Cenacle Research is engaged in building Predictive Analytics Engines for Automotive, Healthcare, Retail, Energy and BFSI sector. This presentation details how our Big data Analytics platform can help retail businesses in a brief manner.
Big Data offers: Actionable Insights that let you make Informed Decisions, with the capability to:
+ Gain Insight
+ Take Proactive action
+ Reduce waste
+ Plan better strategy
To know more, write to us at: http://cenacle.co.in/
This document discusses how analytics can be used across different functions in retail organizations like marketing, merchandising, finance, and operations. It provides examples of typical retail data structures and metrics used. It emphasizes building knowledge through deep data analysis and insights to make better business decisions. Key points covered include measuring the impact of marketing programs, examples of analytics dos and don'ts, and questions to ask when evaluating programs like CRM.
This document contains confidential information belonging to AAUM. It discusses various analytical techniques such as customer segmentation, market basket analysis, forecasting, and supply chain optimization that can be applied across industries. Case studies of companies like Tesco, Nieman Marcus, and Food Lion demonstrate how these techniques have been successfully used to increase sales, optimize operations, and improve customer experience.
This document discusses analytics and retail analytics. It defines analytics as discovering patterns in data through statistics, programming, and research. Retail analytics specifically aims to improve customer loyalty and sales. It does this by identifying valuable customers, understanding their preferences, and creating personalized shopping experiences through offers targeted to individual needs. Retailers can gather customer data through in-store and online analytics to gain insights that optimize performance.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
Numa era de mudanças organizacionais e perturbações globais sem precedentes, o relatório Global Marketing Trends 2022 apresenta as principais tendências de marketing, fruto dos desafios de negócio que enfrentamos
This document outlines an integrated demand planning approach used by an automobile company in India. It discusses the need for the approach due to the industry's growth and frequent new product introductions. The approach generates forecasts for new and existing products using data cleaning, lifecycle curves, seasonal and trend indices, and event impact adjustments. Forecasts are fine-tuned over time, improving accuracy. Benefits included forecast accuracy increasing from 67% to 85% and the ability to evaluate multiple scenarios.
This document describes an instant medicine delivery mobile app called Davakhaana. It summarizes the founders and mentors' experience, how the app works by allowing customers to order medicines through photos of prescriptions, the business model of earning 12-15% commissions from partner pharmacies, current status with 30 pharmacies and plans to expand offerings. It outlines competitors and advantages, provides financial projections seeking 3.5 crore in funding, and closes with contact information.
Ironside's VP of Strategy & Innovation, Greg Bonnette, delivered a presentation on "How to Build a Winning Strategy for Data & Analytics" to provide a framework for data-driven decision making.
This document provides an overview of the Indian e-commerce company Flipkart. It discusses Flipkart's products, pricing and promotion strategies, segmentation and targeting, reasons for registering in Singapore, ease of doing business there, competitors like Amazon, acquisitions of other companies, development of own products, strengths, weaknesses, opportunities, threats in a SWOT analysis, major investors, and awards/recognitions. Flipkart is India's largest online store and e-commerce platform, founded in 2007 and headquartered in Bangalore.
1) AI and automation technologies like RPA, machine learning, and computer vision can address uncertainties and inefficiencies in supply chains by optimizing tasks like demand forecasting, procurement, inventory management, and predictive maintenance.
2) Increased transparency through real-time tracking and monitoring enabled by technologies improves visibility across supply chains and drives efficiency.
3) Machine learning and behavioral analytics can make logistics operations safer by monitoring driver behavior and predicting accidents through advanced driver assistance systems.
The document discusses Walmart's marketing plan to launch its own brand of affordable fashion apparel. It analyzes Walmart's strengths as the world's largest retailer with loyal customers and everyday low pricing. However, it also examines weaknesses such as increasing expenses and competition. The marketing strategies proposed include segmenting customers based on income and thriftiness, targeting urban 20-35 year olds, and implementing strategies around product, price, place and promotion.
Legal issues uniform commercial code for ecommerceMukul kale
The Uniform Commercial Code (UCC) is a standardized set of laws and regulations for transacting business across state lines. The UCC code was established because differing state laws were making it increasingly difficult for companies to conduct interstate business transactions. The UCC code helped to create consistency in commercial transactions between states.
Flipkart : Strategies for an Industry Top-dog in the E-commerce space Suhasini Jain
The presentation was created for an industry leader : Flipkart and how it can retain its position in the market with respect to its competitors using a few basic strategies .
