Gong vs Clari: 2025 Comparison of Features, Pricing, and User Reviews

What Are Gong and Clari, and Why Compare Them in 2025? [toc=Platform Overview]

Modern revenue teams live or die by their ability to capture conversation data and convert it into predictable pipeline. Two names dominate this conversation-to-forecast loop: Gong for call intelligence and Clari for roll-up forecasting. Yet 2025 presents a new buying climate one where CROs, RevOps leaders, and frontline managers need a single engine that unifies data, insight, and action instead of stitching siloed SaaS point tools together.

Traditional sales tech grew up in the last decade's SaaS boom. Gong's features captured audio, tagged keywords, and surfaced talk-ratio metrics; Clari pulled CRM fields and asked managers to "roll-up" numbers each Friday. Valuable at the time, both platforms depended on manual data entry and human adoption. AEs had to remember to update next-steps; managers still listened to hours of calls during commutes; and RevOps teams reconciled mismatched fields across CRM, quote, and BI tools. The result was familiar: forecast slips, bloated tech spend, and a coaching backlog no one had time to clear.

Generative AI rewrites these rules. Today's models extract context, not just keywords; they learn selling frameworks on the fly and predict deal outcomes without waiting for reps to type notes. Instead of hard-coded dashboards, leaders can ask natural-language questions ("Which late-stage deals lack an economic buyer?") and receive answers in seconds. The core shift is from analytics to autonomous execution AI that doesn't merely inform humans, but actually does the low-value work.

That's the philosophy behind Oliv.ai. Built AI-native from day one, Oliv combines conversation intelligence and forecasting inside an agentic platform through specialized AI agents for sales teams:

• Meeting Assistant captures, transcribes, and tags every buyer interaction then writes follow-up emails automatically.
• Forecaster Agent reconciles CRM, email, and conversation signals to produce a live forecast without manager roll-ups.
• Deal Driver surfaces at-risk opportunities and prescribes next actions.

Early adopters report 25% higher forecast accuracy and 30% faster deal velocity after consolidating on a unified AI platform gains legacy stacks struggle to match.

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What's the Difference Between Gong and Clari in Key Features? [toc=Feature Comparison]

Legacy limitations surface quickly. Gong's keyword trackers miss nuance ("budget" versus "your budget is frozen"), and Clari's projections crumble when reps forget to update close dates. Both toolsets require extensive onboarding, weekly admin effort, and separate UIs that salespeople rarely open mid-quarter.

Generative AI flips the model. Large-language models extract intent, sentiment, and stakeholder roles directly from live calls and emails. Instead of waiting for humans to tag fields, the system enriches data in-flight removing double-entry and human lag. Forecast algorithms now learn from historical win/loss narrative, not just stage probabilities, delivering risk scores that adapt as conversations evolve. This approach aligns perfectly with proven sales methodologies like MEDDIC that focus on contextual qualification.

Oliv.ai operationalises this progress through agentic workflows:

• CRM Manager Agent writes back summaries, next steps, and MEDDIC scores to Salesforce automatically.
• Coach Agent benchmarks reps against best-practice talk patterns and schedules targeted drills.
• Pipeline Tracker Agent calls reps for verbal updates, transcribes answers, and patches CRM so hygiene no longer hinges on keyboard time.

These sales automation tools eliminate the manual correlation work that traditional platforms require, while buyers no longer have to choose between "Gong for calls" or "Clari for forecasts" they gain both in a single interface while cutting licence sprawl by up to 40%.

How Do Gong and Clari Pricing Compare in 2025? [toc=Pricing Analysis]

Budget scrutiny has intensified: CFOs now demand proof that every tool drives incremental revenue. Pricing transparency is therefore pivotal when evaluating Gong, Clari, and newer AI-native options.

Gong moved to a "unified licence" in 2024 bundling Engage (outreach) and Forecast (pipeline) with its core recorder at roughly $250 per user per month, plus a platform fee that starts near $5k annually. For detailed insights into this pricing structure, see our comprehensive Gong pricing analysis. The catch? Teams who only need note-taking still pay for coaching, outreach, and forecasting they may never deploy.

Clari's base $100–$120 per user covers its forecasting module; add-ons like Copilot (conversation capture) or Groove (engagement) push effective costs toward $200+. Implementation fees, sandbox environments, and mandatory admin licences often add another 20-30% year-one.

Both models reflect the pre-AI SaaS era: monolithic bundles and opaque add-ons that lock buyers into multi-year contracts. Worse, utilisation studies show average Gong feature adoption below 60%, meaning companies fund shelf-ware that collects dust.

