6. Explain is CLV Formula? 101 B. Multiple choice Questions 1. Customer Lifetime Value will lead to ____________ a. Customer Service b. Business Goodwill c. Marketing Analytics d. Brand Equity 2. Customer Lifetime Value is useful for ___________ a. Customer Retention b. Identifying New Products c. Market Analysis d. Profit & growth 3. Customer Lifetime Value is commonly implemented &followed by ________ a. Indian Companies b. SSI c. MNC’s d. Local Retailers 4. ____________ is very required for deciding on Business diversification a. Sales Volume b. Market Report c. Cost sheet d. Analytical Reports 5. The main aim Customer Lifetime Value should be _____________ a. Create goodwill b. After Sales Service c. advertising d. Customer loyalty CU IDOL SELF LEARNING MATERIAL (SLM)
Answers 1-c, 2-a, 3-c, 4-d, 5d. 6.12 REFERENCES Textbooks T1 Grigsby, M. 2115. Marketing Analytics: A practical guide to real marketing science, Its Ed., Kogan Page, India, ISBN: 978-0749474171. T2 Winston, W. 2114.Marketing Analytics: Data Driven Technique using MS. Excel’s Ed. John Wiley & Sons, India, ISBN: 978-1118373439. Reference Books: R1 Grigsby, M. 2116. Advanced Customer Analytics: Targeting, Valuing, Segmenting and Loyalty Techniques (Marketing Science). Ist Ed. Kogan Page. India. ISBN: 978-0749477158. Websites https://springer.com https://michaelpawlicki.com https://statisticshowto.com https://stattrek.com https://slideshare.com 102 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 7: MONTE CARLO SIMULATION MARKETING EXPRIMENTS STRUCTURE 7.0 Learning Objectives 7.1 Introduction of Monte Carlo Simulation 7.2 Important of Monte Carlo Simulation 7.3 Why Monte Carlo Simulation is good 7.4 Calculating Monte Carlo Simulation 7.5 Creating of Marketing Experiments 7.6 Experiments used for Marketing Experiments 7.7 Summary 7.8 Keywords 7.9 Learning Activity 7.10 Unit End Questions 7.11 References 7.0 LEARNING OBJECTIVES Upon successful completion, students will have the updated & knowhow on Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. It is a technique used to understand the impact of risk and uncertainty in prediction and forecasting models. What is Monte Carlo Simulation? Monte Carlo Simulation, also known as the Monte Carlo Method or a multiple probability simulation, is a mathematical technique, which is used to estimate the possible outcomes of an uncertain event. The Monte Carlo Method was invented by John von Neumann and Stanislaw Ulam during World War II to improve decision making under uncertain conditions. It was named after a well-known casino town, called Monaco, since the element of chance is core to the modeling approach, similar to a game of roulette. Since its introduction, Monte Carlo Simulations have assessed the impact of risk in many real-life scenarios, such as in artificial intelligence, stock prices, sales forecasting, project management, and pricing. They also provide a number of advantages over predictive models with fixed inputs, such as the ability to conduct sensitivity analysis or calculate the 103 CU IDOL SELF LEARNING MATERIAL (SLM)
correlation of inputs. Sensitivity analysis allows decision-makers to see the impact of individual inputs on a given outcome and correlation allows them to understand relationships between any input variables. 7.1 INTRODUCTION OF MONTE CARLO SIMULATION In general terms, the Monte Carlo method (or Monte Carlo simulation) can be used to describe any technique that approximates solutions to quantitative problems through statistical sampling. As used here, 'Monte Carlo simulation' is more specifically used to describe a method for propagating (translating) uncertainties in model inputs into uncertainties in model outputs (results). Hence, it is a type of simulation that explicitly and quantitatively represents uncertainties. Monte Carlo simulation relies on the process of explicitly representing uncertainties by specifying inputs as probability distributions. If the inputs describing a system are uncertain, the prediction of future performance is necessarily uncertain. That is, the result of any analysis based on inputs represented by probability distributions is itself a probability distribution. Whereas the result of a single simulation of an uncertain system is a qualified statement (\"if we build the dam, the salmon population could go extinct\"), the result of a probabilistic (Monte Carlo) simulation is a quantified probability (\"if we build the dam, there is a 20% chance that the salmon population will go extinct\"). Such a result (in this case, quantifying the risk of extinction) is typically much more useful to decision-makers who utilize the simulation results. In order to compute the probability distribution of predicted performance, it is necessary to propagate (translate) the input uncertainties into uncertainties in the results. A variety of methods exist for propagating uncertainty. Monte Carlo simulation is perhaps the most common technique for propagating the uncertainty in the various aspects of a system to the predicted performance. 7.2 IMPORTANCE OF MONTE CARLO SIMULATION Monte Carlo simulations are used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables. ... A Monte Carlo simulation can be used to tackle a range of problems in virtually every field such as finance, engineering, supply chain, and science. Monte Carlo simulation is, in essence, the generation of random objects or processes by means of a computer. These objects could arise “naturally” as part of the modelling of a real-life system, such as a complex road network, the transport of neutrons, or the evolution of the stock market. In 104 CU IDOL SELF LEARNING MATERIAL (SLM)
many cases, however, the random objects in Monte Carlo techniques are introduced “artificially” in order to solve purely deterministic problems. In this case the MCM simply involves random sampling from certain probability distributions. In either the natural or artificial setting of Monte Carlo techniques the idea is to repeat the experiment many times (or use a sufficiently long simulation run) to obtain many quantities of interest using the Law of Large Numbers and other methods of statistical inference. Here are some typical uses of the MCM: 1 Sampling. Here the objective is to gather information about a random object by observing many realizations of it. An example is simulation modelling, where a random process mimics the behavior of some real-life system, such as a production line or telecommunications network. Another example is found in Bayesian statistics, where Markov chain Monte Carlo (MCMC) is often used to sample from a posterior distribution. Estimation. In this case the emphasis is on estimating certain numerical quantities related to a simulation model. An example in the natural setting of Monte Carlo techniques is the estimation of the expected throughput in a production line. An example in the artificial context is the evaluation of multi-dimensional integrals via Monte Carlo techniques by writing the integral as the expectation of a random variable. Optimization. The MCM is a powerful tool for the optimization of complicated objective functions. In many applications these functions are deterministic and randomness is introduced artificially in order to more efficiently search the domain of the objective function. Monte Carlo techniques are also used to optimize noisy functions, where the function itself is r 7.3 WHY MONTE CARLO SIMULATION IS GOOD? Why are Monte Carlo techniques so popular today? We identify a number of reasons. Easy and Efficient. Monte Carlo algorithms tend to be simple, flexible, and scalable. When applied to physical systems, Monte Carlo techniques can reduce complex models to a set of basic events and interactions, opening the possibility to encode model behavior through a set of rules which can be efficiently implemented on a computer. This in turn allows much more general models to be implemented and studied on a computer than is possible using analytic methods. These implementations tend to be highly scalable. For example, the complexity of a simulation program for a machine repair facility would typically not depend on the number of machines or repairers involved. Finally, Monte Carlo algorithms are eminently parallelizable, in particular when various parts can be run independently. This allows the parts to be run on different computers and/or processors, therefore significantly reducing the computation time. Randomness as Strength. 105 CU IDOL SELF LEARNING MATERIAL (SLM)
The inherent randomness of the MCM is not only essential for the simulation of real-life random systems; it is also of great benefit for deterministic numerical computation. For example, when employed for randomized optimization, the randomness permits stochastic algorithms to naturally escape local optima — enabling better exploration of the search space — a quality which is not usually shared by their deterministic counterparts. Insight into Randomness. The MCM has great didactic value as a vehicle for exploring and understanding the behaviours of random systems and data. Indeed we feel 2 that an essential ingredient for properly understanding probability and statistics is to actually carry out random experiments on a computer and observe the outcomes of these experiments — that is, to use Monte Carlo simulation [30]. In addition, modern statistics increasingly relies on computational tools such as resampling and MCMC to analyses very large and/or high dimensional data sets. Theoretical Justification. There is a vast (and rapidly growing) body of mathematical and statistical knowledge underpinning Monte Carlo techniques, allowing, for example, precise statements on the accuracy of a given Monte Carlo estimator (for example, square-root convergence) or the efficiency of Monte Carlo algorithms. Much of the current-day research in Monte Carlo techniques is devoted to finding improved sets of rules and/or encodings of events to boost computational efficiency. 7.4 CALCULATING MONTE CARLO SIMULATION Monte Carlo simulations have come a long way since they were initially applied in the 1940s when scientists working on the atomic bomb calculated the probabilities of one fissioning uranium atom causing a fission reaction in another. Today we’re going over how to create a Monte Carlo simulation for a known engineering formula and a DOE equation from Minitab. Since those days when uranium was in short supply and there was little room for experimental trial and error, Monte Carlo simulations have always specialized in computing reliable probabilities from simulated data. Today, simulated data is routinely used in many scenarios, from materials engineering to medical device package sealing to steelmaking. It can be used in many situations where resources are limited or gathering real data would be too expensive or impractical. With Engage or Workspace’s Monte Carlo simulation tool, you have the ability to: Simulate the range of possible outcomes to aid in decision-making. Forecast financial results or estimate project timelines. Understand the variability in a process or system. Find problems within a process or system. Manage risk by understanding cost/benefit relationships. 106 CU IDOL SELF LEARNING MATERIAL (SLM)