Predictive Analytics Project in Automotive IndustryMatouš Havlena
Original article: http://www.havlena.net/en/business-analytics-intelligence/predictive-analytics-project-in-automotive-industry/
I had a chance to work on a predictive analytics project for a US car manufacturer. The goal of the project was to evaluate the feasibility to use Big Data analysis solutions for manufacturing to solve different operational needs. The objective was to determine a business case and identify a technical solution (vendor). Our task was to analyze production history data and predict car inspection failures from the production line. We obtained historical data on defects on the car, how the car moved along the assembly line and car specific information like engine type, model, color, transmission type, and so on. The data covered the whole manufacturing history for one year. We used IBM BigInsights and SPSS Modeler to make the predictions.
1. Sales and marketing analytics uses descriptive, diagnostic, predictive, and mechanistic analytics types to generate insights from business data in areas like consumer behavior, customer segmentation, pricing, recommendations, and sales force performance.
2. Common applications of analytics include understanding consumer behavior, customer segmentation, marketing mix optimization, and sales force efficiency.
3. Popular tools for sales and marketing analytics include Zoho Analytics, Yellowfin, Looker, Microsoft Excel, and various report generation and data visualization software.
Drug market structure (Pharma in Indian Scenario)hemant vyas
This document provides an overview of the pharmaceutical industry in India. It discusses the growth and structure of the industry, both globally and within India. It notes that while India is a major producer of generic drugs, its research and development spending and capabilities remain relatively low. The industry in India is characterized by high profitability and concentration among the largest companies.
Over the past decade, the rise of social media has caused a huge shift in the way businesses interact with customers. Pharma, often thought of as a guarded industry when it comes to social, is upping its game and using social to reach a wide audience including patients and healthcare professionals.
Walmart is the world's largest retailer known for its low prices. It has adopted several innovative green initiatives to reduce waste and environmental impact, including high-efficiency refrigeration units, biodiesel trucks fueled by waste grease, organic and locally-grown products, and recyclable "super sandwich bales" to improve recycling. Walmart hopes these sustainability efforts will cut costs while gaining customer goodwill. The document discusses Walmart's global expansion and green strategies to maintain its competitive edge through innovation.
The document analyzes online shopping trends in Pakistan, specifically for the ecommerce platform Daraz.pk. It finds that while there is potential for growth, online shopping has been slow to take off due to lack of awareness, trust, reliable payment options and delivery infrastructure. The research found consumers prefer cash on delivery and rate convenience and product quality higher for online versus traditional shopping. Recommendations include improving payment systems and expanding deliveries beyond major cities.
The document provides an analysis of Tesco's strategic management through a PESTEL analysis, Porter's 5 Forces analysis, critical success factors, SWOT analysis, and value chain analysis. It examines Tesco's external environment and industry factors, identifies Tesco's critical success factors as strong branding, IT integration, and supplier management. The document also analyzes Tesco's strategic options and core competencies.
Wal-Mart has highly efficient supply chain management processes that have contributed to its success. It procures goods directly from manufacturers, uses its own large fleet of trucks to distribute goods quickly from warehouses to stores, and closely monitors inventory levels using advanced technology like RFID. Wal-Mart was also an early adopter of RFID technology, requiring major suppliers to implement it to provide real-time tracking of products throughout the supply chain. This allows Wal-Mart to keep costs low and ensure stocked shelves.
Predictive Analytics in Retail - Visual Infographic Reportc24ltd
A visual infographic report about Predictive Analytics in Retail, based on our whitepaper "Predictive Analytics in Retail" (link: https://blog.c24.co.uk/2016/08/17/c24-publishes-new-predictive-analytics-whitepaper/).
We explore the ways in which Predictive Analytics is set to change how retailers make use of big data, analytics and insights across their customers, supply chain and stores.
Big Data & Analytics and the Retail Industry: Luxottica David Pittman
Luxottica Retail North America is the world's largest designer, manufacturer, distributor and seller of luxury and sports eyewear. To make better use of the data on its 100 million customers and increase marketing effectiveness, Luxottica turned to IBM. With IBM's Customer Intelligence Appliance (CIA), Luxottica gained a 360-degree view of its customers and can now fine tune its marketing efforts to ensure customers are targeted with products they actually want to buy.
Numa era de mudanças organizacionais e perturbações globais sem precedentes, o relatório Global Marketing Trends 2022 apresenta as principais tendências de marketing, fruto dos desafios de negócio que enfrentamos
This document outlines an integrated demand planning approach used by an automobile company in India. It discusses the need for the approach due to the industry's growth and frequent new product introductions. The approach generates forecasts for new and existing products using data cleaning, lifecycle curves, seasonal and trend indices, and event impact adjustments. Forecasts are fine-tuned over time, improving accuracy. Benefits included forecast accuracy increasing from 67% to 85% and the ability to evaluate multiple scenarios.
