The Customer Really Does Rule

Among the business lessons and rules learned over the years is that the customer really does rule. This was learned in the context of understanding that there are a finite number of sources of actual, hard cash for a business. Among the alternatives are:

•  Borrowing it (in the form of debt or equity or venture capital)

•  Selling assets (if you have them to sell) or

•  Getting it in the form of revenue from customers

Among the three, it makes sense that if one could choose, they would choose revenue from customers. Debt, equity, and venture capital, in the beginning start up phases, are fine. Unfortunately each has continuing costs associated with it. Continued borrowing over time can become onerous and eventually lead to a company’s demise. Selling assets is fine until the assets run out. But over time, revenue is the sustainable source of cash that is the reward that the customer bestows upon a company for its excellence and the value of its offerings. There is nothing onerous in reasonably “growing the top line” on a continuing basis.

Now customers have numerous choices as to where they send their money and who they reward, i.e. they have alternative choices called “the competition”. A competitor, by definition, is “the customer’s alternative choice”. There are direct competitors (those that are very much alike in appearance), indirect competitors (those that do not look alike but serve the same customer need), DIY (do it yourself) alternatives and in some instances, doing nothing is an alternative choice for the customer.

So how does a business capture the customer reward?

Since the goal is to have the customer send you the money, and lots of it, the first step in maximizing cash from revenue is to find a group of customers that can be served in a meaningful and sustainable, economic fashion. This is called “target market selection”. One of the first major strategic decisionsthat any company makes is deciding what market it will serve. Since it can’t be all things to all people, it must be something meaningful to some group. In nature there is a saying “no species can live everywhere, but each species must live somewhere”. Translated into the business world, this means find a specific, relevant target market that is compatible to your business strengths. Focus on that market. Don’t spend a lot of time considering irrelevant markets; a waste of resources.

Once that target market has been selected, the second major strategic decision that a company must make is deciding what will be its basis for a sustainable competitive advantage. There will usually be alternative choices for the customer’ money in the target market; called competition. And in order to maximize the revenue stream from the customer, one must have a unique and distinctive advantage over those alternative choices. Lower cost, unique features, superb service, distinctive positioning, are a few of the alternatives for establishing a competitive advantage. Whatever one selects, be sure it is sustainable and affordable.

Well, having selected a target market and established a basis for competitive advantage, the next step is to set revenue goals and operational tracking measures that will be the predictors and evidence of the wisdom of the strategic decisions. Another lesson or rule is that one should always be number one in market share within the relevant target market, or at least a close number two. The customer’s response in revenue terms is what drives market position. The more they like and value what you are doing, the more revenue they will send you. Market leadership reflects the relevance of the market selected the strength of the offer’s unique and distinctive advantage and the value seen by the customer. Conversely a weak market position indicates the weakness of the strategic decisions and, of course, less revenue.

As noted above, operationally, the relative value of the offer as seen by the customer, in comparison to their alternative choices, is an accurate leading indicator of what their actual in market performance will be. Value can be determined by:

•  Ranking and valuing the offer’s features in terms of their importance

•  Rating one competitor Vs another on the features, and

•  Rating each competitor Vs the other in terms of its perceived value (CVA score)

All these measures aid in predicting what the customer will do. Since customers usually behave in relationship to the value they perceive, the highest value score for a competitor will lead to the highest revenue stream to that competitor.

There is another aspect to being the market leader and that is the competitor with the highest market share (by virtue of selling the most volume) is usually the low cost producer within the selected market segment; or they should be. Through scale and experience effects, market leaders should have the lowest costs. Combined with the greatest revenue, this makes the market leader the competitor with the highest margins and returns, i.e. the financial leader. Not a bad combination.

In the long run, some companies seem to continually outperform the others in terms of market position, margins, returns, and creating shareholder value. Others do not, lagging behind in market share and financial performance. Since the marketplace is neutral to everyone, why do some companies do better than others? Winning companies have a winning strategy as it relates to target market selection, unique and distinctive offers, cost control and investing scarce cash resources. Winning companies become number one with their customers in their respective markets. And they understand the value of being the low cost producer. But most importantly, they recognize the value of the customer who is the final arbiter of their success. WHAT’S IN YOUR WALLET?

“Enjoy the value it brings it you”

Artificial Intelligence 101: A Snapshot

By Team Acumentica

 

What is Artificial Intelligence(AI)?

 

In plain and simple terms, Artificial Intelligence (AI), also called Machine Intelligence (MI), leverages computers and machines to emulate human problem-solving and decision-making processes.

 

What is an Artificial Intelligence (AI) Model?

 

An AI system is built by developing AI models. An AI model consists of stochastic mathematical and statistical algorithms that collect, process, analyze, and convert data into predictive and prescriptive decision support systems to solve specific real-world problems.

 

What are the Different Types of AI?

 

There are two types of AI:

 

  1. Weak AI or Narrow AI

This is also called Artificial Narrow Intelligence (ANI). It is AI trained and focused on performing specific tasks. Nowadays, weak AI is ubiquitous, found in smartphones, Amazon Alexa, Google Siri, Acumentica Frida, and autonomous vehicles.

