Why Startups Should Focus On Pre-Launch Metrics

Everyone agrees that measuring and monitoring startup performance is a critical success factor for fledgling enterprises. However, while much is written about measuring startup performance post-launch, there is less attention to pre-launch metrics. In this post, I make the case that establishing a disciplined pre-launch culture, manifested by a history of goal setting, measurement, monitoring, and acting on feedback, sets the stage for success. 

One essential action founders need to take is measuring and monitoring their venture’s performance. Every successful venture I work with demonstrates a disciplined approach to these tasks. These founders review their business models continually at each stage of development and growth. These entrepreneurs understand that to be effective; they need to find a business model that builds a repeatable and scalable transaction with the customer. In addition, each business model element must work together to provide consistent value to the customer.

Successful founders identify risk or growth areas within their business model, establish measurable goals, test new strategies and actions, and monitor progress. It sounds simple, but it takes a good deal of focus, prioritization, and discipline to conduct these activities and everything else in the venture realization process. I will provide some metrics to consider to measure and monitor our business model’s efficacy. It is vital to limit the number of metrics you are tracking. Focus on a small priority number and make sure these are metrics that directly demonstrate importantly and stage appropriate progress. The data must be actionable and show you what you need to do differently.

High-quality metrics change how you view your business model’s workings and facilitate changes in your team’s behavior. Metrics should be actionable, quantifiable when possible, testable & causal, and comparative:

  1. You want to measure specific and actionable aspects of the business model. For example, knowing how many initial views you are getting on your website is not as actionable as understanding how many actual people are visiting. Monitoring the number of people who take the specific call to action is a better metric.
  2. I always push entrepreneurs to find ways to quantify the behavior or emotional customer outcome they are hoping to achieve. It can be challenging, but it forces the entrepreneur to think deeply about the customer behavior you are trying to change.
  3. Suitable measures should support experimentation, a critical component of innovation.

When a metric enables you to show that two variables are correlated, you can design tests to establish causality. For example, if you try to see which pricing strategy converts more customers, you can run a/b tests, showing random customers different product offers. If you did not change anything else and have a relatively large sample of participants, you should predict which pricing model converts more customers. Finally, good metrics should provide opportunities to compare results across periods or different customer segments. It demonstrates the direction of the specific aspect of your business model. For example, are customer conversions or repeat business numbers increasing or decreasing?

One last important aspect of effective metrics – the team must all understand the metric and why it is essential. When I studied organizational innovation, the first step was to see how people at all levels and across the company defined it. You might be surprised to find that there was no commonly understood measure of innovation in many organizations. If you don’t have a common understanding of the goal and how to best measure it, you won’t achieve the desired outcome. The closer your metrics check these boxes, the better you can determine the best course of action for improvement.

A founder may need to monitor many potential metrics or key performance indices (KPIs). To determine aspects of your business model to measure and when, I break startup metrics across four categories related to significant business model areas: customer engagement metrics, MVP metrics, profit model metrics, and resource acquisition metrics. Additionally, I look at that one or two critical metrics that need to meet certain levels for your business model to be viable.

Customer Engagement Metrics

Customer engagement metrics are a primary category of startup performance measures associated with revenue growth. From the early stages of your venture development, understanding and measuring customer behavior is a foundational activity. If you think about what typically goes into the customer segment element, you define the customer’s profile, including demographics, lifestyle, and essential behavioral characteristics. You also identify the problem that the customer is trying to solve and the associated context. Finally, you list your current assumptions about specific challenges or pain points that the customer is currently experiencing.

As you prepare for early customer discovery, you have the opportunity to measure the degree that these various assumptions are, in fact, valid. Right from the beginning, I encourage students to develop the customer profile to be as quantifiable as possible. This effort is vital for several reasons, including market size calculations and early access metrics. Demographics are readily quantifiable, but lifestyle and behavior are more complex. I always suggest that founders establish goals for finding and engaging early customers. I have them set up a spreadsheet with categories to check, including critical demographics and behaviors (or behaviors that serve as a proxy for the actual customer behavior). You want to measure how many target customers you are finding within the specified segment, where are you accessing them (sources), how many convert to actual engagement. If you are not increasing these numbers, it says something about your market access and the challenge of creating early awareness.

Once you begin customer discovery and engagement, you can start to validate your core assumptions about the importance of solving the problem in question, the severity of the pain points, and the degree that the customer is dissatisfied with current market solutions. You should create a scale that measures these customer sentiments during your interviews or survey efforts. Pay particular attention to any variation across segments or differing contexts. For example, look for the number of customers who desperately want to solve the problem versus those that see it as something that would be helpful but not urgent.