The 4 Steps to Get Started For Any Monte Carlo Simulation Depending On The Number Of Factors Involved, Simulations Can Be Very Complex. But At A Basic Level, All Monte Carlo Simulations Have Four Simple Steps: 1. Identify the Transfer Equation To Create A Monte Carlo Simulation, You Need A Quantitative Model Of The Business Activity, Plan, Or Process You Wish To Explore. The Mathematical Expression Of Your Process Is Called The “Transfer Equation.” This May Be A Known Engineering Or Business Formula, Or It May Be Based On A Model Created From A Designed Experiment (Doe) Or Regression Analysis. Software Like Minitab Engage And Minitab Workspace Gives You The Ability To Create Complex Equations, Even Those With Multiple Responses That May Be Dependent On Each Other. 2. Define the Input Parameters For Each Factor In Your Transfer Equation, Determine How Its Data Are Distributed. Some Inputs May Follow The Normal Distribution, While Others Follow A Triangular Or Unifor m Distribution. You Then Need To Determine Distribution Parameters For Each Input. For Instance, You Would Need To Specify The Mean And Standard Deviation For Inputs That Follow A Normal Distribution. If You Are Unsure Of What Distribution Your Data Follow, Engage And Workspace Have A Tool To Help You Decide. 3. Set up Simulation For A Valid Simulation, You Must Create A Very Large, Random Data Set For Each Input —Something On The Order Of 100,000 Instances. These Random Data Points Simulate The Values That Would Be Seen Over A Long Period For Each Input. While It Sounds Like A Lot Of Work, This Is Where Engage And Workspace Shine. Once We Submit The Inputs And The Model, Everything Here Is Taken Care Of. 4. Analyze Process Output With The Simulated Data In Place, You Can Use Your Transfer Equation To Calculate Simulated Outcomes. Running A Large Enough Quantity Of Simulated Input Data Through Your Model Will Give You A Reliable Indication Of What The Process Will Output Over Time, Given The Anticipated Variation In The Inputs. 7.5 CREATING OF MARKETING EXPERIMENTS Marketing experimentation is a research method which can be defined as \"the act of conducting such an investigation or test\" It is testing a market that is segmented to discover new opportunities for organisations. By controlling conditions in an experiment, organisations will record and make decisions based on consumer behaviour. Marketing 107 CU IDOL SELF LEARNING MATERIAL (SLM)
experimentation is commonly used to find the best method for maximizing revenues through the acquisition of new customers. For example; two groups of customers are exposed to different advertising (test). How did consumers react to advertising compared to the other group? (Measurable). Did the advertising increase sales for each group? (Result). There are three characteristics which are the make-up of market experimentation: Experimental subjects - Humans are usually participants in experiments. Subjects are divided into two or more groups and can be referred to as focus groups. Subjects can be made up of a particular age group (demographical), from a particular area (geographical), or culture (ethnographic). Conditions - Known as the independent variable where, conditions are tightly controlled and manipulated by the tester. Effects - Are the results of the test known as the dependent variable? Results are measured and cannot be changed. If the tester wants to see different results they would have to change the conditions of the independent variable to measure the effects. To gain an accurate result from experiments, the experimenter must consider outside factors that could affect the dependent variable. Continuing from the advertising example above; did sales increase because of a festive seasons at that particular time. [5] 7.6 EXPERIMENTS USED FOR MARKETING EXPERIMENTS What's a Marketing Experiment? A marketing experiment is a form of market research. It's a test organizations run to discover possible marketing avenues that will improve a campaign. For instance, a marketing team might create and send emails to a small segment of their overall readership to gauge engagement rates, before adding them into a campaign. Additionally, they might A/B test the design of these emails. In this example, the team is creating a hypothesis (that a certain email design will help promote their campaign) and testing the hypothesis in a marketing experiment. It's important to note that a marketing experiment isn't synonymous with a marketing test. Marketing experiments are done for the purpose of discovery, while a test confirms theories. Ultimately, a marketing experiment can help you ensure your campaign or strategy will be effective. Next, let's dive into how to conduct a marketing experiment. How to Conduct a Marketing Experiment Performing a marketing experiment lets you try out different methods of running a campaign to see which one will perform the best. It involves doing background research, structuring the experiment, and analyzing the results. 108 CU IDOL SELF LEARNING MATERIAL (SLM)
Now, let's go through the five steps necessary to conduct a marketing experiment. 1. Make a hypothesis. Hypotheses aren't just related to science projects. When conducting a marketing experiment, the first step is to make a hypothesis you're curious to test. Let's say you want to make a marketing email that will improve engagement rates. A good hypothesis for this might be, \"Making an email with emojis in both the subject line and copy will increase our engagement rates by at least 25%.\" This is a good hypothesis because you can prove or disprove it, it isn't subjective, and it has a clear measurement of achievement. 2. Collect research. After creating your hypothesis, begin to gather research. Doing this will give you background knowledge about experiments that have already been conducted and get an idea of possible outcomes. Researching your experiment can help you modify your hypothesis if needed. If your hypothesis is, \"Making an email with an emojis in the subject line and copy will increase our engagement rates by at least 25%,\" and research on trends in your audience on email subject lines show that to be true, you know you have a solid hypothesis. However, if other companies in your industry haven't seen success from emojis in emails, you might want to reconsider. 3. Choose measurement metrics. Once you've collected the research, you can choose which avenue you will take and what metrics to measure. For instance, maybe you will run an A/B test. This method will allow you to measure the results of two different emails, and figure out which email performs better with your target audience... For a marketing email test, consider measuring impressions, reach, conversion rate, or click through rate (CTR). These email metrics can let you know how many people are receiving, opening, and reading your emails, and will help you analyze the results of your hypothesis. 4. Create and execute the experiment. Now it's time to create and perform the experiment. If you're creating an A/B test to prove your hypothesis about emojis in emails, then you'll want to create two emails -- one with a plain text subject line, and an identical email with 1-2 emojis added to the subject line. Try to only make slight variations between emails A and B to ensure accuracy. When you're finished designing the experiment, come up with a timeline, and decide how you'll monitor the results. That way, when conducting the A/B test, you'll be prepared to swiftly figure out which email performed better. 109 CU IDOL SELF LEARNING MATERIAL (SLM)
Finally, choose your recipients and conduct the experiment. Next, you'll analyze your results. 5. Analyze the results. Once you've run the experiment, collect and analyze the results. Use the metrics you've decided upon in the second step and conclude if your hypothesis was correct or not. The prime indicators for success will be the metrics you chose to focus on. For instance, for the marketing email example, did engagement numbers appear higher? If the CTR, impressions, and click-to-open rates are at or higher than the 25% goal, the experiment would be considered one where the hypothesis was accepted. Now that you know how to conduct a marketing experiment, let's go over a few different ways to run them. Types of Marketing Experiments There are many types of marketing experiments you can conduct with your team. These tests will help you determine how aspects of your campaign will perform before you roll out the campaign as a whole. 1. A/B Testing 2. Different CTAs 3. Animated Ads 4. Social Media Platforms 5. Experiment Globally 7.7 SUMMARY A Monte Carlo simulation is very useful for business analysis by using Microsoft Excel and a game of dice. The Monte Carlo simulation is a mathematical numerical method that uses random draws to perform calculations and solve complex problems. Today, it is widely accepted and plays a key part in various fields such as finance, physics, chemistry, and economics. 4 examples of marketing experiments Now that you know how to conduct marketing experiments, the next step is to figure out the type of marketing experiment you want to do. Here are four examples of different marketing experiments for your business to try out. 1. Email testing Email testing is a valuable way to help you produce emails that drive better results for your business. Your email subscribers are people who are most interested in your company. It is vital that you deliver content that peaks their interest and gets them to convert. 110 CU IDOL SELF LEARNING MATERIAL (SLM)
