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Many people have a misconception about networking events, and lose out on new business opportunities as a result. They either don't appreciate the real benefits and techniques of networking and don't attend events, or they attempt to 'sell on the first date', causing resentment. You can either attempt to make a sale for a quick buck (which is particularly likely to backfire at a networking event), or you can try to open a long-term relationship, creating new opportunities and a high lifetime value customer (which is how it's meant to be done). Networking, when done properly, is an excellent tool for referrals. But you have to appreciate that it's done on the basis of giving rather than receiving and this doesn't always come naturally to sales professionals. The old saying that it's about getting to 'know, like and trust' is still true. This workshop is about having your prospects and customers getting to know, like and trust you, and building that lifetime value as a result. By the end of this programme, participants will be able to: Understand what networking is - networking etiquette Know how and where to network Clarify their objectives - why network Use the 4 basic questions to start a conversation Build rapport quickly and easily Answer the question 'What do you do?' effectively in a few seconds Deliver a 60-second pitch Break into a group Prepare for a network meeting Identify opportunities Use tools to assist in networking 1 Introduction Aims and objectives 2 What is networking? Why network - objectives and goal setting Networking etiquette Preparation - online and offline tools to use Identify networking opportunities - where to network Know what you have to offer 'Know, like and trust' - the process 3 What do you do? Answer in 5-10 seconds Create and deliver a 60-second pitch Who is your target market? 4 Starting a conversation Breaking into a group Building rapport The 4 questions to start a conversation Moving on 5 Communicate and engage LISTEN - 4 types of listening skill Ask powerful questions Influence - don't sell What can you do to help others - give to get 6 Power of referrals Who can give you referrals? When to give or ask for referrals Have a referral system Showing appreciation 7 Social media and other online tools Using LinkedIn and other social media Online directories 8 Next steps Following up Arranging one-to-one meetings Developing relationships

Duration 2 Days 12 CPD hours This course is intended for IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS StatisticsBase. Anyone who wants to refresh their knowledge and statistical experience. Overview Introduction to statistical analysis Describing individual variables Testing hypotheses Testing hypotheses on individual variables Testing on the relationship between categorical variables Testing on the difference between two group means Testing on differences between more than two group means Testing on the relationship between scale variables Predicting a scale variable: Regression Introduction to Bayesian statistics Overview of multivariate procedures This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results. Introduction to statistical analysis Identify the steps in the research process Identify measurement levels Describing individual variables Chart individual variables Summarize individual variables Identify the normal distributionIdentify standardized scores Testing hypotheses Principles of statistical testing One-sided versus two-sided testingType I, type II errors and power Testing hypotheses on individual variables Identify population parameters and sample statistics Examine the distribution of the sample mean Test a hypothesis on the population mean Construct confidence intervals Tests on a single variable Testing on the relationship between categorical variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Identify differences between the groups Measure the strength of the association Testing on the difference between two group meansChart the relationship Describe the relationship Test the hypothesis of two equal group means Assumptions Testing on differences between more than two group means Chart the relationship Describe the relationship Test the hypothesis of all group means being equal Assumptions Identify differences between the group means Testing on the relationship between scale variables Chart the relationship Describe the relationship Test the hypothesis of independence Assumptions Treatment of missing values Predicting a scale variable: Regression Explain linear regression Identify unstandardized and standardized coefficients Assess the fit Examine residuals Include 0-1 independent variables Include categorical independent variables Introduction to Bayesian statistics Bayesian statistics and classical test theory The Bayesian approach Evaluate a null hypothesis Overview of Bayesian procedures in IBM SPSS Statistics Overview of multivariate procedures Overview of supervised models Overview of models to create natural groupings

Duration 2 Days 12 CPD hours This course is intended for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful. Overview By the end of this course, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from data. This course is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The course will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You?ll discover how to tune the algorithms to provide the best predictions on new and unseen data. As you delve into later sections, you?ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. Data Exploration and Cleaning Python and the Anaconda Package Management System Different Types of Data Science Problems Loading the Case Study Data with Jupyter and pandas Data Quality Assurance and Exploration Exploring the Financial History Features in the Dataset Activity 1: Exploring Remaining Financial Features in the Dataset Introduction to Scikit-Learn and Model Evaluation Introduction Model Performance Metrics for Binary Classification Activity 2: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve Details of Logistic Regression and Feature Exploration Introduction Examining the Relationships between Features and the Response Univariate Feature Selection: What It Does and Doesn't Do Building Cloud-Native Applications Activity 3: Fitting a Logistic Regression Model and Directly Using the Coefficients The Bias-Variance Trade-off Introduction Estimating the Coefficients and Intercepts of Logistic Regression Cross Validation: Choosing the Regularization Parameter and Other Hyperparameters Activity 4: Cross-Validation and Feature Engineering with the Case Study Data Decision Trees and Random Forests Introduction Decision trees Random Forests: Ensembles of Decision Trees Activity 5: Cross-Validation Grid Search with Random Forest Imputation of Missing Data, Financial Analysis, and Delivery to Client Introduction Review of Modeling Results Dealing with Missing Data: Imputation Strategies Activity 6: Deriving Financial Insights Final Thoughts on Delivering the Predictive Model to the Client

