High Tech Strategies > Resource Center

Resource Center

High Tech Strategies uses frameworks and methods that make innovation and new-product success predictable. We employ psychographic, qualitative, and market segmentation methods that reveal the hidden requirements for business growth.

This resource center only includes tools and assets that we’ve created or use ourselves. There’s nothing trendy or superficial—just the very best techniques that we’ve found to be essential to achieving sustained business success. This library contains the following resources:

  • Models and Frameworks
  • Online Courses
  • Articles
  • White Papers
  • Diagnostic Tools and Analysis
resource center

Resource List


Go-To-Market Masterclass

Go-To-Market Masterclass is a real-time, interactive online course that enables entrepreneurs, CEOs and product leaders to ensure the ongoing success of their new products or innovations, without having to visit a classroom or interrupt their work schedules.



Diffusion of Innovations

A summary of Diffusion of Innovations by Rogers, E. M., First edition. New York: The Free Press. (1962) — Diffusion of Innovations is the most popular model for understanding how new products and innovations gain momentum and diffuse (or spread) through a specific market or population.



Crossing the Chasm

The chasm concept was created at Regis McKenna Northwest in the 1980s. This summary describes the initial framework, called The Marketing Chasm, that was later popularized by Geoffrey Moore in a book called “Crossing the Chasm.” Link to an early example of:  The Marketing Chasm (1988)



CAL White Paper

The Customer Alignment Lifecycle (CAL) helps you avoid the loss of sales traction by staying aligned with the ever-changing needs of your customers. In the CAL white paper, we explain what CAL is, how it works and how companies use it to transform the success rate of their new products and innovations.



Accelerating the Adoption of EVs

This analysis provides EV manufacturers and suppliers with an opportunity to accelerate our transition to a clean-transportation future. The facts suggest that the lowering of perceived risk — primarily through the temporary suspension of product differentiation — will be the true driver of EV market transformation.



CAL Infographic

The Customer Alignment Lifecycle (CAL) helps your entire organization stay aligned with the ever-changing needs of your customers. Use the CAL Infographic to achieve alignment across all key dimensions of customer value, maintain sales traction, and ensure growth in uncertain times.



10 Reasons Tech Products Fail

Many of the actual reasons high-tech companies fail are not captured in statistical surveys. Why is the rate of high-tech failure so high, and why do so many high tech companies fail?  This paper provides an in-depth, qualitative analysis of the reasons behind high-tech failure.



Low Risk Reinvention White Paper

Low Risk Reinvention is one of the most powerful techniques developed by High Tech Strategies. In this white paper we describe how intangible attributes allow the development of a low-risk offering, which is the most important dimension of value for mainstream customers and buyers.



Dynamic Product Perception

The concept of dynamic product perception, which describes the way products or ideas move through the innovation-adoption lifecycle, is a critical element in any discussion about intangible product attributes. Over time, customers select products based on intangible attributes, rather than product functionality.



How a Crisis Can Dramatically Boost Product Adoption

Product adoption is typically determined by its cost benefit ratio, which is a measure of its value to the customer.  COVID-19 helps startups and established companies amplify the value of their product. And the best way to measure this value is with a cost benefit analysis.

Characteristics of Early Adopters

Early adopters play a significant role in the beginnings of your high-tech company. Unfortunately everything you learn about marketing to early adopters will fail miserably when you try to use it in the future.

Crossing the Chasm Confusion

A comprehensive research project conducted by High Tech Strategies confirms that there is an epidemic of misunderstanding surrounding “crossing the chasm” and the theory behind the framework. In this article we identify the six areas that create the greatest amount of confusion.

Frequently Asked Questions

Business people love numbers because numbers make them feel secure. But in emerging markets, numbers are rarely reliable. And managers that rely on numbers are unlikely to succeed.

In many cases, quantitative analyses use the past to predict the future. But we live in an era when the future almost never resembles the past. It is extremely difficult to take the pace of technology into account. Extrapolating today’s trends into the future almost never works.

Bare statistics tend to miss the nuances of the market. A survey might show that 60 percent of all customers use a company’s product. But a qualitative approach might reveal that the customers are unhappy with the company’s service, and many are considering switching to a competitor.

Yet, as companies grow, they tend to rely more and more on quantitative techniques. They become locked up in numbers and big data. They end up with products that do not match the needs of the market nearly as well as the products of entrepreneurs. Creativity is squeezed out of the system.

When you are creating new markets, no one really knows where you are headed. You have to be more creative. A well-known CEO at Apple once said he is wary of numbers-oriented analysis: The only quantitative data I use are what people have done, not what they are going to do. No great marketing decisions have ever been made on quantitative data.

Other than confusing the difference between “disruptive” and “discontinuous,” the most common misunderstanding among people who read Crossing the Chasm is they tend to believe that all markets and populations have a chasm. But the chasm model only applies to “discontinuous innovations” and does NOT offer useful guidance for continuous innovations.

This distinction is not presented with enough detail in the chasm book, and the key to differentiating the two types of innovation requires more than looking for a change in behavior. The degree of discontinuity is also influenced by the ability of an industry or population to learn new things.

This is one of the fundamental misrepresentations in Crossing the Chasm. An innovation can be easy for a specific market segment to learn about and adopt, even though it requires a change in behavior.

However not all industries or social systems learn at the same rate. So an innovation that is continuous for one group or market, might be a discontinuous innovation in a different geographical area or culture or industry, because learning new things is more difficult for some populations.

The chasm model does not acknowledge the potential duality inherent in some innovations.

The field of statistics is based on the fact that it is often impossible to collect the data of an entire population. Instead of trying to measure an entire population, it is possible to gather a subset of that data and use statistics to draw conclusions about the population. This subset of data is called a “random sample.”

The Central Limit Theorem states that the distribution of your statistical [random] samples approaches a normal distribution as the sample size gets larger — no matter what the shape of the population distribution. This fact holds especially true for sample sizes over 30. As you take more samples, especially large ones, your graph of those sample averages will look more like a bell curve, a.k.a. a normal distribution.