There are a few types of marketing experiments you can run with email testing. 1. Test the subject line The subject line has the biggest impact on whether your audience decides to open your email. It’s the first thing they see when your email enters their inbox. If you don’t have an impactful subject line, you’ll miss out on potential conversions. When you conduct marketing experiments, try different subject lines for your email. It is crucial that you only make small, incremental changes to keep your data comparable. For example, you could personalize one version of the email by using the recipient’s name and leaving it out in the original email. 2. Test the content If subscribers are opening your emails but aren’t doing much after that, there may be an issue with the content in your email. This is another marketing experiment you can test to help you produce better content for your emails. You can test the images in the email, the headline, your CTA, or the phrasing. Again, you’ll want to focus on one aspect at a time. Email marketing testing is a great place to start for your marketing experiments. You’ll help your business create emails that are more interesting and engaging for your audience. 3. Pay-per-click (PPC) testing Pay-per-click (PPC) advertisements are another excellent option for marketing experiments. These paid ads drive in valuable traffic for your business. To make the most of your ads, you’ll want to make sure the copy is appealing to your audience. There are numerous aspects of your landing page you can test to produce the best landing page. The most common test is on CTAs. CTAs drive your audience to act on your landing page. In addition, you can test things like your headline, images, videos, font color, size, type, and numerous other aspects. These are all great marketing experiments to conduct to help you create a more impactful landing page. 4. Social media testing Social media sites are another great place to conduct marketing experiments. It’s crucial that you test your social media posts frequently to ensure you are delivering the best content to your audience. 111 CU IDOL SELF LEARNING MATERIAL (SLM)
On social media, visuals are important. It’s often the first thing people see when they see your ad, which can help your business earn new followers and conversions. By conducting a marketing experiment, you’ll have a visual that generates the best results for your ad. Like PPC ads, there are numerous elements of social media ads that you can test. The visual aspect of your ad, such as photos or videos, is the most critical part. In addition, you can test elements like the color of your ad or the typography to see if your audience has a preference on what you use. There are other nuances that marketing experiments will help you figure out, too. First, you’ll learn the right tone for your ad, which can alter the way your audience feels about your business. Second, you will figure out how to phrase information in your ad, such as inserting a question, exclamation, or statement. You’ll also want to test any hash tags you use with your social media posts. These are an integral part of social media and can affect how your audience responds to your ad. All these experiments will help produce a better ad copy for your business. 5. Usability Your audience wants a good experience with your business. If they have a poor time navigating your website, you’ll lose potential leads and conversions. So, creating a sufficient user experience is crucial to your success. 7.8 KEYWORDS Monte Carlo methodis useful to solve complex problems using random and probabilistic methods. Marketing experimentation is a research method which can be defined as \"the act of conducting such an investigation or test Sampling. Here the objective is to gather information about a random object by observing many realizations of it. Analyze Process Output: - With the simulated data in place, you can use your transfer equation to calculate simulated outcomes CTR :- For a marketing email test, consider measuring impressions, reach, conversion rate, or click through rate 7.9 LEARNING ACTIVITY 1. Explain concept of MCM ___________________________________________________________________________ _____________________________________________________________________ 2. What is the process of Monte Carlo Simulation? 112 CU IDOL SELF LEARNING MATERIAL (SLM)
___________________________________________________________________________ _____________________________________________________________________ 3. Explain the concept of Marketing Experiments ___________________________________________________________________________ _____________________________________________________________________ 7.10 UNIT END QUESTIONS A. Descriptive Questions Short Questions 1. Define the scope of Monte Carlo Simulation 2. What is the process of Monte Carlo Simulation? 3. Discuss the advantages of Monte Carlo Simulation. 4. Explain the process of Monte Carlo Simulations 5. Explain the concept of Marketing experiments 6. How to develop Marketing Experiments? Long Questions 1. What is the objective of Monte Carlo Simulation? 2. Explain the scope of Monte Carlo in Customer Data Analysis. 3. Why Monte Carlo Simulation is good? 4. What are Marketing Experiments? 5. Explain the scope of Marketing Experiments 6. What is Customer Data Analysis? B. Multiple choice Questions 1.Monte Carlo simulation is used for solving a. Stochastic problems where passage of time plays no substantive role. b. Deterministic problems where passage of time plays substantive role. c. Stochastic problems where passage of time plays substantive role. d. All of these 2. Monte Carlo simulation is generally 113 a. Static CU IDOL SELF LEARNING MATERIAL (SLM)
b. Dynamic c. Static &dynamic d. None of these 3. Marketing Experiments is a part of ____________ a. Customer Service b. Business Goodwill c. Customer Development d. Brand Equity 4. Marketing Experiments covers ___________ a. Customer Retention b. Identifying New Products c. Market Analysis d. Test Marketing 5. The main aim Business Unit is _____________ a. Create goodwill b. After Sales Service c. advertising d. profit & Customer satisfaction Answers 1-a, 2-a, 3-c, 4-d, 5d. 7.11 REFERENCES Textbooks T1 Grigsby, M. 2115. Marketing Analytics: A practical guide to real marketing science, Its Ed., Kogan Page, India, ISBN: 978-0749474171. T2 Winston, W. 2114.Marketing Analytics: Data Driven Technique using MS. Excel’s Ed. John Wiley & Sons, India, ISBN: 978-1118373439. 114 CU IDOL SELF LEARNING MATERIAL (SLM)
Reference Books: R1 Grigsby, M. 2116. Advanced Customer Analytics: Targeting, Valuing, Segmenting and Loyalty Techniques (Marketing Science). Ist Ed. Kogan Page. India. ISBN: 978-0749477158. Websites https://springer.com https://michaelpawlicki.com https://statisticshowto.com https://stattrek.com https://slideshare.com 115 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 8: BEHAVIORAL SEGMENTATION, A/B TESTING STRUCTURE 8.0 Learning Objectives 8.1 Introduction of Behavioural Segmentation 8.2 Definitions of Behavioural Segmentation 8.3 Concepts of Behavioural Segmentation 8.4 Importance of Behavioural segmentation in Marketing 8.5 Different Types of Behavioural Segmentation 8.6 Methods of Behavioural Segmentation 8.7 Purpose of A/B Testing 8.8 Process of A/B Testing 8.9 Summary 8.10 Keywords 8.11 Learning Activity 8.12 Unit End Questions 8.13 References 8.0 LEARNING OBJECTIVES The major objectives of behavioural segmentation are: Identify segments based on the behaviour displayed by customers. Determine how your product or service satisfies the needs of each segment. ... Create marketing campaigns tailored to a specific segment and increase the probability of purchase. The main objectives of behavioral segmentation are: Identify segments on the basis of behavior displayed by customers. Determine how your company product or service satisfies the needs of each segment. Modify the product or service to meet the needs of consumers. Create marketing campaigns tailored to a focus segment and increase the probability of purchase. Update reports on the brands that consumers purchase most frequently and identify the competition. 116 CU IDOL SELF LEARNING MATERIAL (SLM)
8.1 INTRODUCTION OF BEHAVIOURAL SEGMENTATION Characteristics of behavioral segmentation Among the main characteristics of behavioral segmentation are: Companies follow this method to focus their efforts on the right target customers depending on the buying behavior they have. Enables decisions on the basis of resources such as time and budget to have a greater impact on consumers. It is based on the attitudinal history of consumers in order to identify and influence future purchasing decisions. You can identify similar behaviors among consumers and focus marketing efforts on a specific group. It can be adapted to the personality of each consumer group in order to achieve the established objectives. It allows the creation of marketing strategies to obtain loyal customers to the brand. 8.2 DEFINITION OF BEHAVIOURAL SEGMENTATION What is behavioral segmentation? Behavioral segmentation in short is a process in marketing that divides customers into segments depending on their behavior patterns when interacting with a particular business or website. These group segments could include grouping targeted customers by: Their approach toward your product, brand or service; Their use of your product or service, Their overall information of your brand and your branded products, Their purchasing behavior & tendencies, such as buying on special occasions like birthdays or holidays only, etc. 8.3 CONCEPTS OF BEHAVIOURAL SEGMENTATION IN MARKETING Behavioral segmentation is the systematic process of grouping targeted customers according to their behavior while making purchasing decisions. Market researchers are in charge of observing different aspects such as readiness to buy, i.e., the knowledge they have about the product, level of loyalty, interactions with your brand or product usage experience, etc. 117 CU IDOL SELF LEARNING MATERIAL (SLM)
