Customer Intelligence

The top 13 customer intelligence platforms in 2023

By
Joel Passen
January 25, 2023
5 min read

Customer Intelligence (CI) has become a critical tool for organizations looking to gain a competitive edge in customer engagement and satisfaction. By collecting, analyzing, and leveraging customer data at scale, businesses can make informed decisions that will help them better understand their customers’ needs and preferences. With the rise of advanced technologies like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP), customer insights have become more accessible than ever before. As a result, the number of Customer Intelligence Platforms available today proliferates, with more sophisticated tools emerging each year. This article will discuss the top 13 customer intelligence platforms in 2023 across various subcategories, such as sales intelligence, product intelligence, health score tools, productivity tools, and support intelligence.

What is Customer Intelligence?

   

Customer Intelligence (CI) collects and analyzes key customer-generated data to glean crucial insights, risks, trends, and opportunities. CI is heavy on integrations and often uses advanced data sciences like artificial intelligence (AI), machine learning (ML), and natural language processing (NLP).

CI is about data — some you may have already been using and new data now available thanks to technological advances. To grasp the magnitude of Customer Intelligence, imagine if you could unite and analyze all your customer interactions — emails, tickets, chats, call transcripts, and community data. Now imagine harmonizing this new knowledge stream with data in your CRM, CSPs, and usage tracking systems to create new analytical frameworks, reports, dashboards, and critical workflows. That is the essence of Customer Intelligence.  

It goes without saying that core to any commercially viable CI solution is a sophisticated data privacy element. While our customers want you to use their feedback, suggestions, and more to improve the value they derive from your products and services, they also expect solutions built for the privacy-first era. They want you to fix bugs, make your product less confusing, build critical features and service them better. CI means better listening — active listening.

Customer Intelligence Subcategories

The proliferation of Customer Intelligence platforms doesn’t come as a surprise. Customer Experience has emerged as a top concern amongst business leaders, with more than 87% of senior business leaders indicating that customer experience is the leading growth engine for their businesses. The investment community has also taken a keen interest in Customer Intelligence-related startups pumping billions of dollars into the space in the past 48 months. The funding has been distributed across a variety of categories and line-of-business-focused segments. Let’s break CI down into a more digestible conversation. 

Customer Intelligence is quickly growing into a broad category. Our research taught us that a burgeoning ecosystem of CI categories and segment-specific platforms go deep to solve unique customer-related challenges. Nearly every Customer Intelligence solution leverages advanced data sciences to provide a missing layer to today’s B2B GTM stack. Based on conversations with over 100 B2B product and customer leaders, the most beneficial systems are those that create a System of Intelligence. But no matter the application, it is clear that leaders are looking for deeper insights with which to create more durable and profitable customer relationships.  

Customer and Product Intelligence

Sturdy.ai

US-based Sturdy represents a strong example of an innovative, commercially-ready, Customer Intelligence solution. Sturdy collects unstructured data sources like customer emails, tickets, chats, meetings, community data, and more via public APIs. It then restructures the data while also anonymizing it to address privacy concerns. The “clean” data is combined with other data sources like CRM data and then is unified into one searchable system that every team can use. Sturdy consolidates hundreds, sometimes thousands, of data silos, then employs AI, NLP, and ML to surface essential signals and themes that help teams improve products, relationships, and revenue. The platform has a no-code automation engine and a suite of APIs (Sturdy’s Data Exhaust) to route essential data and insights to the people, teams, and systems that need them most.  

CI systems like Sturdy can transform massive amounts of unstructured data (think email) into knowledge delivered autonomously to any business unit, team, person, or system. Sturdy makes insights accessible to end users and back-office analytics teams alike. Leaders are investing in AI-forward systems of intelligence because they see it as paving the path to taking customer-centricity to the next level. 

Who buys Sturdy?  

Customer and product leaders.

Pricing

Sturdy doesn’t list pricing on their website, stating, "Sturdy’s business plan is based on the volume of data you process and the Signals you use. We tailor our plans to best fit your needs, so please contact us for a custom quote.” It’s also worth noting that Sturdy has enterprise and SMB “quick start” plans. 

Sales-Focused Solutions

Gong.io

The most mature category of CI products are those designed for sales and other pre-revenue teams. The leader in the space, Gong.io, has pioneered the Revenue Intelligence category, which is closely related to Customer Intelligence. Sales-focused CI solutions primarily analyze recorded sales calls for coaching opportunities and conversational insights about customer buying behaviors. 

Gong makes mention that their platform can support customer success and marketing teams by focusing on moving them “closer to revenue.” Gong also can help managers use conversational insights to identify coaching opportunities for remote workers, as it seems with this entire category. 

