1. The document discusses campaign optimization through the use of business intelligence and data mining. It outlines the key concepts, definitions, and typical campaign management lifecycle.
2. Target group definition is an important part of campaign design and involves profiling customers and selecting targets using segmentation schemes and data-driven approaches. Performance is analyzed by examining campaign response data and modeling customer behavior.
3. Optimization helps ensure the right treatment is provided to the right customer through the right channel at the right time, improving customer understanding, flexibility, reliability of execution, and measurement.
The document outlines a three-week marketing analysis plan. Week 1 involves establishing a value creation framework by understanding current marketing metrics, operational processes, and customer metrics. Week 2 focuses on finalizing the scope and approach, including data extraction requirements. Week 3 consists of performing a value analysis and documenting the results. The plan includes numerous meetings and discussions to gather information on historical campaign performance, review documents, define the analysis scope, and finalize the value analysis. The overall goal is to define a campaign pilot to test new marketing initiatives and business models.
Barbara Canning Brown Toys R Us senior managment presentation -- CRM VISIONCRM Strategies, LLC
Toys R Us had been driving its response business from the program level rather than the customer. I saw a tremendous opportunity to grow sales and bottomline by introducing an RFM segmentation and propensity modeling program. The RFM test programs delivered increment 640% lift in response and +6M in incremental profit. It was a huge win for the company
Marketing Campaign Management & Execution Process Final SubmissionPoonam Gupta
This document discusses a marketing campaign management process and tool that was developed to address several requirements. The tool integrates data from multiple sources, automates processes, enables scoring and profiling, tracks performance, and provides reporting and analytics. It establishes a framework for campaign planners to set targets, gauge return on investment, and ensure budget fulfillment. The tool utilizes past campaign performance to develop "yield curves" that help predict campaign phasing and outlook over multiple quarters. This provides a more scientific approach than relying solely on intuition.
The implementation of the RFM segmentation at Toys R Us had scheduled touch points where progress, testing approach and future developments were reviewed. This was one of those meeting with Barbara Canning Brown leading the meeting and Eleanor Hong, Harte Hankes and our analytics vendor in attendance
This slide provides a quick overview of different aspects of marketing research. This ppt is expected to help researchers, faculties, and students to understand various aspects of Research and especially 'Marketing Research'.
Youtube link of the video in ppt: https://www.youtube.com/watch?v=Mm0g8mVHffE&feature=youtu.be
Dart builds sophisticated customer segmentation models using statistical techniques and intuition. The goal is to create distinct customer segments that are predictive of behavior and can be implemented for marketing purposes. Dart analyzes customer, transaction, and demographic data to develop segments. The segmentation process involves data preparation, analysis, model development, and finalizing the segments with descriptive profiles and financial analysis. Segments are monitored over time and recalibrated as needed to keep the segmentation strategy relevant.
1. The document discusses campaign optimization through the use of business intelligence and data mining. It outlines the key concepts, definitions, and typical campaign management lifecycle.
2. Target group definition is an important part of campaign design and involves profiling customers and selecting targets using segmentation schemes and data-driven approaches. Performance is analyzed by examining campaign response data and modeling customer behavior.
3. Optimization helps ensure the right treatment is provided to the right customer through the right channel at the right time, improving customer understanding, flexibility, reliability of execution, and measurement.
The document outlines a three-week marketing analysis plan. Week 1 involves establishing a value creation framework by understanding current marketing metrics, operational processes, and customer metrics. Week 2 focuses on finalizing the scope and approach, including data extraction requirements. Week 3 consists of performing a value analysis and documenting the results. The plan includes numerous meetings and discussions to gather information on historical campaign performance, review documents, define the analysis scope, and finalize the value analysis. The overall goal is to define a campaign pilot to test new marketing initiatives and business models.
Barbara Canning Brown Toys R Us senior managment presentation -- CRM VISIONCRM Strategies, LLC
Toys R Us had been driving its response business from the program level rather than the customer. I saw a tremendous opportunity to grow sales and bottomline by introducing an RFM segmentation and propensity modeling program. The RFM test programs delivered increment 640% lift in response and +6M in incremental profit. It was a huge win for the company
Marketing Campaign Management & Execution Process Final SubmissionPoonam Gupta
This document discusses a marketing campaign management process and tool that was developed to address several requirements. The tool integrates data from multiple sources, automates processes, enables scoring and profiling, tracks performance, and provides reporting and analytics. It establishes a framework for campaign planners to set targets, gauge return on investment, and ensure budget fulfillment. The tool utilizes past campaign performance to develop "yield curves" that help predict campaign phasing and outlook over multiple quarters. This provides a more scientific approach than relying solely on intuition.
The implementation of the RFM segmentation at Toys R Us had scheduled touch points where progress, testing approach and future developments were reviewed. This was one of those meeting with Barbara Canning Brown leading the meeting and Eleanor Hong, Harte Hankes and our analytics vendor in attendance
This slide provides a quick overview of different aspects of marketing research. This ppt is expected to help researchers, faculties, and students to understand various aspects of Research and especially 'Marketing Research'.
Youtube link of the video in ppt: https://www.youtube.com/watch?v=Mm0g8mVHffE&feature=youtu.be
Dart builds sophisticated customer segmentation models using statistical techniques and intuition. The goal is to create distinct customer segments that are predictive of behavior and can be implemented for marketing purposes. Dart analyzes customer, transaction, and demographic data to develop segments. The segmentation process involves data preparation, analysis, model development, and finalizing the segments with descriptive profiles and financial analysis. Segments are monitored over time and recalibrated as needed to keep the segmentation strategy relevant.
Marketing management involves choosing target markets and building relationships with them. Demarketing aims to reduce demand for a good or service to a level a firm can supply. Transaction-based marketing focuses on limited communications during exchanges while relationship marketing develops long-term partnerships for mutual benefit. Customer relationship management leverages technology to integrate stakeholders into all aspects of a business and satisfy customers.
CRM involves becoming customer-focused by understanding customer needs through market research and adapting to meet those needs. It focuses on strategically significant customers, like those with high lifetime value or who inspire change. Technology plays a key role in CRM by collecting customer data that can be used to personalize marketing and increase loyalty through financial, social, and structural relationship programs.
Microsoft Word - Customer Centric Sales Strategies - William SurmonWilliam Surmon
Cross selling is an important strategy for growing revenue, but should be done responsibly based on customer insights. A thorough analysis of the customer base can identify opportunities for profitable cross selling by segmenting customers based on factors like life stage, income, and existing product holdings. The potential for cross selling and increasing product usage can then be determined for each segment. This helps ensure customers are offered additional products they can benefit from and afford. Tracking attrition also provides insights to improve the customer experience.
This document discusses designing a metrics dashboard for a sales organization. It recommends identifying key performance metrics that support sales objectives and strategy to help managers effectively oversee the sales team. Some benefits of a dashboard include gaining insight into sales drivers, identifying areas needing improvement, and enabling performance benchmarking. The document provides a framework for selecting metrics based on both corporate perspectives and elements of sales performance. It also outlines a process for creating a dashboard that includes selecting appropriate metrics, designing the dashboard, and implementing it.
Customer Relationship Management unit 1 introductionGanesha Pandian
The document discusses customer relationship management (CRM). It defines CRM as a business strategy focused on identifying and building loyalty with profitable customers. CRM has evolved from functional approaches like sales automation to more strategic approaches. Relationship marketing aims to create long-term partnerships rather than isolated transactions. CRM provides benefits like increased revenue, customer retention, and knowledge. It requires organizational support and faces challenges like implementation difficulties.
1) Revenue management techniques help increase revenue but traditionally fail to account for demand generation functions like marketing. Integrating revenue management, marketing, pricing, and distribution channels allows firms to optimize total demand profit.
