Technology
What is Customer Success?
In most companies, it is a department or a team. I would argue that it should be foundational in a company’s culture. Companies need to focus on providing products and services that solve critical business problems for their clientele. By doing so, they create a predictable revenue stream and install base that supports future growth.
In a quarterly executive meeting a decade or so ago, the head of the Support organization stated this team was the most important. The head of Engineering then stated that her team was the most important. I chimed in and stated, “Without Sales, nothing happens, but ultimately, if all teams are not focused on the same objective, like a tripod, then all teams will ultimately fail.” Our CEO agreed, and that was the end of the discussion.
You could also argue that Marketing and Services should be included, and I would agree, since it goes back to all teams being focused on a singular, overarching goal.
In a previous post about creating Customers for Life, I wrote about an implementation to address customer churn, a byproduct of the company’s failure in one or more areas. This was a wake-up call for me, as we were very focused on the success of our largest accounts and most productive channel partners – totaling 70% of our revenue, but we took the other “less valuable” accounts for granted. The lesson learned was that 30% of $62M is a large number (a “long tail”), and by applying the same techniques to those accounts, we increased organic growth while minimizing churn, improving our overall Net Revenue Retention (NRR) rate.
Why Customer Success Teams Struggle
- Lack of Ownership: They don’t own the accounts and often lack the motivation and accountability for each customer’s health and success.
- Stay Reactive: They are reactive rather than proactive advocates for customers.
- Lack of Resources: They are spread too thin and lack the capacity to actively engage with all but a few customers.
- Enter Too Late: They are not introduced early in the sales process, which is a great way to demonstrate commitment to the prospect’s success if they select you as a vendor.
- Stay Low in the Org Chart: They do not develop relationships beyond a small operational team, limiting executive visibility and expansion potential.
- Ad Hoc in Nature: They lack formal processes, including detailed documentation, that help ensure consistency and continuity over time.
How to Position Your Team for the Win
- SWOT: Review your strengths and weaknesses. Why do companies buy from you? (or, what are you really selling?) What are you known for? What do people like and appreciate? Where do you fall short? (opportunities for others) Accentuate the positive and focus on improvements where needed.
- We often received customer feedback that when they called our support team, their problem was solved on the initial call. With other vendors, it often took 2-3 people to reach someone knowledgeable who could help. We promoted this when selling and reinforced the importance of maintaining this positive image to our internal teams.
- We also received feedback that some of our technical features were lagging behind the competition, so my team and I helped identify the most critical features, then worked with Engineering to prioritize them and focus on bringing in new customers who needed them. It was a win-win.
- Be Proactive: It is often possible to anticipate problems or make improvements based on your understanding of the customer and their history. Being part of the solution means that you don’t wait for the next problem to engage.
- When I had my consulting company, we provided managed services for several large companies. We had proprietary monitoring tools that reported conditions that often led to outages if left unchecked. We addressed the issue and informed the customer once it was resolved. Our monthly summary report listed the likely outages avoided, the average duration of similar outages, and the cost avoided (based on the hourly cost of downtime). Key people saw our value at least monthly, so when it came time to renew our service, the process was fast and painless.
- Become the Internal Liaison: The customer success team should serve as the main conduit for information. Introduce your Services or Engineering teams to the customer early. This doesn’t just solve problems; it uncovers new opportunities to provide value (and sell additional services) that position the customer for even greater success. Engagement and a sense of partnership go a long way.
- I will often introduce the Services team when problems or needs arise. Their expertise and insights can be very valuable, often leading to services that position the customer for even greater success.
- Go Above and Beyond: People remember that. Teams begin to rely on you. And Executives begin to see your company and products as critical to their success. This creates long-term value for your company.
- Focus on the Future: Ask your customers, “How can we help with your upcoming initiatives and projects?” This is a great way to learn what they will be working on, to show your interest in their success, and to identify how your company and products can help them achieve it.
These are things that have been very successful for me when I was leading two large global regions, when I was a top Account Executive at a company with a small customer success team, and as a Consultant. I set expectations, led by example, and they began doing much more of what I expected from the customer success team. We started seeing improvements in the first 30 days.
While leadership doesn’t have to come from designated leaders, cultural changes usually require the commitment, involvement, and support of the organization’s top executives. Everyone can positively influence a company’s direction and success.
When the customer wins and views you as a key partner, your concerns about churn become minimized.