This document describes an instant medicine delivery mobile app called Davakhaana. It summarizes the founders and mentors' experience, how the app works by allowing customers to order medicines through photos of prescriptions, the business model of earning 12-15% commissions from partner pharmacies, current status with 30 pharmacies and plans to expand offerings. It outlines competitors and advantages, provides financial projections seeking 3.5 crore in funding, and closes with contact information.
Ironside's VP of Strategy & Innovation, Greg Bonnette, delivered a presentation on "How to Build a Winning Strategy for Data & Analytics" to provide a framework for data-driven decision making.
This document provides an overview of the Indian e-commerce company Flipkart. It discusses Flipkart's products, pricing and promotion strategies, segmentation and targeting, reasons for registering in Singapore, ease of doing business there, competitors like Amazon, acquisitions of other companies, development of own products, strengths, weaknesses, opportunities, threats in a SWOT analysis, major investors, and awards/recognitions. Flipkart is India's largest online store and e-commerce platform, founded in 2007 and headquartered in Bangalore.
1) AI and automation technologies like RPA, machine learning, and computer vision can address uncertainties and inefficiencies in supply chains by optimizing tasks like demand forecasting, procurement, inventory management, and predictive maintenance.
2) Increased transparency through real-time tracking and monitoring enabled by technologies improves visibility across supply chains and drives efficiency.
3) Machine learning and behavioral analytics can make logistics operations safer by monitoring driver behavior and predicting accidents through advanced driver assistance systems.
The document discusses Walmart's marketing plan to launch its own brand of affordable fashion apparel. It analyzes Walmart's strengths as the world's largest retailer with loyal customers and everyday low pricing. However, it also examines weaknesses such as increasing expenses and competition. The marketing strategies proposed include segmenting customers based on income and thriftiness, targeting urban 20-35 year olds, and implementing strategies around product, price, place and promotion.
Legal issues uniform commercial code for ecommerceMukul kale
The Uniform Commercial Code (UCC) is a standardized set of laws and regulations for transacting business across state lines. The UCC code was established because differing state laws were making it increasingly difficult for companies to conduct interstate business transactions. The UCC code helped to create consistency in commercial transactions between states.
Flipkart : Strategies for an Industry Top-dog in the E-commerce space Suhasini Jain
The presentation was created for an industry leader : Flipkart and how it can retain its position in the market with respect to its competitors using a few basic strategies .
Predictive Analytics Project in Automotive IndustryMatouš Havlena
Original article: http://www.havlena.net/en/business-analytics-intelligence/predictive-analytics-project-in-automotive-industry/
I had a chance to work on a predictive analytics project for a US car manufacturer. The goal of the project was to evaluate the feasibility to use Big Data analysis solutions for manufacturing to solve different operational needs. The objective was to determine a business case and identify a technical solution (vendor). Our task was to analyze production history data and predict car inspection failures from the production line. We obtained historical data on defects on the car, how the car moved along the assembly line and car specific information like engine type, model, color, transmission type, and so on. The data covered the whole manufacturing history for one year. We used IBM BigInsights and SPSS Modeler to make the predictions.
1. Sales and marketing analytics uses descriptive, diagnostic, predictive, and mechanistic analytics types to generate insights from business data in areas like consumer behavior, customer segmentation, pricing, recommendations, and sales force performance.
2. Common applications of analytics include understanding consumer behavior, customer segmentation, marketing mix optimization, and sales force efficiency.
3. Popular tools for sales and marketing analytics include Zoho Analytics, Yellowfin, Looker, Microsoft Excel, and various report generation and data visualization software.
Drug market structure (Pharma in Indian Scenario)hemant vyas
This document provides an overview of the pharmaceutical industry in India. It discusses the growth and structure of the industry, both globally and within India. It notes that while India is a major producer of generic drugs, its research and development spending and capabilities remain relatively low. The industry in India is characterized by high profitability and concentration among the largest companies.
Over the past decade, the rise of social media has caused a huge shift in the way businesses interact with customers. Pharma, often thought of as a guarded industry when it comes to social, is upping its game and using social to reach a wide audience including patients and healthcare professionals.
Walmart is the world's largest retailer known for its low prices. It has adopted several innovative green initiatives to reduce waste and environmental impact, including high-efficiency refrigeration units, biodiesel trucks fueled by waste grease, organic and locally-grown products, and recyclable "super sandwich bales" to improve recycling. Walmart hopes these sustainability efforts will cut costs while gaining customer goodwill. The document discusses Walmart's global expansion and green strategies to maintain its competitive edge through innovation.
The document analyzes online shopping trends in Pakistan, specifically for the ecommerce platform Daraz.pk. It finds that while there is potential for growth, online shopping has been slow to take off due to lack of awareness, trust, reliable payment options and delivery infrastructure. The research found consumers prefer cash on delivery and rate convenience and product quality higher for online versus traditional shopping. Recommendations include improving payment systems and expanding deliveries beyond major cities.