2) Under a total demand profit optimization framework, demand forecasts drive appropriate promotion strategies, customer-centric pricing considers customer value and willingness to pay, and customers are incentivized to book through most profitable channels.
3) Future benefits come from tightly coupling revenue management with customer intelligence and data to develop customer-centric pricing based on individual customer preferences, behaviors and value.
Equitec's production-based solutions are a result of the multidimensional data obtained from Consumer Dynamics, the company's proprietary information platform. By incorporating the consumer decision process (CDP) model with the Consumer Dynamics platform, similar variables can be recognized and analyzed to provide solutions for firms.
This document discusses developing an IT architecture for a global retail bank to meet expanding consumer expectations. It proposes using a Total Quality Management model with three principles: satisfy customer expectations, satisfy supplier expectations, and continuously improve processes. The scope is the sales and fulfillment functions. It analyzes key business components and identifies six priority solution enablers to modernize the architecture using a Quality Function Deployment approach.
Consumer Behavior project. Examine and define best ways for Consumer Research Company (Equitec) to target and reach new customers, along with suggesting new ways for the company to market itself.
This document discusses marketing information systems and marketing research. It defines the key components of a marketing information system, including accounting information systems, marketing research, and marketing intelligence. It also outlines the marketing research process from defining the problem to communicating results. Marketing research involves both primary and secondary data collection methods like surveys, experiments, observation, and focus groups. The goal of a marketing information system is to provide accurate, timely data to support marketing decisions.
Unit 9 covers marketing information management and marketing research. Chapter 28 discusses marketing research and the purpose of gathering market information. It defines marketing research as the process of gathering, analyzing, and reporting information related to marketing goods and services. A marketing information system is a set of procedures that regularly generates, stores, analyzes and distributes information for use in business decisions. Chapter 28 also discusses types of marketing research like quantitative research, qualitative research, attitude research, market intelligence, media research and product research. Chapter 29 continues the discussion of conducting various types of marketing research.
An complete guide to help small industries in framing there digital marketing strategy using tools like Google SEO, Adwords, Social Media Promotion and Email/SMS marketing along with case study.
The document summarizes notes from a peer group discussion on approaches to customer relationship management (CRM). Key takeaways included integrating CRM tools like Salesforce across departments for better information sharing, using customer surveys more frequently to drive continuous improvement, and developing customer scorecards to better segment the customer base and measure profitability. Future opportunities discussed capturing more customer data, analyzing it for strategic insights, and empowering customers with self-service options.
The document outlines the key steps in the marketing research process:
1. Define the problem and research objectives by determining what specific questions need to be answered.
2. Develop a research plan by determining the appropriate data sources, research methods, instruments, sampling approach, and contact methods.
3. Collect the information by executing the research plan, being careful to avoid errors.
4. Analyze the collected information through statistical analysis and data tabulation.
5. Present the findings to management in a way that is directly relevant to the defined problem.
6. Allow management to make decisions informed by the research findings.
The document provides an overview of key concepts from chapters in Kottler and Wood related to collecting market information, forecasting demand, and analyzing a company's current situation. It discusses developing a marketing information system, types of internal and marketing data, the marketing research process, and variables that impact demand forecasting. It also outlines analyzing a company's internal factors like resources, offerings, results and relationships as well as external macroenvironmental and microenvironmental trends that influence strategic decisions.
1) A customer profitability analysis evaluates the costs and revenues assigned to segments of a company's customer base. It focuses on determining which customers are profitable versus unprofitable.
2) The general approach involves segmenting customers, calculating the revenue and costs attributable to each segment using activity-based costing, and then analyzing the profitable versus unprofitable segments.
3) A case study showed an insurance company used customer profitability analysis to identify that recently retired customers were unprofitable for a certain policy, so it adjusted agent commissions to discourage selling to that segment.
1) The document discusses various aspects of knowledge-based marketing such as segmentation, positioning, promotion, product development, pricing, and customer relationship management.
2) It emphasizes the importance of understanding customer needs and behaviors through market research and data analysis to inform marketing strategies and decisions.
3) New technologies like data mining, customer databases, and digital tools allow companies to gain deeper insights into customers and customize their marketing accordingly.
Managing marketing information to gain customer insights. MarketingDearMudassir
This document provides an overview of principles of marketing and managing marketing information to gain customer insights. It discusses assessing marketing information needs, marketing research, and analyzing and using market information. Specific topics covered include marketing information systems, assessing marketing information needs, developing and collecting marketing information through research, analyzing the information using tools like CRM, and distributing and using the marketing information.
Contact strategy boosts response and limits opt-outHanson Wade
The diminishing effectiveness of ongoing conference marketing activities lead a well known IT conference producer to adopt an analytics-lead approach to data segmentation and sourcing. Conversion rates rose whilst costs and opt-outs fell, ensuring the ongoing value of the marketing database.
This document discusses how website analytics can be used to track online visitor behavior and optimize website effectiveness. Website analytics collects data on internet activity to determine how visitors are using a site and how they are finding it. This data can provide insights into how well marketing efforts are working, what visitors do on the site, how long they stay and more. Key metrics include pageviews, visits, bounce rates, session duration and conversion rates. The goal is to engage visitors and better understand their needs and behaviors.
Txtbuddies is a mobile marketing platform that allows advertisers to create and manage SMS campaigns. The platform provides tools for targeting campaigns by demographics like gender and age, as well as by country, city, and mobile carrier. It also offers analytics on viewer demographics and campaign performance. Campaigns can be created by selecting media content to include in messages, setting flight parameters like dates and caps, and defining targeting criteria. The dashboard provides consolidated views of campaign status and metrics to help users optimize future campaigns. Mediawire is the company behind the Txtbuddies platform and provides various mobile marketing solutions to clients.
Marketing management involves choosing target markets and building relationships with them. Demarketing aims to reduce demand for a good or service to a level a firm can supply. Transaction-based marketing focuses on limited communications during exchanges while relationship marketing develops long-term partnerships for mutual benefit. Customer relationship management leverages technology to integrate stakeholders into all aspects of a business and satisfy customers.
CRM involves becoming customer-focused by understanding customer needs through market research and adapting to meet those needs. It focuses on strategically significant customers, like those with high lifetime value or who inspire change. Technology plays a key role in CRM by collecting customer data that can be used to personalize marketing and increase loyalty through financial, social, and structural relationship programs.
Microsoft Word - Customer Centric Sales Strategies - William SurmonWilliam Surmon
Cross selling is an important strategy for growing revenue, but should be done responsibly based on customer insights. A thorough analysis of the customer base can identify opportunities for profitable cross selling by segmenting customers based on factors like life stage, income, and existing product holdings. The potential for cross selling and increasing product usage can then be determined for each segment. This helps ensure customers are offered additional products they can benefit from and afford. Tracking attrition also provides insights to improve the customer experience.
This document discusses designing a metrics dashboard for a sales organization. It recommends identifying key performance metrics that support sales objectives and strategy to help managers effectively oversee the sales team. Some benefits of a dashboard include gaining insight into sales drivers, identifying areas needing improvement, and enabling performance benchmarking. The document provides a framework for selecting metrics based on both corporate perspectives and elements of sales performance. It also outlines a process for creating a dashboard that includes selecting appropriate metrics, designing the dashboard, and implementing it.
Customer Relationship Management unit 1 introductionGanesha Pandian
The document discusses customer relationship management (CRM). It defines CRM as a business strategy focused on identifying and building loyalty with profitable customers. CRM has evolved from functional approaches like sales automation to more strategic approaches. Relationship marketing aims to create long-term partnerships rather than isolated transactions. CRM provides benefits like increased revenue, customer retention, and knowledge. It requires organizational support and faces challenges like implementation difficulties.
1) Revenue management techniques help increase revenue but traditionally fail to account for demand generation functions like marketing. Integrating revenue management, marketing, pricing, and distribution channels allows firms to optimize total demand profit.
