The Science of Scaling

I posed this question at the 2019 Annual Saastr Conference in Silicon Valley. The audience almost unanimously chose Option A.

I called B.S. I agree with the choice. I don’t agree that, as entrepreneurs, we follow it.

Why? As entrepreneurs, the first metric we mention when describing our business is revenue. As investors, the first question we ask is about revenue growth. In board meetings, the first slide shown illustrates revenue. “Triple. Triple. Double. Double.” This phrase, meaning triple revenue in year one and two then double revenue in year three and four, is the perceived blueprint for future unicorn status. We don’t prioritize customer retention. We are obsessed, almost out of the gate, with revenue growth. And it’s killing our businesses.

Startup failure is unnecessarily high due to a premature obsession with top line revenue growth.

...and illustrates how key go-to-market decisions, such as price, hiring profiles, demand generation channels, and sales process, evolve as progress is achieved.

The remainder of this eBook is organized by the three stages of the framework, elaborating on the definition, measurement, and optimal execution required in each. Remember, the overarching mission is not slower growth, but healthier growth. The goal is not a short term “triple, triple, double, double” but a long term “home run”.

We use “product-market-fit” to make critical decisions such as when to scale but we lack a scientific, data-driven definition of the term.

“What is product-market-fit?”

Every year, I challenge my students at Harvard Business School with this question. I find it intriguing that for a term that is so well socialized throughout the entrepreneur ecosystem and so critical to determining when to scale, it has such a varied, non-rigorous definition. Well versed students reference ​Marc Andreessen​’s definition, “being in a good market with a product that can satisfy that market”, but worry the definition leaves too much up to subjective interpretation, especially with regard to the words “good” and “satisfy”. Other astute students reference Sean Ellis’ quantitative approach of “at least 40% percent of surveyed customers indicating they would be "very disappointed" if they no longer had the product”. However, students referencing this approach worry that data gathered in a customer survey may be corrupted with false positive risk.

So, how can we take a more data-driven, scientific approach to product-market-fit?
I find “better-in-class” companies use long term customer retention as an indicator of product-market-fit. The idea is to “let the customer’s wallet do the talking”. The argument is a customer’s decision to renew or repeat purchase is the most factual, true positive indicator of their satisfaction with the product and, in turn, product-market-fit. In aggregate, the tech sector considers an annual customer retention rate above 90% to be the world class benchmark. Therefore, we can argue that companies have product-market-fit when annual customer retention exceeds 90%.

We are getting closer. I agree customer retention is the best statistical representation of product-market-fit. However, customer retention is a ​lagging​ indicator. It often takes quarters or even a year for companies to understand the true retention rate of customers that we acquire today. We do not have years or even quarters. Time and money, especially in an early stage setting, are not on our side. We need to test, learn, and iterate in much faster cycles.

For this reason, “best-in-class” startups use a ​leading​ indicator of customer retention to quantify product-market-fit. Some entrepreneurs in Silicon Valley refer to the leading indicator as the “ah-hah'' moment. If the leading indicator is objective, rather than subjective, and truly correlates with long term retention then we have defined a data-driven, time-sensitive approach to understanding product-market-fit.

Defining the leading indicator(s) of customer retention

Unfortunately, there is not a single leading indicator of customer retention definition universally applicable to all company contexts. However, the following definition framework is universally optimal.

[Customer Success Leading Indicator] is “True” if ​P% of customers achieve E event(s) within T time
Documented examples of leading indicators from modern day unicorns, organized in this format, are below.

1. Slack: 70% of customers send 2,000+ team messages in the first 30 days
2. Dropbox: 85% of customers upload 1 file in 1 folder on 1 device within 1 hour
3. HubSpot: 80% of customers use 5 features out of the 25 features in the platform within 60 days

We can bring this chart to life using a fictitious company, TeleMed. TeleMed sells software to doctors enabling them to meet with patients over video rather than in-person. A well-designed customer retention leading indicator could be:

[Customer Success Leading Indicator] is “True” if ​70% of customers conduct a video conference with a patient within 2 months.

