The Critical Role Of Positioning In Marketing and Sales?

Introduction

Before diving into how Positioning impacts your marketing and sales, a business must understand what Positioning is. With over 21+ years of transforming businesses, “positioning” is one aspect that I see almost all companies need to reassess and focus on. Business owners, CEOs, and sales and marketing executives think their Positioning can be done without refocusing. However, a business should rethink its Positioning based on negative customer feedback, low-win bid rates, lost opportunities, and poor customer perception. Remember, it’s not what we think of our company, products, and services but what your ideal customers and prospects think.

What is Good Positioning?

Simply, a company’s product/service positioning is about providing customer-centric value that best-fits customers who love and want more.

Positioning impacts many aspects of a business. It affects how you market and sell products, directly affecting revenue and ROI. It determines how customers perceive a business. It affects what you build and what is offered to customers. It impacts marketing and sales costs. From an operations perspective, Positioning affects a business’s COGS (Cost Of Goods Sold) and SG&A (Selling, General And Administrative ) costs. Furthermore, good Positioning increases employee productivity from a people and culture perspective.

 When it’s mapped out, the value of Positioning impacts nearly every financial measure of a business, particularly profit margins. In short, good Positioning impacts the health of a company. Based on our research and experience, companies must take the time to reassess their Positioning if they are facing marketing and sales challenges.

How to implement Good Positioning?

A business can develop and implement good Positioning by;

  • Understanding clearly your best-fit customers’ personas and characteristics.
  • Know your unique attributes and capabilities.
  • Know the value and benefits of your product/services quantitatively and qualitatively.
  • Understand your Competitors.
  • Develop value-based context.

Utilizing positioning tools and techniques together with having discussions with the right team members in your company, a business can achieve good Positioning.

By executing the above strategically, a business will get continuous insights into the external market, create innovative alternatives, develop a business design and ensure the executability of that design by orchestrating and developing the organization’s capabilities. It is not principally about creating a positioning statement or document, although both play a role.

How can I ensure my Positioning Increases sales?

If a business’s Positioning is good, they will notice an increase in their prospecting rates, sales closure rates, and sales growth. Their Top-Line growth will increase. Furthermore, they will notice a reduction in their sales and marketing costs, that is if your your tracking them (which is very important to do). Moreover, pay close attention to the variances in a company’s profit margins with good Positioning. If executed right, monitoring and tracking their positioning change, they will increase the overall health of your company.

How good is your Positioning today? Do you want to get better? 

A structured positioning assessment will clearly help you understand where you currently are and what need you to better position your business.

There is an adage “The definition of insanity is doing the same thing repeatedly, expecting a different result”. If you are stuck or challenged, make the correct change. Wrong Positioning may be a blind spot and pain point that you might need to mitigate.

Do you think you have a positioning problem? Acumentica can help by:

  • Performing a Positioning assessment of your business through analysis and team-based interviews.
  • Utilizing our fact-based positioning tools, processes, and methodologies.
  • Executing the inferences from the assessment to reach a good positioning state.
  • Tracking and monitoring a company’s positioning strategy.

Contact Our CXO Executives

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Increase A Business Online Visibility And Sales

How to increase a business online visibility and sales?

By Team Acumentica

As a small business owner your working on a shoe-string budget. We get it. Over the 20  years of experience working with GROWING  small businesses online visibility and sales, there has been a plethora of learned lessons. We want to outline for you what steps you need to take that is going to you help increase your digital visibility, foot traffic, conversion rate, and sales without any paid ads.

We  want to set and precedent and recommend do not to waste your hard earned money on social media and search engine marketing until you have optimally executed the below. We have seen time and time again how companies burn $Millions with little or ROI to show for it.

So let’s get to it. Below are the steps a company needs to take:

  • Conduct a Digital Assessment of your business – Understand the health of your website in real-time and fix your website issues based on the recommendations. Design your website that gives your targeted niche customers a better online experience from quote management, web chats, to purchasing seamlessly online. However, addressing the simple low hanging fruits will position your business better on various search engines radar screens.
  • Search Engine Optimization – Use the right keywords that your targeted customers personas will query to increase page rank higher organically without ads.  Always track and monitor your SEO.
  • Map optimization – Is your business on all Search Engine Maps? If not, this is a missed opportunity. The big search tech companies strategy is to use it’s Maps system to recommend businesses to customers or consumers. The goal is for your business to rank higher organically without any paid ads.
  • Enriched marketing content –  Provide quality content your target market niche. Yes, the marketing content you compile  is very important. Big tech companies use business content as a benchmark to make the right business recommendations. If they see your business as an expert in your field, they will recommend your business.
  • Google Business Page  –  Google business page is another linchpin system from Google that is imperative to have.  A business that meets a search engines criteria gets a higher authoritative token. This then translates to recommending a business to a customer.
  • Website analytics – Understand who is coming to your website and their user journey in real-time. If you know what they searching for on your website, you can then connect with them through a personal email campaign. This is a sales generating opportunity.
  • Analyze Your Digital Data –  Track and monitor the digital progress your business is making. Your data tells you a story about your digital performance.  Getting insights into your web data and making improvements will accelerate your page rank.

We like to point out that above is a continuous improvement always making the right changes to be ranked higher. The goal is to increase your page rank without any paid ads. This will in turn lower your marketing and sales costs and increase your foot traffic and revenue.