 

  1. Strong AI or AGI (Artificial General Intelligence)

Artificial General Intelligence (AGI) theoretically refers to a machine with intelligence comparable to a human being. It would be consciously aware of its surroundings and capable of learning, planning, and solving problems independently. While AGI is still in its theoretical phase, researchers and enthusiasts are actively exploring its development.

 

Difference Between Machine Learning (ML) and Deep Learning (DL)

 

Machine Learning (ML) and Deep Learning (DL) are often used interchangeably, but they are distinct. Both are subfields of AI, with deep learning being a subset of machine learning.

 

Machine Learning

 

Machine Learning (ML) refers to technologies and algorithms that enable machines to recognize patterns, perform decisions, provide recommendation support functions, and self-learn and improve over time. The three types of machine learning are:

 

  1. Unsupervised Learning

Uses unlabeled data, allowing the system to identify patterns and associations. A common use is clustering, which groups similar data points together. Examples include e-commerce recommendation systems like those on Netflix.

 

  1. Supervised Learning

Requires human intervention. The system is fed labeled training data to learn and make predictions. For example, teaching a system to recognize images of apples involves classification problems, where the system learns to identify apples from labeled images.

 

  1. Reinforcement Learning

Involves rewarding the system for correct actions and penalizing it for incorrect ones. Over time, the system learns through trial and error, reinforcing good actions. This is similar to how humans learn.

 

Where is Machine Learning Used Today?

 

Machine learning is used in various domains, such as:

 

  • Healthcare: Implementing dynamic treatment regimens for patients with long-term illnesses.
  • Autonomous Cars: Tesla and Waymo.
  • Traffic Light Control.
  • Sales: Acumentica AI Customer Generating System.
  • Stock Predictions: Acumentica AI Stock Predictive System

Additionally, machine learning is used in everyday applications like spam filtering in Google, fraud detection in banks, and voice recognition in Amazon Alexa.

 

What is Deep Learning?

 

Deep Learning is a branch of machine learning that uses neural networks comprised of many layers. Unlike machine learning, where the agent is given processed data, deep learning uses raw data and autonomously determines relevant data. This reduces human intervention and allows the use of vast datasets, both structured and unstructured. Deep learning systems become more intelligent over time with more data.

 

Where is Deep Learning Used Today?

 

Deep learning is used in various applications, such as:

  • Fraud Detection.
  • Natural Language Processing (NLP): Acumentica AI Growth System.
  • Customer Relationship Management: Acumentica AI Customer Generating System.
  • Stock Predictions: Acumentica AI Stock Predictive System
  • Computer Vision.
  • Agriculture.
  • AI Voice Recognition System: Acumentica.
  • Virtual Assistants.
  • E-commerce.
  • Manufacturing.

 

How Does AI Work?

 

AI systems work similarly to refining petroleum for vehicle fuel. Data, whether structured or unstructured, is collected and processed to remove outliers. The clean data is then fed into an AI system with intelligent learning algorithms that use the data to self-learn and solve problems with minimal human intervention. Big data plays a crucial role in the effectiveness of AI inferences.

 

Why Acumentica?

Your growth is our success. This is our DNA. We focus on building relationships and growing companies by increasing revenue, ROI, while reducing costs.

At Acumentica, we are dedicated to pioneering advancements in Artificial General Intelligence (AGI) specifically tailored for growth-focused solutions across diverse business landscapes. Harness the full potential of our bespoke AI Growth Solutions to propel your business into new realms of success and market dominance.

Elevate Your Customer Growth with Our AI Customer Growth System: Unleash the power of Advanced AI to deeply understand your customers’ behaviors, preferences, and needs. Our AI Customer Growth System utilizes sophisticated machine learning algorithms to analyze vast datasets, providing you with actionable insights that drive customer acquisition and retention.

Revolutionize Your Marketing Efforts with Our AI Marketing Growth System: This cutting-edge system integrates advanced predictive analytics and natural language processing to optimize your marketing campaigns. Experience unprecedented ROI through hyper-personalized content and precisely targeted strategies that resonate with your audience.

Transform Your Digital Presence with Our AI Digital Growth System: Leverage the capabilities of AI to enhance your digital footprint. Our AI Digital Growth System employs deep learning to optimize your website and digital platforms, ensuring they are not only user-friendly but also maximally effective in converting visitors to loyal customers.

Integrate Seamlessly with Our AI Data Integration System: In today’s data-driven world, our AI Data Integration System stands as a cornerstone for success. It seamlessly consolidates diverse data sources, providing a unified view that facilitates informed decision-making and strategic planning.

Each of these systems is built on the foundation of advanced AI technologies, designed to navigate the complexities of modern business environments with data-driven confidence and strategic acumen. Experience the future of business growth and innovation today. Contact us.  to discover how our AI Growth Solutions can transform your organization.