As I mentioned in a recent post on customer discovery surveys, founders have an opportunity to gather some fundamental metric data from this early-stage activity. By asking a couple of specific questions in the survey, you can, in essence, begin to generate early sales funnel data that can be useful to establishing your market entry strategy later in the venture process. The first question asks the customer how they heard about the survey.? In the survey question, you provide all the channels used to solicit customer respondents. The listing should be specific and align with the methods you used. For example, if you use certain social media, list them individually— – Instagram, Facebook, WhatsApp, etc. Information about which channels result in strong response rates is critically important data. This information provides early historical data about your sales funnel. What are some of the best ways to create awareness and potentially quality leads for your venture?

By responding to the survey, customers show you how to reach them and what percentage are interested enough to take action – completing your survey. At this point, founders know how many surveys they sent out per channel and how many returned. Therefore, you have conversion rate data from awareness to demonstrated interest. You can go a step further with one more question.
A second question that complements the channel question is whether the customer is interested in staying in touch with you. By checking “Yes” or leaving their email, they communicate their interest in solving the problem. Validating their interest with how they learned of the survey now gives you additional conversion data by promotional channel. In the venture realization process, discovering early customer data is essential in future customer acquisition strategies.

I typically have founders create a table listing all the access channels to send surveys out to customers. Next, founders list how many customers they plan to reach each channel. With these numbers as a base, you can collect data on the number of surveys viewed, percentages of customer respondents, and of those the number who state interest in participating in future solution tests. Later on, founders can measure how many of these early customers participate in minimum viable product tests to measure continued interest. In effect, you now have some early sales funnel data that you can apply to early financial projections and post-launch benchmarks. 

One final customer engagement area to measure is the time it takes to move customers through the engagement process – from awareness to active participation. You get a sense of potential sales cycle time by collecting data on how long it takes to find your target customer, scheduling interviews or surveys, and actual participation. This metric is crucial in B2B business models when soliciting interest from enterprise decision-makers. 

MVP Metrics

There are several metrics to consider during the early solution design stage. Typically referred to as minimum viable product (MVP), these early build and test activities are essential to measure and monitor. As a starting point, it is important to connect what you have learned during the customer discovery phase to the actual design of the MVP.

During this first part of the process, you have the opportunity to review your current assumptions about what outcomes the customer expects or desires from an effective solution. Articulate customer outcomes clearly and quantify them whenever possible. Along with the outcome review, you should also articulate any specific product benefits associated with the customer’s needs. Customer outcomes and product benefits are closely associated, and your assessment should reflect this relationship.

Once you have defined customer outcomes and associated product benefits, you can prioritize them according to their needs. You will understand how customers value specific results from your customer discovery activities and research current market offerings. Additionally, you should identify existing solutions and potential gaps in the marketplace. One approach to help with this prioritization is the importance satisfaction matrix. Here, you rank the importance of the outcome and the level of satisfaction that the customer has with current, existing solutions. If the result for the customer is significant and the level of satisfaction with existing products is relatively low, you should look to prioritize this need area. As you test MVP iterations, you can measure and monitor customers’ importance – satisfaction levels throughout the early product development process.

Another way to collect data and create early product performance data is by applying pre & post-test measures as customers use your MVP to solve their particular problem. When possible, you can capture customer behaviors and emotions before using your product and then compare the responses after they have used your product. This kind of data helps you measure any changes in customer behavior due to using your solution. You can also measure this impact as you iterate new product versions.

During MVP iterations, you can also collect data on how many customers stay engaged (retention rates) from one test version to another? What are the attrition (churn) rates? Which features are they using, and do they continue to use during the MVP testing period (stickiness)? Are these early participants referring your solution to other potential customers (referral rates)? You can also integrate pricing sensitivity data to provide support for pricing strategies. Eventually, you can tie testing data with the percentage of MVP participants who become paying customers.

Profit Model Metrics

This category of startup metrics concerns early indicators of profitability. An important starting point for understanding new ventures’ path to profitability is the contribution margin of an individual sales transaction. Sometimes referred to as unit economics, this metric looks at one sales transaction takes the revenue generated from the sale of the one product or service unit, and deducts the costs directly associated with the individual unit transaction. These specific costs are usually accounted for as costs of goods sold and include any labor, raw materials, or other expenses incurred only when the unit sale occurs. This calculation provides information about the amount of profit the sale of the unit contributes to the gross profit and before any fixed operating costs are applied, which leads to the calculation of net profit or loss. A startup will never become profitable unless the unit economics work; each sales transaction contributes profit to operating costs.