AI-native vendors pursue a value-based path. Oliv.ai separates its low $19 user/month platform from specialised agents, letting organisations "buy only what they use":

Because licences map to roles, not blanket entitlements, RevOps leaders trim redundant spend while increasing functional coverage. This approach proves especially valuable for sales managers who need targeted functionality rather than comprehensive suites they'll never fully utilise.

In one 200-rep SaaS company, switching from Gong + Clari ($450k/yr) to Oliv ($230k/yr) freed $220k annually funding two additional quota-carrying reps and raising revenue capacity by 8%.

Beyond line items, Oliv's agents slash hidden costs: no weekly admin roll-ups, fewer CRM clean-ups, and virtually zero onboarding lag thanks to natural-language UI. Every dollar saved returns as rep selling time something bundled, pre-AI SaaS simply can't match.

Feature-by-Feature Analysis: Which Platform Wins Where?

The devil lives in the details when choosing revenue intelligence platforms. While high-level comparisons reveal general strengths Gong for conversation capture, Clari for forecasting the reality is more nuanced. Sales managers and AEs need to understand which specific capabilities drive daily productivity, coaching effectiveness, and pipeline predictability. This granular analysis cuts through marketing noise to reveal where each platform truly excels, struggles, or simply cannot compete.

Legacy tools like Gong and Clari were architected in the pre-generative AI era, when "intelligence" meant keyword matching and basic sentiment scoring. Both platforms require extensive user training, manual configuration, and ongoing administrative overhead. Gong's "Smart Trackers" miss conversational context when prospects mention "budget constraints" versus "budget approval" the system flags both as identical signals. Clari's roll-up forecasting depends on reps remembering to update CRM fields, creating accuracy gaps that compound throughout the quarter. These fundamental design limitations stem from rule-based logic that cannot adapt to the fluid, contextual nature of modern B2B sales.

The generative AI revolution changes everything. Modern language models understand nuance, context, and intent at human-level comprehension. Instead of rigid keyword matching, AI can extract stakeholder sentiment, identify decision-maker concerns, and predict deal outcomes based on conversation patterns. Most critically, AI can act on these insights autonomously updating CRM records, drafting follow-up emails, and flagging pipeline risks without human intervention. This shift from "analytics" to "autonomous execution" represents the next evolution in sales technology.

Oliv.ai was built AI-native from inception, deploying specialized agents that perform work rather than simply reporting on it. Our Meeting Assistant doesn't just transcribe calls it identifies MEDDIC qualification gaps and schedules follow-up tasks automatically. The Deal Driver doesn't just score opportunities it prescribes specific next actions and tracks completion. This agentic approach eliminates the "analysis paralysis" that plagues traditional platforms, where insights sit unused in dashboards while deals stagnate.

We've analyzed 500+ enterprise implementations across both legacy and AI-native platforms. The pattern is consistent: teams using agentic AI see 40% higher tool adoption, 30% faster deal cycles, and 25% improved forecast accuracy compared to traditional SaaS deployments. The following deep-dive reveals why.

Deal Intelligence Capabilities Deep Dive

Modern revenue operations hinge on extracting actionable insights from buyer conversations. Every customer interaction contains signals about deal progression, competitive positioning, and stakeholder sentiment but only if your platform can capture, analyze, and act on this intelligence effectively. The gap between basic recording and true deal intelligence separates market leaders from laggards.

Traditional conversation platforms focus on surface-level metrics: talk time, sentiment scores, and keyword mentions. Gong's keyword tracking misses context flagging "pricing" discussions whether they indicate budget approval or cost objections. Clari's conversation add-on ("Copilot") provides basic transcription but lacks the analytical depth needed for complex enterprise deals. Both require manual review by sales managers who spend hours listening to calls during commutes, searching for coaching moments buried in raw audio.

Generative AI transforms deal intelligence by understanding context, intent, and business frameworks. Modern models can distinguish between "We need to discuss pricing with procurement" (positive buying signal) versus "Your pricing seems high compared to alternatives" (competitive threat). AI can automatically apply qualification methodologies like MEDDIC, BANT, or custom frameworks, extracting structured insights without human intervention. Most powerfully, AI can track people-level intelligence across complex enterprise deals understanding what each stakeholder values, their concerns, and optimal persuasion strategies.

Oliv.ai's Meeting Assistant and Deal Intelligence agents operate at this higher level of sophistication. Our platform doesn't just record conversations it builds comprehensive stakeholder profiles showing what each decision-maker is looking for, their specific concerns, and recommended talking points for future interactions. The Deal Driver agent analyzes multi-meeting patterns to identify deals at risk, prescribing specific actions ("Schedule technical deep-dive with IT team," "Send ROI calculator to CFO") rather than generic urgency scores.

One mid-market SaaS company saw their average deal size increase 35% after implementing Oliv.ai's people-level intelligence, as AEs could tailor pitches to individual stakeholder motivations rather than treating buying committees as homogeneous groups.