Who buys Gong.io?  

Sales and RevOps Leaders at SMB and enterprise companies with significant BDR and corporate-level sales teams. 

Pricing

Gong has a lot of great content on their site for sales and RevOps pros, but, like most others, they don’t provide pricing information. However, their site says pricing is based on an annual platform fee and the volume of recorded calls. Others to watch in this category are Invoca and Databook. Both are taking innovative approaches to provide sales teams with Customer Intelligence.

Invoca.com

Invoca, like Gong.io, is a sales-focused platform that analyzes transcripts from sales calls to surface opportunities. The Invoca solution is called center-ready, and they list large customers like Verizon, Robert Half, and 1-800-Junk on their website. AI-forward technology provides the power to analyze all sales conversations, and the user interface provides multiple views of the overall prospect's journey and, often, beyond.   

Who buys Invoca?  

Sales, Call Center, and RevOps Leaders at B2C companies with larger agent-based, sales call centers.

Pricing

Invoca offers plans for both brands & agencies and pay-per-call marketers. They offer Pro, Enterprise, and Elite tiers in the former and Performance Professional and Enterprise in the latter. Neither list pricing on the website. 

trydatabook.com

Another player in the sales-focused category is Databook. Databook provides “strategic enablement for account-based selling,” allowing teams to focus on more “doing” and less “planning.” Databook’s website classifies strategic enablement as “the art of leveraging information, process, and technology to successfully craft the strategies needed to drive effective sales execution.” This is all to say that they provide data to better inform and optimize your account-based sales process. 

To accomplish this, Databook leverages its proprietary data sciences tech to analyze publicly available data. It crawls all your accounts to provide and finds and ranks prospective accounts. Databook positions itself as an Enterprise Customer Intelligence Platform — another system of intelligence — to help you close more deals. 

Who buys Databook?  

Sales and RevOps Leaders at B2B companies with account-based sales and marketing motions.

Pricing

Databook does not provide any pricing information on its website. You can request a free demo on their contact us page.

Support / Contact Center Intelligence

In addition to sales-focused CI, the support-focused call center category is very well represented in funding and product maturity. Companies like Observe.AI, Balto, and Forethought have raised $358MM to analyze interactions like support tickets and agent-managed phone calls. These solutions seek to reveal coaching opportunities, quality of service issues, sentiment, and compliance matters. 

Observe.ai

Observe.ai is a noteworthy solution in the Support / Call Center Intelligence subcategory. The platform analyzes agent calls and tickets. Then, using its proprietary conversation intelligence engine, it looks for what they call Moments, out-of-the-box and customer-defined themes. Consolidated views of all agent conversations and Moments give leaders good visibility into coaching/training and quality of service issues. 

Who buys Observe.ai?  

Call Center, Support, and Service Operations Leaders at B2C and B2B companies with larger agent-based support call centers.

Pricing

Observe.ai does not provide any pricing information on its website. Instead, the company offers live demonstrations to walk prospective customers through the platform and its features based on various use cases.

Balto.ai

Leaders evaluating Observe.ai should also consider evaluating Balto. Balto’s conversational intelligence solutions offer benefits to agents, supervisors, and leadership with the goal of improving agent performance. Their AI enables companies to train and onboard their agents faster with prescriptive content suggestions and triggers that alert supervisors of critical moments and coaching opportunities. Balto promises to ensure that “your agents will say the right thing on every call,” real-time guidance is programmed to assist agents with the next best actions and workflows. Balto’s secret sauce is the real-time alerts that managers receive when agents need assistance allowing teams to be as proactive as possible.    

Who buys Balto.ai?  

Call Center, Support, and Service Operations Leaders with larger agent-based call centers at B2C and B2B companies.

Pricing

As with the norm, Balto does not provide specific pricing information but allows prospects to elect for personalized demos.

Product Intelligence

Product Intelligence is another healthy category of the Customer Intelligence space. These solutions aim to serve product and user experience teams with customer-generated insights related to product adoption and roadmap suggestions. Pendo and Aha! have been at it the longest and focus on collecting usage data and surveys. While an up-and-comer, Enterpret is building the next generation of customer feedback intelligence by leveraging the voice of the customer.

Pendo.io

Pendo is a category leader in the Product Intelligence segment. It combines your product’s feedback, analytics, and in-app guides into one workspace. Pendo solicits and collects qualitative and quantitative data to understand customer engagement and product efficacy. With tools to impact and measure product engagement to deliver content to users at critical junctures like onboarding, Pendo is a feature-rich product intelligence solution. This maturity extends to Pendo’s commercial motions. In short, they have plans and associated feature bundles to fit small start-ups and enterprises alike.

