Video Review
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Attention is like having your best sales coach in every call, powered by AI and never needing a coffee break.
Sam Quinn
July 31, 2025
★★★★☆ 4/5
Coaching. Consistency. Confidence.
Attention is an AI-native sales enablement platform that provides real-time coaching and conversation intelligence to help reps navigate calls like seasoned pros. By analyzing live conversations and surfacing context-aware prompts, it accelerates onboarding, improves win rates, and standardizes top-performer behaviors across teams. Designed for scaling sales organizations, it turns every call into an active coaching session that drives consistent, data-backed revenue growth.
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Overview
Attention is an AI-native sales enablement platform that redefines how reps learn, improve, and perform in real time. While most sales tools analyze conversations after the fact, Attention positions itself directly in the moment, delivering actionable prompts during live calls and surfacing insights that can immediately alter the trajectory of a deal. This is not another “conversation recorder with AI lipstick”—it’s a platform designed from the ground up to make AI the core engine of sales performance. Attention combines real-time coaching, deal risk intelligence, call analysis, and CRM automation into a single workflow, helping teams move from “I think that went well” to “I know exactly what to do next.” By embedding intelligence directly into the sales motion, it shifts enablement from reactive to proactive, compressing years of hard-won experience into every call a rep makes.
Who Is It For
Attention is built for any sales organization where consistency, speed to ramp, and deal execution can’t be left to chance. It’s a perfect fit for:
- Sales managers and directors who are tired of reviewing endless call recordings and want to scale coaching across large teams without sacrificing quality.
- Account Executives managing multi-stakeholder, complex deals who need help navigating objections, pricing discussions, and executive conversations without dropping the ball.
- SDRs and BDRs who need structure in discovery and prospecting calls, and who benefit from having a virtual coach guide them toward higher conversion rates.
- Revenue Operations leaders who crave visibility into performance patterns and pipeline risks, and who want coaching strategies to be driven by data rather than gut instinct.
- Startups and scaling teams that want to “clone” their top performers quickly, ensuring new hires replicate successful talk tracks and habits without requiring months of shadowing.
If you’re in an industry where messaging consistency and compliance are critical—like financial services or healthcare—Attention also doubles as a safeguard, ensuring reps stick to approved language and avoid costly missteps. Essentially, it’s for teams that believe good selling shouldn’t be an accident of personality or tenure—it should be repeatable, scalable, and supported by AI.
Use Cases
Live Deal Coaching
Reps get real-time prompts during calls to handle objections, qualify prospects, and drive deals forward.
Onboarding Acceleration
New hires ramp faster by adopting top-performer behaviors through AI-guided coaching.
Manager Amplification
One sales leader can coach dozens of reps simultaneously, scaling knowledge without stretching bandwidth.
Pipeline Risk Monitoring
Deal risk signals surface proactively, helping teams recover opportunities before they go cold.
Performance Benchmarking
Identifies what top performers do differently and packages those behaviors into repeatable playbooks.
Compliance Enforcement
Ensures reps in regulated industries maintain consistent, approved messaging without manual oversight.
Standout Features
Attention’s real-time AI coaching engine is its defining feature. It listens to calls in progress and surfaces prompts tailored to the flow of conversation, whether that’s handling a sudden pricing objection, asking about decision-making authority, or nudging the rep to clarify next steps. This goes beyond static scripts—it’s live, dynamic coaching that feels like a mentor sitting next to you.
Another standout is deal risk intelligence, which analyzes conversations and sales activities to flag potential issues—like a missing economic buyer, stalled momentum, or lack of urgency—before they turn into lost opportunities. By highlighting these risks, it gives both reps and managers a proactive playbook for recovery.
Attention also excels in performance benchmarking, using AI to identify the talk tracks, behaviors, and engagement styles of top-performing reps. It then distills those behaviors into playbooks that can be scaled across the team. Add in CRM integration and workflow automation, and you get a tool that not only makes reps better but also eliminates the administrative drag that often keeps them from selling.
PROS
- Real-time coaching that adapts dynamically to live conversations, providing reps with immediate, contextual guidance.
- AI-first foundation, meaning the platform isn’t an add-on—it’s designed entirely around machine learning and natural language processing.
- Automatic CRM updates reduce administrative work, improving data accuracy and freeing reps to focus on selling.
- Accelerates onboarding, allowing new hires to adopt the behaviors of top performers from day one.
- Scales efficiently, giving managers the ability to coach dozens of reps simultaneously without lowering impact.
CONS
- If prompts aren’t calibrated, reps may feel overwhelmed or distracted by constant nudges—think “AI Clippy,” but for sales.
- Audio quality matters; poor connections or noisy environments can throw off transcription and coaching accuracy.
- Adoption requires a cultural shift—reps and managers must embrace live coaching rather than relying solely on post-call reviews.
- Pricing is on the higher end compared to lightweight conversation intelligence tools, which may deter smaller teams.
- Limited multi-language capabilities make it less adaptable for globally distributed sales organizations.
What We Liked
We loved that Attention feels truly AI-native—its coaching, insights, and automation all revolve around machine intelligence, rather than slapping AI on top of a pre-existing workflow. The real-time prompts are one of the most useful features we’ve seen in sales enablement—they’re subtle, contextual, and often the difference between a prospect brushing you off and leaning in. The acceleration in onboarding is also impressive; new hires don’t need months of call reviews to find their footing because the AI guides them through live calls from day one. The ability to analyze patterns across thousands of calls and turn them into data-driven playbooks is another huge win—it shifts coaching from “art” to “science.” And finally, the scalability—managers can effectively be everywhere at once, ensuring coaching is consistent without burning out.
What We Didn’t Like
Like any powerful tool, Attention requires discipline to use well. If your sales process is loose or undefined, the AI won’t magically create structure—it can only enhance what’s there. Some reps, particularly seasoned ones, may bristle at live coaching prompts, perceiving them as intrusive or micromanaging. The pricing, while justified for the value, can feel like a barrier for smaller or more budget-conscious teams. And while the customization options are strong, aligning the prompts with your company’s exact messaging and sales methodology requires upfront investment of time and energy. Finally, while the English-language support is excellent, international teams operating in multiple languages may find its limitations frustrating.
Pricing
Attention positions itself as a premium solution, with per-seat pricing tailored to team size and feature access. Smaller teams can start with foundational tiers that offer real-time coaching and CRM sync, while enterprise organizations unlock advanced analytics, multi-team reporting, and custom playbook integrations. Pricing is higher than lightweight tools, but the ROI can be significant if measured against faster ramp times, increased win rates, and better pipeline visibility. Think of it as less of a “software cost” and more of a “revenue multiplier”—the returns often outweigh the spend when implemented effectively.