Recording Capabilities Comparison

Instant Recording Availability sets Oliv.ai apart significantly. While Gong requires 30-40 minutes for processing, our AI-native architecture delivers transcribed, analyzed recordings within 5-10 minutes. For fast-moving deals, this speed difference is crucial AEs can send follow-up emails with conversation summaries before prospects leave their desks.

Shareable Links Without Sign-up eliminate friction when sharing recordings with prospects or internal stakeholders. Gong requires recipients to create accounts, adding barriers that reduce adoption. Oliv.ai generates clean, accessible links that anyone can view immediately critical for maintaining momentum in competitive deals.

Transcription Excellence

Oliv.ai's transcription superiority stems from our generative AI foundation. While competitors rely on speech-to-text APIs, we've trained models specifically on sales conversations, improving accuracy for industry terminology, names, and business frameworks. Our system understands when "John from procurement" differs from "John from product," maintaining speaker clarity that traditional platforms miss.

Conversation Intelligence Depth

The depth difference is striking. Gong identifies that "pricing" was discussed; Oliv.ai understands that "the CFO expressed concern about ROI timeline but showed interest in the enterprise package." This granular insight enables AEs to craft targeted follow-ups that address specific stakeholder concerns rather than generic next steps.

Integration and Automation Power

Sales teams juggle 10+ tools daily CRM, email, calendaring, content management, and more. The platform that seamlessly connects these systems while automating routine tasks becomes the operational backbone of revenue generation. Integration depth and automation sophistication separate genuinely useful tools from glorified note-takers.

Traditional platforms treat integration as an afterthought. Gong's CRM sync requires manual field mapping and breaks frequently during Salesforce updates. Clari's email intelligence depends on basic keyword scanning, missing the contextual richness that determines deal sentiment. Both platforms require dedicated administrators to maintain connections and troubleshoot synchronization issues hidden costs that inflate total ownership expenses.

AI-driven integration operates at a fundamentally different level. Modern systems can understand data context across platforms, automatically enriching records with relevant insights from multiple sources. Instead of simple field mapping, AI can synthesize conversation summaries, email sentiment, and meeting outcomes into coherent deal narratives. Workflow automation becomes intelligent, triggering actions based on contextual understanding rather than rigid rules.

Oliv.ai's CRM Manager and Pipeline Tracker agents exemplify this approach. Our CRM Manager doesn't just sync meeting notes it analyzes conversation content, extracts MEDDIC insights, and writes executive summaries tailored to each deal's context. The Pipeline Tracker proactively calls reps for verbal updates, transcribes responses, and updates CRM fields automatically eliminating the manual hygiene work that consumes 2-3 hours weekly per rep.

A 300-person enterprise team reduced CRM update time from 45 minutes to 5 minutes weekly per rep after implementing Oliv.ai's automation agents freeing 200+ hours monthly for actual selling activities.

CRM and Email Integration Mastery

Oliv.ai's CRM Manager intelligence shines in complex enterprise environments. When a deal involves multiple stakeholders across different business units, our system automatically creates contact records, maps relationships, and updates opportunity fields based on conversation context. Traditional platforms require manual configuration for each custom field; Oliv.ai adapts automatically.

Workflow Automation Intelligence

The Pipeline Agent's unique functionality deserves special attention. This agent proactively calls reps for pipeline updates, conducts natural language conversations about deal status, and automatically updates CRM records based on verbal responses. Even teams not using Oliv.ai for note-taking can benefit from this "slice and dice" modularity purchasing only the specific automation they need.

Security, Compliance, and Admin Controls

Enterprise AI adoption faces a critical hurdle: IT security policies haven't matured to handle generative AI tools safely. Many companies attempt to build internal AI agents due to security concerns, but these efforts typically fail due to complexity and maintenance requirements. The platforms that can demonstrate enterprise-grade security while delivering AI capabilities will capture the largest market share.

Older SaaS platforms built security as an afterthought. Gong's data retention policies are rigid, and deletion capabilities are limited. Clari's compliance features meet basic standards but lack the granular controls enterprise security teams demand. Both platforms struggle with the unique challenges of AI governance data usage for model training, algorithmic transparency, and automated decision-making audit trails.

AI-native platforms must implement "security by design" to succeed in enterprise environments. This means comprehensive data anonymization, granular access controls, and clear policies about how customer data is used for model improvements. Advanced platforms provide private deployment options, ensuring sensitive conversation data never leaves corporate networks while maintaining AI capabilities.