Therefore, the chart tells us that the company acquired 24 new customers in January. After 1 month, 3% of those 24 customers had actually conducted a video conference with a patient. After 2 months, 27% of those 24 customers conducted a video conference with a patient. After 3 months, 33% of those 24 customers conducted a video conference with a patient. According to TeleMed’s definition of the customer success leading indicator, they had not achieved product-market-fit in the early part of this year. However, the company executed a number of adjustments, likely changes to the product, target customer, sales process, and on-boarding approach, and the situation has greatly improved. In October they acquired 55 new customers. After 1 month, only 6% of those 55 customers conducted a video conference with a patient. However, after 2 months, 70% conducted a video conference with a patient! The execution paid off. This company has achieved product-market-fit. We do not need to wait for long term retention to surface. This company is ready to proceed to the go-to-market stage.

Here are a few guidelines as we design our customer acquisition cohort analysis.

1. In order to align all levels of the organization around product-market-fit pursuit, we recommend
   this chart be the first slide in the board deck, ahead of the P&L and top line revenue
   performance.
2. The cohorts can be organized by daily, weekly, monthly, or quarterly time periods. Selecting the
   appropriate time metric is similar to defining the “T” factor in the customer retention leading indicator discussed earlier. A company like Dropbox should probably use daily customer acquisition cohorts and evaluate the cohorts’ progress toward the leading indicator on a daily basis. Workday should probably use quarterly customer acquisition cohorts and evaluate the cohorts’ progress toward the leading indicator on a quarterly basis.
3. The “Customers Acquired” column are not cumulative numbers. These figures represent new customers acquired in that month.
4. It is possible that the product usage within a cohort declines over time. Customers could dedicate their energy early on to using the product, find that the product is not useful, and stop using it. Companies need to instrument the cohort analysis to capture this behavior shift if it occurs.
5. The time (T) of achieving the leading indicator is less important than continued improvement within the cohort over time. In the example above, we could argue transitioning to the go-to-market-fit stage in November even though the pure definition of product-market-fit had not been achieved yet. None of the prior cohorts have achieved 70% within 2 months. However, the prior cohorts were showing continued improvement month-over-month with the expectation that they would reach 70% and continue to rise. Furthermore, looking down the columns, recent cohorts at their 2 month and 3 month anniversary were substantially healthier than past cohorts at the same tenure.

Adjusting the approach for large enterprise deals

The above cohort analysis does not work for early stage ventures selling 6-digit deals or higher to large enterprises. These ventures can surpass $1 million in revenue with less than 10 customers and may only acquire 1 or 2 new customers every quarter. Therefore, an alternative approach to evaluating the pursuit of product-market-fit is necessary.

In these situations, companies assemble a customer health card with a half dozen or so criteria. Common criteria fall into the following categories:

1. Status on the technical setup and integration of the product
2. Number of users that are activated and active
3. Breadth of product usage
4. Quantifiable value realization
5. Executive sign off on reference-ability

The board literally reviews the “green”, “yellow”, “red” summary status for each company as well as the statuses of each of these criteria, especially for new customers and laggard deployments.

The “Why Now” on Prioritizing Customer Retention ahead of Revenue Growth

Decades ago, prior to broad adoption of the Internet, software was sold, deployed, and used in an “on-premise” manner. This meant companies had to purchase, provision, and maintain their own server networks to run the software purchased for their organizations. The process to set up and train the organization on the software was long and expensive, often taking 12 to 18 months and costing millions and sometimes tens of millions of dollars.

In many cases, the software wasn’t very good. It was hard to use. Adoption rates were low. The term “shelfware” was popularized because most software was never adopted and “sat on the shelf”. Why did this happen? It was because adoption didn’t really matter. Sales did. Once the customer was sold, they were stuck with the purchase for the next 5 to 10 years at least. In this context, the best sales team won.