Who buys Pendo?  

Product Management, Product Operations, Product Marketing, and Operations leaders at small and large B2B and B2C companies. 

Pricing 

Pendo is one of the few vendors that offers detailed pricing information on their website featuring four separate plans: Free, Starter, Growth, and Portfolio. While the freemium offering allows users to get a taste of the power of Pendo, it offers a scant limit of 500 monthly active users (meaning your product users), product analytics, and in-app guides. 

The Starter package increases monthly active users to 2,000 and adds their Net Promoter Score (NPS) tool. This package costs $7,000 a year. In addition to these offerings, Pendo’s Growth plan provides Sentiment analytics and can be used in a single web or mobile app. And finally, Pendo’s Portfolio package allows users to use the software across unlimited web and mobile apps. In addition to sentiment analytics, it provides cross-app reports and portfolio summaries. 

aha.io

Where Pendo focuses on customer feedback, Aha! provides a platform for product road mapping. More of an ideation and product creation platform for product managers than feedback analysis play, it’s a surprise to us that Aha! doesn’t integrate out-of-the-box with Pendo. Integrating Pendo data requires a Zapier integration.

The Aha! suite offers a collaborative seven-step framework for the product development process The first step establishes a clear vision and goals. The Ideate phase captures brainstorms and crowdsourced ideas. The Plan phase helps users prioritize, estimate value, and manage capacity. Showcase allows users to share roadmaps and go-to-market plans. The Build phase allows users to deliver new functionality through agile development. The Launch step brings these new features to market. Lastly, the Analyze phase allows you to see your product come to life by tracking customer usage. 

Who buys Aha!?  

Product Management and Engineering leaders at small and large B2B and B2C companies. 

Pricing

Like Pendo, Aha! also offers a freemium option for their Aha! Create, a digital notebook for product builders. Interestingly enough, Aha! offers a free 30-day trial for its premium products. This allows users to access all features, easily invite colleagues to collaborate, and does not require a credit card upfront. Following the free trial, the Aha! Develop offers an agile tool for healthy development teams at $9 per user per month. Aha! Ideas is a comprehensive idea management tool that starts at $39 per user per month. Last but not least, the Aha! Roadmaps offering starts at $59 per user per month. 

Enterpret.com

Enterpret, similar to Pendo, is building a customer feedback platform. Unlike Pendo’s approach, which leverages data from surveys and other solicitations, Enterpret looks at external reviews and internal interactions like support tickets. The platform then allows users to create and search a taxonomy to find and track product insights. Enterpret is equipped with semantic search capabilities making it easy to query keywords and topics. Their core offering aims to help teams prioritize product roadmaps, discover product gaps, and detect quality issues. The company was founded by software engineers and backed by notable investors.    

Who buys Enterpret?  

Product Management and Engineering leaders at SaaS companies. 

Pricing 

There is no pricing information available on the Enterpret site. Like many others listed above, prospective customers can fill out a demo form for more information.

Productivity Tools

Productivity-focused CI apps like Theysaid.io (FKA ‘Nuffsaid) and Retain.ai help customer success teams understand which customers need the most attention and which are black holes for your resources. For example, Theysaid.io uses a proprietary engine to prioritize tasks that matter most and log information to other systems without app-switching. This might be particularly useful to teams that use an “at scale” or “one to many” approach to manage customers. 

TheySaid.io

TheySaid bills itself as a modern approach to customer success platforms. Customer interactions are consolidated in a single workspace. The analysis is done on the aggregate data to find trends. Customers are asked questions as they interact with products gathering inputs that make up quantitative trends. When a trend hits defined thresholds, workflows are kicked off. This can be particularly helpful for teams that employ a one-to-many approach. 

Users of TheySaid create role-specific questions vetted by third-party experts and sent at specific times during the customer journey. Risks are then scored and given a label. TheySaid state on their website that getting started takes just a few hours.

Who buys TheySaid?  

Customer Success Leaders are at SMBs that have not leveraged a traditional customer success platform.

Pricing 

Although no pricing information is offered on the website, the demo form states that prospective customers can try TheySaid for free.

Retain.ai

Like Theysaid, Retain.ai aims to create a single source of record for every customer. And, like TheySaid, getting started is quite easy. Just select what applications, workflows, pages, and attributes you want Retain.ai to track. Have your teams install a browser plugin, and the system starts tracking things like time-to-serve, engagement, team productivity, and more. Customers receive a holistic view of customer engagement across all systems view dashboards. Retain.ai has some sample case studies on its website, but it's unclear what market segment the product is geared towards.