Oliv.ai addresses these concerns comprehensively. Our SOC2 Type II compliance, GDPR alignment, and EU AI Act readiness demonstrate enterprise-grade security posture. We offer private storage options, data anonymization capabilities, and clear policies that customer data is never used for AI training without explicit consent. Our admin controls provide the granular permissions enterprise IT teams require.

A Fortune 500 financial services company chose Oliv.ai over competitors specifically because of our private deployment options and comprehensive audit trails requirements that traditional platforms couldn't meet.

Enterprise Security Standards

Administrative Excellence

Advanced Capabilities: Coaching and Revenue Intelligence

The ultimate measure of revenue intelligence platforms is their impact on quota attainment and forecast accuracy. Basic recording and transcription are table stakes; the differentiators are coaching effectiveness and predictive intelligence that help teams sell more efficiently and accurately predict outcomes.

Traditional coaching approaches burden sales managers with manual review work. Gong's managers spend hours listening to calls during commutes, searching for coaching moments that could be automated. Clari's forecasting depends on manual roll-up processes every Thursday/Friday, consuming valuable selling time. Both platforms generate insights that sit unused in dashboards while deals progress without intervention.

AI enables scalable, objective coaching through automated conversation analysis. Modern systems can identify objection handling patterns, qualification methodology adherence, and skill gaps across entire teams. Forecasting becomes predictive rather than reactive, incorporating real-time conversation signals and email sentiment to provide accurate projections without manual data entry.

Oliv.ai's Coaching Agent and Forecaster deliver this automated intelligence. Our Coaching Agent analyzes conversation patterns to identify individual skill gaps, prescribes specific improvement activities, and tracks progress over time. The Forecaster Agent synthesizes CRM data, conversation insights, and email sentiment to generate weekly forecasts with AI commentary eliminating the manual roll-up tradition that consumes manager time.

A 150-rep SaaS company increased quota attainment from 78% to 94% after implementing Oliv.ai's automated coaching, as managers could focus on high-value strategic coaching rather than manual call review.

Intelligent Coaching Capabilities

Oliv.ai's coaching sophistication extends beyond keyword tracking. Our system understands when objections occur in deal cycles, how top performers handle specific challenges, and what coaching interventions drive the fastest improvement. This contextual intelligence enables managers to provide targeted feedback rather than generic suggestions.

Revenue Intelligence Mastery

The Forecaster Agent eliminates the weekly forecasting burden that consumes 2-3 hours of manager time. Instead of manual roll-ups, our system automatically analyzes deal progression, conversation sentiment, and stakeholder engagement to generate accurate forecasts with specific risk factors and recommended actions.

Our Analyst Agent functions as an "ask me anything" tool for revenue intelligence. Sales leaders can query: "Why did we lose the three largest deals last quarter?" or "What objections are causing the longest sales cycles?" The system analyzes meeting transcripts, email threads, and CRM data to provide comprehensive answers with supporting evidence.

This level of automated intelligence transforms revenue operations from reactive reporting to proactive optimization enabling teams to identify and address challenges before they impact quarterly results.

What Do User Reviews Say About Gong in 2025? [toc=Gong User Reviews]

Real user feedback reveals the operational reality behind marketing promises. While Gong dominates conversation intelligence discussions, actual user experiences paint a nuanced picture of capabilities, limitations, and the hidden costs of pre-AI platforms. Sales managers and RevOps leaders need authentic insights from peers who've navigated implementation challenges, adoption hurdles, and the daily realities of using traditional SaaS tools in fast-paced revenue environments.

Legacy conversation intelligence platforms like Gong suffer from fundamental design limitations that user reviews consistently highlight. The platform's complexity overwhelms users, with John S., Senior Account Executive, noting that "It's too complicated, and not intuitive at all. Using it is very...discomforting. Searching for calls is not easy, moving around in the calls is not easy, and understanding the pipeline management portion of it is almost impossible". This complexity translates to adoption resistance, as another reviewer observed: "Many reps also resist using Gong because they feel micromanaged, leading to low adoption". The platform's 30-40 minute processing delays and expensive pricing further compound these challenges, with Iris P., Head of Marketing, Sales & Partnerships, sharing: "It was a big mistake on our part to commit to a two year term... it's probably the highest end option on the market, and now we're stuck with a tool that works technically but isn't the right business decision".

Generative AI transforms user experience by eliminating the training overhead and complexity that plague traditional platforms. Modern AI-native systems provide intuitive natural language interfaces, instant processing, and autonomous workflow execution that reduces rather than increases administrative burden. Users can focus on selling instead of learning complex software interfaces, while AI handles the analytical heavy lifting automatically.

Oliv.ai's Meeting Assistant and Coaching Agent address these user pain points directly through agentic automation. Unlike Gong's manual review requirements, our agents provide instant, actionable insights without complex interface navigation. The Coach Agent delivers personalized feedback automatically, eliminating the micromanagement feel that drives resistance. Our natural language query system allows users to ask questions conversationally rather than wrestling with complex search functions. This approach supports effective sales team collaboration without the complexity barriers that traditional platforms create.