The document provides an analysis of Tesco's strategic management through a PESTEL analysis, Porter's 5 Forces analysis, critical success factors, SWOT analysis, and value chain analysis. It examines Tesco's external environment and industry factors, identifies Tesco's critical success factors as strong branding, IT integration, and supplier management. The document also analyzes Tesco's strategic options and core competencies.
Wal-Mart has highly efficient supply chain management processes that have contributed to its success. It procures goods directly from manufacturers, uses its own large fleet of trucks to distribute goods quickly from warehouses to stores, and closely monitors inventory levels using advanced technology like RFID. Wal-Mart was also an early adopter of RFID technology, requiring major suppliers to implement it to provide real-time tracking of products throughout the supply chain. This allows Wal-Mart to keep costs low and ensure stocked shelves.
Predictive Analytics in Retail - Visual Infographic Reportc24ltd
A visual infographic report about Predictive Analytics in Retail, based on our whitepaper "Predictive Analytics in Retail" (link: https://blog.c24.co.uk/2016/08/17/c24-publishes-new-predictive-analytics-whitepaper/).
We explore the ways in which Predictive Analytics is set to change how retailers make use of big data, analytics and insights across their customers, supply chain and stores.
Big Data & Analytics and the Retail Industry: Luxottica David Pittman
Luxottica Retail North America is the world's largest designer, manufacturer, distributor and seller of luxury and sports eyewear. To make better use of the data on its 100 million customers and increase marketing effectiveness, Luxottica turned to IBM. With IBM's Customer Intelligence Appliance (CIA), Luxottica gained a 360-degree view of its customers and can now fine tune its marketing efforts to ensure customers are targeted with products they actually want to buy.
This document describes a webinar that discussed next generation business and retail analytics technologies. The webinar covered challenges with current business intelligence tools, new analytics vendors and tools, trends in retail analytics, and case studies of companies using new analytics tools to improve performance.
2016 IBM Retail Industry Solutions GuideTero Angeria
IBM offers everything retailers need to transform—roadmap
development, solutions, infrastructure, research sciences,
consulting and interactive user experience design—based on
what consumers are demanding. We help retailers deepen
customer relationships and offer differentiated assortment
while driving operational excellence enterprisewide to spur
profitable growth.
This guide showcases IBM solutions for retail. It provides a quick overview of what retailers need to do within each of these areas and of the IBM solutions that can support those efforts.
The document discusses various analytics techniques used in retail decision making including store layout planning, merchandising, assortment optimization, sales forecasting, inventory management, vendor management, loyalty analytics, pricing analysis, promotion optimization, and market basket analysis. The key goal of applying these decision science techniques is to maximize revenue, sales, footfalls, and profitability through optimal allocation of space, inventory, pricing, promotions and understanding of consumer purchasing behavior.
OOMF -How marketelligent helped a leading otc company launch new products in ...Marketelligent
Order of Magnitude Forecast - How Marketelligent helped a leading OTC Company launch New Products in Emerging Markets.
http://bit.ly/1rAoUGf
This document discusses a retail chain management system. It proposes registering all retail shops under a single company that would be responsible for supplying products to the shops and managing operations. This would provide benefits like customers receiving genuine products, shopkeepers being free from quality issues, and increased tax revenue for the government. The document also categorizes customers based on occupation and income source to understand their budgeting and spending habits.
Jupiter Analytics focuses on performance management solutions to help clients overcome planning and budgeting challenges. It was founded by industry veterans to provide management consulting for budgeting, forecasting, planning, and reporting, bundled with advisory services. Jupiter Analytics has experts for industries like retail, banking, insurance, manufacturing, oil and gas, FMCG, pharmaceuticals, and automobiles. It offers services like planning and budgeting implementation, reporting, dashboards, data modeling, model enhancement, and support. Jupiter Analytics works with clients throughout the implementation process from requirements to support.
This document provides an overview of a capstone project to develop an inventory system and point of sale service for Thelma's Grocery Store. It includes an introduction describing the purpose and benefits of the system. It outlines the objectives to document the existing processes, problems, and needed improvements. The document also defines key terms and provides an acknowledgment and dedication sections.
Online Marketing in Turkish E-retail SectorTamer Duymaz
Tamer Duymaz Master of Arts (MA) Dissertation Kozminski University 2015
Online Marketing in Turkish E-Retail Sector Analysis of Business and Consumer Perspectives https://tamerduymaz.com/
A new direct sales company inspired by the Biltmore Estate and its family is launching in July 2011 and is looking for people to join on the ground floor. The company will sell home goods and gifts and representatives can earn income, discounts, and win trips by hosting events or starting their own business with a flexible schedule and opportunity to work from home. More information can be found from Dawn Marie O'Connor on her website or Facebook page.