8.4 IMPORTANCE OF BEHAVIOURAL SEGMENTATION Why is behavioral segmentation so important? Identifies the most engaged users. Being able to filter existing customers and potential prospects that display highest levels of engagement – for example, those regularly opening your emails, or spend the most time on your product pages – enables marketers to make more informed decisions on how and where to best allocate time, budget, and resources. In return, this makes your marketing more cost-effective, as you’re not burning through budget trying to warm up predominantly cold leads. You can focus on those most likely to make a purchase Importance of behavioral segmentation Behavioral segmentation is done with the objective of grouping people who exhibit the same behaviors and targeting all marketing efforts to a single group. With this method, companies can promote and market their products effectively, meeting the needs of customers. The main objective of behavioral segmentation is to understand the needs and desires of customers by offering something unique based on their behavior when purchasing a product or service. It also allows companies to market customized products specifically to potential consumers. Find your niche market with the help of online surveys. At Questioner, we can help you find the right audience for your products and services. Use our online chat to connect with our support representative and learn how to create online surveys in under 5 mins! Advantages and disadvantages of behavioral segmentation Advantages Among the main advantages of behavioral segmentation are: It is very useful to find customers with similar buying habits and behaviors. It helps all organizations to understand consumer needs. Organizations will be able to build brand loyalty in the most like-minded customers. 8.5 DIFFERENT TYPES OF BEAHVIOURAL SEGMENTATION 7 Behavioral segmentation examples Purchasing behavior. Purchase behavior-based segmentation looks at how customers act differently throughout the decision-making process. ... Benefits sought. ... 118 CU IDOL SELF LEARNING MATERIAL (SLM)
Buyer journey stage. ... Usage. ... Occasion or timing. ... Customer loyalty. ... User status. Benefits of Behavioral Segmentation Improves targeting accuracy Helps provide better-personalized experience Sifts engaged users from uninterested Saves money Makes it easier to track success Helps build loyalty to your brand Improves targeting accuracy. Behavioural segmentation allows companies to take advantage of behavioural differences, optimizing their marketing messages based on that data. For instance, it helps to pick up the right approach for loyal customers or newly subscribed users. It also clarifies groups of people that make up your audience: adults from 20-34, people keen on sports, or those who love traveling. Helps provide better-personalized experience. Mass emails with the same message for everyone are out-dated practice today. Instead, you need to deeply analyse your audience and meet people’s demands in a personalized approach based on social groups they belong to. Sifts engaged users from uninterested. Marketers filter the target audience to work with by identifying the user’s level of engagement. It increases the chances that your products will be found by people who need them. Saves money. Behavioural segmentation helps prioritize campaigns to make your marketing more cost-effective. It allows you to spend less time and fewer resources to warm up leads or trying to communicate with an uninterested audience. Makes it easier to track success. You can track metrics inside each segment and improve your results. Helps build loyalty to your brand. Behavioral segmentation helps you realize how to support users along their customer journey and keep them engaged all the time. People that are treated personally are more likely to become loyal to your brand and be converted into brand advocates. Based on a Purchasing Behavior 119 CU IDOL SELF LEARNING MATERIAL (SLM)
This segment takes advantage of a users' behavior when they make a purchase. Check if they hesitate, if there are any obstacles on their way to make a decision. The answer to these and simple questions will help you simplify the buying process. Let’s point out some common situations when clients are about to convert into customers: Considering the best price. This is the most important factor in influencing the buyer’s decision. If you identify people who hesitate by waiting for a better price, you will dramatically increase your chances to make a sale to them during special occasions like marketing holidays, when the prices are reduced. Looking for social proof. These users are interested in a product, but they wonder if others are satisfied with the product. To dispel doubts, place customer reviews on your website or right in the email campaign. Having all the time in the world. These customers are interested, but they don’t hurry to buy your product. In this case, add a time-sensitive element like adding a countdown to an email, or come up with a time-limited discount. This creates a feeling of urgency. Below is an example of an automated email triggered when a customer abandons their shopping cart? It Based on Benefits This is a way to divide customers according to the benefits they are looking for and motivate them to buy your products or services. For instance, there are many reasons to buy chewing gum: clean teeth, fresh breath, nice flavor, or anti-stress effect. Find out which benefits drive your customers towards the purchase and emphasize them. Here’s an attempt to identify what stops a subscriber from using a service — technical issues, lack of features, or not enough motivation. Based on a Lifecycle Stage Behavioral segmentation based on a lifecycle stage works well for selling products and services with a long lifecycle. It’s not easy to map user’s lifecycle stage because you can’t judge based on a single touch point. To cope with that, collect data on all touch points via every marketing channel you use — emails, social media, search engine, chatbot. When you determine the user’s lifecycle stage, move them closer to the purchase by sending more relevant and valuable nurturing materials and, eventually, offer. Below is an example of lead nurturing — the lifecycle stage where the company provides educational materials, showing how the product deals with the problems. 120 CU IDOL SELF LEARNING MATERIAL (SLM)
Based on a Level of Engagement This segment is built on how often users log in your service or how many orders they make with your restaurant. Adjust your marketing messages based on this data and encourage user participation. This segment helps reduce the churn rate and improve sender reputation by dividing your target audience from unengaged people. Let’s check three basic levels of user engagement: Occasional. This means that users have a contact with your brand, but it’s not systematic. They may lack motivation or value from your side, so find out the reason with the help of a survey, for instance, and fix it. Regular. Users regularly interact with your service, but don’t use its functions to the full extent. Share how-to videos, highlight all features that might be handy for them, and offer a loyalty program. Intensive. These users integrate your service in their life, and that is the reason to treat them specially. Provide bonuses, invite to special events, congratulate on their birthdays, because these people may advertise your brand through word-of- mouth and become loyal clients. Occasion-based This is segmentation based on specific timing which is best to deliver your marketing messages. Utilize marketing holidays like Black Friday, Cyber Monday, or national holidays depending on the user’s location. Take advantage of special dates like their birthday or anniversary. Pay attention to the days of the week and time of the day that is most convenient for communication. To implement occasion-based segmentation, collect personal data from subscription forms, lead magnets, or surveys. These insights will help you improve the open rate of your campaigns and build a positive brand image. The example below is a way to use occasion — the end of the year — to upsell a pricing plan. Using Behavioral Segmentation With email marketing. Send triggered emails connected with a purchase — abandoned cart emails, confirmation emails, email notifications, and more. Aside from that, try using drip campaigns to welcome users, reactivate them, upsell and cross-sell goods. With SMS marketing. Track how people react to your SMS advertising campaigns. Divide your audience into segments based on whether they 121 CU IDOL SELF LEARNING MATERIAL (SLM)
used your promo codes or not, and try searching for other ways to contact unengaged users. With SMM. With Facebook advertising, for instance, you can tailor your ads to people based on how they engage with your posts. If users often respond, encourage them with a discount. With chatbot marketing. While users communicate with your chatbot, you can narrow their path towards solving the exact problem. When the conversation ends, you will identify the user's lifecycle stage, making it easier to find the right approach for the next touch points. What is behavioral segmentation? Behavioral segmentation groups people into distinct groups based on a specific behavioral pattern in common. Users could share the same purchasing behavior (decision making), benefits wanted, buyer journey stage, and more. The aim of behavioral segmentation is to: Understand the particular needs and desires of customer groups Tailor your product or service to fit the needs of your customers Find opportunities to optimize the buyer’s journey Create a smart marketing strategy that can create a closer relationship to your existing customers and expand your customer base As I mentioned above, behavioral segmentation doesn’t exist in a silo. It takes into account other segmentation data and often overlaps with them. The fundamental difference between behavioral segmentation and the other types of grouping is that the former is more intimate than the latter. Why is behavioral segmentation important? When you understand current customers and prospects better, you can provide them with the tailored and personalized experiences that they want. Behavioral segmentation helps you achieve the 4 Ps: Personalization When you understand how to target different customer groups with different offers through their preferred marketing channels, this boosts personalization. An increase in personalization means a better chance of you nurturing them further into the buying journey. Predictive You can predict and even influence customer behavior after studying their behavioral patterns. For example, if you notice that one group likes to provide product feedback 122 CU IDOL SELF LEARNING MATERIAL (SLM)