Learn how to use this powerful tool to import and clean data and create some amazing visuals. Course overview Duration: 2 days (13 hours) Power BI Desktop is a powerful tool for working with your data. It enables you to import multiple data sources and create effective visualisations and reports. This course is an introduction to Power BI to get you started on creating a powerful reporting capability. You should have a good working knowledge of Excel and managing data before attending. Objectives  By the end of the course you will be able to: Import data from multiple data sources Edit and transform data before importing Create reports Create different visualisations Create data models Build data relationships Use the drill down features Create measures Use the Power BI Service Build dashboards Use the mobile app Content Essentials Importing Data Power BI Overview Data sources Importing data Transforming Your Data Editing your data Setting data types Removing columns/rows Choosing columns to keep Setting header rows Splitting columns Creating Reports Creating and saving reports Adding pages Renaming pages Interactivity Refreshing your data Adding Columns Columns from example Custom columns Conditional columns Append Queries Importing folders Setting up and using append queries Creating Chart Visualisations Adding chart elements Choosing chart types Setting properties Setting values, axis and legends Using tooltips Visual filters Setting page and report filters Creating Tables, Cards, Gauges and Maps Adding table elements Adding maps Working with cards Working with matrices KPIs and Gauges Conditional Formatting Setting rules Removing conditional formatting   Working with Data Models Merge Queries Setting up and using merge queries Merging in columns of data Creating a Data Model The data model Multiple data tables Connecting tables Building relationships Relationship types Building visuals from multiple tables Unpivoting Data Working with summary data Unpivoting data Using Hierarchies Using built in hierarchies Drill down Drill up See next level Expand a hierarchy Create a new hierarchy Grouping Grouping text fields Grouping date and number fields Creating Measures DAX functions DAX syntax Creating a new measure Using quick measures Using the PowerBI Service Shared workspaces My workspace Dashboards Reports Datasets Drill down in dashboards Focus mode Using Q&A Refreshing data Using Quick Insights Power BI Mobile App Using the Power BI Mobile App

Take your sales people from average to high performance. Motivate and develop experienced sales professionals with some new insights and learning. Applying NLP principles, techniques and models, this workshop will introduce the core attitudes and behaviours that differentiate the excellent sales person from the average one. The programme will help participants: Understand and adopt the mindset and beliefs needed for sales excellence Build rapport and connect with buyers at a deeper and more personal level Recognise some of the thinking and language patterns that make each individual unique Ask powerful questions to further understand the unique world of the individual and how they make decisions Apply tools and techniques to empathise with clients - seeing things from their perspectives Tailor their sales approach to the individual buyer's style, and talk in their language Influence with integrity and sell to organisations and individuals successfully 1 Introduction Aims and objectives of the programme Personal introductions and objectives Workshop overview 2 An introduction to NLP and sales excellence with NLP An overview of NLP and applying it to selling The pillars of NLP The NLP model of communication The difference that makes the difference 3 Building enhanced rapport Defining rapport and why it is important when selling Going beyond the initial small talk Building relationships with individual decision-makers Matching and mirroring Levels of rapport 4 Understanding the buyer's personal buying map How we take in, filter and process information How we judge others based on our own experiences of the world The different ways in which we communicate when selling Recognising and understanding the language and thinking patterns of others Adapting your sales communication style to different buyers 5 Making sense of the buying process How we filter information through our senses Understanding how we see, hear and experience the world Visual, auditory and kinaesthetic buyers Listening for key insights What different buyers want from you to help them to buy Applying sensory awareness to the sales process 6 Successful sales mindset The connection between thoughts and actions The sales beliefs of excellence Identifying negative thoughts and beliefs that are holding you back How to change your mindset Adopting the sales beliefs of excellence 7 Powerful questions Reviewing and honing your questioning skills Understanding the questions that great sales people ask Avoiding assumptions Clean language questions Getting to the bottom of it - precision questions Turbo-charging how you qualify 8 Influencing with integrity Understanding empathy Stepping into the buyer's shoes Speaking the buyer's language Tailoring your sales approach to the individual Match, pace, lead - how to take your buyer with you 9 Putting it all together Personal learning summary and action plans

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Increasing sales is the core of objective for all salespeople and it is vital they are given the tools and techniques to thrive in this highly competitive environment. The landscape within which salespeople operate is ever shifting, and now more than ever it is recognised that the key to successful selling is understanding the customer's needs and working collaboratively with them to achieve their objectives. This highly practical programme has been developed to support salespeople to develop their all-round sales skills using a customer-focused approach. The course will be fun and informal, using practical exercises to help new and experienced salespeople ensure they are equipped to deal with the challenges of selling. This course will help participants: Develop core sales skills such as building rapport, questioning and presenting benefits Identify the roles and goals of key contacts and recognize the importance of consultative selling Understand how to achieve sales by uncovering needs, matching benefits and promoting value Understand how to structure and control a customer interaction and set clear objectives for each account Develop techniques for handling objections, questions and staying positive Master the art of closing a sale and gaining agreement Understand tactical selling and how to build multiple contacts and relationships Develop skill and confidence in selling to both new prospects and existing customers 1 Consultative selling - key principles for success Recognise the importance of consultative selling and being client-focused Build the right processes to achieving sales targets - questions before features Assess your core sales skills; building rapport, asking questions, presenting features and benefits, closing 2 Consultative sales call skills How best to structure and control a customer meeting or call to be client-centric: Four Cs The importance of setting clear objectives for each call and account Setting the agenda and pre-call preparation Planning sessions 3 Your mission, message and meaning - comparative advantage Defining sales messages and USPs; positioning value and quality not price Knowing your target product and services and their value to the customer Understanding your customers buying role and qualifying the opportunity 4 An effective sales meeting - part 1 Opening the sales interview - and building rapport Gaining and retaining the full attention of the customer Probing and identifying real needs using effective sales questions Planning and practice sessions for consultative selling 5 An effective sales meeting - part 2 Matching customer needs and wants to products and services available Presenting your product or service using features, advantages, and benefits Recognising and responding to buying signals and other sales opportunities Planning and practice sessions 6 Closing the sale successfully Anticipating objections and seeing them as positives, including price objections Handling objections using proven methods and models How and when to ask for the sale professionally Follow up and follow-through Planning and practice sessions