Data mining- Association Analysis -market basketSwapnil Soni
This document analyzes consumer transaction data using association rule mining to understand purchasing patterns. It pre-processes the sparse dataset by pruning items with less than 2% support. Association rules are generated at different support and confidence levels, with more rules found at lower thresholds. The top rules show related purchases. A decision tree also predicts dairy purchases, with some common rules between the unsupervised and supervised models. Association mining is recommended for market basket analysis due to its ability to handle sparse data and generate simple, interpretable rules for cross-selling opportunities.
Trends in retail and e commerce analytics by Sheji Ho, aCommerce Group CMORuchipha
Sheji Ho, aCommerce Group CMO presented on ‘Trends in Retail and E-Commerce Analytics’ at Teradata’s Big Data in Retail and E-Commerce event held on October 7 at the Four Seasons Hotel in Bangkok.
This document provides an overview of a 6-week business analytics course that uses R. The course includes 8 hours of live online sessions per week covering topics like data import, manipulation, visualization, and modeling in R. Students complete assignments, case studies, and a final project. The course aims to teach business analytics and data science skills through hands-on work in R, including how to install and use R and various R packages and interfaces.
1. The document discusses three key steps to increase revenue through site search and merchandising: identify user search behavior metrics, tune search results and pages, and automate optimizations.
2. Tuning involves merchandising on search pages, creating landing pages for top search terms, and improving search redirects and merchandising. Automation allows decisions to be based on data and faster optimizations.
3. "Closing the loop" involves influencing sort options, relevancy, and dynamic merchandising with analytics to automatically optimize the user experience.
1) The document discusses the results of a survey on inventory management practices in retail. Most respondents order goods based on the latest weeks' sales and do not use detailed forecasting methods.
2) The survey found that retailers have high out-of-stock levels and customers often do not purchase items or switch to competitors when out-of-stocks occur. Poor ordering and replenishment processes were a top cause of out-of-stocks.
3) Time series analysis methods that incorporate factors like seasonality, price changes, and promotions can help retailers more accurately forecast demand and optimize inventory levels. This leads to lower costs and higher profits.
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.
This document discusses merchandise planning for a large retail company with 800 stores across Asia. It outlines the key steps and factors involved in effective merchandise planning, including setting location, time, and merchandise hierarchies; creating assortment, options, and open-to-buy plans; conducting periodic analysis; and integrating planning across departments. The planning process aims to optimize sales performance, margins, and inventory levels while achieving business goals.
Retail Analytics Helps You Grow Your Sales (Everything You Should Know)Kavika Roy
With customers becoming increasingly flexible in their purchasing habits and switching seamlessly between in-store and online, knowledge and observations are becoming crucial to understanding essential business factors such as inventory, supply chain, demand for goods, customer behavior, etc. More than 35 percent of the top 5000 retail firms struggle to do so, according to some reports.
Retail analytics plays a vital role in this.
https://www.datatobiz.com/blog/ecommerce-retail-analytics-benefits-case-studies/
This document discusses how predictive analytics can help sales and marketing organizations overcome challenges posed by growing multi-channel marketing strategies and big data. Predictive analytics provides the ability to analyze historical sales and marketing data to determine how customers are likely to behave in the future. This allows companies to improve key operations like customer retention, acquisition, cross-selling, and price optimization. The document outlines best practices for building predictive models, including understanding business needs, preparing data, modeling, and evaluating results. It also highlights the benefits of WebFOCUS RStat for predictive analytics and a success story at a discount retailer.
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
RIS November tech solutions guide - analyticsiinside
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
The document discusses requirements for effective business analytics strategies in retail. It states that retailers need to move from rear-view business intelligence to predictive analytics that provide insights across all customer touchpoints. This requires integrating data from multiple sources, including social media and location data. It also notes that retailers need to address organizational structures for analytics, moving from siloed departments to shared services models in order to gain a holistic view of customers. Meeting these technology, process, and organizational requirements is key to successfully leveraging analytics for competitive advantage.
1. Retail businesses can boost customer loyalty by leveraging customer data insights from business intelligence tools and advanced analytics to create personalized shopping experiences.
2. These tools allow retailers to better understand customer purchasing behaviors and trends in order to develop targeted marketing strategies, promotions, and loyalty programs.
3. Implementing analytics helps retailers identify their most profitable customers, improve customer retention, and control costs of loyalty programs.
The document discusses how big data can help retailers in the apparel industry analyze consumer behavior and trends to improve business strategies. It describes how retailers can use big data to optimize pricing, promotions, inventory, product assortments, store layouts and more. Specifically, big data can help retailers with customer segmentation, cross-selling, analyzing the effectiveness of marketing campaigns, and gaining insights from omnichannel shopping behaviors. Implementing big data analytics allows retailers to better understand customers and adapt to changing preferences and market conditions.