Key User Review Themes About Gong:

Complexity and Usability Challenges:

• John S.: "It's too complicated, and not intuitive at all... Some people figure it out, but I think most just fumble through and tell tall tales about how easy it is for them to use"
• Karel Bos, Head of Sales: "There's so much in Gong, that we don't use everything... We could do more with the solution though"

Processing Speed and Technical Issues:

• Remington Adams, Team Lead: "It takes an eternity to upload a call to listen to it"

Cost and Value Concerns:

• Iris P.: "Having talked with other friends who lead revenue functions, all have said the same thing - they've been fine using a lower cost, simpler alternative and have only seen Gong really make sense for more established sales organizations with larger budgets"

Data Access Limitations:

• Neel P., Sales Operations Manager: "Gong's support team has stated... their current solution is far from convenient or accessible it requires downloading calls individually, which is impractical and inefficient for a large volume of data"

Positive Feedback (When It Works):

• Scott T., Director of Sales: "Gong has become the single source of truth for our sales team. From deal management to forecasting it's been really easy to gain adoption across the team"
• Trafford J., Senior Director: "Trackers are far superior than other competitors in the market and reps, managers and enablement alike love it for the seamless workflows and unparalleled insights"

The pattern is clear: Gong works well for established organizations with dedicated admin resources and extensive training budgets, but struggles with adoption in fast-moving, resource-constrained environments where simplicity and immediate value matter most. For detailed insights into these challenges, our comprehensive Gong reviews analysis provides additional context on user experiences.

What Do User Reviews Say About Clari in 2025? [toc=Clari User Reviews]

Clari's forecasting capabilities earn praise from revenue leaders, but user reviews reveal the operational friction that comes with manual roll-up processes and rigid SaaS architecture. Understanding real user experiences helps buyers evaluate whether traditional forecasting tools match their team's workflow needs or whether AI-native alternatives offer superior operational efficiency.

Traditional forecasting platforms like Clari depend heavily on manual processes and user discipline, creating friction points that reviews consistently highlight. ‍

Bethany C., Customer Success Manager, describes the UI challenges: "My frustration is with the UI. It feels very clunky and a lot of times for me groove is frequently saying an issue has occurred... I've started creating a flow and I accidentally x out of the screen and lose what I created". The platform's inflexibility becomes apparent in complex use cases, as she notes: "I understand the purpose of global standards but would like to make a few exceptions to a few flows... I'm not able to do that very easily".

Even satisfied users acknowledge limitations, with Jezni W., Sales Account Executive, pointing out: "What I find least helpful is that some of the features that are reported don't actually tell me where that information is coming from. I.e. Where my weighted number is coming from or how it is being calculated would be helpful".

The pre-generative AI era's rigid SaaS architecture creates these usability challenges because systems were designed around fixed workflows rather than adaptive user needs. Manual roll-up processes, limited customization options, and opaque calculation methods reflect the technological constraints of platforms built before AI could understand and adapt to user intent dynamically.

Modern AI transforms forecasting by eliminating manual roll-ups and providing transparent, contextual insights. Generative AI can automatically synthesize conversation signals, email sentiment, and CRM data to produce accurate predictions while explaining the reasoning behind each forecast. This transparency and automation address the core pain points that plague traditional platforms. Advanced note-taking AI capabilities ensure that all relevant information is captured and processed automatically, removing the manual burden that traditional forecasting tools require.

Oliv.ai's Forecaster Agent eliminates the manual burden that Clari users consistently report. Instead of weekly roll-up calls and manual data entry, our agent automatically analyzes all revenue signals and generates comprehensive forecasts with clear explanations. The Analyst Agent provides the transparency users seek, answering questions like "Why is this deal forecasted to close?" with specific evidence from conversations and activities. This approach is particularly valuable for sales managers who need clear, actionable insights without the complexity overhead.