We are here to listen and help.  Contact Us should you have any questions. And if you don’t have the resources and bandwidth, Acumentica’s  Artificial Intelligence Digital Growth System and expert team can increase your online growth for you.

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Increase Digital Presence Organically Without Paid Ads

Increase Your Digital Web Presence The Right Way

Empirical evidence on the value of Paid advertisements has proven  it does NOT yield a HIGH ROI as originally anticipated. Large companies are pulling their once costly digital ad campaigns. Why? Because majority of customers don’t believe in ‘push’ advertisements. They will only click on trusted links they are searching for and not the barrage of advertisement popping up on their screens. This approach is called pull marketing.

We believe there is a compelling opportunity for a business to transform and enhance their web presence (pull marketing) by ranking higher on the World Wide Web without any paid ads by optimizing their website, leveraging the latest technologies and implementing SEO and content marketing. In doing so, a business can lower their sales and marketing costs while in tandem increase their prospecting and sales. Notably, we like to point out that it takes time so see results. If making tweaks constitute to web growth, then every business under the sun would do it.

Rightfully so, the big tech search corps have gotten smarter with their search algorithms and only recommend business who meet their and the customers criteria’s. They do this by giving a business a authoritative token. The higher the token, the more likely they will recommend a business. And this takes time for a company to rank higher.

This is why it is important for business to track and monitor their digital data and make the necessary changes based on web and revenue growth. It’s also important for a business to understand this is continuous improvement and not a one step process.

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What is Prescriptive Marketing?

What is Prescriptive Marketing?

Before we touch base on the meaning of prescriptive marketing, it’s paramount to first understand the different maturity stratum of marketing analytics. They are;

Descriptive Marketing –  In our point of view, this is the first level of marketing. It’s called the Data Collection phase. It has to do with Big Data. This is where data is collected and data mined from heterogeneous data ecosystems to gain insights into a customer, competitor or market. Organizations today have to pay close attention to this level of analytics because it ‘s the precursor to moving to next level. Emphasis should on validating and maturing your program logic to obtain a 360-degree view of your customer, competitor, market, and business data. The risk of not having good data will promote outliers and skewed data resulting inaccurate analysis.

Predictive Marketing – In this phase, the insightful information collected gets fed into built-in statistical techniques and algorithms to predict probable future outcomes of a customer based on their personas. Understanding data relationships aids in being able to segment a customer based on certain characteristics relationships. The data maturity roadmap should always be to move to a state to have deep personalized customer understanding. Sentiment analysis is a common type of predictive analytics. That is the input to a model in plain information whereas the output to the model is a weighted score that is positive or negative or a numeral variance between +1 or -1. In this case, the model computes and is predicting the data that we don’t have which is a sentiment label.

Prescriptive Marketing – This is the last stage of the maturity model of marketing analytics. In a nutshell, prescriptive marketing is a new way of thinking about customer-concentric relations utilizing the technologies of big data and machine learning which when coalesced is called Prescriptive Marketing. Applying Prescriptive analytics is going to big game changer to organizations today because it positively impacts customer experience at every customer value-life-cycle touch points; directly boosting customers loyalties and revenues.
We believe that Prescriptive Marketing is at its infancy stage and there is allot of untapped potential to discovering and learning more about building a personalized relationship with one’s customers.

 

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Difference Between Business Analytics, Predictive Analytics and Prescriptive Analytics

There has been a great deal of buzz about analytics today. Names such as descriptive analytics, predictive analytics, and prescriptive analytics are used interchangeably causing confusion among people. So let’s break it down to it’s simplest form to better understand the difference.
There are three stratum of analytics.

1. Business Analytics – This is the first state of analytics, and it has to BIG DATA. This is where data is collected and data mined from heterogeneous data ecosystems to gain insights into a business. In this level, it only informs you what is going on with your business or system. For example, Google analytics informs the business user the number of new viewers coming to your site, but it does not tell what to do with the information. It does not tell you how to increase the number of new qualified users to your site. It’s only descriptive. Over 80% of today’s companies are descriptive. However, organizations today have to pay close attention to this level of analytics because it ‘s the precursor to moving to next level. Emphasis should on validating and maturing your program logic to obtain a 360-degree view of data of customer data. The risk of not having good data will promote outliers and skewed data resulting inaccurate analysis.

2. Predictive Analytics – In this phase, the insightful information collected gets fed into built-in statistical and algorithm models to predict probable future outcomes of a customer based on their personas. Understanding data relationships aids in being able to segment a customer based on certain characteristics relationships. The data maturity roadmap should always be to move to a state to have deep, personalized customer understanding. Sentiment analysis is a common type of predictive analytics. That is the input to a model in plain information whereas the output to the model is a weighted score that is positive or negative or a numeral variance between +1 or -1. In this case, the model computes and is predicting the data that we don’t have which is a sentiment label. This type of analytics predicts what is probably going to happen over a period based on historical, present and future relational data analysis. For example, in an e-commerce site, there are certain type of customers who only purchase products if there is a discount. They are called “discount customers”. Thus, in the area of predictive analytics, the system predicts and notifies you the probability of a customer buying based on the classification segmented persona profile.

3. Prescriptive Analytics – This is the last level of analytics, where the system autonomously recommends or prescribes a solution to specific problems increasing business value.

 

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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.

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