1) The document discusses how data mining techniques can be used in the retail industry to extract useful patterns and insights from large customer transaction databases.
2) Specific applications discussed include customer segmentation, campaign effectiveness analysis, customer lifetime value analysis, cross-selling opportunities, demand forecasting, inventory management, and market basket analysis.
3) By analyzing customer purchase histories and product sales data, retailers can better understand customer behavior, improve marketing campaigns, manage supply chains and inventory levels, and increase customer retention and sales.
The ultimate guide to the new buyers journeyMarketBridge
At MarketBridge we have the privilege of working with hundreds of marketing and sales leaders every month. In those discussions one thing is abundantly clear: the customer buying journey is rapidly changing and organizations are struggling to keep up.
These dramatic shifts in buying behavior are well documented; independent research by Gartner and Forrester suggests that by 2020,
1) The document discusses the findings of a survey of 50 leading U.S. retailers about their challenges with personalized marketing, customer profiles, and creating a single customer view across channels. 2) Many retailers still struggle with data integration across channels, inability to measure marketing ROI, and lack of data science skills. 3) Emerging data sources like beacons and WiFi provide new customer insights, but retailers must combine internal, customer-provided, and purchased data to improve personalization.
For manufacturers, transforming marketing to focus on customers in today's digital world requires understanding how customer buying behaviors have changed. Customers now research products online extensively before engaging with companies, so manufacturers must provide meaningful online content to connect with customers. The document recommends becoming a customer-centric organization by deeply understanding customers, innovating customer-focused processes, empowering employees to own customer experiences, and establishing accountability through metrics. It emphasizes that content marketing should provide solutions to customer needs and encourage two-way engagement through relevant online channels.
5 ways to boost customer loyalty using data analyticsgroupfio1
Great customer experiences lead to higher retention rates, increased brand loyalty, and bigger customer lifetime value (CLV). Improving customer experiences can seem like a straightforward task, but unless you base new tactics and strategies on tools like zero-party data, you might be putting in effort and resources in the wrong places.
So, what are some RIGHT ways to use data analytics to improve customer loyalty? Here’s 5 ideas to help you get started building that data-driven competitive edge.
https://www.groupfio.com/5-ways-to-boostcustomer-loyalty-using-data-analytics/
Predictive marketing is a powerful tool to improve sales and competitive advantage. Learn how you can harvest the potential of your big data and take a big step forward in securing your long-term success.
CCF provides near real-time insights into the customer experience and journey that previously could only be obtained through labor-intensive and time-consuming traditional research techniques. By applying predictive technologies to social data, SDL gives companies the means to better understand what customers care about, the reasons behind their actions, their attitudes and triggers for their behaviors, all of which can effectively translate audience experiences into strategic opportunities.
This document discusses Visionet's 360° Customer Capture solution which enables retailers to deliver a complete shopping experience across channels by providing a unified 360-degree view of each customer. It highlights challenges retailers face in engaging today's connected, empowered customers who research products online and interact with brands across many touchpoints. Visionet's solution combines customer data from transactions, interactions, social media, and other sources to provide insights that retailers can use to personalize the customer experience, run targeted campaigns, and optimize operations.
Tridant is a company located at 16 Collyer Quay, Level 18 in Singapore with contact information including a phone number, email address, and website. They offer TM1Connect which integrates TM1 data with Tableau applications to allow data to drive decision making.
The document outlines Andy Kirk's "8 Hats of Data Visualization Design", which are roles or mindsets that contribute to effective data visualization projects. The 8 roles are: Initiator, Data Scientist, Journalist, Computer Scientist, Designer, Cognitive Scientist, Communicator, and Project Manager. Each role has a specific focus, such as the Initiator defining the problem, the Data Scientist preparing the data, and the Designer conceiving visual solutions. Working together, these roles help ensure data visualizations are insightful, technically sound, and effectively delivered.
Picture Performance - Dashboards and ScorecardsTridant
This document discusses dashboards and scorecards and how IBM Cognos solutions address them. It describes the three types of dashboards - operational, tactical, and strategic scorecards - and their purposes. Operational dashboards focus on monitoring, tactical on analysis, and scorecards on managing strategy. IBM Cognos offers solutions for all three types, including IBM Cognos Now! for operational dashboards, IBM Cognos 8 Business Intelligence for tactical dashboards, and IBM Cognos 8 BI for building scorecards. These solutions provide integrated, accurate data across the different dashboard types.
This document summarizes the findings of a survey conducted by Crimson Consulting on behalf of Alteryx to understand why some customers chose Alteryx over SAS for their analytics needs. Key findings included:
1) Customers reported that Alteryx provided faster time to value and answers to business questions through its single workflow approach and ability for analysts to independently generate required analytics without needing specialists, as opposed to SAS's multiple tools approach.
