Vetting Stocks Using Our Advanced AI Stock Predicting System

A Comprehensive Guide To Vetting Stocks

 

Before we begin:

It is impossible to argue that technology does not play a significant part in determining investment strategies in the modern economy. Our prediction system that is driven by AI is an extremely helpful instrument for doing stock research since it offers insights based on intricate algorithms and extensive datasets. Nevertheless, in order to make use of this technology, one must have a grasp of both its potential and its restrictions. The purpose of this post is to give a comprehensive guidance on how to correctly evaluate each stock by making use of our AI stock forecasting technology.

The Importance of Having High-Quality Data When Getting Started

The first processing of data

Make sure the data that is being fed into the AI system is of a good quality before you start to rely on AI-based forecasts. Inaccurate estimates might result from data that is either incorrect or incomplete.

 Sources of the Data

Our cutting-edge artificial intelligence stock prediction system compiles information from a wide variety of reliable sources, such as financial statements, real-time market data, and news feeds, in order to present a comprehensive picture of each stock.

Feature Analysis: Locating the Most Important Variables

Metrics that are Quantitative

In order to provide a full quantitative analysis, this model incorporates financial ratios such as price-to-earnings, return on equity, and debt-to-equity.

Interpretation of Feelings

The technology analyzes market sentiment using Natural Language Processing (NLP), taking into account buzz on social media and news items in addition to the opinions of industry professionals.

The Engine Room of Machine Learning is in the Algorithms

Models for Deep Learning Systems

For the purpose of forecasting stock prices using both historical and current data, our platform makes use of sophisticated regression models.

The revolutionary impact of deep learning models on stock market forecasting

In our never-ending quest for accuracy and insight in the world of finance, we have harnessed the power of cutting-edge machine learning and deep learning models to take the art of stock prediction to new and uncharted heights. These sophisticated models are utilized by our AI-driven system, which runs at the cutting edge of technical innovation. This allows our system to decipher the complexity of stock markets.

Bringing Clarity to the Confusion:

The complex network of data, trends, and feeling that characterizes stock markets calls for answers that go beyond the normative. Our deep learning models have been painstakingly developed in order to comprehend and react appropriately to the complex patterns that are inaccessible to conventional approaches. These models understand the subtle movements and underlying dynamics that impact stock prices because they analyze enormous amounts of historical data and integrate information that is current at the same time.

The Harmony of Information:

Deep learning, which is similar to conducting a symphony, brings together disparate data sources to provide predictions that are in harmony. It reveals previously unknown linkages, assesses the influence of broad-scale economic forces, and recognizes dormant patterns that may otherwise evade human notice. Our AI system is then tasked with conducting this data symphony in order to create forecasts that are consistent with analytical rigor.

Bringing the Future into Focus:

Learning from experience and using that knowledge to make predictions about the future is at the heart of what deep learning is all about. Deep learning’s foundational concept, neural networks, are modeled after the neural structure of the human brain in order to comprehend complex relationships. This conglomeration of neurons, which are connected together in complex layers, elucidates the temporal subtleties and non-linear relationships that are at the root of changes in stock prices.

An Adventure Across Neural Networks:

Our artificial intelligence system’s neural networks investigate the complexities of historical stock data, which enables the system to discover patterns, trends, and abnormalities in the data. These networks are always learning, which allows them to modify their connections and improve their ability to predict the future over time. Because of this dynamic adaptation, the system is able to navigate through the turbulence of market dynamics and deliver predictions that are tailored to real-world events. Moreover, this dynamic adaptation enables the system to provide accurate forecasts.

Beyond the Capacity of Human Cognition:

Deep learning models overcome the constraints that are imposed by human cognition and are able to analyze enormous datasets with an unprecedented level of speed and precision. These models adapt to new data as it becomes available, which deepens their understanding and improves their ability to make accurate predictions. They explore the world of big data, investigate the multidimensional landscape of market factors, and then translate the findings of this investigation into ideas that can be put into practice.

