragmented or siloed today, Magnify's implementation process is designed to help you progressively improve that picture. The models strengthen over time as more signals are connected and more historical outcomes become available to learn from.
For finance and RevOps leaders concerned about AI transparency: Magnify is designed to explain why a forecast changed, what signals are driving a specific risk or expansion prediction, and how to interpret model outputs. The goal is for finance teams to treat Magnify as a trustworthy system of record — not a black box producing numbers they can not interrogate.
Pricing is based on the scale of your revenue and customer base. Typical tiers consider the size of your Revenue and Success teams, your total customer count, and ARR segment.
Most teams see measurable ROI within the first quarter — making Magnify's cost readily offset by the retention protection and expansion revenue it generates.
Magnify stores and processes customer data in secure, enterprise-grade environments compliant with SOC 2 Type II and other common enterprise security standards.
All connections to your existing tools are API-based, using best practices for encryption both in transit and at rest. Magnify does not share or monetize your data outside of your authorized workflows under any circumstances.
For enterprise procurement teams with specific compliance requirements, our team is available to walk through our security posture, data handling practices, and available documentation in detail.