Who buys Retain.ai?  

Customer Success Leaders at B2C companies (based on their sample case studies).

Pricing

The Retain.ai website does not provide any pricing information. Those interested in learning more can fill out their demo form.

Health Score Tools

Arguably, customer health score solutions appear more as an output of Customer Intelligence than a category. These solutions target SMB buyers who haven’t adopted a more robust customer success platform. Companies like Akita and Involve.ai analyze product usage, NPS, the number of support tickets, and customer sentiment and then, with the help of data science, ascribe a health score to your accounts. Similar to Theysaid, Involve.ai takes it further by recommending playbooks once an account reaches a certain health threshold.

Akitaapp.com

Akita is the go-to customer success software for SaaS businesses. Akita provides a hub for telemetry-based customer data, activity, and metrics. Beyond storing all the information, it lets customers set up unlimited alerts when certain criteria are met. Like Involve.ai, automated playbooks can be triggered in response to customer behaviors or attributes. This frees up valuable time to focus on high-value tasks. Beyond this automation lies Akita’s task management capabilities, built to provide a single and simple interface for workflows. Thinks of this as a workspace for CSMs

Who buys Akita?  

Customer Success Leaders 

Pricing

Akita offers three transparent pricing options. Start, Connect, and Customize offerings can be purchased on a monthly or annual subscription. Prospective customers are incentivized to go annual by saving 20% after 12 months. The Start plan offers basic features and costs $160/month (if billed annually) for up to three users. Each additional user costs $47.20 per month. The Connect Plan offers “powerful integrations for a scalable customer success strategy.” This plan costs $480 per month (again, if billed annually). Similar to the Start plan, this plan includes three users, with each additional user costing $63.20 per month. Last but not least is the Customize plan. This option requires connecting with an Akita representative to learn more about their advanced integrations. Before committing to any of these plans, however, prospective customers can test Akita out on a free 14-day trial. This free trial includes unlimited user licenses, playbooks, custom segments, and health scores.

Involve.ai

Involve.ai touts that they’re an early warning system to predict churn and upsell opportunities. Their platform is built to help customers capture and analyze customer sentiment. After organizing and analyzing customer sentiment, Involve delivers actionable insights regarding retention, churn risk and upsell opportunities. Additionally, Involve provides customers with an actionable customer health score powered by their proprietary AI model built to analyze customers’ qualitative and quantitative data. Like Akita, Involve provides automated workflows and playbooks to maximize team efficiency.

Who buys Involve.ai?  

Customer Success Leaders at SMBs that have yet to adopt a customer success platform 

Pricing

Involve.ai doesn’t provide a specific pricing breakdown but a tool that hints at potential costs based on the number of clients and revenue. For example, a company with a $5MM ARR, 2% Annual Churn Rate ($100,000), and fifty customers can expect to pay $12,000 annually for Involve.ai.

By now, it’s clear that Customer Intelligence is a diverse and quickly evolving market. This list is not exhaustive. The common theme for all the systems mentioned here is data centricity. They all hinge on getting data in one place and analyzing it to provide better insights about customer behaviors.   

Whether you’re already sold on the value of Customer Intelligence or looking for ways to take your customer relationships to the next level, check out these key considerations you need to know about choosing the right Customer Intelligence platform to accelerate your goals. 

When choosing a CI platform, consider the following:

  • Insights for various teams: Customer Intelligence isn’t just for customer success teams. Product and engineering teams can immediately benefit from learning more about customer frustration, confusion, and wants directly from the voice of the customer. Marketing teams can transform positive insights into customer references. Revenue operations and business intelligence teams can create new analytical frameworks from previously unavailable data. Choose a system that helps you democratize customer insights and one that helps to create a collective reality for every team that wants to better understand your customers.
  • Fast time to value: Let’s face it, we’ve all bought platforms that were oversold, hard to implement, and even harder to administer. Look for solutions that can deliver insights to your specific use cases quickly. Understand the resources required to start receiving value and what resources are needed to maintain the program in the future.
  • Tech stack: When choosing a Customer Intelligence platform, the platform you select must integrate deeply with the critical components of your current GTM tech stack. And don’t forget about customer email. More than 50% of B2B customer-to-business communications start with an email.
  • Avoid duplicate functionality: CI platforms often have similar functionality to systems you already have, like customer success platforms and CRM systems. Look to compliment your existing system with rich data from a Customer Intelligence solution.
  • Security: Does the platform have a clear and transparent take on data security? Ensure that any system you choose is SOC 2 Type II ready.
  • Data privacy: How does the platform handle data privacy? What is the technical approach to safeguarding your customers’ PII? Will the solution meet the security and privacy requirements of your infosec and data privacy teams?