Leading the Way Towards the Future of Investment:

We are blazing a trail for a brand-new era in investment strategy by being the first to include deep learning models into our prediction framework. The deep learning components of our AI system are responsible for weaving together the complex tapestry that is comprised of historical background, market patterns, and sentiment analysis. This apex of data-driven innovation is set to revolutionize the way investors think about, approach, and participate in the ever-changing world of finance.

Even as we continue to develop and improve the AI-driven system we use, our deep learning models will continue to serve as the driving force behind our dedication to innovation. Every time we make a forecast, we renew our commitment to revolutionizing market insights by forging one neurological connection at a time.

The Risk Assessment Process: An Essential Element

Indexation of Volatility

The artificial intelligence system performs a calculation to determine the possible volatility by making use of statistical metrics such as standard deviation and Beta. This provides an indication of the risk that is involved.

Comparisons of Risk and Reward

In addition to projecting future stock movements, the system also offers an analysis of the risk-to-reward ratio associated with each stock, which is intended to facilitate decision-making.

Compliance with Ethical Standards and Regulations

Openness and honesty

In spite of the fact that machine learning models are sometimes referred to as “black boxes,” our method offers feature significance rankings in order to make its predictions more understandable.

Controls of Compliance

The artificial intelligence system complies with the regulatory standards, which helps to ensure that stock forecasts do not come under the heading of insider trading or market manipulation.

Limitations: Things You Should Keep an Eye Out For

Anomalies in the Market

Artificial intelligence, despite its capability, is not infallible. It is possible that it will be unable to effectively foresee dramatic market occurrences such as crashes or booms.

 The Bias of Algorithm

Because inherent biases in the training data might cause forecasts to be inaccurate, it is vital to take into account human oversight when making the ultimate investment choice.

The final word

Our artificial intelligence-based stock prediction system provides a comprehensive platform for the evaluation of each stock. It does this by offering insights that are derived from in-depth data analysis and cutting-edge machine learning algorithms. Despite the fact that the system is a powerful instrument for making educated investments, it is essential to be aware of its limits and to include it into a more comprehensive investment plan.

Investors may considerably enhance their chances of making good judgments about the stock market by improving their grasp of how to successfully employ the features of the system and sticking to a balanced strategy that combines the forecasts of artificial intelligence with human monitoring.

Acumentica has built its pursuit of Artificial General Intelligence (AGI) in finance on the back of years of intensive study into the field of AI investing. Even if AGI Investing is still a long way off, what we’ve accomplished so far is very remarkable. We show our unique ecosystem of sophisticated deep-learning models tuned for outstanding forecasting accuracy, the sophisticated AI Stock Predicting System. You may optimize your investing plans with the help of this cutting-edge system’s unrivaled market visibility and in-depth analytic capabilities as it thoroughly analyzes each stock.

Elevate your investment by registering. To delve deeper into how our technology can revolutionize your financial strategy, contact us. Experience the future of confidence investing today.

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Unveiling the Power of Advanced AI Solutions

By Team Acumentica

Introduction:

Artificial Intelligence (AI) has revolutionized the way businesses make decisions and optimize their processes. In recent years, two prominent branches of AI have emerged: predictive AI and prescriptive AI. While both have their merits, this article aims to shed light on why advanced AI, with its prescriptive capabilities, can be a game-changer compared to generative AI.

  1. Understanding Predictive AI:

Predictive AI, also known as generative AI, focuses on forecasting future outcomes based on historical data and patterns. It excels at making predictions, such as stock prices, customer behavior, or equipment failures, by analyzing vast datasets and identifying trends. Predictive AI provides valuable insights into what might happen, helping organizations make informed decisions.

  1. The Limitations of Predictive AI:

Despite its benefits, predictive AI has limitations. It stops at providing predictions and doesn’t offer guidance on what actions to take next. For instance, if a predictive AI model forecasts a potential drop in product demand, it won’t suggest strategies for mitigating the impact. This limitation leaves businesses with the responsibility of interpreting predictions and devising their own solutions.