2) Under a total demand profit optimization framework, demand forecasts drive appropriate promotion strategies, customer-centric pricing considers customer value and willingness to pay, and customers are incentivized to book through most profitable channels.
3) Future benefits come from tightly coupling revenue management with customer intelligence and data to develop customer-centric pricing based on individual customer preferences, behaviors and value.
Equitec's production-based solutions are a result of the multidimensional data obtained from Consumer Dynamics, the company's proprietary information platform. By incorporating the consumer decision process (CDP) model with the Consumer Dynamics platform, similar variables can be recognized and analyzed to provide solutions for firms.
This document discusses developing an IT architecture for a global retail bank to meet expanding consumer expectations. It proposes using a Total Quality Management model with three principles: satisfy customer expectations, satisfy supplier expectations, and continuously improve processes. The scope is the sales and fulfillment functions. It analyzes key business components and identifies six priority solution enablers to modernize the architecture using a Quality Function Deployment approach.
Consumer Behavior project. Examine and define best ways for Consumer Research Company (Equitec) to target and reach new customers, along with suggesting new ways for the company to market itself.
This document discusses marketing information systems and marketing research. It defines the key components of a marketing information system, including accounting information systems, marketing research, and marketing intelligence. It also outlines the marketing research process from defining the problem to communicating results. Marketing research involves both primary and secondary data collection methods like surveys, experiments, observation, and focus groups. The goal of a marketing information system is to provide accurate, timely data to support marketing decisions.
Unit 9 covers marketing information management and marketing research. Chapter 28 discusses marketing research and the purpose of gathering market information. It defines marketing research as the process of gathering, analyzing, and reporting information related to marketing goods and services. A marketing information system is a set of procedures that regularly generates, stores, analyzes and distributes information for use in business decisions. Chapter 28 also discusses types of marketing research like quantitative research, qualitative research, attitude research, market intelligence, media research and product research. Chapter 29 continues the discussion of conducting various types of marketing research.
An complete guide to help small industries in framing there digital marketing strategy using tools like Google SEO, Adwords, Social Media Promotion and Email/SMS marketing along with case study.
The document summarizes notes from a peer group discussion on approaches to customer relationship management (CRM). Key takeaways included integrating CRM tools like Salesforce across departments for better information sharing, using customer surveys more frequently to drive continuous improvement, and developing customer scorecards to better segment the customer base and measure profitability. Future opportunities discussed capturing more customer data, analyzing it for strategic insights, and empowering customers with self-service options.
The document outlines the key steps in the marketing research process:
1. Define the problem and research objectives by determining what specific questions need to be answered.
2. Develop a research plan by determining the appropriate data sources, research methods, instruments, sampling approach, and contact methods.
3. Collect the information by executing the research plan, being careful to avoid errors.
4. Analyze the collected information through statistical analysis and data tabulation.
5. Present the findings to management in a way that is directly relevant to the defined problem.
6. Allow management to make decisions informed by the research findings.
The document provides an overview of key concepts from chapters in Kottler and Wood related to collecting market information, forecasting demand, and analyzing a company's current situation. It discusses developing a marketing information system, types of internal and marketing data, the marketing research process, and variables that impact demand forecasting. It also outlines analyzing a company's internal factors like resources, offerings, results and relationships as well as external macroenvironmental and microenvironmental trends that influence strategic decisions.
1) A customer profitability analysis evaluates the costs and revenues assigned to segments of a company's customer base. It focuses on determining which customers are profitable versus unprofitable.
2) The general approach involves segmenting customers, calculating the revenue and costs attributable to each segment using activity-based costing, and then analyzing the profitable versus unprofitable segments.
3) A case study showed an insurance company used customer profitability analysis to identify that recently retired customers were unprofitable for a certain policy, so it adjusted agent commissions to discourage selling to that segment.
1) The document discusses various aspects of knowledge-based marketing such as segmentation, positioning, promotion, product development, pricing, and customer relationship management.
2) It emphasizes the importance of understanding customer needs and behaviors through market research and data analysis to inform marketing strategies and decisions.
3) New technologies like data mining, customer databases, and digital tools allow companies to gain deeper insights into customers and customize their marketing accordingly.
Managing marketing information to gain customer insights. MarketingDearMudassir
This document provides an overview of principles of marketing and managing marketing information to gain customer insights. It discusses assessing marketing information needs, marketing research, and analyzing and using market information. Specific topics covered include marketing information systems, assessing marketing information needs, developing and collecting marketing information through research, analyzing the information using tools like CRM, and distributing and using the marketing information.
Contact strategy boosts response and limits opt-outHanson Wade
The diminishing effectiveness of ongoing conference marketing activities lead a well known IT conference producer to adopt an analytics-lead approach to data segmentation and sourcing. Conversion rates rose whilst costs and opt-outs fell, ensuring the ongoing value of the marketing database.
This document discusses how website analytics can be used to track online visitor behavior and optimize website effectiveness. Website analytics collects data on internet activity to determine how visitors are using a site and how they are finding it. This data can provide insights into how well marketing efforts are working, what visitors do on the site, how long they stay and more. Key metrics include pageviews, visits, bounce rates, session duration and conversion rates. The goal is to engage visitors and better understand their needs and behaviors.
Txtbuddies is a mobile marketing platform that allows advertisers to create and manage SMS campaigns. The platform provides tools for targeting campaigns by demographics like gender and age, as well as by country, city, and mobile carrier. It also offers analytics on viewer demographics and campaign performance. Campaigns can be created by selecting media content to include in messages, setting flight parameters like dates and caps, and defining targeting criteria. The dashboard provides consolidated views of campaign status and metrics to help users optimize future campaigns. Mediawire is the company behind the Txtbuddies platform and provides various mobile marketing solutions to clients.
This document discusses Datamine's services for telecommunications companies, including building a customer-centric IT infrastructure to enable behavioral modeling and advanced customer segmentation using metrics, attributes, demographics and behavior scores. It provides solutions to simplify understanding complex customer data by encapsulating data handling complexities and implementing procedures to provide reliable customer information. Datamine also offers consulting services in IT, analytics, CRM and BI including requirement gathering, system architecture, data modeling and user interface design using standards like UML and RUP.
eMarketer Webinar: Mobile Ad EffectivenesseMarketer
The amount spent on mobile display advertising is expected to increase dramatically in 2014 as companies like yours shift budgets from desktop to mobile. But as you spend more on mobile, are you confident the metrics you’re using to gauge the effectiveness of your ad spend are valid? Topics in this webinar include: How have performance metrics for mobile display ads changed during the past year? Where are prices headed, and how does mobile display compare with desktop? Which mobile display ad formats are most effective—banners, rich media, video, social, local, native? What needs to be improved to further increase the effectiveness of mobile display ads?
This document outlines a marketing campaign plan for a new mobile banking application launched by First Citizen's Bank. The campaign's objectives are to raise awareness of the new app to 40% of target customers and achieve trial usage rates of 50% within 1 year and regular usage rates of 30% within 1 year. The 6-month, $1.7M multi-channel campaign uses print, broadcast, outdoor, and internet advertising to promote the app's benefits like convenience and security to their target audience of Gen X professionals in the East Coast. Key messages are that mobile banking saves time while maintaining the bank's focus on personal relationships.
This document provides information about value added services (VAS) in the mobile industry. It defines VAS as non-core services beyond standard voice and fax. Examples include ringtones, games, music, and information services. The document discusses how VAS has become important for mobile operators as a source of additional revenue due to declining average revenue per user from traditional services. It outlines the evolution and architecture of VAS and provides lists of major VAS categories and companies in India.
The album artwork shows the artist provocatively dressed on a beach towel, giving off a "california vibe" to match the album title. Her bold hair color and the artwork's summery feel suggest carefree music for relaxed listeners. The imagery aims to highlight the type of people who would enjoy the music.