   

In conclusion:

We’re still in the early innings of CI. The challenges to achieving the potential are eroding as quickly as the technical capabilities are evolving, creating a new must-have system for the modern post-sale tech stack. Many organizations aren’t aware of how rapidly it’s evolving and may not realize the benefits Customer Intelligence can bring to various teams in their companies.

As we look ahead to 2023, it's clear that Customer Intelligence will continue to be one of the most essential tools businesses can use to stay competitive and understand their customers better. By leveraging customer data through CI platforms, companies are able to make informed decisions that will help them improve customer engagement and drive sales and revenue retention. They ultimately increase customer satisfaction levels across all channels to ensure your customers grow with you, not away from you.    

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What Is a QBR? (And Why Most of Them Are Broken)

Alex Atkins
January 15, 2026
5 min read

Quarterly Business Reviews (QBRs) were invented with good intentions: get out of the weeds, meet with your customer, and align on outcomes every quarter.

In practice? Many QBRs have become 40-slide product monologues that take weeks to build, bore executives, and don’t change much of anything.

As Aaron Thompson argues in his widely shared post “QBRs are Stupid” [1], the traditional way we do QBRs is often more about checking a box than driving real business value. But when done right—and when modern tools are involved—a QBR (or more broadly, an “Executive Business Review”) can still be one of the highest leverage motions in Customer Success, Sales, and Account Management.

This post breaks down:

  • What a QBR is (and what it’s supposed to be)
  • Who uses QBRs and why they matter
  • The traditional steps to creating a QBR
  • How QBRs are evolving (less “quarterly,” more “business review”)
  • How Sturdy.ai can run QBRs for any account in seconds—not hours or days

What Is a QBR?

A Quarterly Business Review (QBR) is a structured, typically executive-level meeting between a vendor and a customer to:

  • Review business outcomes and value delivered
  • Align on goals, strategy, and risks
  • Agree on a plan for the next period (not always a quarter anymore)

Unlike a status meeting, a QBR is supposed to focus on outcomes, strategy, and impact, not tickets, small features, or sprint updates.

Industry bodies like TSIA (Technology & Services Industry Association) and customer success leaders (e.g., Gainsight, Winning by Design) have consistently emphasized that effective business reviews should be outcome-based, data-backed, and jointly owned by vendor and customer [2][3].

Who Are QBRs For?

QBRs are heavily used across:

  1. Customer Success (CS) / Account Management (AM)  
    • To prove ongoing value
    • Reduce churn and expand accounts
    • Align on adoption, usage, and business outcomes
  2. Sales / Strategic Accounts / Customer Directors  
    • To maintain executive relationships
    • Surface expansion opportunities
    • Show roadmap alignment to strategic initiatives
  3. Professional Services / Consulting / Agencies  
    • To connect deliverables to business impact
    • Discuss ROI, timeline, and next phases
    • Reset expectations where needed
  4. Product & Executive Teams  
    • To hear voice-of-customer at the highest level
    • Validate product direction with strategic accounts
    • Identify common themes and risks across the portfolio

In modern SaaS and B2B, QBRs have shifted from a “CS-only” ritual to a cross-functional motion that spans CS, Sales, Product, and Leadership [4].

Why QBRs Matter (When They’re Done Right)

When they’re not just slidedecks for slidedeck’s sake, QBRs can:

  • Prove value
    Tie your product directly to metrics your customer’s executives care about: revenue, cost savings, risk reduction, NPS, time-to-value.
  • Protect and grow revenue
    Well-run business reviews correlate with higher renewal and expansion rates because they build trust and keep your solution aligned with evolving needs [2][5].
  • Align on strategy and roadmap
    They create formal space to talk about: “Where is your business going?” and “How does our roadmap support that?”
  • Surface risk early
    Adoption gaps, champion turnover, budget changes—QBRs are where these get raised and addressed proactively.

The problem is not the idea of a QBR; it’s the way traditional QBRs are executed.

The Traditional QBR: Steps, and Where They Go Wrong

Let’s walk through the typical (old-school) QBR workflow and why it’s so painful.

Step 1: Define Objectives and Audience

What’s supposed to happen:

  • Clarify the purpose of the review:
    • Renewal risk?
    • Proving ROI?
    • Expansion discussion?
    • Strategic alignment with a new initiative?
  • Confirm who will attend: executive sponsors, day-to-day users, procurement, etc.
  • Tailor the content to those people, not a generic template.