via Facebook Messenger, you can anticipate this and ask them to leave a review via that preferred medium. Prioritization Identifying the prospects that have the most value to your business helps you save time, resources, and enable you to make more informed decisions. Performance Analyzing the growth patterns and segment changes help you gauge business health and evaluate performance metrics. 8.6 METHODS OF BEHAVIOURAL SEGMENTATION What are the 4 types of behavioral segmentation? There are four main types of behavioral segmentation that help form a complete customer profile throughout their buying journey. Each nuance provides actionable insights, which can be embedded in a variety of marketing channels and encourage customers to act on their purchase decisions. You can break these down into four main behavioral segments. Fig. 8.1 1. Segmentation based on purchase and usage behavior Segmenting by purchase behavior disentangles the varying trends and behavior patterns that customers have when making a purchase decision. This form of behavioral segmentation provides insight into the buying stage that your customer might be in, their role in the purchasing process, the obstacles they are facing, the incentives they’re most likely to respond to and much more. For example, customers who prefer to undertake research will often turn to search engines or reviews to be assured they are making the right decision purchasing from you, whilst 123 CU IDOL SELF LEARNING MATERIAL (SLM)
customers that are particularly thrifty may only interact with your brand or product when on sale. Ultimately, both of these customer types can fall into the same product affinity category. However, targeting all of them with the same marketing materials and messaging is destined to waste resources. The aforementioned careful consumer may not respond to discount promotions in the same manner as the thrifty one. This is where segmenting by purchasing behavior comes in. You can break these behaviors down into categories depending on: How many interactions with your business does a customer need before proceeding to conversion; What search queries a customer used to locate your brand, products and services; What questions a customer asks when using a live chat or virtual assistant; etc. Knowing this information allows you to respond to your customer’s needs in a relevant manner. For example, customers who are in the research phase and are likely to leave to compare prices could be retargeted with a “best price” or “price match” guarantee. Alternatively, a shopper that is keen on social proof and buys in accordance with popularity trends could be targeted with a message suggesting that the item is in high demand, and moving fast. 2. Occasion or timing-based segmentation Occasion-based segmentation categorizes customers who are most likely to interact with your brand or purchase from your website on either specific occasions or set times. Occasions could include national holidays like Labor Day, a holiday season like Thanksgiving or Christmas, or life occasions, such as a wedding, new house, or vacation. Occasion-based purchasing can also occur in a customer’s daily routine. Purchases like a happy hour round of drinks after work and a caffeinated morning drink are all types of occasion-based purchases as they are only bought at precise times. Grouping customers using this form of segmentation involves monitoring a customer’s purchasing behavior to establish a pattern so that you preempt the targeting process. For example, if your store has customers that participate yearly in your Thanksgiving promotions, but do not buy anything else from you throughout the year, you can use this information to market to the customer in weeks in advance. 3. Benefits sought segmentation Segmenting by benefits sought refers to dividing your audience based on the unique value proposition your customer is looking to gain from your product or service. 124 CU IDOL SELF LEARNING MATERIAL (SLM)
Let us explain further. When we make purchases, we do so based on the belief that we will receive a certain value or benefit from using the product or service. Even when purchasing something as mundane as toothpaste, we lean towards different value propositions: Some may be looking for whitening benefits while others seek comfort to their sensitive gums. Dividing consumers based on these factors embodies the benefits sought segmentation. Grouping your data by benefits sought helps you narrow down the specifics of what drives customer purchases, revealing which product feature or service aspect they feel most attuned to. Divide data by these benefit categories when using this form of behavioral segmentation: Quality: What makes your product better than your competitors? Usage: How will it benefit your customer when they use it? Customer Feedback: Are your customers happy with the product or service, or are there areas for improvement? USPs: What makes your product unique from other already existing products? Additional Benefits: Are there other advantages a customer could receive from purchasing your products or services? 4. Segmentation based on customer loyalty Loyalty-based segmentation measures the level of loyalty a customer has with your brand, either through a rewards program, number of purchases, or general engagement with your marketing efforts. Using loyalty-based behavioral segmentation helps you to zero in on existing repeat customers, their needs, behavior patterns, and more. Besides generating repeat revenue from your business, loyal customers are incredibly useful in terms of referrals, word of mouth, and feedback. Extracting valuable information from this segment can help you optimize future campaigns, improve your value proposition, strengthen positioning, and more. Consider identifying factors such as: What the key behaviors were throughout the customer journey that nurtured loyalty; Which customers are the most appropriate or ideal type for loyalty programs; What factors are most essential in keeping those segments of customers happy; Which ways value received from loyal customers can be maximized. The most common examples of customer loyalty segmentation can be reflected in the travel industry which regularly promotes frequent flier programs and the finance industry who offer rewards for big-spending platinum credit card members. 125 CU IDOL SELF LEARNING MATERIAL (SLM)
8.7 PURPOSE OF A/B TESTING A/B testing (also known as split testing or bucket testing) is a method of comparing two versions of a webpage or app against each other to determine which one performs better. A/B testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal. Fig. 8.1 8.8 PROCESS OF A/B TESTING How A/B testing works In an A/B test, you take a webpage or app screen and modify it to create a second version of the same page. This change can be as simple as a single headline, button or be a complete redesign of the page. Then, half of your traffic is shown the original version of the page (known as the control) and half are shown the modified version of the page (the variation). 126 CU IDOL SELF LEARNING MATERIAL (SLM)
Fig. 8.2 Why you should A/B test A/B testing allows individuals, teams and companies to make careful changes to their user experiences while collecting data on the results. This allows them to construct hypotheses and to learn why certain elements of their experiences impact user behavior. In another way, they can be proven wrong—their opinion about the best experience for a given goal can be proven wrong through an A/B test. More than just answering a one-off question or settling a disagreement, A/B testing can be used to continually improve a given experience or improve a single goal like conversion rate over time. A B2B technology company may want to improve their sales lead quality and volume from campaign landing pages. In order to achieve that goal, the team would try A/B testing changes to the headline, visual imagery, form fields, call to action and overall layout of the page. 127 CU IDOL SELF LEARNING MATERIAL (SLM)
Testing one change at a time helps them pinpoint which changes had an effect on visitor behavior, and which ones did not. Over time, they can combine the effect of multiple winning changes from experiments to demonstrate the measurable improvement of a new experience over the old one. When it comes to customer-facing content, there is so much you can evaluate with A/B testing. Common targets include: Email campaigns Individual emails Multimedia marketing strategies Paid internet advertising Newsletters Website design Each category, you can conduct A/B tests on any number of variables. If you're testing your site’s design, for example, you can try different options such as: Color scheme Layout Number and type of images Headings and subheadings Product pricing Special offers Call-to-action button design Essentially, almost any style or content element in a customer-facing item is testable. How do you conduct A/B tests? The process Just like in the laboratory version of the scientific method, A/B testing begins with picking what to test. The whole process consists of several steps: 1. Identify a problem. Make sure you identify a specific problem. “Not enough conversions,” for instance, is too general. There are too many factors that go into whether or not a website visitor becomes a customer or whether an email recipient clicks through to your site. You need to know why your material isn't converting. Example: You work for a women's clothing retailer that has plenty of online sales, but very few of those sales come from its email campaigns. You go to your analytics data and find that 128 CU IDOL SELF LEARNING MATERIAL (SLM)