The title "Teenage Dream" indicates youthful songs to appeal to a young audience. A collaboration with Snoop Dogg aims to introduce new elements and fans from different genres. The single "California Girls" ties in with the carefree, provocative imagery often associated with Californians. The record label selects popular artists, so being signed is a positive sign for the music.
A2 Cross Media Promotion Campaign Analysisruthers64
This document provides guidance on analyzing promotional materials for a music album, including a digipak and poster. It outlines key elements to examine for each material, such as the main image, typography, composition, color scheme, and mode of address. Specific aspects are identified for different sections of the digipak, including the front and back covers. The document also provides examples of past student work and prompts the reader to introduce the artist, analyze each section of the materials, and relate design elements to audience appeal and music genre.
The document discusses key aspects of procurement and order processing including:
1) Procurement refers to receiving, recording, filling, and assembling orders for shipment. It involves identifying suppliers, soliciting proposals, selecting suppliers, and reviewing supplier performance.
2) Order processing includes activities like creating sales orders, checking inventory availability, scheduling deliveries, generating billing documents, and tracking payments.
3) Master data like customer, material, and pricing information is critical for minimizing errors during order processing.
Google Analytics vs Omniture SiteCatalyst vs In-ouse Webanalytics at iMetricsRoman Zykov
This document compares Google Analytics, Adobe/Omniture SiteCatalyst, and an in-house web analytics system. It provides an overview of Wikimart's custom system, including its data collection, storage, and users. Key areas of comparison include commerce metrics, campaign management, data export/import, product analytics, and support. The document concludes that for a large e-commerce site like Wikimart, SiteCatalyst is best for deep product analysis and managing a large number of marketing campaigns, while an in-house system enables deep analytics and integration with offline data.
The document describes Datamine's campaign management platform. It includes modules for defining target groups and campaigns, executing campaigns through various channels, analyzing campaign performance, and reporting. The platform uses customer data and segmentation rules to identify target groups. It allows interactive profiling and testing of target groups. Campaign results can be monitored through specialized reports.
11 Steps to Analyze Data for Campaign PerformanceStrongView
To succeed in today's rapidly evolving marketing landscape, you need to understand how to collect, analyze, and leverage the massive and varied amount of data available. A system of data analysis, usable by data novices and ninjas alike, can unlock your campaigns’ performance potential.
Hear from StrongView’s Senior Strategist, Catherine Magoffin, as she lays out a step-by-step, soup to nuts process for data analysis, focused on digital marketing performance.
Key Topics
* Why it is so important to begin utilizing your customer data, today
* 11 Steps for harnessing your customer data into action
* Real life examples of success from Cooking.com and Redfin
The document discusses target group analysis for communication projects. It provides an overview of the topic, including what target group analysis is useful for, important information to gather, and common methods used. These methods include quantitative analysis through statistical data and qualitative analysis using interviews, focus groups, and observations. The document also provides examples of target group descriptions and discusses how quantitative and qualitative methods can be combined in analysis.
The document provides a post-campaign report for a Google AdWords campaign run by GOMC students for PureFit protein bars. It includes sections on industry context, evolution of campaign strategy, key results including high click-through rates for nutrition-focused ads, and recommendations. The group learned about effectively optimizing AdWords campaigns, communicating with advertisers and clients, and that customers searching gluten/soy-free terms engaged well with PureFit's products. Challenges included limited availability and diverse skills, which were addressed through delegation and frequent emails.
Data Mining in telecommunication industrypragya ratan
Telecommunication companies generate huge volumes of data from their operational systems. They use data mining methods and business intelligence technology to handle business problems by analyzing call detail, customer, and network data. The main applications of data mining in telecommunications include fraud detection, network fault isolation, and improving market effectiveness. Data mining helps telecom companies detect fraud, gain customer insights, retain customers, determine profitable products and services, and identify factors influencing customer call patterns.
This document provides an overview of data mining in the telecommunications industry. It discusses how telecom companies generate tremendous amounts of data and can use data mining tools to extract hidden knowledge and insights from large datasets. Specifically, data mining allows telecom companies to better understand customers through segmentation and profiling, detect fraud, analyze network performance, and identify factors that influence customer call patterns to improve profitability. The document also covers types of telecom data, data preparation techniques like clustering, and applications of data mining such as marketing, fraud detection, and network fault isolation.
How to Report Marketing Results to Your ClientsHubSpot
The document provides guidance on how to effectively report marketing results to clients in order to maintain retainers, motivate collaboration, and create opportunities for upselling and referrals. It recommends focusing reports on key metrics like traffic, leads, and sales; telling the results as a story with highlights, challenges, and next steps; and scheduling regular reporting meetings with all stakeholders to review performance and get feedback. Case studies are also presented showing how consistent reporting meetings helped improve clients' marketing and increase their business results.
This document provides an overview of application trends in data mining. It discusses how data mining is used for financial data analysis, customer analysis in retail and telecommunications, biological data analysis, scientific research, intrusion detection, and more. It also outlines statistical and visualization techniques used in data mining as well as privacy and security considerations. The document concludes by encouraging the reader to explore additional self-help tutorials on data mining tools and techniques.
Charlotte Motor Speedway is launching a social media campaign to increase awareness, viewership, and revenue. The campaign will target business professionals aged 25-55 and focus on promoting CMS's corporate offerings and building relationships through social media. The campaign theme is "Life's a race, get on track" and will position CMS as an escape from stress and opportunity for work-life balance. Executions include updating CMS's website and social media channels like Facebook, Twitter, LinkedIn, and a new blogger page and mobile app to engage fans.
Data mining is an important part of business intelligence and refers to discovering interesting patterns from large amounts of data. It involves applying techniques from multiple disciplines like statistics, machine learning, and information science to large datasets. While organizations collect vast amounts of data, data mining is needed to extract useful knowledge and insights from it. Some common techniques of data mining include classification, clustering, association analysis, and outlier detection. Data mining tools can help organizations apply these techniques to gain intelligence from their data warehouses.
Business intelligence (BI) provides tools for exploring, analyzing, and modeling large amounts of complex data. It consists of statistical modeling, data mining, and multidimensional data exploration technologies. BI is built on well-defined data marts and models customer data to provide customer intelligence. It uses several technologies to support decision making, CRM, customer loyalty, campaign management, and marketing. BI requires integrating data from various sources into a data warehouse where advanced analytics can be performed to generate insights.
This document provides an overview of customer segmentation techniques and applications for telecommunications. It defines customer segmentation as splitting a customer database into meaningful groups based on specific criteria. The goals are to gain customer insights, enable targeted marketing, and achieve competitive advantages. Various types of segmentation are described, including structural, categorical, and behavioral. Examples are given using dimensions like tenure, profitability, and risk. Effective customer metrics, technologies, infrastructure, and the segmentation lifecycle are also outlined.
Feedback Management System The Criterion platform is a modern IT infrastructure which simplifies and empowers customer and employee survey lifecycle. Offers a new range of possibilities including continuous data flows (towards your marketing databases) and real-time analysis of the results. Corporate Criterion lets you design complex questionnaires and define surveys in terms of participants - consumers to be asked, execution resources, planning and administration. Electronic questionnaires become available to the authorized users, posting the answers directly to your database systems (data warehouse or marketing database). Data analysis and presentation is easier than ever through powerful reports performing in real time mode. Either
The document provides information on campaign management best practices including campaign preparation, execution, and tracking. It discusses setting goals and targets, defining responses, building the campaign, adding members, and mass email. Campaign success can be measured using Salesforce's standard reports or custom reports to analyze metrics like responses, conversions, opportunities, and ROI. Integrating email marketing partners allows sending mass emails while complying with daily limits.