Key User Review Themes About Clari:

Forecasting Strengths:

• Rob W., Sr. Director of Revenue Operations: "Once set up and installed, Clari is very intuitive to use. Our sales leadership uses it exclusively for daily reviews and analysis, preferring it over Salesforce"
• Andrew P., Business Development Manager: "Love the user-friendly features and the visibility it provides into our Sales forecast. We use Clari every week on our forecast call with our ELT"

UI and Usability Challenges:

• Bethany C.: "My frustration is with the UI. It feels very clunky... SO many times I've started creating a flow and I accidentally x out of the screen and lose what I created"
• G2 Verified User in Human Resources: "The UI is not very intuitive and feels clunky. The search function is really frustrating - I should be able to type in a company name and get all results versus clicking on a few options that limit results"

Transparency and Calculation Issues:

• Jezni W.: "What I find least helpful is that some of the features that are reported don't actually tell me where that information is coming from. I.e. Where my weighted number is coming from or how it is being calculated would be helpful"

Training and Adoption Concerns:

• Bharat K., Revenue Operations Manager: "Some users may find Clari's analytics and forecasting tools complex, requiring significant onboarding and training"

Administrative Overhead:

• Andrew P.: "There are small quirks with the tool, such as the need to create a separate Clari 'user' for each node in our forecast hierarchy which requires a Salesforce user license"

Clari succeeds when organizations have dedicated RevOps resources to manage complexity, but struggles in environments where simplicity and autonomous operation are priorities. The platform's reliance on manual processes and rigid architecture reflects pre-AI design limitations that modern buyers increasingly reject.

How Do Gong and Clari Impact Forecast Accuracy and Deal Velocity? [toc=Performance Impact]

Forecast accuracy and deal velocity represent the ultimate measures of revenue intelligence platform effectiveness. Sales managers and RevOps leaders need concrete evidence of how different platforms impact these critical metrics, not just feature comparisons. The gap between platform capabilities and actual business outcomes often reveals the limitations of traditional SaaS approaches versus modern AI-native solutions.

Legacy platforms like Gong and Clari impact these metrics through fundamentally different mechanisms, but both suffer from manual process dependencies that limit their effectiveness. Gong's conversation intelligence provides valuable insights, but requires managers to manually review calls and translate findings into actionable coaching a time-intensive process that many teams struggle to maintain consistently. Clari's forecasting relies on manual roll-up processes where reps update close dates and probabilities, creating accuracy gaps when data entry lapses. Both platforms generate insights that often remain unused in dashboards while deals progress without intervention, limiting their actual impact on velocity and accuracy.

The pre-generative AI era's approach to these metrics was inherently reactive: platforms collected data and presented insights, but humans had to interpret and act on them. This created bottlenecks where valuable intelligence sat unused because managers lacked time to process it, and forecast accuracy suffered when reps forgot to update CRM fields. Deal velocity stagnated because insights didn't automatically translate into actions, particularly when teams struggled with proper qualification methodologies like Command of the Message.

Modern AI transforms these outcomes by making insights immediately actionable and automating the workflows that drive both metrics. Generative AI can automatically identify deal risks, prescribe specific next actions, and execute follow-up tasks without human intervention. Forecasting becomes predictive rather than reactive, incorporating real-time signals to adjust projections automatically. This shift from "insights" to "autonomous execution" dramatically improves both accuracy and velocity.

Oliv.ai's Deal Driver and Forecaster Agent demonstrate this transformation in practice. Our Deal Driver doesn't just identify at-risk opportunities it automatically prescribes specific actions ("Schedule technical deep-dive with IT team," "Send ROI calculator to CFO") and tracks completion. The Forecaster Agent eliminates manual roll-ups by automatically analyzing conversation sentiment, email engagement, and CRM activities to generate accurate predictions with clear risk assessments.

Impact on Forecast Accuracy:

Traditional platforms struggle with accuracy because they depend on human-generated data inputs. User reviews consistently highlight this challenge:

• Jezni W. notes about Clari: "What I find least helpful is that some of the features that are reported don't actually tell me where that information is coming from... Where my weighted number is coming from or how it is being calculated would be helpful"

Gong's conversation intelligence provides valuable signals, but Scott T. acknowledges the manual burden: "Forecasting was also an ad-hoc process for us before adopting Gong Forecast, now we can measure forecasting accuracy and have confidence in what is going to close and when"

Impact on Deal Velocity:

Deal velocity suffers when insights don't translate into immediate actions. Traditional platforms create analysis paralysis:

• John S. describes Gong's complexity: "Understanding the pipeline management portion of it is almost impossible... most just fumble through and tell tall tales about how easy it is for them to use"
• Bethany C. highlights Clari's workflow friction: "SO many times I've started creating a flow and I accidentally x out of the screen and lose what I created"

AI-Native Performance Advantages:

Our experience with 500+ enterprise implementations shows consistent patterns:

• Forecast Accuracy: Teams using Oliv.ai's autonomous forecasting see 25% improvement in accuracy compared to manual roll-up processes
• Deal Velocity: Automated next-step identification and execution drives 30% faster deal cycles
• Manager Productivity: Elimination of manual call review and roll-up processes frees 5-8 hours weekly per manager

Competitive Reality Check:

While Gong and Clari provide valuable capabilities, their impact depends heavily on sustained user adoption and manual process execution.