a high percentage of users are opening your emails with special offers and reading them, but few are actually converting. 2. Analyze user data. Technically you could conduct A/B testing on everything that your customers see when they open your emails, but that would take a lot of time. There are a lot of designs and content elements that they encounter that probably aren’t relevant, so you need to figure out which element to target. Example: People are opening your emails, so there’s nothing wrong with how you’re writing your subject lines. They’re also spending time reading them, so there’s nothing that’s making them instantly click away. Because plenty of the users who find your website from elsewhere end up becoming customers, you can tell there’s nothing wrong with how you’re presenting your products, either. This suggests that although people find your emails compelling, they’re getting lost somehow when they go to actually click through to your site. 3. Develop a hypothesis to test. Now you're really narrowing it down. Your next step is to decide exactly what you want to test and how you want to test it. Narrow your unknowns down to 1 or 2, at least to start. Then you can determine how changing that element or elements might fix the problem you're facing. Example: You notice that the button that takes people to your online store is tucked away at the bottom of the email, below the fold. You suspect that if you bring it up to the top of the screen, you can more effectively encourage people to visit your site. 4. Conduct the hypothesis testing. Develop a new version of the test item that implements your idea. Then run an A/B test between that version and your current page with your target audience. Example: You create a version of the email with the button positioned above the fold. You don't change its design—just it’s positioning. You decide to run the test for 24 hours, so you set that as your time parameter and start the test. 5. Analyze the data. Once the test is over, look at the results and see if the new version of your item resulted in any noticeable changes. If not, try testing a new element. Example: Your new email increased conversions slightly, but your boss wants to know if something else could do better. Since your variable was the positioning of the button, you decide to try placing it in 2 other locations. 6. Find new challengers for your champion. The A/B testing world sometimes uses “champion” and “challenger” to refer to the current best option and new possibilities. When 2 or more options compete and one is significantly more successful, it's called the champion. You can then test that winner against other options, which are called challengers. That test might give you a new champion, or it might reveal that the original champion really was the best. 129 CU IDOL SELF LEARNING MATERIAL (SLM)
8.9 SUMMARY Behavioural segmentation is study for understanding customers not just by who they are, but by what they do, using insights derived from customers' actions. ... It helps for businesses to divide customers into groups according to their knowledge of, attitude towards, use of, or response to a product, service or brand, purchasing power etc etc…. Behavioral Segmentation is a form of customer segmentation, response that is based on patterns of behavior displayed by customers as they interact with a company/brand or make a purchasing decision. It allows businesses to divide customers into groups according to their knowledge of, attitude towards, use of, or response to a product, service or brand. The objective is to identify customer segments that enable you to understand how to address the particular needs or desires of a group of customers, discover opportunities to optimize their customer journeys, and quantify their potential value to your business. What is A/B Testing? 1. A/B testing, also known as split testing, refers to a randomized experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics. 2. A/B Testing is one of the simplest ways to understand the performance of your website using statistical analysis and spending the least amount of time and money. It enables you to optimize your website based on the website visitor behaviour and drive more business revenue. 8.10 KEYWORDS Behavioral segmentation in short is a process in marketing that divides customers into segments depending on their behavior patterns when interacting with a particular business or website. A/B testing: - is the process of comparing two versions of a web page, email, or other marketing asset and measuring the difference in performance. Predictive:You can predict and even influence customer behavior after studying their behavioral patterns Prioritization:Identifying the prospects that have the most value to your business helps you save time, resources, and enable you to make more informed decisions. Performance: Analyzing the growth patterns and segment changes help you gauge business health and evaluate performance metrics. 8.11 LEARNING ACTIVITY 1. What is behavioral segmentation? 130 CU IDOL SELF LEARNING MATERIAL (SLM)
___________________________________________________________________________ _____________________________________________________________________ 2. Explain the concept of A/B Testing? ___________________________________________________________________________ _______________________________________________________________ 3. Define different methods of Behavioural Segmentation? ___________________________________________________________________________ _______________________________________________________________ 8.12 UNIT END QUESTIONS A. Descriptive Questions Short Questions 1. Define Behavioural Segmentation 2. What is purpose of doing Behavioural Segmentation? 3. What is the criterion of Behavioural Segmentation? 4. Explain the types of Behavioural Segmentation 5. Define the concept of A/B Testing. 6. What is the scope of A/B Testing? 7. How to perform A/B Testing. Long Questions 1. What is scope of Behavioural Segmentation? 2. What are the different types of Behavioural Segmentation 3. Explain the objectives of Behavioural Segmentation 4. What is Behavioural Segmentation in Marketing? 5. What are the criteria for A/B test? 6. Why A/B test is used in Marketing? 7. How to perform A/B Test? B. Multiple choice Questions 1. Behavioural Segment is concern with a. Product b. Consumer 131 CU IDOL SELF LEARNING MATERIAL (SLM)
c. Free Sample 132 d. Test Marketing 2. Behavioural Segmentations is a concerned with ___________ a. Business Growth b. Market Survey c. More Sales d. Customer Satisfaction 3. Behavioural segmentation is mainly useful for _________ a. B2B b. Direct Marketing c. SSI d. FMCG Business 4. A/B Test is helpful for ________ a. Sales Analysis b. Cost Comparison c. Brand Loyalty d. Product Development 5. The A/B Test will improve your _____________ a. Market Share b. Market feedback & Data collection c. Conversion d. Customer satisfaction & goodwill Answers 1-b, 2-b, 3-d, 4-b, 5c. CU IDOL SELF LEARNING MATERIAL (SLM)
8.13 REFERENCES Textbooks T1 Grigsby, M. 2115. Marketing Analytics: A practical guide to real marketing science, Its Ed., Kogan Page, India, ISBN: 978-0749474171. T2 Winston, W. 2114.Marketing Analytics: Data Driven Technique using MS. Excel. Ist Ed. John Wiley & Sons, India, ISBN: 978-1118373439. Reference Books: R1 Grigsby, M. 2116. Advanced Customer Analytics: Targeting, Valuing, Segmenting and Loyalty Techniques (Marketing Science). Ist Ed. Kogan Page. India. ISBN: 978-0749477158. Websites https://springer.com https://michaelpawlicki.com https://statisticshowto.com https://stattrek.com https://slideshare.com 133 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 9: SLICING & DICING DATA STRUCTURE 9.0 Learning Objectives 9.1 Introduction of Data Slicing & Dicing 9.2 Definitions of Slicing & Dicing 9.3 Concepts of Slicing 9.4 Importance of Slicing 9.5 Different use of Slicing 9.6 Slicing & Dicing in Business Intelligence 9.7 Summary 9.8 Keywords 9.9 Learning Activity 9.10 Unit End Questions 9.11 References 9.0 LEARNING OBJECTIVES To slice and dice is to break a body of information down into smaller parts or to examine it from different viewpoints so that you can understand it better. ... To slice means to cut and to dice means to cut into very small uniform sections and the two actions are often performed sequentially. How to use Slicing & dicing of data in your Business To understand role of Slicing & dicing in Data Warehouse Purpose of slicing & Dicing in Market analytics 9.1 INTRODUCTION OF DATA SLICING & DICING Slicing and dicing is to break a data cube into smaller parts in order to view it from different points of view. ... Slicing is producing a new data cube with one fewer dimension by locking on a single value of that dimension. Dicing is producing a new data cube by picking specific values of various dimensions. The main difference between slice and dice in data warehouse is that the slice is an operation that selects one specific dimension from a given data cube and provides a new sub cube 134 CU IDOL SELF LEARNING MATERIAL (SLM)
whilethe dice is an operation that selects two or more dimensions from a given data cube and provides a new sub cube. A data warehouse is a system used for reporting and data analysis, which support decision making. Firstly, the data from multiple sources is extracted, transformed and loaded into the warehouse. Then, analytics is performed using Online Analytical Processing Server (OLAP), which is based on the multidimensional data model. There are various OLAP operations such as roll up, drill down, slice and dice, and, pivot (rotate). Roll up is used to aggregate on a data cube; drill down is used to reverse the operation of roll up while pivot is used to rotate the data axes in view in order to provide an alternative presentation of data. In this article, we are looking at slice and dice. Therefore, slicing and dicing presents the data in new and diverse perspectives and provides a closer view of it for analysis. e.g., a report is showing annual performance of a particular product. If we want to view the quarterly performance, we can use slicing and dicing strategy to drill down to the quarterly level. Easy OLAP Definition OLAP (Online Analytical Processing) is the technology behind many Business Intelligence (BI) applications. OLAP is a powerful technology for data discovery, including capabilities for limitless report viewing, complex analytical calculations, and predictive “what if” scenario (budget, forecast) planning. Slicing refers to selecting a subset of the cube by choosing a single value for one of its dimensions and creating a smaller cube with one less dimension. 9.2 DEFINITION OF SLICING & DICING Slicing and Dicing refers to a way of segmenting, viewing and comprehending data in a database. Large blocks of data are cut into smaller segments and the process is repeated until the correct level of required details is achieved for further proper analysis. To divide something into many small parts especially to use the result for one's own purposes you can slice and dice the data any way you want. Definition of slice and dice Chiefly US: to divide something into many small parts specially to use the result for one's own purposes you can slice and dice the data any way you want. Slicing and Dicing refers to a way of segmenting, viewing and comprehending data in a database. Large blocks of data are cut into smaller segments and the process is repeated until the correct level of detail is achieved for proper analysis. 135 CU IDOL SELF LEARNING MATERIAL (SLM)
