Technology driven enterprise solutions are products or services that use advanced technologies such as artificial intelligence, telematics, or blockchain to solve problems or create value for enterprise customers. Startups developing technology driven enterprise solutions face different challenges and opportunities than startups in other domains, and this may affect how they approach the startup lifecycle, the founder tasks, and the investor expectations.

In this article, we will explore the three stages of the startup lifecycle - idea, problem-solution fit, and product-market fit. We will also discuss some common mistakes and pitfalls that founders may encounter at each stage, and how to avoid them.

Idea Stage

The idea stage is where the founder(s) come up with the initial concept for their startup, based on a problem they want to solve or an opportunity they want to seize. The key tasks in this stage are to validate the problem, research the market, identify the target customers, and formulate the value proposition. The key metrics are qualitative feedback from potential customers, such as interviews, surveys, or focus groups.

In summary, founder(s) need to identify who their target customers are, what problem they are solving for them, and how they will reach them with their solution. In business model terms, this means working mainly on customer segments, value propositions (duh), and channels.

Some common mistakes and pitfalls in this stage are:

• Choosing a problem that is not significant, urgent, or frequent enough for enterprise customers to pay for a solution
• Assuming that the founder's own experience or intuition is enough to validate the problem and the customer segment
• Not involving potential customers or stakeholders in the ideation and validation process
• Failing to research the market size, potential, and competition for the startup's idea

Fundraising is still possible during the idea stage. Investors look for the founder's passion, vision, and commitment to the problem they are trying to solve. They also look for the market size, potential, and opportunity for the startup's idea. They want to see that the founder has done some research and validation of the problem and the customer segment. They may also look for the founder's domain expertise, background, and network.

When the founder(s) have validated that their target customers have a real and urgent problem that they are willing to pay for a solution, and that their MVP can deliver that solution effectively and efficiently, they can consider themselves at the next stage.

Problem-Solution Fit

The problem-solution fit stage is where the founder(s) develop a minimum viable product (MVP) that demonstrates how their solution can solve the problem for their target customers. The key tasks in this stage are to build the MVP, typically for or during PoC projects, test with early adopters, collect feedback, and iterate on the product. Metrics switch to quantitative indicators of customer satisfaction, such as usage rate, financial value add to customer, or customer lifetime value.

Even with only the MVP, founder(s) need to establish how they will interact with their customers, how they will generate revenue from their solution, and what resources they need to create and deliver their solution. In business model terms, founder(s) are working mainly on the revenue model, relationships and resources. If the startup hasn’t graduated from the idea stage with a clear understanding of customer job to be done and solution they are willing to pay for, the problem solution fit journey becomes very complex. Founder(s) end up working on too many business model building blocks in parallel. Assuming that the startup has validated the idea stage sufficiently, common roadblocks in this leg of the journey include:

• Building an MVP that is too complex, expensive, or risky for enterprise customers to adopt or integrate.
• Relying on vanity metrics instead of meaningful feedback.
• Ignoring or dismissing negative feedback or being too attached to the original idea or vision.
• Not iterating on the solution based on customer feedback or pivoting too frequently or drastically without a clear rationale.

Depending on where the startup is based from and its target market(s), problem solution fit stage is when VC’s enter the funding scene. Such investors look for hard facts. They want to see that the startup has some traction, validation, and product-market fit indicators, such as retention rate, net promoter score, or customer lifetime value. Also they want proof of to the startup's ability to build a minimum viable product (MVP) that demonstrates how their solution can solve the problem for their target customers. They also look for the startup's ability to test the MVP with early adopters, collect feedback, and iterate on the product. 

Founder(s) receive PMF bragging rights when they have achieved a positive and scalable unit economics, meaning that the cost of acquiring and serving a customer is lower than the revenue generated by that customer, and that there is a large and growing market for their product. If there is economies of scale in place as well, a unicorn may be born.

Product-Market Fit

The product-market fit stage is where the founder(s) refine their product and business model to achieve a favorable fit between their solution and the market demand. The objectives are to optimize the product features, pricing, distribution, and marketing strategies, and to measure the impact of these changes on the customer behavior and revenue. The founder(s) are validating that the current iteration of the MVP, now called the product, will be purchased and utilized repeatedly by satisfied customers. Success in all these activities presents itself in unit economics (LTV/CAC) and growth.

At this stage, the next frontier is validating this is a scalable business. Hence the business model blocks in question are key activities, key partnerships, and cost structure. Meaning that, once there are more customers, the business becomes more efficient and cost effective. The founder(s) need to define what activities they need to perform to operate their business, what partners they need to collaborate with to leverage their strengths and mitigate their weaknesses, and what costs they need to incur to create and deliver their solution. They also need to optimize their product features, pricing, distribution, and marketing strategies, and measure their growth and profitability.

Some common mistakes in this stage are:

• Assuming that the startup has product market fit, when in reality, it’s in problem solution fit stage - not having a clear and compelling value proposition, pricing strategy, or distribution channel for the solution.
• Not understanding the decision-making process, budget cycle, or procurement policies of enterprise customers.
• Not having a scalable and repeatable sales and marketing process or relying on a few large customers or contracts.
• Not measuring the impact of the solution on the customer's outcomes, satisfaction, and retention.

This stage consists many rounds of investments. Investors look for the startup's ability to refine their product and business model to achieve a fit between their solution and the market demand. They also look for the startup's ability to optimize their product features, pricing, distribution, and marketing strategies, and to measure the impact of these changes on the customer behavior and revenue. They want to see that the startup has a positive and scalable unit economics, meaning that the cost of acquiring and serving a customer is lower than the revenue generated by that customer, and that there is a large and growing market for their product.

Conclusion

By understanding the relationship between the startup stages and the business model canvas, completing each stage with full validation before moving onto the next and by avoiding some common mistakes and pitfalls, technology driven enterprise solutions startups can increase their chances of success and create value for their customers and themselves.

This article is generated with text and image support from CoPilot.