Why it matters:
McKinsey and Gartner both emphasize executive conversations that center on the customer’s business priorities, not your internal agenda [5][6]. If you don’t decide the objective and audience upfront, you end up with a “kitchen sink” deck that satisfies no one.

Where it goes wrong:
Teams often skip this step and reuse the same template for every account, regardless of size, segment, or lifecycle stage.

Step 2: Gather Data (Usage, Outcomes, Support, Voice-of-Customer)

What’s supposed to happen:

  • Pull product usage data (logins, key feature adoption, utilization vs. license)
  • Capture business outcomes (KPIs, ROI estimates, improved cycle times, etc.)
  • Summarize support data (tickets, escalations, time-to-resolution)
  • Incorporate voice-of-customer: NPS, CSAT, survey results, call notes, emails

Why it matters:
Data-backed QBRs are more credible and effective. TSIA’s research on outcome-based engagement models shows that value evidence (data plus narrative) is a core driver of renewal and expansion [2].

Where it goes wrong:

  • Data is scattered across CRM, helpdesk, product analytics, call recordings, Slack, and email
  • CSMs or AMs spend hours to days cobbling it together manually
  • Important context (like that frustrated email from the VP last month) gets missed because it lives outside the “official” systems

Step 3: Build the QBR Deck

What’s supposed to happen:

A concise, outcome-focused structure such as:

  1. Executive Summary  
    • Key wins this period
    • Key risks and challenges
    • Recommended next steps
  2. Your Goals & Strategy  
    • Recap of the customer’s stated objectives
    • Any changes in their business (M&A, leadership, budget shifts)
  3. Value & Outcomes  
    • KPI trends
    • ROI or impact stories
    • Before/after comparisons where possible
  4. Adoption & Usage  
    • Feature adoption
    • Usage by segment/team
    • Gaps and opportunities
  5. Support & Experience  
    • Ticket trends
    • NPS/CSAT highlights
    • Themes from feedback
  6. Roadmap & Alignment  
    • Relevant roadmap items
    • How they map to the customer’s goals
  7. Joint Plan / Next 90 Days  
    • Clear action items, owners, and dates
    • Milestones for the next review

Why it matters:
This structure keeps the meeting focused on the customer’s business—not on an endless product tour. Gainsight and other CS thought leaders consistently recommend an “outcomes-first” format that leads with business results, not feature lists [3].

Where it goes wrong:

  • The deck is 40–60 slides of feature screenshots and charts
  • The story is missing: data with no narrative, or narrative with no data
  • It’s built from scratch every time, burning hours of CSM and AM bandwidth

Step 4: Internal Review and Alignment

What’s supposed to happen:

  • CS, Sales, and sometimes Product or Leadership review the QBR deck together
  • Align on:
    • Renewal / expansion posture
    • Risk areas to probe
    • Who will say what in the meeting

Why it matters:
Cross-functional alignment ahead of the call means you present a unified front. Research on strategic account management underscores the importance of coordinated communication across all vendor stakeholders [7].

Where it goes wrong:

  • Internal prep is rushed or skipped
  • Different people show up with different agendas
  • The customer experiences a fragmented, reactive conversation

Step 5: Run the Meeting

What’s supposed to happen:

  • Start with outcomes and their priorities, not your agenda
  • Spend more time on discussion than on presenting slides
  • Ask questions like:
    • “What’s changed in your business since we last met?”
    • “What would make this partnership a no-brainer for you next year?”
    • “Where are we falling short of expectations?”

Why it matters:
Harvard Business Review and other executive communication research shows that senior leaders want vendors to:  

  1. understand their business context, and
  2. co-create solutions, not just present information [6].

Where it goes wrong:

  • It’s a monologue; the vendor talks for 80–90% of the time
  • The “review” is mostly a product tour or roadmap dump
  • Action items are vague or never captured

Step 6: Follow-Up and Execution

What’s supposed to happen:

  • Share a succinct recap:
    • Decisions made
    • Action items, owners, and due dates
    • Updated success plan
  • Track progress and refer back to it in the next review

Why it matters:
Without follow-up, QBRs become “nice conversations” that don’t change outcomes. TSIA and Forrester both highlight the importance of codifying customer outcomes and success plans as part of a recurring cadence [2][8].