Leading Next-Generation Sales Teams: The Mandate for Predictable Revenue
The sales landscape has fundamentally shifted. I keep reading posts and stories about AI replacing sales teams, and it may be for more commodity-type sales, but it will be some time before it replaces Enterprise sales teams. Building relationships and trust is the foundation for an executive to take a risk on your product, especially when it is critical to their success. AI is not yet at that level, and as behavior changes with every key release, building trust in AI will be challenging for many years to come. But today, AI can be a powerful enablement tool for your team when leveraged correctly.
Your prospects no longer need salespeople for information; they need us for Insight. They have done their research. They expect their time to be an investment, not a discovery exercise. Does your presence and knowledge project confidence and inspire trust? Does the prospect view you as someone interested in helping their business, or just someone trying to close a deal? Impress them, and you could earn the opportunity to dig deeper. Disappoint them, and good luck recovering.
Two years ago, I was selling to a Fortune 100 Financial Services company. I understood their business needs, and we met them easily. We demonstrated that we could take a key manual process that typically took 7 weeks to complete, automate it and maintain full compliance, and complete the task within 10 minutes. The SVP told me his priorities for selecting any new vendor were: 1 – Company Stability; 2 – Relationship with the Vendor; 3 – Product Quality; 4 – Product Value to their business; and 5 – Total Solution cost. Before selling their IP, the company fired the sales team, and the remaining execs stepped in and offered the deal at an even greater discount. It never sold because the executive team didn’t understand what mattered to this buyer. The company had a high-level relationship with the stakeholders, but lacked the trust and credibility that I had built over several months. This is one of the main reasons why I believe AI won’t take over Enterprise Sales anytime soon.
So, how do you get it right?
The question for every CRO or VP of Sales isn’t whether their team is busy, but whether their activity is revenue-focused and drives predictable, scalable results. There’s plenty of money to be made, but following the same old tired formulas seldom works.
For leaders aiming to build next-generation teams that deliver zero surprises in the forecast, the approach must be recalibrated around three core pillars: Strategic Preparation, High-Agency Coaching, and Outcome-Focused Messaging (“context”). It is much more than cold calling for two hours a day or having 5-10 meetings per week. Those things matter, but they are just activities if you are not targeting the right companies and people, or if your team blows it once you have found them. This will be a significant cultural shift for many companies.
Strategic Preparation: From “Discovery” to “Insight”
When a prospect books a meeting, they are giving us one of their most precious assets: time. If we treat that time as a standard discovery call, we set negative expectations, which signals the lack of perspective (the ‘P’ in PIE) and perceived value. This isn’t theory—it’s the PIE framework (Perspective, Insight, Experience) I’ve used for years to sell large deals, turn around at-risk customers, and scale teams.
The C-Suite Mandate: Accelerate deal velocity by focusing on specific quantifiable impact for your prospects, and increase win rates by targeting identifiable business pain.
- Come with an Understanding of their Market, Changes, and Competition. Before the first call, we must show we’ve already invested time in understanding their operational constraints, competitive pressures, and budget priorities. The goal is to move the conversation immediately from the tired, “What keeps you up at night?” to “We have seen [problem] with companies in your industry. Is that something you have experienced or have concerns about?”
- Long Discovery Calls or Presentations Typically Won’t Work. Customers are fatigued by generic questions. Every interaction must be purpose-driven and meaningful. If the call runs longer than planned, it must be because the conversation has become mutually valuable, not because the seller was ill-prepared and just kept talking.
- Discussions Must Be Targeted to the Problems They Are Most Likely Experiencing. This is where we leverage Insight (the ‘I’ in PIE). Use your background and AI to hypothesize the top three pain points before you dial. Our role is to validate these points, quantify the impact, and then introduce a Shared Vision of Success (our solution) anchored by measurable business outcomes.
Player-Coach: Enhancing Team Capabilities, Not Just Motivating Activity
If you are a sales leader who only focuses on closing your team’s most challenging deals, you are creating a dependency, not a capability. A Player-Coach must be accountable for the team’s numbers and its health. That can be a big job.
The C-Suite Mandate: Drive organic growth by building repeatable processes and cultivating high-agency talent.
- Not a One-Size-Fits-All Proposition. True coaching is not a template. It requires a methodical but human approach to diagnostics. That takes time, effort, and a genuine desire to help people grow.
- Identify Skills Gaps and Tailor Efforts. Test skills, identify gaps, and create targeted efforts to build skills that address someone’s specific deficiencies. This personalized attention builds the high-performance culture and accountability required to sustain long-term success.