Fast forward to 2020. The internet has changed two things. First, it no longer takes months to deploy and use software. Cloud, SaaS, and the broader subscription economy have significantly reduced the friction to adopt software. These trends have also reduced the friction to stop using software. Second, every customer has a huge megaphone called social media to tell the market about good and bad product experiences. For both of these reasons, companies are starting to realize the long term health of their business is ​more dependent on customer retention than customer acquisition​. However, the continued premature focus on top line revenue growth is misaligned with these trends. Go-to-market design and execution is, in a way, o​perating in a by-gone era​.

Aligning go-to-market execution with customer retention

With a more scientific definition of product-market-fit in place, the company has a precise “north star” to focus on. Most companies associate customer retention issues with deficiencies in product or customer on-boarding. However, I find a much different diagnosis. Most customer retention issues originate in sales and marketing. Customer retention is driven by the types of customers targeted by marketing and the expectations set during the sales process. Remember, the odds are against us at this early stage. Only 20% of Series A funded businesses will succeed. Best-in-class companies at this stage align all aspects of the go-to-market with the “north star” of the customer retention leading indicator. The chart below summarizes how. 

The first three components, target market, GTM playbook, and Sales Hire, are the most critical decisions at the Product-Market Fit stage. The buyers we choose to sell to as well as how we sell and on-board them will be the most important drivers of the customer retention leading indicator. A unique salesperson profile is needed to execute this early playbook. Scalable demand generation, pricing, and sales compensation are not important at this stage. If we are developing scalable cold calling campaigns, launching a tiered pricing model, or designing a robust sales compensation plan at this stage, we are not focused on the right things.

Target Market: Stack the deck with early adopters from smaller companies
Who should we target as our first customers? This question often leads to a debate between large customers that yield powerful reference-ability versus small customers that enable rapid learning. On one hand, we should pursue a “big-brand” customer. If we can acquire and make the customer successful, it sends a powerful signal to the market that if this new product was good enough for the big brand, it must be good enough for everyone else. On the other hand, we should pursue the smallest customers within their target market. Small customers are easier to connect with, make decisions faster, and have simpler product adoption requirements than larger companies. Therefore, pursuing smaller organizations provides the fastest path to learning.

As entrepreneurs, we pursue the “big-brand” customer most often. However, the choice is not optimal. We under-estimate the difficulty of setting a meeting, the high bar of IT and security requirements, and the “red tape” interfering with product adoption even after purchase. We should err toward the smaller customers to foster rapid learning. We should reflect on how small we can go within our target market definition where our product still creates value and start there.

The other consideration is the optimal person within the target customer. We need “early adopters” not “laggard followers”. We are still learning and refining our product and business. We need early customers who are excited to innovate with us. Often, an “early adopter” is more about the individual buyer within the organization than the organization itself. These buyers view themselves as first movers. They enjoy playing with new products and don’t mind that there are bugs. They are excited to send us lots of feedback and ideas. They enjoy being part of the innovation process. Early adopters care less about customer references or robust ROI studies. Save case study and ROI driven customers for the scale up stage. We are not ready for them.

Go-to-Market Playbook: Win at all cost
There are two themes for the GTM playbook at this stage, “win” and “do things that don’t scale”. “Win” is the customer retention leading indicator, not a signed contract or payment.

“Do things that don’t scale” is advice from Y Combinator founder, Paul Graham, and should be kept at the forefront of our minds at this stage. I remember chatting with David Cancel, CEO of Drift, at this stage of his business. He was literally flying out to have one-on-one on-boarding meetings with customers that were paying him $50 per month, as the CEO! “Do things that don’t scale”. Throw everything and the kitchen sink at achieving our early indicator of customer retention. One-on-one, “white glove” on-boarding processes, even for low value customers, are good. Mass on-boarding sequences are not optimal at this stage.