Where it goes wrong:

  • Notes live in someone’s notebook or a random doc
  • No shared source of truth for the success plan
  • The next QBR starts from scratch, again

How QBRs Are Evolving

Several trends are reshaping how leading teams approach QBRs:

1. From “Quarterly” to “Right Cadence”

Not every account needs a formal review every quarter. Many organizations now use:

  • Tiered cadences:  
    • Strategic: monthly / quarterly
    • Mid-market: 2–3x per year
    • Long-tail: automated or one-to-many reviews
  • Event-based reviews:  
    • Post-implementation
    • Pre-renewal
    • After major org or product changes

This aligns with best practices in scaled customer success, where engagement is driven by value moments and risk signals, not arbitrary calendar quarters [3][4].

2. From “Slide Deck” to “Shared Workspace”

Instead of a static PowerPoint, teams are moving toward:

  • Live dashboards (usage, outcomes, health)
  • Shared success plans (in CRM or CS platforms)
  • Collaborative docs with real-time notes and ownership

The review becomes a conversation anchored in live data, not a one-way presentation of stale screenshots.

3. From “CS-Only” to Cross-Functional

Sales, Product, and Leadership are increasingly:

  • Joining key business reviews
  • Using them to validate roadmap, gather voice-of-customer, and shape account strategy
  • Treating QBR artifacts as input into forecasting, product planning, and exec reporting

This shifts QBRs from a “CS ritual” to a company-wide motion for strategic accounts.

4. From Manual to AI-Accelerated

The most important evolution: how the QBR is created.

Instead of:

  • Manually pulling data from 6+ systems
  • Rebuilding decks from scratch
  • Hoping someone remembered that critical email or call

Organizations are now using AI and automation to:

  • Aggregate all customer interactions and signals
  • Summarize risks, opportunities, and sentiment
  • Auto-generate QBR-ready narratives and visuals

This is where tools like Sturdy.ai fundamentally change the game.

How Sturdy.ai Can Run QBRs for Any Account in Seconds

Traditional QBR prep can easily consume 5–10+ hours per account once you factor in:

  • Data gathering
  • Deck building
  • Internal alignment
  • Revisions

Multiply that across a CSM’s portfolio and it becomes obvious why QBRs either get skipped or watered down.

Sturdy.ai flips this on its head.

At a high level, Sturdy.ai:

  1. Ingests your real customer data  
    • Emails
    • Call transcripts
    • Support tickets
    • CRM notes
    • Product usage and other signals (where integrated)
  2. Understands what matters  
    • Themes and topics (requests, bugs, risk signals)
    • Sentiment and urgency
    • Stakeholder changes and escalation patterns
    • Outcome-related language (ROI, time savings, revenue impact, etc.)
  3. Auto-builds QBR-ready insights in seconds
    For any account, Sturdy.ai can surface:
    • What’s going well (wins, positive feedback, adoption signals)
    • What’s not (repeated complaints, unresolved issues, risk indicators)
    • Which outcomes you’ve actually helped drive
    • Concrete recommendations and action items for the next period
  4. Generates QBR artifacts instantly
    Instead of starting with a blank slide, you start with:
    • An executive summary tailored to that account
    • Key metrics and trends pulled from your systems
    • Highlighted quotes and examples from real interactions
    • A suggested agenda and next-steps section

What used to take hours or days of manual prep becomes a seconds-long operation:

“Run QBR for ACME Corp.”

…and you have a structured, account-specific review ready to refine and deliver.

Why This Matters for Modern CS, Sales, and Account Teams

When QBRs are no longer time-prohibitive:

  • You can run them for more accounts, not just the top 10%
  • You focus on quality of conversation, not on slide assembly
  • You capture real, holistic context, not just what’s in one system
  • You can standardize excellence, instead of relying on heroics from your best CSMs

Instead of asking, “Do we have time to do a QBR for this customer?”, the question becomes:

“Given we can generate a review in seconds, what’s the right cadence and format for this account?”

That’s the shift from QBRs-as-admin-work to QBRs-as-a-strategic-advantage.

Bringing It All Together

  • QBRs were created to align on outcomes, prove value, and co-create a plan—not to be product demos with extra steps.
  • Traditional QBRs are broken because they’re manual, generic, and often misaligned with what executives actually care about.
  • The fundamentals still matter: clear objectives, data-backed story, joint success plan, and strong follow-up.
  • QBRs are evolving toward flexible cadence, collaborative formats, cross-functional ownership, and heavy use of data and AI.
  • With Sturdy.ai, you can run QBRs for any account in seconds, pulling from the full reality of your customer interactions—not just the few metrics someone had time to find.

If you’re spending hours or days preparing for each QBR, you’re paying the “old tax” on a motion that no longer has to be that painful. The value of the QBR is in the conversation, not the manual labor behind the slides.