- Leverage the Team – Role Playing and Team Reviews. We must create a culture where knowledge sharing and feedback loops are the norm. Leverage team reviews and structured role-playing to sharpen execution. This is how we transform luck into a predictable process.
Give teams the latitude to adjust their messaging and test approaches. Adapt messaging to business trends, changes in the competitive landscape, and changing terminology. Then, have your team share their experiences and findings (good and bad) for review, feedback, and refinement. Structured agility helps your team maintain its competitive edge.
The Leadership Mandate: Context Over Content
We are past the AI hype cycle. The C-Suite doesn’t care about the tool; they care about the ROI and the risk of poor execution. As leaders, we cannot just hand our teams a login and say, “Go use AI.” That’s a recipe for chaos and a quick erosion of professional credibility. We must lead by example.
We need to teach our teams that AI generates content (not always accurate), but humans provide context. The two work hand-in-hand.
- Do use AI to deepen your understanding of the prospect’s industry so you can become a true consultant. Use the technology to gain understanding and market intelligence and tie it to your Experience (the ‘E’ in PIE) as preparation before any call.
- Don’t use AI to automate a thousand bad emails. Mass communication is cheap; individualized insight is priceless.
- Do use AI to research the one hundred prospects that actually matter. Focused efforts yield significantly better results.
- Don’t use AI to fake expertise. This can quickly kill credibility, as any good consultant will tell you.
The “Million Dollar Deal“ isn’t won by a bot. A human wins it by understanding the nuances of the prospect’s business, building trust, and navigating the internal structure and politics. AI is simply the tool that clears the path so you can do that work faster and with better data. AI is leverage, not a crutch.
Call to Action: Are You Building a Team or a Capability?
The next-generation sales leader understands that customer success is at the heart of everything we do. We win when they succeed. Your most valuable asset isn’t your pipeline—it’s the predictable capability of the individuals on your team. Consistently doing the right things is critical to success.
The challenge for every business leader today is this: Are you enabling your teams to sell like consultants, or are you still measuring them (and driving their behavior) on activity-based metrics? Focus on building intelligent and creative teams that deliver consistent results with zero surprises. It doesn’t happen overnight, but it is an investment in your future success.
Let’s discuss how we can implement the PIE framework and position your team to deliver scalable, organic growth.
Lessons Learned from GTM Consulting
For the past two years, I have performed part-time, contract go-to-market consulting. My wife had a surgery that went wrong 18 months ago, so I needed something that would allow me to take care of her, stay sharp, earn money, and help companies grow. What I encountered was quite different from what I expected, so I thought I would pass it along.
Most of the work was with small to midsize companies, but the problems and needs mirrored what I have encountered at larger companies. The main difference is that large companies tend to look to software to address problems. In contrast, smaller companies often lack the budget for what they view as a solution that increases complexity.
Here are my Top 5 findings:
- GTM plans are often developed at the highest levels, often in isolation, without market testing and validation.
- An interesting aside is that the company is often really seeking sales optimization but believes it is doing things “well enough” today and therefore needs to focus on new offerings and revenue streams.
- New perspectives on past performance and failures are well received but more surprising than anticipated. This leads to a better understanding of needs, which builds consensus moving forward.
- Sales teams are sometimes pitted against one another, rather than working together to help everyone achieve more (Coopetition – “A rising tide lifts all boats.”)
- Sometimes the competing team isn’t sales, but support. The team wants to help the customer (which is great), but works outside its defined scope instead of bringing in the services and sales teams to work jointly to solve the customer’s problem.
- Sales teams are focused on selling features rather than solving business problems.
- Training those teams on solution selling and understanding the prospect’s needs pays off.
- CRMs are not consistently used and often reflect idealized fiction rather than reality.
- Old, dead, or unqualified opportunities; lack of recent contact or interaction; deals that have slipped more than once; and a lack of understanding (company, needs, players, business environment) all point to an unrealistic pipeline.
- Sales management and teams are not leveraging AI to help focus their efforts.
- Conversely, they may view AI as a panacea, investing time and money in tools that supplement a strong team rather than focusing on strengthening the team.
Here are the related Lessons Learned:
- Selling is a byproduct of problem-solving. You can’t solve problems if you don’t know what they are. Every interaction with a prospect should focus on gathering information, building trust and relationships, and leveraging prior interactions to demonstrate that your solution will solve their problem and ease their pain.
- Here’s solution sales again. Teaching teams to ask better questions, listen more, and validate their understanding increases their standing with prospects.