The one component of the long-term GTM playbook worth codifying at this stage is the ​Customer Retention Qualifying Matrix. Qualifying matrices like BANT and MEDDIC are commonly used in sales to understand the likelihood that a customer will buy. However, they do not help us understand whether the customer will succeed with the product and ultimately remain as a customer. Common components of the Customer Retention Qualifying Matrix include whether IT is aware of implementation tasks, the end user(s) are part of the purchasing process, not just the decision maker(s), the customer’s tech stack is compatible with the product, etc. As a seller, we can get a signed contract without having these items in place. In fact, accomplishing these tasks may actually slow the deal down. However, not completing these tasks before the purchase will likely put successful product adoption at risk. We are solving for customer retention, not signed contracts.

Sales Hire: Half Product Manager, Half Account Executive
Getting this hire wrong is a top 10 reason for Series A funded business failure. The first pothole most organizations fall into is pre-maturely hiring a sales leader. I can hear the Series A investor now: “Go find someone that has scaled a business to $100 million”. The hire is a complete mis-alignment for the tasks required at this stage. The second pothole is hiring an account executive from the large incumbent in our space. Yes, this account executive is successful selling to our buyer however, when they joined the incumbent, they went through weeks of sales training, were provided a sales playbook, and were scaffolded with an experienced sales manager. This “process execution” salesperson will not succeed in our environment where these ​assets and infrastructure d​o not exist.

At this stage, look for a mix between an account executive and a product manager. The first sales hire should have the skills to handle objections and comfort discussing money like an account executive. However, they should also have the ability to pattern recognize feedback from the target market and communicate the patterns to engineers. Focus on these attributes when evaluating candidates:

1. Comfortable in ambiguous, rapidly changing environments. Self starter.
2. Motivated more by innovating than making money. Avoid the salesperson primarily motivated
   by money at this stage.
3. Ability to dive into customer needs through deep discovery skills and identify patterns
4. Strong collaboration skills to work in cross-functional teams, primarily with product and engineering

 

In the product-market fit phase, we demonstrated that we could acquire and retain customers consistently. Go-to-market fit means we can acquire and retain customers consistently ​and scalably.​ Part of scalability is ensuring we have a large enough target market to support our growth aspirations. The other part is, as we pursue that growth, we can do so in a profitable manner. In an early stage environment, it is advisable to measure profitability using unit economics rather than operating margin or EBITDA. Some of our costs increase with scale, which we often refer to as variable costs, while other costs remain relatively stable with scale, often called fixed costs. Unit economics allow us to extract out the fixed costs so we can more closely analyze how financially sustainable scale is for our business. Therefore, the quantifiable goal of the go-to-market fit phase is to prove the company’s ability to acquire and retain customers with strong unit economics.

The software industry currently rallies around three unit economic goals.

1. LTV/CAC > 3
2. Payback period < 12 months
3. Magic Number > 1.0

Through fairly simple algebra, we can express the long term goal of:

• LTV/CAC > 3

...using near term activities:

The study shows top performing sellers listen most of the time on the first call. Bottom performers speak most of the time. This fact has been known anecdotally in sales for decades and is nicely illustrated statistically here by Gong. Why? Because world class selling is about buying. It is first and foremost about understanding the buyer’s perspective, assessing if we can help them, and, if so,
The Science of Scaling
   20
 tailoring our presentation to the buyer’s context. That is what top sellers do. In a world where buyers have exponentially more data at their fingertips and are less dependent on human sellers to make buying decisions, the performance variation between these top sellers and the bottom segment will widen.

Unfortunately, we often fail to design their GTM playbook to align with this best practice. Let’s reflect on our current sales training program or the one we aspire to implement. How much is focused on teaching our salespeople about our product versus our buyer? We are typically focused on the former not the latter. We are wiring our sellers to act like the bottom performers rather than the top performers.