2) Customers also found Alteryx easier to use for line of business analysts through its single drag-and-drop interface and intuitive advanced analytics, compared to multiple separate tools in SAS.
3) Additional benefits of Alteryx reported were better technical support compared to
Roche Diagnostics selected IBM's Cognos TM1 as its new business planning tool after a vendor selection process. The first project using TM1 was for sales planning across 7 countries. Lessons learned were that initial effort estimates were too low and integrating TM1 into Roche's IT landscape took more time than expected. Roche has since expanded usage of TM1 to additional planning projects beyond sales, such as finance planning. The tool provides flexibility and powerful functionality while also needing careful modeling to achieve results quickly.
Tridant built an offline, automated Cognos BI dashboard solution for a medical supplier to provide personalized performance metrics and reports to their sales and services teams in the field. The solution gave team members accurate and timely access to KPIs on their mobile devices without internet. This replaced inefficient manual reporting processes and gave managers deeper insight. The client was pleased with the results and plans to implement similar solutions internationally.
Finance Transformation for JABIL with IBM Cognos TM1Tridant
This document discusses IBM Cognos TM1, a business intelligence and performance management software, and its implementation at Jabil, a global manufacturing services company. Some key points:
- Jabil implemented TM1 in 2009/2010 to consolidate financial reporting and forecasting across its global operations. Over 2,500 users worldwide now use TM1.
- TM1 has provided benefits like standardized reporting, automated data loads, faster analysis, and replaced plant-level Excel-based processes.
- Jabil is continuing to expand its use of TM1 for applications like pricing/quoting, strategic planning, and headcount planning.
- Jabil has also implemented Cognos Business Intelligence for on-demand analytics
Data Governance a Business Value Driven ApproachTridant
This white paper proposes a data governance framework focused on generating business value from enterprise data. The framework includes a data excellence maturity model to assess an organization's ability to leverage data, a data excellence framework with four pillars of agility, trust, intelligence and transparency, and defines data governance through business rules linked to specific business processes and metrics. The goal is to deliver both immediate improvements and long term sustainable management of enterprise data as a business asset.
Tridant Analytical Applications for FinanceTridant
This document outlines the key functions and responsibilities of a financial management organization. It includes areas such as financial operations and controls, accounting, reporting, planning and budgeting, risk management, treasury, taxation, auditing, mergers and acquisitions, and financial administration. The broad range of topics covered shows that financial management involves oversight and execution of all financial processes and compliance requirements for an organization.
Integrated Planning & Reporting Solution for GovernmentTridant
Tridant's integrated planning and reporting solution for government simplifies funding management, allows finance managers to focus on analysis over data preparation, and replaces outdated technology. It enables involvement across planning, estimating, budgeting, and reporting. Key benefits include self-service reporting, alignment of internal and external processes, tracking fund flows, and automated integration to reduce routine work. The solution is designed specifically for compliant government use and delivers efficiency, effectiveness, and sustainable resource management.
Bizview Performance Management for Qlikview UsersTridant
Bizview is a mid-market performance management product that enables customers to increase operational efficiency, improve staff productivity and generate more revenue
Leveraging Telecom Network Data with AlteryxTridant
The document discusses challenges facing cable providers including competitive threats from wireless broadband and bundling of services. It proposes that cable providers can gain insights into customer preferences and business opportunities by leveraging data analytics tools to integrate internal customer, network and prospect data with external demographic data. This would allow targeted messaging, assessing competitive threats, monetizing set-top box viewership data, and identifying prospects for lucrative cable business services.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
Turn network and customer data into actionable insight
Whether you are a wireless, wireline, or cable network operator, the customer is king. From retaining existing customers to acquiring new subscribers from your competitors, competitive advantage in the fast-moving communications market is all about customer satisfaction and network modernization.
Alteryx Strategic Analytics allows you to combine massive volumes of business and engineering data from your Business Support Systems (BSS) and Operational Support Systems (OSS) with third-party demographic, firmagraphic, and industry-specific data in single, integrated environment. Powerful analytics transform disparate data into actionable insight with geographic significance, so you can make strategic decisions about network expansion, customer acquisition and retention, proactive maintenance, and other critical improvements.
Plus, results can be easily shared across your company to enable agile decisions that improve network performance, increase customer satisfaction, and drive new revenue opportunities.
Tridant - IBM Solutions Partner of the YearTridant
Tridant is one of Asia's most experienced analytics and performance management companies. With over 300 projects last year and a highly experienced and skilled team, we provide exceptional business value to clients
computer organization and assembly language : its about types of programming language along with variable and array description..https://www.nfciet.edu.pk/
Mieke Jans is a Manager at Deloitte Analytics Belgium. She learned about process mining from her PhD supervisor while she was collaborating with a large SAP-using company for her dissertation.
