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What are the most effective BI data techniques for identifying new market opportunities?

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Business intelligence (BI) is the process of collecting, analyzing, and presenting data to support decision-making and strategic planning. One of the main goals of BI is to identify new market opportunities that can help a business grow and gain a competitive edge. But how can you use BI data techniques effectively to find and explore these opportunities? Here are some of the most effective BI data techniques for identifying new market opportunities.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought…
Jose Antonio Lanzguerrero Obeid

Scaling Businesses | Chatbots | AI and Machine Learning | Conversational Commerce | Product and Company Builder | Music…
Jaina Gandhi

Data Science | Data Analytics | Business Intelligence | Media Analytics | Salesforce Datorama | Tableau | Snowflake |…

1 Data mining

Data mining is the technique of extracting patterns, trends, and insights from large and complex data sets. Data mining can help you discover hidden relationships, segments, and preferences among your customers, products, and markets. For example, you can use data mining to find out which customer groups are most likely to buy a certain product, or which markets have the highest demand for a specific service. Data mining can also help you identify gaps and niches in the market that you can fill with your offerings.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought Leader | Views are my own
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When you use AI for data mining, it becomes a breeze to spot patterns in data that we humans may miss. It becomes easier to spot what our customers need and tailor our product recommendations accordingly, thus driving customer loyalty and sales revenue. For example, you can use clustering techniques to group customers, classification techniques to classify customer feedback as positive, negative, or neutral. And regression can be used to predict sales.

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Alexander Radomski

?Der Mensch ist nicht das, was er denkt, sondern das, was er tut, um die Welt besser zu machen.“ – Albert Schweitzer
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Absolut richtig! Data Mining ist eine ?u?erst wertvolle Technik, um wertvolle Einblicke aus gro?en Datenmengen zu gewinnen. Durch das Entdecken von Mustern und Trends k?nnen Unternehmen fundierte Entscheidungen treffen und ihre Produkte und Dienstleistungen gezielt verbessern oder neue Marktchancen identifizieren. Es ist eine essenzielle Praxis in der heutigen datengetriebenen Wirtschaft.

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2 Data visualization

Data visualization is the technique of presenting data in graphical or interactive formats, such as charts, maps, dashboards, and infographics. Data visualization can help you communicate and explore your data more effectively, as well as highlight key findings and insights. For example, you can use data visualization to compare and contrast different markets, regions, and segments, or to show how your performance and market share vary over time and across locations. Data visualization can also help you generate and test hypotheses, as well as inspire new ideas and questions.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought Leader | Views are my own
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Data visualization is the secret sauce behind the chaos of numbers. it helps to uncover the story behind the data so that we can take smarter, faster business decisions.

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Alexander Radomski

?Der Mensch ist nicht das, was er denkt, sondern das, was er tut, um die Welt besser zu machen.“ – Albert Schweitzer
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Mit z.B. Power BI eine führende Plattform für Datenvisualisierung und Business Intelligence. Mit seinen leistungsstarken Funktionen k?nnen Daten aus verschiedenen Quellen importiert, transformiert und analysiert werden, um aussagekr?ftige Visualisierungen wie interaktive Dashboards und Berichte zu erstellen. Durch die Integration von Power BI k?nnen Daten noch effektiver kommunizieren und untersucht werden, um wichtige Erkenntnisse zu gewinnen und fundierte Entscheidungen zu treffen.

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3 Data storytelling

Data storytelling is the technique of creating and delivering engaging and persuasive narratives based on data. Data storytelling can help you convey the value and impact of your data insights, as well as influence and inspire your audience to take action. For example, you can use data storytelling to showcase how your products or services can solve a problem or meet a need in a new market, or to demonstrate how your business can benefit from entering or expanding in a new market. Data storytelling can also help you build trust and credibility, as well as connect emotionally with your audience.

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Jose Antonio Lanzguerrero Obeid

Scaling Businesses | Chatbots | AI and Machine Learning | Conversational Commerce | Product and Company Builder | Music Curator and Producer
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Understanding how data impacts businesses helps us tell stories with it. It is much more impactful to tell the story of a customer who becomes our fan and returns 3x more times (with the added revenue) than to speak of a loyalty program in technical terms.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought Leader | Views are my own
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The art of storytelling is a great skill to have. As humans, we are moved less by the "what" behind the data, but influenced by the "so what" behind the data. For example its one thing to say, there is a gap in the market that we serve, but if we can also say how that gap is leaving our customers frustrated, then its so much more powerful and will force our stakeholders to act.