I label this flawed approach to GTM playbook design as “inside-out”, or starting with the product. Instead, we need to take an “outside-in” approach by starting with our buyer.

This approach yields a GTM Playbook that ​supports​ the buyer through their journey. The illustration below illustrates a GTM playbook framework that positions the buying journey as the foundation for all other components.

The framework identifies five components of the GTM playbook.

1. Buyer Journey
2. Prospecting Guide
3. Discovery Guide
4. Presentation Guide
5. Customer Success Guide

When designing the buyer journey, we should view the exercise through the lens of a buyer who doesn’t even know our product exists yet. Below is an example buyer journey. This example is the buyer journey for a software company that helps businesses monitor their employee morale through a simple, weekly survey asking employees to rate their current happiness. We will call the company “Happy Employee Inc.”

The buyer journey framework establishes the foundation for the GTM Playbook to support.

The third common prospecting mistake is repeating the same message through the same medium across all 6 attempts. Sellers should envision their prospecting efforts as a continuous dialogue with a buyer across multiple mediums. If we had 1 minute every day to speak with our buyer, we wouldn’t tell them the same thing every time. We would facilitate a story-line of information based on the assumptions we have on their needs. Even though the buyer is not responding, they are likely listening.

GTM Playbook Component #3: Discovery Guide
The Gong study shown earlier illustrated that top salespeople listen most of the time in the first meeting and bottom performers talk the most. Our playbook needs to codify how our sellers should go about questioning and understanding the buyer’s perspectives in the first meeting, often referred to as “discovery”. In a way, the discovery guide instructs our sellers how to determine where the buyer is on the buying journey model. The guide is not a script of questions that should be asked sequentially. Instead, it is a simple one-page document organized by the buyer journey stages with suggested questions or techniques that can be used at each stage.

GTM Playbook Component #4: Presentation Guide
Once our salespeople understand where the buyer is on the buying journey, they can assess whether we can help the buyer and, if so, tailor the presentation of the product to the buyer’s perspective. The biggest mistake sellers make at this stage is failing to leverage the information gathered about the buyer’s context as they explain their offering. Instead, sellers move into auto-pilot, showing the same product features in the same order using the same language for every buyer. World class sellers never give the same demo. They tailor the messaging, nomenclature, and feature emphasis to the buyer. One very important clarification, great salespeople do not lie. They simply help the buyer connect their unique needs to the aspects of the product that are most applicable. This sales approach is critical toward the pursuit of world class customer retention and unit economics. The approach also clearly establishes the value of the sales team beyond the generic information available on the company website.
Unfortunately, few professional sellers can pull off this goal, especially in the first few months on the job. Our presentation guide needs to help mere mortal sellers to do this. Therefore, as an effective form of “training wheels”, we can create 3 to 5 different presentation “swim lanes” that can be used depending on our findings in the discovery stage. Therefore, we have simplified the presentation approach from a complicated “tailor the pitch to every buyer” to “ run the discovery process and then choose the best presentation approach from these 3 options”.

 

How fast should we scale? Establish a pace and watch the speedometer. If the speedometer breaks, slow down and fix the issue. If the speedometer looks good, accelerate. At the next board meeting, when our investors put pressure on us to scale as fast as possible, we can now come back to them with a predictable plan. “Our plan is to hire 2 salespeople a month for the next 6 months and monitor our leading indicators. If they are good, we will accelerate to 4 salespeople a month for 6 months. If they still look good after another 6 months, we will accelerate to 8, and so on.” Now we have a scientific, data-driven approach to scale.

Align go-to-market execution with the pursuit of growth
With growth comes a new set of risks. We mitigate these risks by aligning the components of our GTM strategy with growth.

