While building a technology is an essential part of any startup, it is also necessary for founders to validate the problem, better understand the users, define a possible business model, and find a way how their solution will be further adopted in the market.
Each of these aspects are especially relevant for AI, IoT, and other cutting-edge technologies which prototypes development can be complicated by high-tech hardware or software.
- Define a Particular Problem
Prior to choosing a tech stack and prototyping, it is essential to define a particular problem which the product is supposed to solve.
It may be useful to ask the following questions:
• Who will be affected by the issue?
• How do they usually address it?
• Which alternatives have already proven to be partial or ineffective solutions?
• Are people going to adopt your method instead of the existing approaches?
• What value will the product bring to the customers?
The first two steps usually enable product scoping and help differentiate a feasible idea from a failed one: technically feasible but without a particular problem to solve.
- Make Sure to Validate the Proof of Concept
At this stage, it is critical to validate the proof of concept (PoC) and reduce risks involved in product development.
Such validation can be achieved through customer discovery, competitor analysis, PoC prototyping, customer testing, and feedback incorporation.
Specifically for AI products, there is a necessity to take into account how relevant data is, model accuracy and performance, potential liability for errors, etc.
For IoT products, the focus should be on other factors, such as a connection, devices’ compatibility, maintenance, or even the application’s environment.
These aspects, among others, determine how the product will be finally validated, which also depends on particular customer segments and their requirements.
- Scope Your Business Model According to the Chosen Architecture
When designing the technical scope of a product, it is essential to keep the relevant use cases in mind while also avoiding overspending on underutilized features.
IoT products, for example, often involve a variety of edge and cloud components which imply the necessity for balancing costs against performance, reliability, maintenance, data privacy, and other factors.
Meanwhile, when prototyping an AI product, one may consider a pipeline, model’s selection, training and validation, monitoring, and deployment.
In either case, an effective approach is to design a product MVP which will be sufficient to test the key hypotheses before moving to a more comprehensive architecture and expanding the feature set.
Another critical aspect of product development is a business model which implies economic viability, adherence to the customer’s budget constraints, value provision, and sustainable growth.
When building a business plan, it is essential to define the target audience and decision-makers, elaborate on the value offered by the product, estimate costs related to customer acquisition and product implementation, determine revenues, profit margins, and potential objections.
In the sphere of enterprise technology, such decision-makers can also include not only end-users but operation management, finance departments, and even the executive leadership.
Therefore, the target audience should also be defined during the customer discovery phase.
- Choose the Right Venture Building Ecosystem
In the sphere of venture building, Aperture Venture Studio represents one of the possible options.
Depending on the company’s needs, a venture studio can assist in opportunity identification, product scoping, proof of concept validation, team raising, and prototyping.
This practice can be beneficial for any technical founder aiming to transform their disruptive idea into a product with the involvement of experts in product design, marketing, and sales.
In this regard, Aperture Venture Studio also provides a wide range of services, including educational resources, portfolio company co-founding, and venture building consultation.
As soon as a founder chooses a venture studio, it is essential to analyze the services provided and resources available before making a final decision.
- Measure Success with Real Customer Evidence
While developing a product, a startup can measure its progress not on project deliverables but on achievable outcomes.
These indicators are closely linked to the above-mentioned steps and depend on a product’s nature, market segment, and chosen business model.
For enterprise apps, such metrics can be connected to customer acquisition, whereas for the MVP launch, any customer feedback can be critical.
In either case, the indicators should be aligned with a company’s long-term goals and current capabilities: for early-stage products, it makes little sense to focus on user retention rather than on expansion and adoption.
Final Remarks
The ultimate success of a venture is determined by project scoping, customer discovery, business modeling, prototyping, and development.
A better understanding of these aspects allows a startup to build a feasible plan and allocate resources in the best way possible.
The most critical point is to define a particular need or an unaddressed problem which a product will solve.
This understanding, in turn, informs a wide range of recommendations, including scope reduction, resource redistribution, MVP choice, or even the shift from enterprise software towards social media platforms or vice versa.
Discussion: In the context of founding AI and IoT start-ups, is customer discovery more difficult than product scoping or business model shaping at the beginning of the venture?
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