II. The Rise of Prescriptive AI:

Prescriptive AI goes a step further. It not only predicts outcomes but also prescribes actionable solutions to achieve desired results. By factoring in various constraints, objectives, and real-time data, prescriptive AI recommends optimal courses of action. This can range from supply chain optimization and resource allocation to healthcare treatment plans and financial investment strategies.

  1. Real-World Applications of Prescriptive AI:

Prescriptive AI finds applications in numerous industries. In healthcare, it assists doctors in tailoring treatment plans for patients based on their unique medical histories and current conditions. In logistics, it optimizes routes for delivery trucks, reducing fuel costs and delivery times. In finance, it suggests investment portfolios that maximize returns while managing risk.

  1. The Power of Informed Decision-Making:

One of the key advantages of prescriptive AI is its ability to empower users with actionable insights. Instead of leaving decision-makers to navigate a sea of data, prescriptive AI guides them towards optimal choices. This not only saves time but also enhances the quality of decisions.

  1. Combining Predictive and Prescriptive AI:

While prescriptive AI offers a holistic approach to decision-making, it doesn’t render predictive AI obsolete. In fact, the synergy between the two can be formidable. Predictive AI can feed data into prescriptive models, helping them make more accurate recommendations. The combination of prediction and prescription creates a powerful tool for businesses.

VII. Conclusion:

In the realm of AI, predictive AI has paved the way for data-driven insights, but it has its limitations. Advanced AI, with its prescriptive capabilities, takes decision-making to the next level by not only predicting outcomes but also offering actionable solutions. Businesses that embrace prescriptive AI gain a competitive edge, making informed decisions that drive success in an increasingly complex world. As technology continues to advance, the adoption of prescriptive AI is poised to become a transformative force across industries.

Acumentica AI Growth Solutions and Services

At Acumentica our AI Growth systems are built around  increase sales, ROI while lowering costs.

  • Collect: Simplifying data collection and accessibility.
  • Organize: Creating a business-ready analytics foundation.
  • Analyze: Building scalable and trustworthy AI-driven systems.
  • Infuse: Integrating and optimizing systems across an entire business framework.
  • Modernize: Bringing your AI applications and systems to the cloud.

Acumentica provides enterprises AI solutions they need to transform their business systems while significantly lowering costs.

For more information on how Acumentica can help you complete your AI journey, Contact Us or  explore Acumentica AI Growth Systems.

 

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Grow Your Online Presence Through Map Optimization

Map optimization is an integral stratum of digital marketing that businesses often overlook. It correlates to the process of improving a business’s visibility on maps and navigation systems, such as Google Maps and Waze to name a few. This is imperative because, in today’s digital age, more and more consumers are using online maps to find businesses and services in their local area. As such, having a strong online presence on maps is crucial for any business looking to attract new customers and increase its visibility. This article annotates the need, value, and benefits of map optimization.

Why Map Optimization?

To commence with, map optimization can help businesses increase their visibility on online maps and navigation systems. By creating and optimizing a Google My Business listing, businesses can make sure that their information is accurate, up-to-date, and easily accessible to potential customers. This includes important details such as business hours, contact information, and customer reviews. By having this information readily available, businesses can make it easier for customers to find them and increase their chances of being selected over their competitors.

In perpetuity, map optimization can also enhance the customer experience by making it easier for them to find businesses and services in their local area. This is a very important strategy that the big search techs are pushing towards as they want to recommend local business first. In addition, they want their flagship maps system to be in the forefront of peoples search. Its used now more than ever before.

This is because online maps and navigation systems allow customers to search for businesses based on location, category, or keyword, making it easier for them to find what they are looking for. Furthermore, by providing customers with more accurate up-to-date information about a business, map optimization can improve customer engagement and increase the chances of customers choosing that business over others. This results in increase sales and a ROI. It is important to note that there are best practices for optimizing your Google My Business listing for search. This includes providing complete and accurate information, using keywords in your listing, and encouraging customers to leave reviews. By following these best practices, businesses can improve their search visibility and increase their chances of being found by potential customers.