Target Market: Separate into Scale vs. Experiment vs Ignore Segments

A sub-question to “how fast to scale” is “where to scale?”. We need to ensure that we scale the segments of our business where we have product-market and go-to-market fit and experiment with or disregard other segments. ​Relying on aggregated performance metrics that average all segments​ in the business can be very dangerous during the Growth and Moat phase. While the overarching customer retention and unit economics may look strong, they ​fail to provide the precision we need to accurately assess which segments are doing well and which are not. Said another way, consolidate metrics may be false positives where strong performance in certain segments masks weak performance in others​. Without analyzing these segments separately, we run the risk of disproportionately scaling an under-performing segment and, overtime, compromising our aggregate performance metrics.

Inherent in the names, product-market and go-to-market, we have three dimensions by which to organize our segment analysis:

1. The ​products​ we sell
2. The ​markets​ we sell to
3. The ​channels​ we sell through

Below is an example analysis along these segments for a fictitious company, “Acme Software”.

As the analysis illustrates, Acme Software is a $30 million business that sells a single product to both mid-market and enterprise buyers. Acme Software sells through a direct sales team and also through a partner program. The company targets an LTV/CAC above 3 and annual logo churn of under 10%. They are planning to launch a new product in the upcoming quarter.

As we analyze the company performance by product-market-channel segments, we see which segments are exceeding the company’s customer retention and unit economic goals and which ones are not. We can feel confident in scaling performing segments. For the remaining segments, we need to decide whether to experiment or ignore. An example decision outcome for Acme Software is below:

As the decision chart illustrates, Acme Software will scale the two direct sales teams selling their current product to the mid-market and enterprise markets. They will continue to experiment with the teams selling through partners. They will also experiment with a team selling the new product to the mid-market through a direct sales channel. The remaining segments will be ignored for now.

As they execute the experiment segments, they should follow the “product-market fit, then go-to-market fit, then growth and moat” sequence. The use of cross-functional teams in these segments will accelerate our achievement of product-market and go-to-market fit. Applying this strategy to Acme Software yields the following organizational structure:

GTM Playbook: Reinforced
During the go-to-market fit stage, we codified the GTM playbook. The playbook serves as the foundation for our new hire training. However, new hires will not simply read these guides and start executing them perfectly on day one. The playbook needs to be continually reinforced through an effective coaching cadence. This coaching cadence is a critical component of GTM management’s role.

Because success and failure is often highly quantifiable in GTM roles, especially sales roles, we can measure each salesperson by the stages of the sales funnel. Below is an example.

With these monthly metrics in place, we can now use them to diagnose specific areas of improvement for each salesperson, customize a coaching plan to each diagnosis, and quantify an improvement goal. An example coaching plan for the five sellers in the above dashboard is below:

As the leader of our business, we should hold our GTM management layer accountable to this monthly cadence and leverage the quantified improvement goals to assess their effectiveness of their coaching.

Sales Hire: Process Executor
During the go-to-market fit phase, we focused our sales resources on codifying the GTM playbook. As we transition to the Growth and Moat phase, we are now ready to bring on the more traditional salesperson profile.

A common mistake when defining this profile is asking our peers at other companies what they look for in sales hires ​and copying/pasting​. Having helped hundreds of companies hire thousands of salespeople, I can tell you that the optimal sales hire for you will be different than that for another business. The optimal sales hire depends on the context of the business, which is largely based on the product we sell, the market we sell to, and the stage we are at as a business.

However, because success and failure in sales is so quantifiable, we have an opportunity to engineer our ideal sales hiring formula. To do so, we list out the 5 to 10 attributes we think will correlate with success in our sales context.

Be clear about the definition of each attribute and the definition of a high, medium, and low score.

Devise a hiring process to assess candidates against these criteria and be disciplined around scoring them.

If we hire 2 salespeople a month for 6 months, we should have a good idea as to which salespeople turned into top performers at our company and which ones did not. We are in a position to ask ourselves why seller A is a top performer and why seller B is not. We can then look back to our hiring formula to see if we are adequately assessing candidates on these attributes and, if not, iterate the formula. Having this tested formula in place is a necessity when we start hiring 10 sales people per month. We should practice it early and often.