This document discusses customer segmentation and provides details on its various phases and processes. It is divided into the following key sections:
1. It outlines a three phase customer segmentation framework: customer segmentation, planning and execution, and institutionalization.
2. It then provides more details on the customer segmentation analytics process, including defining objectives, identifying relevant variables, data preparation, modeling, scoring, profiling segments, and identifying segment strategies.
3. Various statistical tools for segmentation like cluster analysis and CHAID are mentioned. Example attributes for segmenting banking customers and IT company customers are also listed.
The document discusses customer relationship management (CRM) strategies and the use of data in CRM. It describes the C-MAT model for customer management, which involves understanding customer value, behavior and attitudes. It also discusses integrating customer data into CRM strategies using tools like data warehousing and data mining to collect and analyze large amounts of customer data. The document provides examples of how companies can use data mining techniques like correlation, segmentation and propensity analysis to gain insights into customers.
Dart builds sophisticated customer segmentation models using statistical techniques and intuition. The goal is to create distinct customer segments that are predictive of behavior and can be implemented for marketing purposes. Dart analyzes customer, transaction, and demographic data to develop segments. The segmentation process involves data preparation, analysis, model development, and validation of segments. Segments are then profiled and analyzed financially to optimize marketing strategies.
Customer Feedback Management
Corporate Criterion enables systematic, on-going user experience management and analysis, across a wide range of customer touch points - continuous user experience feeds towards your management dashboards.
The Survey process. Redefined
Design complex, structured questionnaires, define surveys in terms of target group (consumers to be contacted), execution resources, planning and administration. Depending on the configured channels and timing, consumers will be invited to participate as they become eligible according to target group membership, triggers and randomization.
Customer experience measurements through Corporate Criterion become parts of the customer record – within the data warehousing or the Marketing database – ready to be cross-analyzed against any customer dimension and attribute.
The document discusses how predictive analytics can be used in marketing. It provides examples of how retailers have used techniques like regression analysis, customer segmentation, and predictive modeling to 1) forecast demand based on retail data and factors, 2) determine optimal pricing, and 3) develop predictive models for timely ordering. Additionally, it describes how an advertising company used multivariate analysis and predictive modeling to determine the most effective advertising campaigns. Overall, the document outlines how predictive analytics can provide competitive advantages like increased sales and customer retention for businesses.
Customer intelligence enables marketing experts to design targeted promotions and programs through analyzing customer data to improve customer experience and satisfaction. It provides insights from both individual customer and overall market perspectives to inform strategic CRM design and decisions. Customer intelligence modules are integral parts of CRM implementations. It follows a holistic approach using statistical analysis, data mining, and information technologies to generate the most value from customer data for successful CRM strategies.
Design complex, structured questionnaires, define surveys in terms of target group (consumers to be contacted), execution resources, planning and administration. Depending on the configured channels and timing, consumers will be invited to participate as they become eligible according to target group membership, triggers and randomization.
Customer experience measurements through Corporate Criterion become parts of the customer record – within the data warehousing or the Marketing database – ready to be cross-analyzed against any customer dimension and attribute.
The document discusses customer relationship management (CRM) and its key aspects. It defines CRM as a business strategy and infrastructure that enables companies to increase customer value, loyalty, and retention by tracking and managing customer interactions. The document categorizes CRM into strategic, operational, analytical, and collaborative types and notes operational and analytical CRM focus on direct customer interactions and understanding customers respectively. It also outlines requirements for effective CRM software and discusses how CRM supports marketing, employee relationship management, and partner relationship management goals.
Case Studies - Customer & Marketing Analytics for Retail Gurmit Combo
The document discusses three case studies involving customer intelligence and marketing effectiveness services:
1. A luxury retailer case study where customer segmentation and profiling identified their most valuable customers to focus relationship management efforts.
2. A technology company case study where product association analysis and scoring identified accounts likely to purchase docking stations for targeted cross-selling.
3. A CPG company case study where regression modeling decomposed the impact of price, promotion, competition and cross-category effects on sales volumes, revealing promotion strategy optimizations.
Marketing analytics is the study of consumer data to evaluate marketing performance and optimize campaigns. It involves collecting, cleaning, and analyzing consumer data using statistical techniques to understand consumer behavior, refine marketing strategies, and predict future trends. Marketing analytics helps target consumers based on their interests and serve them the right messages at the right time through the right channels. It evaluates past marketing performance, reports on previous campaigns, and predicts future trends to improve marketing plans.
This exercise provided me with the opportunity to tackle real-world scenarios and challenges, showcasing my creativity and expertise. As a seasoned professional, it allowed me to push my limits and think outside the box.
This a a graduate course presentation in current marketing issues relating to BI (business intelligence). Oracle 2006 white paper was extensively referenced as well as Mr Van Den Poel's work "Identifying the slope of a customer".
The document discusses Customer Relationship Management (CRM). It explains that CRM involves collecting customer data, analyzing it to identify target customers, developing CRM strategies, and implementing those strategies. CRM aims to improve customer satisfaction and enhance sales through better management of relationships with customers. It allows organizations to provide personalized customer service, increase customer retention, and gain insights into customer behavior. The key aspects of CRM include operational CRM, analytical CRM, collaborative CRM, and geographic CRM.
The global airline needed to shift its strategy to focus on efficiency while maintaining customers during an economic recession. It wanted a targeting solution for marketing that could be used globally and for individual markets to drive efficiency, effectiveness, and inform strategy. Our solution built a behavioral targeting framework using customer value, travel behaviors, air miles, partner engagement, and communications as filters. This agile framework provided insights to prioritize marketing and streamline communications strategies, reducing costs while increasing gains equivalent to the total loyalty marketing budget in the first year.
NATIONAL INSTITUTE OF DIGITAL 3MARKETINGtherealone799
NIDM (National Institute Of Digital Marketing) Bangalore Is One Of The Leading & best Digital Marketing Institute In Bangalore, India And We Have Brand Value For The Quality Of Education Which We Provide. Our Curriculum/ Courses Are Designed with Practical knowledge are Fully For Job Orientation Bases. We have the best curriculum, trainers and unlimited practical hours on live project.
https://wiseinvestoronline.blogspot.com/2024/06/why-privacy-focused-marketing-is-future.html
Similar to Campaign optimization using Business Intelligence and Data Mining (20)
The document discusses how companies can foster innovation during the COVID-19 pandemic. It argues that innovation is more important than ever to help companies adapt and spot new opportunities. Some key points are:
1) Companies should invest in innovation to increase opportunity discovery and improve employee morale.
2) To empower remote innovation, companies can create an online innovation portal with resources, ideas, and a community for innovators.
3) Strategic initiatives like prototyping as a service, measuring innovation engagement, and recognizing top performers can help establish innovation as an "always-on" function.
The Minimum Viable product and why it is critical for a startup. How to get from an idea to an MVP through a prototype. How to speed up your software prototyping process. Techniques to help you experiment and capture feedback.
As a founder, It is very important to deeply understand the notion of the MVP. You need to use it as part of a method or a framework to help you make better product decisions – and mitigate or avoid known risks. So this definition by Eric Ries, defines the MVP as ‘ …a product with just enough features to satisfy early customers, and to provide feedback’.
Your MVP must solve the problem for your customers; your users should get value out of it; your MVP should be good enough so the users engage with it and potentially pay for it;
Your early customers should be so happy with your product to act as promoters – to recommend it to others and publicly share positive feedback.
https://www.theinnovationmode.com/
Moving from an idea to a Minimum Viable Product
A quick introduction to the notion of the MVP – what a Minimum Viable Product is, why you need, and why it is a critical success factor for startups
How to move from a problem to a properly-defined MVP - steps, activity and best practices to follow
the book: https://www.theinnovationmode.com/
No matter the type (corporate or public one) a hackathon is always a great opportunity to showcase your talent and skills: yes, hackathons are also about team spirit, innovation, collaboration and fun but the primary motivation of the typical participant is to win it and capitalize on that (reputation, opportunity, networking).