There are a plethora of real-world examples of businesses that have immense success contributing to increase foot traffic and sales with smart map optimization. For example, local restaurants and cafes can enhance their online search visibility by creating a Google My Business listing and optimizing it for search. They can also use their listing to provide customers with up-to-date information about menu items, business hours, and special promotions. Similarly, construction and manufacturing companies are using smart map optimization to increase their visibility in local search results, making it easier for potential customers to find them.

In conclusion, businesses should prioritize smart map optimization as it is a cost-effective and efficient way to increase visibility, improve customer experience, and boost local search visibility. By optimizing their presence on online maps and navigation systems, businesses can increase their chances of being found by potential customers and stand out from their competitors.  We recommend all businesses to first understand where they are on the search engines richter scale. This enables a business to understand their current state before making changes and monitoring them.

Contact us to learn more about how our transformative digital marketing services we can help you optimize your map listings and improve your digital marketing efforts.

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Transform Your Website Into A Sales Generating System

Your website should viewed as one be one of your distinct sales tools or system within your company.  This is where every explorer, lead and customer visits to learn about your business and its offerings. It’s indicative of your brand. It’s a place they go to make informed purchasing decisions. Rightfully so, it’s an area that requires focused attention that doesn’t get equal weight compared to other sales driven tools.

Your website requires to be built the right way and we often see businesses fall short of this. Your website should NOT only be a great looking and aesthetically pleasing site- though this is very important. It’s about it being one of your sales generating tools to attract the right foot traffic, and convert those leads into customers to grow sales.

If you are not looking at your website as a sales generating system and if it’s not making your business money, then you are missing on potential opportunities that drives sales growth.

So, what must a business do to achieve this.  We have recommended a framework of actionable steps, that if executed in a systematic function, will help transform your website into a sales generating system.

  1. Website Assessment

If you have a website already, conduct an website assessment to first understand your current state and where you are on a web rating scale. Understand the health of your website in real-time and fix the website issues based on the recommendations provided. It’s pointless to make changes when you don’t understand the issues first.

  1. Develop Website Strategic Roadmap

Once you have to have gotten the above results, develop a strategic Website roadmap on what you are going to enhance on your website that increases value. All changes made should be measured and tracked at all times.

  1. Company Positioning

We are assuming your company’s ‘Positioning’ is good which is indicative of your positive marketing and sales results. If this is not the case, then focus must be given to reassessing your position. Once this is done, you can embed the right curated content in your website.

Since your website is your sales tool, your users must understand what you do and why you are different. They must understand the qualitative and quantitative value you bring.  If this is clear, this will translate into more sales. Your site should contain content that depicts your company’s unique attributes and capabilities compared to your competitors.

  1. Advanced UX Design

Equal importance must be given to the design of your website. It’s look and feel, and user responsiveness is very important. Make sure that your website is simple but appealing at the same time. Get input from family, friends, employee and peers. Remember it’s not what you think of your website but what what others think of it. This will be your litmus test.

  1. Optimal SEO

Search Engine Optimization is one of pertinent disciplines to increase website traffic. Make sure you have optimal dynamic search keywords (which is changing) to increase your page rank organically without paid ads. This will then result in increasing conversion rates and sales.

  1. Enriched Marketing Content

The other important aspect of increasing your online visibility is making sure you have the right marketing content that pulls the right searchers who want to purchase your products and services.

  1. Web Data Analysis

In all that you do always collect, process, and analyze your web data to get actionable insights and make smart data-driven decisions.

  1. Website Analytics

Keep track of website traffic and convert those leads into customers. Track and Monitor changes for continuous improvement.

In summary, it’s important to point out that this is not a one-time process. It takes time for your site to be recognized and recommended by the big tech search companies. However, it’s very important to develop and deploy a website the right way. This is a continuous  improvement and equal oversight must be given to your web presence like others operational functions in a business. Be different from your competitors, look at your website as your sales generating system, make the right investments, and measure your Return Of Investment (ROI).