One of the most critical metrics for a startup is your breakeven point. In general, breakeven occurs when the sales volume reaches the level at which a product or service will be profitable. Generally, this involves dividing the total fixed and semi-variable costs by the contribution obtained on each sales unit. However, before you begin calculating this metric, make sure you define specific elements of the transaction clearly. The first thing to address is what you consider to be an individual sales unit. The definition of the “unit” depends on your venture’s business model and what drives revenues. A unit may be a specific product or service. But many times, the unit is defined as the customer, client, user, or beneficiary. Some business models may be a physical outlet, such as a rental space, a chair, a kiosk, a desk, or a retail store.

The second factor to address is how your business defines “sales” based on your specific revenue model. For example, is there a cost difference between new and existing products you sell? Do new products have a higher or lower cost of goods sold associated with them? If you define the unit as the customer, is it for one or recurring payments? When a location is a defined unit, are you measuring at a store level or square footage? 

The variable costs per unit are the next factor to determine. For physical products, this is usually straightforward and consists of the cost of producing the product (commonly labor and materials). However, services and software can be more challenging to determine the best way to account for specific costs. For example, software businesses will consider development costs either variable or fixed. One determines this by asking whether developers are salaried employees or outside contractors paid by the project? When employee wages are fixed costs, the enterprise pays them regardless of sale performance. On the other hand, project-based developers are compensated for working on a job associated with a specific sales transaction. No sale, no pay. 

Once you have defined the unit and the variable costs, you can calculate the contribution margin. This metric represents the amount that venture’s revenue will contribute to its fixed costs and net profit. In other words, the amount of cash the unit will contribute to cover fixed expenses (or overhead). This measure demonstrates the profitability of individual products, product lines, and business units.
The breakeven analysis helps the entrepreneur determine whether a particular sales volume will result in a profit or loss. The point at which breaking even occurs is the output volume at which total revenues are equal to total costs. To use this analytical method, you need only to know the fixed costs of operation, variable costs of production, and price per unit.

These projected profit metrics are critical foundational elements that will support your financial projections and become early benchmarks to monitor once you launch.

Resource Acquisition Metrics

This category of startup metrics is associated with acquiring the required resources to execute your business model. There are many types of resources to consider, from funding to critical skills and expertise.

Many of these indicators are associated with the sources and uses of cash. For example, funding metrics focus on how much money is required and when needed. You may want to consider this as monitoring key cash flow events. How much money does the venture need during each stage of the startup’s evolution? When are the funds required? Are the projected monthly payables and receivables on track?

I suggest founders set goals and monitor is the acquisition of needed talent. One way to apply the three Business model canvas elements – key activities, resources, and partnerships – is to see them as interconnected. First, you identify all core activities required to provide value to your customer repeatedly and sustainably. Then, you decide what resources, skills, and expertise the venture needs to excel at these core activities. From here, founders can assess if these necessary resources are already in-house and what gaps exist. You can then go ahead and plan to fill these gaps with advisory vehicles, partnerships, and strategic alliances.

With this information organized, you can set a series of milestones to fill these resources as needed. There are, in effect, sales cycles here to measure and monitor. For example, you will want to record and document the steps to create functional channel partner relationships. Effective channels take to set up time and ongoing management. You should learn what it takes to create an effective channel and establish a roadmap for future channel partners.

Critical Path Metrics

Many startup experts recommend identifying one critical metric that measures a performance outcome crucial to your venture’s survival. This critical metric is sometimes called the one metric that matters (OMTM). Focus is key to startups’ success. It helps to pick the one metric integral to your success at your present stage of venture development. For example, many new ventures need to focus on early customer acquisition, so it might be critical to monitor how many new customers visit your website and take some action, such as joining as a member or paying for a subscription. This required early metric will change over time. First, it may be on customer acquisition rates per channel; later, you will focus on retention (churn rates). The focus allows you to articulate clear goals to all stakeholders, from employees to investors.

In the pre-launch stage, I suggest you document a history of goal achievement using KPIs to measure and monitor progress? Focusing on goal setting, measurement, and monitoring in the early stages of your venture development helps create a disciplined and focused team and culture. In addition, I always have founders provide a detailed plan and timetable focusing on essential pre-launch business model activities such as customer engagement rates, product development goals, team member recruitment, and pre-seed and seed funding rounds. Then, during the early launch phase, you can measure, monitor, and demonstrate goal achievement across these critical activities. 


Investors will be interested in many of the above startup metrics, and entrepreneurs should be prepared to identify, measure, and monitor the key indicators associated with the specific business model and industry in question. One recommendation is to identify one or two of the most critical metrics in each of the above categories and create a one-page “dashboard” that can communicate timely performance information to internal and external stakeholders.

For more on this subject and other entrepreneurship topics, get a copy of Patterns of Entrepreneurship Management, 6th Edition.

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