Demand Generation: Multiple Mediums Tightly Aligned with Sales
During the go-to-market phase, we tested 2 or 3 demand generation channels and proved at least one to be viable from a unit economics standpoint. However, each demand generation channel has a “ceiling”. We will need to unlock new channels to fuel follow on growth aspirations. The “Target Market” section above walked us through a strategy to do so.

Pricing: Assess for Disruption
During the go-to-market phase, we optimized our pricing for scalable unit economics. We can leverage that design during the Growth and Moat stage.

The major pricing mistake at this stage is more categorized around what not to do rather than what to do. The mistake occurs when a company raises prices without having a sustainable differentiation. This strategy can accelerate revenue in the short term but kill us in the medium term. Another way of describing sustainable differentiation is barrier to entry or “moat”, hence the phase label of “Growth and Moat”. A common reason for failure during the growth stage is entry by competition, causing our company to lose product-market or go-to-market fit. We need an effective “moat” to sustain growth.

We as entrepreneurs confuse sustainable differentiation with temporary differentiation. When I ask entrepreneurs about their sustainable differentiation, they often reference a product feature that they have and the competition doesn’t. Most of the time, that feature is a temporary differentiation, not sustainable.

A simple lens we can use to assess our “moat” strategy is to imagine that ten amazingly talented engineers from Google quit their jobs, formed a company to compete with us, raised $50 million from Sequoia, reverse engineered our product, and started selling it for half the price. Does this sound unrealistic? We would be amazed how often something like this happens. The key question is, under these circumstances, why do we still win? If so, we have a sustainable differentiation.

Here are a few categories of sustainable differentiation with examples in today’s software market:

1. Network Effects: ​When a new user signs on, the value of the offering to the existing users
   increase. The classic example is the telephone. The first phone was useless. As more and more people adopted it, the value to the existing users went up. A modern example is LinkedIn. When a new user signs up, additional connection routes through the network become available to existing users. Even if the talented team of ex-Google engineers replicate our product and sell it for half the price, we still win.
2. Brand/category: ​ By defining a category and associate our brand as the market leader, we make it difficult for others to compete and win in the category. HubSpot did this with inbound marketing. As the company accelerated, new entrants latched onto the inbound movement. However, it only fueled demand for HubSpot.
3. Viral distribution: ​ Rarely does viral distribution happen accidentally. It is the result of countless experiments and iterations to maximize the viral coefficient. However, once established, especially with a reasonable user base, the company profits from essentially free growth. This effect occurred at Dropbox, where they presumably achieved a viral coefficient greater than 1 after lots of work on the capability. Ultimately, the channel yielded millions of free new users every month. While the talented ex-Google team can replicate the software, they cannot replicate the viral effect and install base overnight.
4. Switching costs: A​ substantial investment needed by customers to move to a competitor. Salesforce.com benefits greatly from switching costs. Even if the ex-Google team built a CRM just as good, it would be challenging for a customer to port over all of their data and business processes to the new CRM.
5. Learning algorithms:​ The more transactions our algorithm has processed, the more accurate it presumably is. Even if the talented team of ex-Google engineers replicate our product and sell it for half the price, we can still win as long as we have processed exponentially more transactions and the market values accuracy over price.

Getting back to price, companies with a temporary sustainable advantage may raise prices to drive revenue growth. In the short term, revenue accelerates as long as the temporary advantage exists. However, the higher price makes our business an even more attractive and easier target for disruptors. It is fine to drive average revenue per customer. However, use a “land and expand” model that keeps the opening price and friction low and expands revenue per customer as value is seen and trust is developed.

Compensation: Add promotion path
In the go-to-market fit phase, we implemented a compensation plan that balanced new revenue acquisition with customer retention by paying 50% of the commission on the contract signature and 50% on the customer retention leading indicator. This approach to sales compensation works well during the growth and moat phase to preserve product-market and go-to-market fit.