Acumentica is here to help if you need to transform your website.  Contact Us or Learn more about how our AI Digital Growth System that can increase your business online visibility.

 

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What Is Artificial Intelligence?

Read more
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Increase Revenue By Leveraging AI Technologies: Part 1

You are a small brick and motor business. You are good at what you do. You know how to build things but trying to figure out ways to increase revenue on a shoe-string budget. Have you considered using AI tools to address your challenges? For many, it might seem that a company needed to a behemoth like Amazon or Google to leverage and harness the power of AI. In the past, that might have been true as deployment of such tools were costly to implement. However, with the advancements of technology today, AI can be used by all types of businesses no matter their size,  solve specific industry and functional discipline problems and what’s important, it is affordable. In this article, we will help you understand how using AI technologies can impact your sales numbers yielding higher revenue and profit margins.

Before diving into addressing how AI technologies can increase revenue, it’s important to define first what Revenue and AI is and how it applies to the health of a business. This will bring clarity within the context of this article.

In simple terms, revenue optimization is not only about improving earnings from your sales but the sum of your income. It’s taking actionable steps to increase your profits margins and the Return Of Investments (ROI). Artificial intelligence (AI) also called Machine Intelligence (MI) leverages computers and machines that aims to emulate the modality, problem-solving and decisions making capabilities like that of a human.

Now that we defined the two, we like to set the preface and breakdown how a business can deploy AI technologies to increase their revenue. This can we done through the use of AI in;

  1. Sales
  2. Marketing
  3. Digital Marketing

This article explains harnessing AI within the functional discipline of Sales.

AI Sales

Find Customers 

By using AI sales tools or agents, a business can find customers who are seeking to buy their products and services specific to their industry. In addition, it enables a business to gain in depth knowledge about each customer, their background, personas, and characteristics.

We are not talking about leads or Marketing Qualified Leads (MQL) though this inherently are one of attributes of what AI can also do as well.

360 Degree Customer View

A business may have information about their customers in their CRM or ERP systems. However, this information is static and can be myopic. Customers are not static but dynamic and a business needs to have real-time up to date information of their customers and user journey to make insightful data-driven decisions. Having a 360 view of your customers is imperative and a AI system can make this possible.

Predictive Customer Profitability

Based on a business transaction records, an AI system using RFM (Recency, Frequency and Monetary Value) score-based times series and other neural network based models can measure and predict a customer profitability. By doing so a business can segment and create target cohort email marketing campaigns with each customer based on the models inferences.

Predicting Customer Propensity

Customer propensity is understanding the behavior of a customer. It’s a model approach to predict the likelihood of explorers, visitors, leads, and customers are going to purchase a product or service. By doing so a business can only get customer acuity can but increase their Conversion Rate Optimization (CRO).

Prospecting Intelligence

Buy harnessing the power of AI, a B2B and B2C entity can find customers anywhere on the www with a high degree of efficacy. Imagine a system running 24/7 prospecting the web finding customers. That’s the power of AI which aids in maximizing sales and acquire your Total Addressable Market (TAM).

Recommendation Engine

After all the customer data is collected processed and analyzed, it can be arduous to then make the right decision that will yield an optimal result. An AI- powered self -learning engine does not only predicts but prescribes what you must do and focus on. It’s constantly learning and computing millions of data points in order to provide the best recommendation. This decision support system takes the guess out of the equation. It helps a business make smart sales driven decisions.

Increase sales productivity and efficiency

With the above features, attributes and capabilities of a AI sales system, a business will see their an increase in efficiency and productivity while lowering SG&A costs. This accounts for more savings amounting to higher profit margins.

In summary an AI sales  system or Customer Growth System can;

  • Significantly increase sales
  • Prioritize customer focus
  •  Understand and Influence customer behavior
  •  Gain 360-degree Customer intelligence
  •  Increase sales productivity and reduce Costs
  •  Increase ROI

Our goal help you understand how AI can help a business in many business facets. We encourage you to explore our site to learn more.

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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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