The competition is tough, the event itself is demanding with several hours or even days of ideation, coding, iterations and in some cases team challenges.
Is a great idea enough to win a hackathon? The short answer is NO.
You also need the right team, working practices, mentality and the right strategy. Consider the following practical hints to … hack the next hackathon.
Corporate hackathons can inspire teams and promote creativity if properly run. To be successful, a hackathon needs clear objectives, participation rules, deliverables, and assessment criteria. It should generate novel ideas and prototypes, with the goal of boosting innovation culture. Success is defined by participation rates, number of actionable ideas, and impact on team dynamics and morale. The event involves a preparation phase, intensive work period, and assessment of deliverables. Winners receive awards like bonuses or resources to further develop ideas. Overall, hackathons can drive cultural shifts and produce strategic product concepts.
What’s next on Artificial Intelligence, Augmented Reality, Robotics, Data & Visualization and Blockchain
Technology is moving at an incredible pace. We live in an amazing era where things like autonomous cars, personalized medicine and quantum computing are becoming real as we speak; Artificial Intelligence, crypto-currencies, advanced automation, deep learning and concepts like Universal Basic Income are about to reshape our world.
The years to come will bring impressive technological breakthroughs with massive impact on our lives, markets and societies. In our connected world, with the unprecedented level of information, knowledge and ideas exchange, innovation is happening continuously, at scale and in several forms; it is driven by corporations, secret labs, universities, startups, research scientists or simply by thousands of creative individuals across the globe.
Datamine provides data-intensive information technology solutions & services for Telecoms, Banking & Retail industry. Our offering answers the needs of modern management for analytics, process insight, business & market intelligence.
Our products are based on CAS platform - Competition Analysis System - which enables a new range of capabilities for Market insight, price analytics, personalized customer offerings & market strategy. Click 'download' below to get a full corporate profile.
Expertise
Business Intelligence
Market Intelligence
Price Analytics
Data mining
Customer Segmentation
Marketing databases
Recommendation engines
Online CRM components
Campaign Optimization
An interactive product development & evaluation framework …… enabling quick definition of new banking products, and analysis against actual usage
A powerful Customer Interaction framework …… automating and optimizing product recommendations, according to strict business rules
A sophisticated Customer Analytics platform …… enabling customer, billing & usage analysis along with product suitability measures
CAS/R enables marketing users to browser and analyze competition in terms of pricing on specific products. Beyond competition insight, CAS/R offers powerful tools for actionable decisions on your pricing policies, loyalty programs, personalized offers and more.
Intelligent Online marketing
CAS/R can be defined as an analytics framework for modern online retailers offering a wide range of marketing applications including product management, market analysis, Business Intelligence and predictive modeling. It is based on a powerful pricing database against your product catalogue and the ‘market’.
CAS/R includes several additional components enabling real-time, activity-based proposal generation for existing customers, dynamic product pricing schemes, personalized discount models, interactive market analysis and the intelligent alerting suite.
Competition Analysis, for Telcos
Datamine’s Competition Analysis System is a sophisticated, highly engineered data processing and visualization platform providing telcos with outstanding analytical capabilities.
Tariff Optimization, Market Insight
CAS encapsulates the complexity of the typical, fuzzy telecom market enabling telecom professionals and decision makers to understand, study and model competitors, products and strategies through a set of well-defined, easy-to-use business components. By utilizing a powerful billing engine and numerous intelligent data management components, CAS makes tariff optimization and relevant decision-making a simple, robust and fruitful business procedure.
CAS extends to an interactive decision support environment with a wide range of KPIs and statistical figures on the evolution of the customer, tariff suitability, tariff performance, market positioning, competitor’s strategy and more.
Example apparatus and methods provide a gamified adaptive digital disc jockey (DDJ) that optimizes a media presentation based on an audience response according to a gamification process. The DDJ receives data about audience members and determines a state and dynamic of the audience in response to a portion of the media presentation or the dynamics of the media presentation. The DDJ identifies audience leaders or laggards from gamification data or patterns about audience members. The gamification scores may be computed from the reactions or behaviors of audience members. The DDJ automatically adapts the media presentation based on the state and dynamic of the audience in general and/or based on the reactions of people with certain gamification scores. Data relating states, dynamics, gamification scores, and tracks or sequences of tracks from previous presentations may help plan and optimize the presentation and may be stored for planning future presentations.
A device is disclosed for enabling a user to navigate between content using gaze tracking. The device includes a presentation component for presenting a plurality of content to a user in user interface (UI) windows. A camera captures the gaze of the user, and components described herein control focus of the UI windows presented to the user based on the gaze. Multiple UI windows of varying content may be displayed to the user. A processor determines, from the captured gaze, where the user is looking, and the UI window located at the user's gaze point is brought into focus and controlled by the user's gaze. As the user looks to other UI windows, focus is seamlessly moved from one UI window to the next to correspond with what the user is looking at, providing an implicit way to control digital content without conventional computer commands, actions, or special requests.
ORGANIZATION, RETRIEVAL, ANNOTATION AND PRESENTATION OF MEDIA DATA FLES USING...George Krasadakis
A computer system automatically organizes, retrieves, anno
tates and/or presents media data files as collections of media
data files associated with one or more entities, such as
individuals, groups of individuals or other objects, using
context captured in real time from a viewing environment.
The computer system presents media data from selected
media data files on presentation devices in the viewing
environment and receives and processes signals from sen
sors in that viewing environment. The processed signals
provide context, which can be used to select and retrieve
media data files, and can be used to further annotate the
media data files and/or other data structures representing
collections of media data files and/or entities. In some
implementations, the computer system can be configured to
be continually processing signals from sensors in the view
ing environment to continuously identify and use the context
from the viewing environment.
Datamine Ltd is a Greek software company that develops data-driven applications like CAS (Competition Analysis System), a tariff optimization tool, and Corporate Criterion, a customer satisfaction measurement platform. CAS allows telecommunications companies to analyze customer usage and tariff data, develop new tariffs, automate recommendations, and optimize customer interactions. The document describes the features and benefits of CAS for tasks like tariff development, negotiations, recommendations, and acquiring new customers.
Το ςφγχρονο ανταγωνιςτικό περιβάλλον, ςε ςυνδυαςμό με τθ διαρκϊσ εντεινόμενθ προςπάκεια των
επιχειριςεων για άμεςθ και εφςτοχθ ανταπόκριςθ ςτισ ανάγκεσ του πελάτθ, οδθγεί ςε απαιτθτικζσ και ςφνκετεσ
διαδικαςίεσ πϊλθςθσ - τόςο ωσ προσ τθν εκτζλεςθ όςο και ωσ προσ τθν παρακολοφκθςι τουσ. Ταυτόχρονα, οι
διαδικαςίεσ αυτζσ πρζπει να είναι ευκυγραμμιςμζνεσ με ςυγκεκριμζνεσ εςωτερικζσ πολιτικζσ, ςτόχουσ ανάπτυξθσ
ι και περιοριςμοφσ – όπωσ κακορίηονται από τθν εκάςτοτε διοίκθςθ. Η νζα αυτι πραγματικότθτα - πολλαπλζσ
(και κατά περίπτωςθ ανταγωνιςτικζσ) διαδικαςίεσ που εμπλζκονται ςτον κφκλο πώλθςθσ τθσ τυπικισ επιχείρθςθσ,
ςε ςυνδυαςμό με τισ ιδιαίτερα αυξθμζνεσ απαιτιςεισ από τθν πλευρά του πελάτθ- αναδεικνφει τθν ανεπάρκεια
των παραδοςιακϊν μεκόδων ανάλυςθσ πωλιςεων και προςδιορίηει τθν ανάγκθ για αποτελεςματική ανάλυςη
του κφκλου πώληςησ.