The opportunity we often overlook is using compensation to retain our GTM talent. It always puzzled me why we used the annual 3% raise approach with salespeople where, again, success and failure is so quantifiable. A concept I innovated with at HubSpot and then applied to many companies is an extension of the compensation plan called a data-driven promotion path. When a salesperson asks when they will get a raise or a title enhancement, rather than handling these requests with a subjective annual review process, we can use a data-driven promotion path. As a result, we can retain top talent for a lot longer. An example promotion path is below.

In addition to being promoted within the current role of salesperson, a critical capability for development in the growth and moat phase is the management layer. A major pothole we fall into when choosing our sales managers is to promote our best salesperson. The study below shows why this is a flawed approach.

However, we can’t promote our worst salespeople to manager either. Therefore, we need to build a bench with a sales management development program. If we do not, available sales manager capacity can quickly become a bottleneck to scale.

Below is a four stage process to groom internal candidates through.

Phase 1 – Demonstrate adequate skills at each stage of the sales process
Industry data shows that the best salespeople do not make the best sales managers. Observers of this trend speculate the cause is the difference in task of the salesperson role, which can be very independent, and the sales manager role, which entails great people development skills. That said, the worst salespeople do not make great managers either. Our experience suggests that good sales management candidates have mastered each stage of the sales process at an adequate level. They do not have to be the best. They simply need to understand each component so that when they manage a salesperson with a deficiency at this stage, they can coach the person through it. Therefore, we recommend an advanced sales certification that sales leadership candidates need to pass, illustrating competence at each stage of the sales process, before being moved to the next stage. We also recommend they achieve goals for two quarters in a role be another prerequisite to moving to the next stage.

Phase 2 – Develop leadership skills:
After Phase 1, we recommend the sales leadership candidate be placed in a weekly sales leadership curriculum. Each week, the candidate reads assigned best practice literature on critical scenarios they will face as a manager, such as managing conflict, delivering effective feedback, and driving team morale. After each reading, the current sales leader will review the concepts and role play applications of the concepts to our company context. This phase will allow the candidate to better understand the day-to-day requirements of the job and assess whether they are passionate about the role. The phase will also allow leadership to assess the candidates performance in these leadership settings. The time burden on leadership should not be significant, amounting to an hour meeting with the leadership candidate each week. The candidate should continue to achieve their individual quarterly targets through the process.

Phase 3 - Practice Hiring and Coaching Skills with One Salesperson:
If the sales management candidate is still excited about the role after Phase 2 and leadership still believes in the candidate's abilities, we recommend the candidate recruit, interview, hire, on-board, and coach the next sales hire. Through the process, current sales leadership will interview candidates as well. However, they will ask the management candidate about their interview approach and assessment before revealing their own perspective. Current leadership will also coach the management candidate as they onboard and develop the new hire. The management candidate will continue to carry their individual quota through the process. This is temporary. This phase typically lasts 3 to 4 months.

​Phase 4 – Promotion:
If the management candidate progresses through Phase 3 and a leadership position becomes available, we recommend the management candidate be promoted to sales manager and no longer hold individual quota responsibilities. Some organizations attempt a player-coach model. However, industry data and observations suggest this model fails most of the time. It is difficult for a manager to switch between individual quota and team development responsibilities. Oftentimes, one side suffers and it is typically the team development side as player-coaches feel they will not get fired as long as they hit their individual quota. We recommend the new manager be provided with a small team to start, ideally newer salespeople that will be easier for the new manager to develop credibility with, and take on most of the new hiring over the next few quarters. We recommend the current VP of Sales retain direct reports from the veteran top performers and take on minimal new hiring to their team.

What We Learned

• We are ready to scale when we have product-market-fit and go-to-market fit
• Scale is a pace, not a single lump sum event
• We should scale as fast as possible without losing product-market and go-to-market fit.
• Use the speedometer to determine the moment we lose product-market or go-to-market-fit