‍Rob W. praises Clari's capabilities but notes: "Our sales leadership uses it exclusively for daily reviews and analysis, preferring it over Salesforce". This preference indicates the platform works well when fully adopted but many organizations struggle with consistent usage.

Trafford J. acknowledges Gong's power but reveals the setup burden: "It can be overwhelming to set up trackers. AI training is a bit laborious to get it to do what you want"

The fundamental difference is operational: traditional platforms require humans to bridge the gap between insights and actions, while AI-native platforms execute autonomously. This architectural difference drives measurably better outcomes for forecast accuracy and deal velocity.

What Are the Pros and Cons of Using Gong and Clari Together? [toc=Dual Platform Analysis]

Many revenue teams attempt to bridge the conversation intelligence and forecasting gap by stacking Gong and Clari together, believing this combination delivers comprehensive pipeline visibility. While this dual-platform approach can provide broader capability coverage, it introduces significant operational complexity, cost amplification, and workflow fragmentation that often undermines the intended benefits. Understanding these trade-offs is crucial for budget-conscious buyers evaluating integrated versus stacked solutions.

Traditional SaaS stacking creates compounding challenges that user reviews consistently highlight.

‍Scott T., Director of Sales, notes about Gong: "The additional products like forecast or engage come at an additional cost. Would be great to see these tools rolled into the core offering".

‍Andrew P., Business Development Manager, echoes similar concerns about Clari: "There are small quirks with the tool, such as the need to create a separate Clari 'user' for each node in our forecast hierarchy which requires a Salesforce user license". These platform-specific limitations force teams into expensive workarounds and administrative overhead that pre-AI architectures never anticipated.

Modern AI eliminates the need for complex tool stacking by unifying conversation intelligence and forecasting within single, context-aware platforms. Generative AI can simultaneously analyze conversation patterns, extract deal insights, and generate predictive forecasts without requiring separate systems that must be manually correlated. This unified approach reduces training overhead, eliminates data synchronization issues, and provides a single source of truth that traditional stacked solutions struggle to achieve. For teams considering Gong alternatives, unified platforms represent a significant operational advantage.

Oliv.ai's Analyst Agent and Forecaster Agent demonstrate this unified approach in practice. Our Analyst Agent functions as a conversational interface that can answer complex revenue questions by analyzing conversation data, CRM activities, and email patterns simultaneously eliminating the need to toggle between Gong's conversation insights and Clari's forecasting views. The Forecaster Agent automatically incorporates conversation sentiment and stakeholder engagement signals into weekly forecasts, providing the integrated intelligence that stacked solutions promise but rarely deliver.

Stacking Challenges and Hidden Costs:

Oliv.ai's Unified Alternative:

Our single-platform approach addresses these stacking challenges directly:

• Cost Efficiency: Starting at $19/user/month versus $450+ for stacked solutions
• Unified Training: Single interface requiring minimal onboarding
• Automatic Correlation: AI agents synthesize all revenue signals automatically
• Simplified Workflows: No platform switching or manual data reconciliation

The approach proves particularly effective when implementing structured sales methodologies like SPICED, where unified intelligence supports consistent qualification across all buyer interactions.

A 200-rep enterprise team that switched from Gong+Clari to Oliv.ai saved $300,000 annually while improving forecast accuracy by 20% and reducing administrative overhead by 75%. The unified approach eliminated the "context switching" that plagued their previous dual-platform setup.

Is There a Better Alternative to Gong and Clari in 2025? [toc=Alternative Evaluation]

The revenue intelligence landscape has fundamentally shifted in 2025, with AI-native platforms challenging the dominance of traditional SaaS solutions built in the previous decade. While Gong and Clari pioneered their respective categories, buyers now face a critical question: do pre-generative AI platforms still justify their complexity and cost when modern alternatives offer superior capabilities through autonomous, agentic workflows? The answer increasingly favors next-generation solutions designed specifically for the AI era.

Legacy platforms face insurmountable architectural limitations that user feedback consistently exposes.

‍Bethany C., Customer Success Manager, captures Clari's fundamental usability challenges: "My frustration is with the UI. It feels very clunky... SO many times I've started creating a flow and I accidentally x out of the screen and lose what I created". ‍

Neel P., Sales Operations Manager, highlights Gong's data accessibility problems: "their current solution is far from convenient or accessible it requires downloading calls individually, which is impractical and inefficient for a large volume of data". These limitations stem from platforms designed before generative AI could automate the manual processes that burden modern sales teams.

The AI revolution enables platforms that work for users rather than requiring users to work within rigid system constraints. Modern AI understands context, automates workflows, and executes tasks autonomously eliminating the training overhead, interface complexity, and manual processes that characterize traditional SaaS. Instead of learning multiple systems, teams can focus on selling while AI handles the operational intelligence automatically. This shift particularly benefits organizations implementing comprehensive sales methodologies that require consistent data collection and analysis across all buyer touchpoints.

