Overview of the Problem and Framework

The technology plays a major role in the disruption of traditional business (Zervas et al., 2015) and the competitive environment (Yoo, 2010). Start-ups hold a big portion in dis-ruptive innovations according to Srinivasan (2014) as well as contributing to global wealth and economic growth significantly (Gauthier et al., 2019). Access and cheap ways of getting into target markets enabled by predominantly expanding internet connectivity and mobile devices make entrepreneurship attractive for many. Previously made defini-tions of start-ups by Ries (2011), Blank (2006), Graham (2012), Thiel (2014), and Wang et.al. (2016) encompass a common definition of start-up term as

“…new companies that have an innovative and valuable solution and aim to grow fast with a scalable business model under extremely uncertain and resource-lim-ited conditions…”

Software startups provide an excessively diverse amount of new services and products.

Sutton (2000) describes software start-ups with a lack of operational experience, means and capabilities, and the existence of impact from various groups, and constant alteration of technologies and markets. Paternoster et al. (2014) highlight the most prevalent at-tributes of software start-ups as inabilities, novelty, fast progress, inexperienced organi-zation, third party reliance, and time pressure. One of the most recent and progressively adapted software products and services is the software-as-a-service (SaaS) model.

Laatikainen and Ojala (2014) review the existing definitions of SaaS as a scalable and adjustable application used through the browser with multi-tenant hosting capability. Ac-cording to Luoma and Rönkko (2011), customers benefit from outsourcing the operation and maintenance of identical software of usually high volume and on-demand price.

In spite of very promising and advanced conditions, there is a high rate of failure for start-ups. Depending on different research analyses the rate of failure changes from 60 per-cent (Nobel, 2013) to 90 or even more (Startup Genome, 2019). Research on the failure of start-ups is missing although the majority of start-ups fail (Paternoster et al., 2014) as well as the research on start-ups (Hokkanen, 2017). Potential start-up founders can on the other hand benefit from the knowledge on challenges of past start-ups to advance smoother in their journey (Wang et al., 2016). Therefore, this thesis research study fo-cused on the very early stage of start-up development to shed light on the initial chal-lenges and best practices, especially from sales perspective.

The widely accepted framework developed by MacMillan et al. (1987) categorizes chal-lenges under four aspects as product, finance, market or business, and team. This study also contributes by adding environmental and legal challenges to the existing framework.

Understanding customers and the market to find a repeatable business model that can scale is often a major challenge. According to Blank (2006), usually the failure in start-ups results from missing the customers and proving the business model than developing the product.

Blank (2006) states that most of the start-ups have trusted the Technology Adoption Life Cycle model by Rogers (1983) in sales and marketing as well as Moore’s “The Chasm”.

The technology adoption life cycle introduced a model of different customer groups dur-ing the acceptance of a new innovative product that are innovators, early adopters, early majority, late majority, and laggards. Moore (1991) contributed to this model by inserting gaps between customer groups to illustrate the difficulty of moving along the curve where the biggest gap is called “The Chasm” between early adopters and early majority to move from early markets to mainstream markets. Each group has various needs and habits thus these cracks between different customer types appear. Moore (1991) claims that most sales and marketing methods used in the early market are not applicable in the mainstream market which makes crossing the chasm a substantial challenge resulting in tragedy without being usually realized.

However, Blank (2006) asserts that the existence of the business is dependent on cus-tomer development even before reaching to any chasm. He presents cuscus-tomer develop-ment stages as discovery, validation, creation, and company building where the first two are focusing on the early market of technology adoption. Similarly, Ries (2011) proposes phases as finding problem-solution fit with validated learning and experimentation, find-ing product-market fit with build-measure-learn cycles and latter as growth and scalfind-ing.

The study by Giardino et al. (2015) reveals that getting the first paying customer is per-ceived by the majority of startups as their top key challenges. Thus, the “Startup Chasm”

is at the very beginning of the lifecycle. The following figure presents the framework built based on Moore’s (1991) “The Chasm” and Blank’s (2006) “Customer Development”.

Figure 19. Theoretical Framework The Startup Chasm (adapted from Blank, 2006 and Moore, 1991)

The biggest challenge lies at the start of the customer lifecycle and has more significance than the chasm between the early and mainstream markets. To find the first customer and moving to the next stage requires various adjustments and changes. Blank (2006) and Ries (2011) both highlighted the need for validation of initial ideas and introduced iterative processes which introduced pivoting. According to Ries (2011), a pivot is chang-ing the tactics to reach the same vision. He further points out that the original business ideas are altered by around 70 percent of start-ups. Therefore, start-ups may face differ-ent growth trajectories than a smooth technology adoption cycle path based on their iterations and pivots at the early stages. The customer development process can show various oscillations for each startup. Figure 20 illustrates an example path as the second part of the framework.

Figure 20. Iterations in The Start-up Chasm

The growth of each start-up differs from each other and might not pursue a similar shape.

From the financing aspect, this figure also illustrates multiple valleys of death for start-ups in line with pivots and customer growth. Blank (2006) asserts that the gentle pattern of the adoption cycle results is a risky perception of getting customers as a matter of executing sales. The next section will provide a reflection on the case studies according to the theoretical framework proposed by this thesis.