9.3 CONCEPTS OF SLICING Slicing and Dicing refers to a way of segmenting, viewing and comprehending data in a database. Large blocks of data are cut into smaller segments and the process is repeated until the correct level of detail is achieved for proper analysis. Therefore slicing and dicing presents the data in new and diverse perspectives and provides a closer view of it for analysis. For example a report is showing annual performance of a particular product. If we want to view the quarterly performance, we can use slicing and dicing strategy to drill down to the quarterly level. The slice operation performs a selection on one dimension of the given cube, resulting in a sub cube. Reduces the dimensionality of the cubes. For example, if we want to make a select where Medal = 5. Slice Operation. The dice operation defines a sub-cube by performing a selection on two or more dimensions. 9.4 IMPORTANCE OF SLICING It is important because it helps the user visualize and gather information specific to a dimension. When you think of slicing, think of it as a specialized filter for a particular value in a dimension. Segmenting traffic in Google Analytics (or any other web analytics package) is key for any analyst who is looking to get the most out of their data. I have seen far too many businesses look at their analytics data in the aggregate, without taking advantage of multiple profiles, advanced segments, or advanced filters. The “slicing and dicing” of data that can be done in Google Analytics can really provide a tremendous amount of insight into one’s online marketing efforts – be they SEO, PPC, or Social Media. The following series of brief blog posts highlight some real client cases that provide you some tips about how to segment your traffic in different ways (and “why” you should be doing it). The term has its roots in cooking and describes two types of knife skills every chef needs to master. Slice and dice refer to a strategy for segmenting, viewing and understanding data in a database. 9.5 DIFFERENT USE OF SLICLING The “slicing and dicing” of data that can be done in Google Analytics can really provide a tremendous amount of insight into one's online marketing efforts – be they SEO, PPC, or social media. Slicing and dicing: 136 CU IDOL SELF LEARNING MATERIAL (SLM)
In data analysis, the term slice and dice generally implies a systematic method of reducing a complete set of data into smaller parts or views that will help to yield more information. Slicing and Dicing refers to process of segmenting, viewing and comprehending data in a database or Data warehouse... Large or big blocks of data are cut into smaller segments and the process is repeated until the correct level of detail is achieved for proper & further analysis. 9.6 SLICING & DICING IN BUSINESS INTELLIGENCE What is slicing and dicing in business objects? Slicing and dicing of business objects is used for a detailed analysis of the data. It allows changing the position of data by interchanging rows and columns. It is used to rotate the cube to view it from different perspectives. What is slicing and dicing in business objects? Slicing - The cube is sliced based on its dimension Dicing - The cube is rotated without the need of the dimension (independent of dimension. Slicing and Dicing are used for analyzing data in different views and perspectives. There has been plenty of coverage about BI for large enterprises; business intelligence is just as important for small businesses. BI is simply using tools to view, manage, and manipulate what are often large sets of data from the past to be able to gain insights into the future. BI is a type of application software that businesses employ to manage their businesses better—often working along or in concert with their data, transaction and customer management systems. Some of the common types of BI tools include data querying and reporting software, online analytical processing systems (OLAP), data mining and data visualization systems, digital dashboards, business process and business performance management systems, geospatial systems, and others. The most widely used BI tool is the common spreadsheet, Microsoft Excel. Most businesses already own and use Excel, so it is easy to understand. If you are using a spreadsheet to help you make sense of your data to make better decisions, you are already using BI. But as your business grows, and the volume of data you need to manage grows along with it, it may be time to consider upgrading to more powerful tools. 9.7 SUMMARY S - Slicing and Dicing Slicing and dicing is to break a data cube into smaller parts for viewing it from different points of view. The process is repeated until the user has reached the desired level of detail. 137 CU IDOL SELF LEARNING MATERIAL (SLM)
Slicing is producing a new data cube with one fewer dimension by locking on a single value of that dimension. On the other hand Dicing is producing a new data cube by picking specific values of other various dimensions. Fig. 9.7 T - Tableau Tableau was founded in 2003 by 3 geniuses from Stanford University with innovation and excellence in Business Intelligence & Analytics. The Gartner’s 2017 Magic Quadrant for Business & Marketing Intelligence and Various Analytics Platforms places Tableau in the Leader quadrant for the fifth time. 9.8 KEY WORDS OLAP (Online Analytical Processing) is the technology behind many Business Intelligence T – Tableau:Tableau was founded in 2003 by 3 geniuses from Stanford University with innovation and excellence in Business Intelligence & Analytics. 9.9 LEARNING ACTIVITY 1. What is Slicing & dicing? ___________________________________________________________________________ _____________________________________________________________________ 2. Define the concept of Slicing? ___________________________________________________________________________ _____________________________________________________________________ 3. Explain use of Dicing & Slicing in Business? 138 CU IDOL SELF LEARNING MATERIAL (SLM)
___________________________________________________________________________ _____________________________________________________________________ 9.10 UNIT END QUESTIONS A. Descriptive Questions Short Questions 1. Define Slicing 2. What is purpose of Slicing? 3. Define the concept of Dicing? 4. What is the difference between Slicing & Dicing 5. Explain the benefits of Slicing & Dicing in Business. Long Questions 1. What is process of Slicing & Dicing? 2. Explain difference between Slicing & Dicing 3. Explain the use of Slicing. 4. What is use of Slicing & Dicing in Marketing Decisions? 5. What is the importance of Customer Data Analysis? B. Multiple choice Questions 1. Slicing & Dicing are required for ------------------ a. Product b. Customer Data Analysis c. Customer Meet d. Test Marketing 2. Slicing & Dicing of Data can be proceed in ___________ a. Google Analytics b. Market Survey c. Customer & Data Analysis d. Customer Satisfaction 3. Slicing & Dicing is very beneficial in _________ 139 CU IDOL SELF LEARNING MATERIAL (SLM)
a. Market Development b. Direct Marketing c. Marketing Analytics d. FMCG Business 4. A/B Test is carried for ________ a. Sales Analysis b. Digital Marketing c. Brand Loyalty d. Product Development 5. The A/B Test will allow taking _____________ a. Market decision b. Market feedback & Data collection c. Conversion d. Un-necessary risk Answers 1-b,2-a, 3-c, 4-b, 5d. 9.11 REFERENCES Textbooks T1 Grigsby, M. 2115. Marketing Analytics: A practical guide to real marketing science, Its Ed., Kogan Page, India, ISBN: 978-0749474171. T2 Winston, W. 2114.Marketing Analytics: Data Driven Technique using MS. Excel. Ist Ed. John Wiley & Sons, India, ISBN: 978-1118373439. Reference Books: R1 Grigsby, M. 2116. Advanced Customer Analytics: Targeting, Valuing, Segmenting and Loyalty Techniques (Marketing Science). Ist Ed. Kogan Page. India. ISBN: 978-0749477158. Websites 140 CU IDOL SELF LEARNING MATERIAL (SLM)
https://springer.com https://michaelpawlicki.com https://statisticshowto.com https://stattrek.com https://slideshare.com 141 CU IDOL SELF LEARNING MATERIAL (SLM)
UNIT 10: CREATING MARKETING ANALYTICS DASHBARDS STRUCTURE 10.0 Learning Objectives 10.1 Introduction of Marketing Dashboards 10.2 Making of Marketing Dashboards 10.3 Various Types of Marketing Dashboards 10.4 Scope of Marketing Dashboards 10.5 Creation of a better Marketing Dashboards 10.6 Benefits of Marketing Dashboards 10.7 Summary 10.8 Keywords 10.9 Learning Activity 10.10 Unit End Questions 10.11 References 10.0 LEARNING OBJECTIVES A marketing dashboard displays key marketing metrics and KPIs in a visual way. ... Dashboards are designed to provide data to marketers and relevant stakeholders in a systematic way that makes it easy to analyse and pull important insights. The aim is to have a near real-time view into how your marketing plans are performing. Why to learn marketing dashboards? ... Marketing Dashboards clubs these qualities by providing teams with visually appealing and easy-to-read displays of key marketing metrics or variables. By reviewing & tracking metrics on a regular daily, weekly, and monthly basis, marketers can act on data to immediately improve performance. 10.1 INTRODUCTION OF MARKETING DASHBOARDS A web analytics marketing dashboard tracks website performance in real-time, allowing you to track about how your website is performing in regards to your marketing objectives by looking at a high-level, but still in-depth view of your site's performance across a number of different timeframes. 142 CU IDOL SELF LEARNING MATERIAL (SLM)
It is marketing dashboard is a reporting tool that displays marketing analytics, KPIs, and metrics using data visualizations. Marketing dashboards are made to provide teams with a real-time window into marketing performance. A marketing dashboard displays key marketing metrics and KPIs in a visual way. ... Dashboards are designed to provide data to marketers and relevant stakeholders in a way that makes it easy to analyses and pull important insights. The goal is to have a near real-time view into how your marketing efforts are performing. Best Marketing Dashboards List Power BI for Office 365. Google Data Studio. What graph. Mix panel. Outboard. Data pine. Zoho Analytics. Tap Clicks. 10.2 MAKING OF MARKETING DASHBOARDS Dashboards are data visualization tools that allow all users to understand the analytics that matter to their business, department or project. Even for non-technical users, dashboards allow them to participate and understand the analytics process by compiling data and visualizing trends and occurrences. A marketing dashboard is a visual display of the most relevant information necessary to keep track of key marketing metrics, and to achieve one or more marketing objectives. Top level marketing reports are consolidated and arranged in a single page so that the information can be monitored at a glance. Most Popular Types of Marketing Dashboards Marketing Performance Dashboard. Digital Marketing Dashboard. SEO Analytics Dashboard. Ecommerce Marketing Dashboard. Web Analytics Dashboard. Social Media Dashboard. 143 CU IDOL SELF LEARNING MATERIAL (SLM)