This document provides an overview of a specialized information system that combines technologies, statistical models, and business knowledge to automate and optimize the manual credit checking process for contract activations. The key objectives of the system are to automate and optimize credit checking, minimize bad debt, provide risk measurements at the customer level, support flexible business rules, and provide advanced reporting capabilities. The system architecture utilizes a three-tier design with components for scoring models, a customer viewer interface, rule management, and reporting. Customer data, accounts, credit scores, and business rules are used to make automated credit checking decisions.
Information technologies & Analytics for Telcos & ISPsGeorge Krasadakis
Datamine is a Greek analytics company founded in 2005 that provides data-driven solutions like CRM, business intelligence, and customer loyalty programs. It has a team with experience in statistics, data mining, and telecom/banking. Major customers include Greek banks and telecom companies for projects involving campaign management, data warehousing, customer risk assessment, and more. Datamine offers services around data preparation, modeling, reporting, and analytical applications to help customers better understand their data and customers.
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A powerful, high-performance, customer assessment & management platform, acting as a single point of
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information stored in your legacy systems and/or data warehouse. Our solution is based on a dynamic
customer analytics architecture that combines business knowledge with statistical models and cutting edge
software technologies in order to optimize customer interaction.
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
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[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
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The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
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Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
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2. http://www.datamine.gr
Outline
Key concepts & definitions
A common language regarding campaigns, the main dimensions & metrics involved
The need for campaign optimization
The typical campaign management lifecycle and the need for optimization
Designing the Target Group
Data-driven approaches for target group definition – use of BI and Data mining techniques
Performance Analysis
Analyze campaign response data, model customer responses, compile reports
Application within E-Business environments
Campaign, recommendation, profiling and personalization
3. http://www.datamine.gr
Key concepts & definitions
Campaign
A set of systematic promotional activities (multiple offers, scenarios & channels) against a well
defined target group (advanced business logic for accurate customer selection) within a controlled
environment (infrastructure for response gathering, reporting, analysis and modeling).
Campaign Management
Infrastructure & processes enabling efficient design (Target group definition - customer selection,
eligibility criteria, profile analysis), smooth execution (integration with communication channels) and
effective response analysis (response gathering, analysis, reporting and modelling).
Data Mining & BI (Business Intelligence)
−BI is based on several technologies & scientific areas such as information technology, multidimensional
data exploration technologies (OLAP), data mining, statistical modeling, text mining, visualization
techniques
−BI enables companies to explore, analyze, and model large amounts of complex data
−BI can greatly enhance Campaign Management processes from Design (TG definition), Execution
(efficient communication planning), to response analysis & modelling (exploratory and/ or with data
mining)
4. http://www.datamine.gr
The need for optimization
The ultimate goal
Enable the right treatment on the right customer at the right time through the right channel. This
further enables customer understanding (needs, preferences, usage & buying patterns) enabling
customer response analysis and modeling
The roadmap
Design, implement and automate solid campaign management processes. This will provide flexibility (in
handling customers, products and promotions), reliability (regarding execution, response gathering) and
robust measurement & analysis processes - functions. This will enable a systematic monitoring and
analysis framework to support decisioning in general
The business value
− Winning the performance game (On-time Schedule Indicator, Cost Per Activity)
− Customer insight - usage patterns, profiles and customer base trends may reveal significant
cross-selling or up-selling opportunities
− Assessment of marketing actions, special offers or campaigns can be assessed in detail using
customer responses and changes in usage patterns: The Closed Loop Marketing
− Retain (ensure) or increase Customer Satisfaction levels
5. http://www.datamine.gr
Campaign Management
System
Customer
database
Documents
& templates
Communication Channels
Campaigning: lifecycle
Target Group Definition
The MKT user interacts
with CMS in order to
explore the customer
base and design the
most effective target
group
1
Customer Profile Analysis
CMS retrieves customer
information in order to
provide sufficient
segmentation capabilities to
the MKT user
2
Target Group Release for
contact
List of customers –Target
Group- as defined from the
MKT user, and after
applying the selected,
predefined exclusion logic
3
Customer Communication
The offer assigned to the
campaign is being
communicated to the
customer according to the
predefined script or template
4
Customer Response
Customer responses are being
forwarded into the system for
campaign assessment,
monitoring and optimization
5
Campaign Analytics
Campaign performance
statistics, customer
demographics, campaign
lifecycle information, call center
performance reports and
analytics
6
Campaign performance
Assessment
Sufficient input for better
campaign design, customer
behavior modeling. Insight for
process monitoring, KPIs for
assessment studies
7
7. http://www.datamine.gr
Designing the target group
Using Segmentation schemes
effective schemes for categorizing and organizing meaningful groups of customers
Customer Profiling
the process of analyzing the elements (customers) of each segment in order to generalize, describe or
name this set of customers based on common characteristics. It is the process of understanding and
labeling a set of customers
The process
− the target group definition process is an iterative procedure aiming in compilation of a well
structured set of customers with certain degree of homogeneity regarding a set of attributes.
− Involves business knowledge, ideas & creative thinking as well as data-driven concepts, facts
and modelling activities
− Requires effective exploratory analysis and in-depth understanding of the customer base
− Can be optimized using advanced modelling techniques and data mining algorithms
8. http://www.datamine.gr
Designing the target group
The Physical Customer Structure
Physical Customer Identification is a critical point in customer segmentation & insight: A physical
customer may have several accounts with contradictive behavior regarding usage or payment. The
physical customer (a) must be correctly identified and (b) must be efficiently scored in the top level
Physical Customer
Usage History Usage metadata
Customer Care
& Contact History
Application, ordering &
payment History
Time Related Patterns
Statistical &
Data Mining Modeling
Analytics,
segmentation & profiling
Benefits
− A complete picture of the customer, in all dimensions (profitability, risk, loyalty, satisfaction etc)
− Elimination of contradictive communication attempts (bonus due to product A ‘performance’
while in collections procedure due to product B payment habits)
9. http://www.datamine.gr
Dimensions & Filters
Customer
-Risk Class
-Revenue Class
-Socio -Economic data
-Demographics
-Location data (GI)
-Tenure (CLS)
-Traffic Patterns
-Contact Patterns
-Prior Classifications
Product - Services
-Accounts, status & types
-Services & Tariffs
-other properties
Designing the target group: input
Target Group Design
Involves all the important aspects of each customer: risk, tenure, profitability, or Customer value must be
combined in order to explain or optimize a set of metrics or specific behaviors
Measures
-total revenue
-Balance by type (source)
-frequencies
-’recent’ statistics
-’lifetime’ statistics
-AMOU / average duration
-ARPU / average revenue
-Specific Traffic metrics (services
usage – destination analysis,
incoming vs outgoing etc)
-Churn Behavior
-Campaign Responses
-Customer Satisfaction
metrics
Metadata
− Macro segmentation for
management & decision support
and performance evaluation
purposes
− Micro segmentation schemes,
campaign specific, for product
development, up selling or cross-
selling program design, for loyalty
– churn management, marketing
actions
10. http://www.datamine.gr
Designing the target group: CBE
Customer & Products
Attributes enabling the
dynamic target group
definition
1
Dimensions & Measures
Enabling custom views of your
customer base
2
Customer Sample
Random sample of
Customers for verification
reasons
3
Customer Profiling
Analysis of the resulting
customer set versus any
combination of attributes
4
12. http://www.datamine.gr
Campaign response analysis
A Measurement Environment
A set of metrics, KPIs and predefined reports, enabling an instant picture of each specific campaign.
Reports also include suitable comparisons with ‘global constants’ such as group averages, baselines and
predefined limits thus enabling comparative performance analysis of a campaign.