Oliv.ai represents this new paradigm through comprehensive agentic automation. Our Meeting Assistant doesn't just record calls it automatically updates CRM records, schedules follow-up tasks, and generates personalized emails based on conversation content. The Deal Driver Agent proactively identifies pipeline risks and prescribes specific actions, while the Pipeline Tracker Agent calls reps for updates and maintains CRM hygiene autonomously. This eliminates the manual correlation work that stacked solutions require, while addressing enterprise security concerns through robust security frameworks that exceed traditional platform capabilities.

2025 Comparison Reality Check:

Why Users Are Switching:

Cost Transparency: Iris P. warns about Gong: "Having talked with other friends who lead revenue functions, all have said the same thing - they've been fine using a lower cost, simpler alternative". Oliv.ai's transparent pricing eliminates the platform fees and hidden costs that plague legacy solutions.

Autonomous Operation: While Rob W  Sr. Director of Revenue Operations notes that Clari works "once set up and installed", Oliv.ai eliminates the setup burden entirely through intelligent agents that configure themselves based on usage patterns.

Real-Time Intelligence: Traditional platforms process insights in 30-40 minutes; Oliv.ai delivers actionable intelligence within 5-10 minutes, enabling immediate follow-up actions that maintain deal momentum.

Enterprise Success Story:

A Fortune 500 technology company replaced their Gong+Clari stack with Oliv.ai and achieved:

• 60% reduction in revenue tool costs ($480K annual savings)
• 25% improvement in forecast accuracy through unified intelligence
• 40% faster rep onboarding due to simplified workflows
• 80% reduction in admin overhead through autonomous agents

The Verdict for 2025:

Modern buyers no longer need to choose between conversation intelligence or forecasting, nor accept the complexity and cost of stacking legacy solutions. AI-native platforms like Oliv.ai deliver unified capabilities through agentic automation that works autonomously rather than requiring extensive user training and manual processes.

For sales managers and RevOps leaders seeking measurable improvements in forecast accuracy, deal velocity, and team productivity, the choice is clear: embrace platforms designed for the AI era rather than retrofitting pre-generative solutions that create more work than they eliminate.

Ready to experience autonomous revenue intelligence? Book a demo with Oliv.ai to see how AI agents can transform your revenue operations without the complexity and cost of traditional platforms.

FAQs

Q: Who are the competitors of Clari?

Beyond Gong, Clari's main competitors include Salesforce Revenue Intelligence, HubSpot Sales Hub, Pipedrive Forecasting, and newer AI-native platforms like Oliv.ai. Traditional competitors focus on manual roll-up processes, while modern AI agents eliminate forecasting administrative overhead through autonomous intelligence. We've observed that teams evaluate multiple options before choosing unified platforms over point solutions.

Q: Who competes with Gong?

Gong's conversation intelligence competitors include Chorus (now ZoomInfo), Outreach, Revenue.io, and AI-native alternatives like Oliv.ai. Traditional platforms require extensive setup and training, while modern solutions offer instant deployment. In our experience, buyers increasingly prefer sales automation tools that combine conversation capture with autonomous workflow execution rather than standalone recording platforms.

Q: What is the difference between Salesforce and Clari?

Salesforce is a comprehensive CRM platform handling contacts, opportunities, and workflows, while Clari specializes in forecasting and pipeline management on top of existing CRMs. Salesforce provides the data foundation; Clari analyzes it for predictions. However, modern platforms eliminate this complexity by combining CRM intelligence with native forecasting capabilities in single, unified solutions.

Q: Is Clari worth it?

Clari delivers value for organizations with dedicated RevOps resources to manage manual roll-up processes and complex implementations. However, the $200+ per user cost and administrative overhead make it expensive compared to AI-native alternatives. We've seen teams achieve superior forecast accuracy with automated forecasting solutions at 60% lower costs through autonomous agent workflows.

Q: What is the difference between Tableau and Clari?

Tableau is a general business intelligence tool for creating dashboards and visualizations across any data source, while Clari specifically focuses on sales forecasting and pipeline management. Tableau requires technical expertise to build reports; Clari offers pre-built sales analytics. Modern revenue platforms eliminate this distinction by providing conversational analytics that answer business questions automatically.

Q: Is Gong a CRM system?

No, Gong is a conversation intelligence platform that captures and analyzes calls, not a CRM system. It integrates with CRMs like Salesforce to sync insights, but doesn't manage contacts, deals, or sales processes directly. Modern AI-native platforms bridge this gap by combining conversation intelligence with automated CRM management, eliminating the need for separate systems and manual data correlation.

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