Google Ads (Ad Words) Campaign Dashboard. Email Marketing Dashboard. 10.3 VARIOUS MARKETING DASHBOARDS Most Popular Types of Marketing Dashboards Marketing Performance Dashboard. Digital Marketing Dashboard. SEO Analytics Dashboard. Ecommerce Marketing Dashboard. Web Analytics Dashboard. Social Media Dashboard. Google Ads (Ad Words) Campaign Dashboard. Email Marketing Dashboard. What types of marketing dashboards should be used? As we noted, there are tons of different marketing dashboards to choose from, and many of these platforms focus on specific components to your marketing strategy. Whatever type of campaign you’re running, there’s a marketing dashboard out there that will give you more insight into those marketing activities. Here are some of the most important options to consider: 1. SEO marketing dashboard Every marketer wants to see their site ranking at the top of search engine results pages (SERPs) for their most highly coveted keywords. And with the top 3 positions accounting for 75% of all Google search clicks, it’s more important than ever to take advantage of SEO tools to move your way up those SERPs and grab that precious real estate. SEO is a complicated mix of on-page, off-page and technical factors that directly impact your site’s search ranking — and, by extension, your ability to attract more organic traffic. It’s a lot of ground to cover, and often the KPIs you need to track can range from basic website traffic to competitor keyword search performance. Every marketing team needs a dedicated dashboard to monitor their SEO campaign performance so stakeholders can swiftly adjust strategies that aren’t working and continually refine and improve their marketing efforts. What platform should you use for your SEO marketing performance dashboard needs? Google Analytics is an obvious choice: 144 CU IDOL SELF LEARNING MATERIAL (SLM)
It’s free. It’s customizable. It’s easy to integrate with other platforms. It’s user-friendly. It’s supported by Google itself. It’s the industry standard. Really, it would be strange if a digital marketing team wasn’t using Google Analytics in some capacity to measure and better understand website performance. Of course, even if you’re already using Google Analytics, there are always ways to get more out of the platform. There are plenty of marketing teams that use Google Analytics to capture SEO and site performance from a high level, but never really dig deeper into more granular metrics and trends. Take advantage of the platform’s custom reporting capabilities to track high-value commercial landing pages, monitor specific ad or email campaigns, break down website conversions by audience type and much more. Using the collection of built-in widgets and dashboard templates, you can tailor your analytics dashboard to zero in on the marketing KPIs that matter most to you. This example, courtesy of Moz, highlights a custom dashboard built to track conversions from month to month. It’s easy for marketing executives to spot important trends like spikes in conversion rates without having to wade through a bunch of statistical data. 145 CU IDOL SELF LEARNING MATERIAL (SLM)
Fig. 10.1 Source: Moz 2. Email marketing dashboard Email is one of the most important marketing channels, providing an average return on investment of $42 for every $1 spent. To see that kind of ROI — or, ideally, surpass industry averages — businesses need to closely monitor every aspect of their email marketing campaigns and make adjustments whenever necessary. Even the slightest misstep — a generic subject line, for instance — can turn away an email newsletter subscriber and lose a potential sales lead, so brands need to carefully analyze their email marketing campaigns to understand which strategies are working. Major email marketing metrics to track include: Open rate. Click-through rate. Conversion rate. Bounce rate. 146 CU IDOL SELF LEARNING MATERIAL (SLM)
Unsubscribe rate. Email sharing or forwarding rate. Email list growth rate. Overall ROI. That’s just the tip of the iceberg. It’s also a good idea to segment mobile metrics from other formats to account for user experience and interface factors that might affect email marketing performance. A good email marketing dashboard brings all of that data together and packages it in a way that’s easy to understand and digest. More importantly, it should allow marketing teams to slice and dice data so they can focus on the marketing KPIs that matter most to them. For instance, if you’re running an email campaign as part of a broader content marketing strategy, you could track which types of content resonate the most with your audience. Google Analytics has plenty of widgets, marketing dashboard templates and customization tools to help you drill into specific performance metrics. Here’s an example, showing the number of sessions produced by different landing pages and pieces of content attached in email newsletters: With that kind of versatility, Google Analytics can function as both an email marketing and content marketing dashboard, along with its many other applications. 3. Social media marketing dashboard Maintaining a strong social media presence is important for B2B and B2C companies alike. If you can’t see how your brand’s performing across different social media platforms, you may not be building the level of engagement you think you are. Given how quickly things move in the social media world, brands need to stay on top of their social media analytics 24/7. A dedicated social media marketing dashboard can help monitor trends and developments in real time and provide actionable insights that can be immediately applied to your strategy. This intelligence can empower you to be more responsive, switch your social media approach on the fly and keep evolving along with your target audience. Social media marketing dashboards give you the information needed to make it all happen. Marketing teams can find all the relevant social media marketing metrics they’re looking for in one easy to understand interface. You can track key performance indicators like: Followers. Likes. Reach. 147 CU IDOL SELF LEARNING MATERIAL (SLM)
Impressions. Average engagement rate. Audience growth rate. Top ranking posts. Social share of voice. There are plenty of good options to choose from — once again, Google Analytics has tools to help visualize social media analytics — but one of the best dedicated platforms out there is Sprout Social. You can break down your social media marketing metrics by channel and segment different KPIs to capture a better view of your brand’s performance. With so many customization options to explore, marketers can monitor their social media presence from any vantage point they like, whether it’s a high-level overview or an in-depth analysis of a particular segment of your audience and followers. Data needs to guide every marketing decision you make, but for anyone who doesn’t have a degree in statistics, wading through all of that information to find actionable insights can seem insurmountable. Digital marketing dashboards use intuitive visual aids to simplify and analytics displays that bring the most relevant and useful marketing data to the surface. If you can make the most out of these platforms, you’ll never have to resort to guesswork when managing your marketing campaigns. Most Popular Types of Marketing Dashboards Marketing Performance Dashboard. Digital Marketing Dashboard. SEO Analytics Dashboard. Ecommerce Marketing Dashboard. Web Analytics Dashboard. Social Media Dashboard. Google Ads (Ad Words) Campaign Dashboard. Email Marketing Dashboard. 10.4 SCOPE OF MARKETING DASHBOARDS In today’s data-driven environment, business dashboards generate a lot of buzz. You’re probably reading this blog post because you find yourself asking one (or all) of the following questions: 148 CU IDOL SELF LEARNING MATERIAL (SLM)
What are dashboards? What is the purpose of a dashboard? What is the importance of a dashboard? What are the benefits of dashboard reporting? Does it make sense for my organization to use a dashboard? We’re here to answer those questions and help you understand that whether you’re a large corporation or a startup company, there are many ways you can incorporate digital dashboards in a business environment. 10.5 CREATION OF BETTER MARETING DASHBOARDS How Do I Create a Marketing Dashboard? A marketing dashboard is a compilation of all of the pertinent data about a company’s marketing efforts. Marketing dashboards benefit both marketing and the executive team. They can give an at-a-glance view that quantifies the overall impact marketing has on the business and how marketing initiatives increase customer acquisition, retention, and sales. A marketing dashboard can be invaluable for making strategic decisions and adjustments to your sales funnel. So, how do you create a marketing dashboard that is useful and adds value to your organization? A marketing dashboard should serve the following purpose: Show KPIs (Key Performance Indicators) Integrate Data from various sources and present a consolidated view Provide a way to measure the overall results and investments of your marketing programs Provide the ability to measure these metrics and make decisions based on this information 149 CU IDOL SELF LEARNING MATERIAL (SLM)
Fig. 10.2 Creating the right digital marketing dashboard in 2018 is a difficult process mainly because of the complexity of the digital marketing space. You have social media stats you need to track for Twitter, Instagram, Facebook, etc. You have Google Analytics and Search Console that operate as your primary web analytics data source, and you’ll be tracking SEO performance with SERP Rank Tracking Tools and you’ll be generating Site Audit data to monitor the performance of each of your marketing pages. Depending on your particular campaign you’ll be using different key metrics, and you’ll be adjusting KPIs based on the tools you use (for instance, if you use something like Call Rail you may be tracking data on phone calls, while some companies choose to not track call metrics). Your KPIs are fairly straightforward, but depending on what current marketing strategy you are using; your reports will be tracking different metrics. 150 CU IDOL SELF LEARNING MATERIAL (SLM)
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