- Identifying common business problems and describing how your product or service solves them should be the foundation of the plan.
- Perform market analysis. How do other companies describe those problems? Their terminology, often found in job postings by competitors and your target audience, can help create effective messaging that resonates. Work to become the natural fit for what your prospects are seeking and the problems they are likely dealing with.
- Individual contributors get paid to win, but sales management needs to create incentives for collaborative efforts that lead to both wins and ongoing customer growth.
- Paying sales teams for net new business only causes them to ignore install base expansion opportunities. And, if another vendor solves their problems, it is only a matter of time before they replace you.
- For one company, I convinced them to implement a 2% SPIV (like a SPIFF, but team-focused) for every team member who actively contributed to team improvement. SPIV payments were quarterly, and there was a running total so the team could see the fund growth. Initial indications of a positive impact are good.
- Another benefit of collaboration is that it helps teams focus on approaches that work due to ongoing testing and refinement. Collaboration also helps teams focus on a more accurate ICP (ideal customer profile). Sales management can then feed their findings back to Marketing to tailor and fine-tune their efforts.
- CRMs often either lack information or are full of wishful thinking. They focus on activities, and not progress and next steps.
- Using MEDPICC as a foundation for qualification is a much better start.
- Sales managers need to validate the information independently to ensure their teams are upfront and honest. Trust, coaching, and collaboration work together for the win.
- Chasing deals that are unlikely to close wastes valuable resources.
- AI is not a panacea, but it is very effective for research, market validation, prospecting, and meeting preparation.
- Going in prepared builds respect and credibility, saves time, and helps you quickly qualify prospects in or out.
- There may be opportunities to nurture prospects who have potential but aren’t qualified for immediate deals, seeding the pipeline for future opportunities. This could be a great place to leverage AI for personalized journeys with highly relevant curated content.
So, what are your thoughts? Have you seen some of these problems yourself? How did you handle them? Let me know in the comments below.
And if you are looking for assistance with your business, contact me.
Lessons Learned from Selling Kubernetes
Cloud-native, containerization, microservices, and Kubernetes have become very popular over the past few years. They are as complex as they are powerful, and for a large, complex organization, these technologies can be a game changer. Kubernetes itself is a partial solution – the foundation for something extraordinary. It can take 20-25 additional products to handle all aspects of the computing environment (e.g., ingress, services mesh, storage, networking, security, observability, continuous delivery, policy management, and more).
Consider the case of a major Financial Services company, one of my clients. They operated with 200 Development teams, each comprising 5-10 members, who were frequently tasked with deploying new applications and application changes. Before embracing Kubernetes, they deployed massive monolithic applications, with changes occurring only 2-3 times per year. However, with the introduction of Kubernetes, they transitioned to a daily deployment model, maintaining control and swiftly rolling back changes if necessary. This shift not only let them innovate faster but also enabled them to respond to opportunities and address needs more promptly.
Most platforms use Ansible and Terraform to create playbooks, manage configurations, and more. Over time, those configurations could become long and complex and were prone to errors. For more complicated configurations, such as multi-cloud and hybrid environments, the complexity is further amplified. “Configuration Drift,” or runtime configurations that differ from what was expected for various reasons, leads to problems such as increased costs due to resource misconfiguration, potential security issues from incorrectly applied or missing policies, and identity management issues.
The surprising thing was that when prospects identified those problems, they would look to new platforms that used the same tools to solve them. Sometimes, things would temporarily improve (after much time and expense for a migration), but then fall back into disarray as the underlying process issues still needed to be addressed.
Our platform used a new technology called Cluster API (or CAPI). It provided a central (declarative) configuration repository, making it quick and easy to create new clusters. More importantly, it performed regular configuration checks and automatically reconciled incorrect or missing policies. It was an immutable and self-healing Kubernetes infrastructure. It simplified overall cluster management and standardized infrastructure implementation.
All great stuff – who would not want that? This technology was new but proven, but it was different, which scared some people. These were a couple of recurring themes:
- The Platform and DevOps teams had a backlog of work due to existing problems, so they feared falling further behind more than they trusted a better alternative.
- Teams focused on their existing investment in a platform or on the sunk costs spent over a long period, attempting to solve their problems. The ROI on a new platform was often only 3-4 months, but that was challenging to believe, given their own experiences on an inferior platform.
- Teams would look at outsourcing the problem to a managed service provider. They could not explain how the problems would be specifically resolved, but did not seem concerned about that lack of clarity.