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Alexander Radomski

?Der Mensch ist nicht das, was er denkt, sondern das, was er tut, um die Welt besser zu machen.“ – Albert Schweitzer
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Absolut! Data Storytelling ist eine ?u?erst wirkungsvolle Methode, um komplexe Daten in überzeugende Geschichten zu verwandeln, die das Publikum ansprechen und inspirieren. Indem Sie Daten in eine fesselnde Erz?hlung integrieren, k?nnen Sie nicht nur den Wert Ihrer Erkenntnisse vermitteln, sondern auch das Verst?ndnis und die Akzeptanz bei Ihrem Publikum erh?hen. Durch die Betonung von Probleml?sungen, Nutzen und Chancen k?nnen Sie Ihr Publikum dazu motivieren, Ma?nahmen zu ergreifen und von Ihren Daten gestützte Entscheidungen zu treffen. Data Storytelling ist daher eine unverzichtbare F?higkeit für jeden, der Daten nutzen m?chte, um wirkungsvoll zu kommunizieren und Einfluss zu nehmen.

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4 Data modeling

Data modeling is the technique of creating and testing logical and mathematical representations of data and their relationships. Data modeling can help you understand and simulate how different variables and scenarios affect your data and outcomes. For example, you can use data modeling to forecast and estimate the potential revenue, costs, and risks of entering a new market, or to optimize and refine your pricing, marketing, and distribution strategies for a new market. Data modeling can also help you validate and improve your data quality and accuracy.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought Leader | Views are my own
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You can think of data modeling as a "sandbox" where we can try scenario analysis such as "what ifs" and "how about" analysis. For example you can ask questions like what happens if we price the product this way and the model will spin out its analysis. In other words, this is not just guessing but rather educated guesses, that gives us the confidence to take action in the midst of uncertainty.

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5 Data integration

Data integration is the technique of combining and transforming data from different sources and formats into a unified and consistent view. Data integration can help you access and analyze more comprehensive and diverse data sets, as well as reduce data silos and inconsistencies. For example, you can use data integration to merge and compare data from internal and external sources, such as your CRM, ERP, social media, web analytics, and market research, to gain a holistic and in-depth understanding of a new market. Data integration can also help you automate and streamline your data processes and workflows.

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Rabi Jay

Author of 'Enterprise AI in the Cloud' (Wiley) and upcoming "Building Gen AI apps" (Apress) | AI Strategist and Thought Leader | Views are my own
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Data integration helps you to combine data from various sources such as sales figures, customer reviews, chats, tweets etc so that you can get a better view of the customers' needs which will help you to make those snappy decisions with confidence.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Jaina Gandhi

Data Science | Data Analytics | Business Intelligence | Media Analytics | Salesforce Datorama | Tableau | Snowflake | SQL | Python/PySpark | Open to Freelance
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Unlock new market opportunities with Business Intelligence (BI) data techniques — Analyze data, segment customers, study competitors, and use predictive analytics. Harness social media, customer feedback, and geospatial analysis for insights. In today's fast-paced business world, BI tools empower companies to stay ahead by identifying untapped potential, understanding customer needs, and staying agile in an ever-changing market. #BusinessIntelligence #MarketOpportunities

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Shawnawaz Vazirkhan

Enterprise Architect/Manager - Data Analytics, Business Intelligence, Reporting & Insights | Dashboards, Visualization, KPI Metrics & Storytelling | IT Strategy, Technology Assessment & Roadmap | Project Mgmt
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Effective analysis of data leads to better informed insights on new markets and business opportunities. Market behaviour, Customer needs, Competitor knowledge, Social media, Internal Financial and Business Capabilities are some of the areas of analysis to help make readinesses.

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What are the most effective BI data techniques for identifying new market opportunities?

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6

1 Data mining

2 Data visualization

3 Data storytelling

4 Data modeling

5 Data integration

6 Here’s what else to consider

Business Intelligence

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What are the most effective BI data techniques for identifying new market opportunities?

1

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6

1 Data mining

2 Data visualization

3 Data storytelling

4 Data modeling

5 Data integration

6 Here’s what else to consider

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