Customer Contact History
Customer campaign memberships and response history (memberships, contacts, feedback, offers &
promotions attempted) should be maintained and further processed in order to generate related
customer metadata. This ‘customer communication history’ should also be available to other systems as
well, thus extending the knowledge regarding customers, their needs and preferences.
Detailed Campaign History
Campaign History & Reporting provide rich history of the full lifecycle of each specific campaign.
Information on campaign execution events can be used as markers against the evolution of the customer
base (reporting before and prior the campaign) for trends, indirect results or pattern identification.
Formal evaluation
ROI models, comparisons of expected results against actual, analysis versus initial statistical profiles of
the target group, all packed in standardized, well define reports
13. http://www.datamine.gr
Campaign response analysis
Campaign Analysis Cube
Analyze campaign response data in any meaningful way. Start with exploratory analysis, browsing the
results in order to see the shape of the response set. A powerful, high-performance environment for
browsing customer response data. Basic dimensions:
1. Customer segment: enables the projection of the target group of your campaign (and any subset
as well) against the available segmentation schemes
2. Customer Profile type: similarly the customer set can be analyzed in terms of well-known &
understood customer profiles
3. Channel: the channels available/ selected for the specific campaign. Enables analysis of
performance (for instance response rate against channel used and in combination with other
dimensions)
4. Offer: the actual promotion, offering to the customer
5. Contact Time: the time zone (day and time – according to schemes in use)
6. Timing: the time positioning of the communication event in terms of customer critical dates (e.g.
forthcoming contract expiration or renewal process)
7. Script: the actual communication ‘dialogue’ – how the offering has been proposed to the
customer
8. Agent profile: Characteristics of the agent involved (demographics, experience, seniority,
specialization)
14. http://www.datamine.gr
Campaign response analysis
Campaigns – working list
Quick or composite campaign search
functionality and the resulting
campaigns list. To be used as
navigation tool for exploring and
managing campaigns
1
Campaign Viewer
A set of different views against the
selected campaign (from sophisticated
analytics to execution oriented reports)
provide instant & accurate information on
the aspect of interest
2
Cohort Analysis
Specialized computations &
Charts provide direct insight
to campaign performance
factors. Quick tabulation
along with export utilities in
a standardized output
ensures optimum results
with minimum effort
3
15. http://www.datamine.gr
Campaign response analysis
Customer base mapping according to generated profiles
100
75
50
25
0
RevenueRank
Tenure Rank
0 25 50 75 100
Customer Profiles projected against by revenue & tenure
Response A
Response B
Response C
Response D
Response E
Response categories
Categorized customer
responses
Customer projection
Projected on a two
dimensional space
(revenue-tenure)
ranks, and colored by
response category for
the selected profile
16. http://www.datamine.gr
Applying Data Mining
Data Mining
refers to statistical and machine learning algorithms, applied in large amounts of data, aiming in
identifying hidden relations and patterns. Popular data mining models include decision trees,
clustering & association rules.
− Association rules can identify correlations between pages/content not directly or obviously
connected. May lead to previously unknown – not obvious- associations between sets of users with
specific interests thus enabling more efficient treatment of customer
− Clustering is a set of statistical algorithms aiming in grouping together items (customers) that present
at least a certain degree of homogeneity relevant to specific measures. In contrast, the ‘distance’
between groups is maximized, thus forming a physical ‘segmentation scheme’ for further processing or
event direct use.
− Classification refers to a family of algorithms that ‘learn’ to assign items to pre-defined (existing)
groups.
− Sequential Analysis is a methodology for unveiling patterns of co-occurrence
17. http://www.datamine.gr
Campaign response modeling
Sample rules as derived from Decision trees:
CreditLimit >= 15150,007 and ProfessionClass = 'Medical staff' > (positive=91%, negative=9%)
CreditLimit >= 15150,007 and ProfessionClass not = 'Medical staff'
and Residence not = 'ΘΕΣΣΑΛΟΝΙΚΗ - ΠΡΟΑΣΤΙΑ' > (positive=82%, negative=18%)
19. http://www.datamine.gr
Personalization: Definitions, Needs & Business Value
Personalization
− consists of mechanisms used to adapt a web-site in terms of information / content served or
services/ functionality enabled, based on user navigational patterns, their profiles and their
preferences.
− improves customer experience, resulting in more efficient actions through an ‘intelligent web
site’ able to adapt according to user’s profile. May dramatically improve customer (user)
satisfaction & Loyalty, usage boost, cross-selling & up-selling opportunities
Personalization within typical e-commerce environments can take the following forms:
− Recommendation. Determine suitable material (content, links, listings etc) for the specific user
and the specific session. The ‘suitability’ of the material is computed from data mining algorithms
which process large volumes of data and identify ‘hidden’ relationships.
− Localization. User’s physical geography (as registered), or retrieved (connection based) can be
used and ‘appropriate’ content is displayed
− Targeted Advertising. ads that are expected to interest the user most (based on data mining –
profiling & segmentation models)
− Email Campaigns. Personalized messages to highly targeted users (according to their
profiles/interests & segmentation schemes)
20. http://www.datamine.gr
Personalization: An overview
Website
I.T.
Infrastructure
CMS DOC
Billing
User Interaction
Session data that describe
typical user interaction with the
portal/ web site. Includes
requests, user registration and
preference data, navigational
information
1
2 3
User Request/ data
submission
registration and
preference data,
navigational information
Web Analytics Infrastructure Data mining
models
ETL
Data gathering,
Cleansing, preparation &
standardization,
data mining specific
transformations
Analytics Database
Customer profiles,
content structure &
Metadata, processed traffic
information
Recommendations
Engine
Reporting Engine
Personalized
Output
Personalized content
(links, documents),
controlled functionality
4
5
Systematic Raw Data Feed
Raw data describing key portal entities,
traffic data, content. Gathered
systematically from the ETL components for
further processing, analysis and modeling
Portal Personalization transaction
Portal submits visitor's identification data.
RE retrieves metadata, compiles a
Recommendation’s List and forwards it to
the portal
Personalized Data
Recommendations List
as served from RE
21. http://www.datamine.gr
Personalization: Data Requirements
User data includes information that can be used to define profiles of the physical user (individual
and/or company) such as:
− Demographics: gender, age, socioeconomic data, profession, education level, company
attributes etc
− Interests & preferences: communication settings, interests against specific content categories or
functionality offered (as submitted by the user through registration process)
− User experience: experience in the domains of interest, roles etc
Usage data consists of the set of data that describe in detail every single user-portal interaction.
A usually complex, large volume data set including log file information, session specific data,
content structure.
Environmental data refers to information describing the technological infrastructure enabling
each user to access services and content offered (hardware, software, operating system)
‘Portal data’ refers to information providing structural representation, content definitions, relations,
actions, processes (registration, applications, service activation, inquiries etc)
22. datamine ltd
Decision Support Systems
22 Ethnikis Antistasis ave
15232 Chalandri
Athens, Greece
T: (+30) 210 6899960
F: (+30) 210 6899968
info@datamine.gr
http://www.datamine.gr
George Krasadakis
Head of engineering
g.krasadakis@datamine.gr
Contact information
Editor's Notes
the typical lifecycle of a campaign, brief description. Must a.explain the lifecycle and b. show the directions of optimization, i.e. where is the waste of effort, money or negative results
show a hypothetical campaign response analysis using a cube (1-2 slides). The point is to demonstrate that there are patterns regarding customer response. These patterns can be spotted using BI – exploratory analysis and trigger analysts to new target group definition processes. A ‘campaign analysis cube’ may have dimensions such as customer cluster, segment, profile, key-demographics, channel used, agent profile, product offered, recency figures
our advice will be that there is a strong need for powerful multidimensional (exploratory in nature)
and also that further more advance modeling can be used (data mining).