- There was a lack of consistency in the Kubernetes versions used, the add-ons and their versions, and one-off changes that were never intended to become permanent. Reconciling those issues or migrating to new, clean clusters both involved time and effort. That became an excuse to maintain the status quo.
- Unplanned outages were common and usually expensive. Using the cost of those outages as justification for something new was typically a last resort, as people didn’t like acknowledging problems that put a spotlight on them.
- Architects were curious about new and different things, but often lacked the gravitas within business leadership to effect change. They were usually unwilling or unable to explain how real changes happen within their company, or introduce you to the actual decision-makers and budget holders.
Focusing on outcomes and working with the Executives most affected by them tended to be the best path forward. Those companies and teams were rewarded with a platform that simplified fleet management, improved observability, and helped them avoid the risky, expensive problems that had plagued them in the past. And working with satisfied customers who appreciated your efforts and became loyal partners made selling this platform even more rewarding.
Six Ways AI Can Become a Sales Management Enhancer
As a VP of Sales, I would spend the first 60-90 minutes of every day reviewing a dozen news sources for new technology, competitor announcements, proposed legislation, and M&A news. I looked for anything relevant in critical industries, news about our customers or their top customers, and staffing changes within their companies.
My goal was to identify anything that could negatively impact deals in play, threaten the customer base, disrupt the run-rate business, or create opportunities to break into a new company or displace a competitor. You feed your findings and speculations back to your team, along with suggestions, talking points, or specific directions to help them maintain or increase their success for the current quarter plus the next few quarters.
You look for trends and leading indicators that could help your team and your organization achieve greater success. Winning feels good, and the rewards drive you to achieve even more.
Artificial Intelligence (AI) can do all this and more. It will be more consistent, analyze information without bias, and do so faster.
1. Automated Intelligence Gathering
Focus your efforts where they add the most value. AI can automate the collection and analysis of data from multiple sources, including news feeds, legal updates, social media, and competitor websites. This automation can save considerable time and minimize the chances of missing relevant information. Natural Language Processing (NLP) can identify, categorize, and correlate relevant information, providing actionable insights without manual review.
2. Enhanced Lead and Opportunity Identification
In addition to the correlations above, Machine Learning (ML) models can analyze trends and patterns in data to identify potential leads or opportunities for expansion. By understanding market movements, customer behaviors, historical behavior, and presumptive competitor strategies, AI can suggest new targets for sales efforts and highlight areas where teams could gain a competitive edge.
3. Improved Internal Communication and Collaboration
Sales is not just about selling; it also requires internal collaboration to create the best possible products and services and identify the best approaches to generate awareness and interest in your offerings.
AI systems can serve as a central hub for information that benefits various departments within a company. By integrating with CRM, marketing, support, and other internal systems, AI can distribute tailored information to different teams, ensuring everyone has the best insights to perform their roles effectively and promoting a more cohesive, coordinated approach to achieving long-term business objectives.
4. Forecasting and Predictive Analytics
With the ability to process vast amounts of data, AI should significantly improve forecasting accuracy. Predictive analytics can estimate future sales trends, customer demand, and market dynamics, giving businesses more opportunities to make better-informed decisions—leading to better resource allocation, optimized sales strategies, and, ultimately, higher revenue.
5. Increased Efficiency and ROI
By automating routine tasks and providing deep insights, AI can free up sales and management teams to focus on strategic activities. The efficiency gains from AI can result in significant cost savings and a higher return on investment (ROI) as teams do more with less, capitalize on opportunities faster and more effectively, and ultimately make more money for themselves and their company.
6. Continuous Learning and Improvement
Machine learning models will improve over time as they process more data, meaning the insights and recommendations provided by AI will become increasingly accurate and valuable, helping businesses continuously refine their strategies and operations for better outcomes. AI will also provide constructive feedback and suggest next steps in real time, helping everyone using it upskill.
Future Perspectives
While AI may not yet be ready to take over complex roles like enterprise sales, its potential to enhance these roles is undeniable. As AI technology continues to evolve, its ability to provide highly accurate forecasts, improve win rates, shorten sales cycles, and enhance competitiveness will only grow. The future of AI in sales and business management is not just about automation; it’s about augmenting human capabilities to create more effective, efficient, and thriving organizations that can compete in an increasingly competitive global landscape.
So, what do you think? Will this work? Will it be good enough if everyone is doing it? Leave a comment and let us know.
Where Ideas, Experiences, and Lessons Learned Intersect 