References

[1] Aaron Thompson, “QBRs are Stupid,” LinkedIn Pulse (discussion of common QBR pitfalls and how they fail to deliver real value).
[2] TSIA (Technology & Services Industry Association), research and best practices on outcome-based customer engagement and Customer Success motions.
[3] Gainsight, Customer Success thought leadership on Executive Business Reviews and outcome-focused customer engagement.
[4] Winning by Design and similar SaaS consulting frameworks on recurring value reviews and customer-centric cadences.
[5] McKinsey & Company, research on B2B customer value, account management, and executive engagement strategies.
[6] Harvard Business Review and Gartner, articles and research on effective executive conversations and strategic vendor relationships.
[7] Strategic account management literature and SAM programs that emphasize coordinated, cross-functional engagement with key customers.
[8] Forrester, research on customer lifecycle management and the importance of measurable, recurring value communication.

Customer Churn

The Most Dangerous Threat to CROs

Joel Passen
July 1, 2025
5 min read

The most dangerous threat to CROs doesn’t live in the opportunity pipeline.

It's churn.

  • It doesn’t scream like a missed quarterly pipeline goal.
  • It doesn’t show up in dashboards until it’s too late.
  • It's rarely caught by a generic 'health score'.
  • It's the board meeting killer.

Retaining and growing our customers is the only repeatable, compounding, capital-efficient growth lever left in B2B businesses.

📉 CAC is way up.

📉 Channels are saturated.

📉 Talent is expensive.

📉 Competition is fierce.

📉 Switching costs are low.

The path to $100M used to be “sell, sell, sell.”

Today? It’s “land, retain, expand.”

No matter how strong your sales motions are or how slick your product or service looks during the sales process, if your customers are churning, you’re stuck in a leaky bucket loop of doom.

Every net-new dollar you win is offset by dollars you lose. It's just math.

Yet most GTM orgs still operate like retention is someone else’s problem. "That's a CS thing."

  • The CS team might “own” the customer post-sale.
  • Account Management may own the renewal and growth number.
  • Support is in the foxhole on the front line.
  • RevOps might model churn with last quarter’s data.
  • Marketing might send an occasional newsletter via email.
  • Finance may be leaning in on the forecasting.
  • Product is building things that supposedly the customers want.

But in reality, churn is the CRO's problem. We wear it - or should.

If your go-to-market motion isn’t designed to protect and grow customers from Day 1, you’re not just leaving money on the table — you’re setting fire to it.

Retention and expansion aren’t back-end functions. They’re front-and-center revenue motions.

The most valuable work these days starts after the contract is signed — not before.

We need to stop treating post-live as a department and start treating it as the engine of durable growth.

Software

Have you heard this from your CEO?

Joel Passen
April 29, 2025
5 min read

"How are we using AI internally?"

The drumbeat is real. Boards are leaning in. Investors are leaning in. Yet, too many leaders hardly use it. Most CS teams? Still making excuses.

🤦🏼 "We’re not ready."Translation: We don't know where to start, so I'm waiting to run into someone who has done something with it.

🤦🏼 "We need cleaner data."Translation: We’re still hoping bad inputs from fractured processes will magically produce good outputs. Everyone's data is a sh*tshow. Trust me. 🤹🏼♂️ "We're playing with it."Translation: We have that one person messing with ChatGPT - experimenting.

😕 "Just don't have the resources right now."Translation: We're too overwhelmed manually building reports, wrangling renewals, and answering tickets forwarded by the support teams.

🫃🏼 "We've got too many tools."Translation: We’re overwhelmed by the tools we bought that created a bunch of silos and forced us into constant app-switching.

🤓 "Our IT team won't let us use AI."Translation: We’ve outsourced innovation to a risk-averse inbox.

It's time to put some cowboy under that hat 🤠 . No one’s asking you to rebuild the data warehouse or perform some sacred data ritual. You don’t need a PhD in AI.

You can start small.

Nearly every AI vendor has a way for you to try their wares without hiring a team of talking heads to perform unworldly 🧙🏼 acts of digital transformation.

Where to start.

✔️ Pick a use case that will give you a revenue boost or reveal something you didn't know about your customers.

✔️ Choose something that directs valuable work to the valuable people you've hired.

✔️ Pick something with outcomes that other teams can use.

Pro Tip: Your CEO doesn't care about chatbots, knowledgebase articles, or things that write emails to customers.

What do you have to lose? More customers? Your seat at the table?

Any Account. Any Question. Any Time.

Unlock Your Accounts