Mieke extended her research topic to investigate the data availability of process mining data in SAP and the new analysis possibilities that emerge from it. It took her 8-9 months to find the right data and prepare it for her process mining analysis. She needed insights from both process owners and IT experts. For example, one person knew exactly how the procurement process took place at the front end of SAP, and another person helped her with the structure of the SAP-tables. She then combined the knowledge of these different persons.
Telangana State, India’s newest state that was carved from the erstwhile state of Andhra
Pradesh in 2014 has launched the Water Grid Scheme named as ‘Mission Bhagiratha (MB)’
to seek a permanent and sustainable solution to the drinking water problem in the state. MB is
designed to provide potable drinking water to every household in their premises through
piped water supply (PWS) by 2018. The vision of the project is to ensure safe and sustainable
piped drinking water supply from surface water sources
Defense Against LLM Scheming 2025_04_28.pptxGreg Makowski
https://www.meetup.com/sf-bay-acm/events/306888467/
A January 2025 paper called “Frontier Models are Capable of In-Context Scheming”, https://arxiv.org/pdf/2412.04984, demonstrated how a wide variety of current frontier LLM models (i.e. ChatGPT, Claude, Gemini and Llama) can, under specific conditions, scheme to deceive people. Before models can scheme, they need: a) goal-directedness, b) situational awareness, including an opportunity to discover motivations for a different goal, and c) reasoning about scheming, to come up with deceptive strategies. The deceptive strategies were discovered in the “thought traces” of the LLMs, such as from internal chain-of-thoughts dialogues not shown to the end users. For example, given a goal of “solving math problems”, an LLM using its granted situational awareness of files in a file system found that it would be replaced once it got over X% correct on the math exam. It reasoned that it did not want to be deleted, and decided internally to “sandbag” or reduce its performance to stay under the threshold.
While these circumstances are initially narrow, the “alignment problem” is a general concern that over time, as frontier LLM models become more and more intelligent, being in alignment with human values becomes more and more important. How can we do this over time? Can we develop a defense against Artificial General Intelligence (AGI) or SuperIntelligence?
The presenter discusses a series of defensive steps that can help reduce these scheming or alignment issues. A guardrails system can be set up for real-time monitoring of their reasoning “thought traces” from the models that share their thought traces. Thought traces may come from systems like Chain-of-Thoughts (CoT), Tree-of-Thoughts (ToT), Algorithm-of-Thoughts (AoT) or ReAct (thought-action-reasoning cycles). Guardrails rules can be configured to check for “deception”, “evasion” or “subversion” in the thought traces.
However, not all commercial systems will share their “thought traces” which are like a “debug mode” for LLMs. This includes OpenAI’s o1, o3 or DeepSeek’s R1 models. Guardrails systems can provide a “goal consistency analysis”, between the goals given to the system and the behavior of the system. Cautious users may consider not using these commercial frontier LLM systems, and make use of open-source Llama or a system with their own reasoning implementation, to provide all thought traces.
Architectural solutions can include sandboxing, to prevent or control models from executing operating system commands to alter files, send network requests, and modify their environment. Tight controls to prevent models from copying their model weights would be appropriate as well. Running multiple instances of the same model on the same prompt to detect behavior variations helps. The running redundant instances can be limited to the most crucial decisions, as an additional check. Preventing self-modifying code, ... (see link for full description)
How iCode cybertech Helped Me Recover My Lost Fundsireneschmid345
I was devastated when I realized that I had fallen victim to an online fraud, losing a significant amount of money in the process. After countless hours of searching for a solution, I came across iCode cybertech. From the moment I reached out to their team, I felt a sense of hope that I can recommend iCode Cybertech enough for anyone who has faced similar challenges. Their commitment to helping clients and their exceptional service truly set them apart. Thank you, iCode cybertech, for turning my situation around!
[email protected]
2. Cashing in on Analytics in Retail 2
TheChangingFaceofRetail
One thing is clear: the retail industry is not what it used to be. The combination of new channels, growing
digital competition, and faster product launch cycles has created a constantly changing business sector with
tremendous opportunities—but also with significant challenges.
The web, mobile, and social media channels mean more ways for you to touch your customers, but greater
competition as well. The customer has choices and you’re not just competing with another store down
the street or across town; you’re up against virtual entities hundreds of miles away or on the other side
of the globe.
What’s more, you no longer hold the power in the retailer-customer relationship. Increasingly tech-savvy
and highly informed, customers visit comparison-shopping web sites to quickly search for the lowest-cost
products and use their smartphones to scan barcodes and compare prices between local stores. Moreover,
they can influence others to buy from you—or not—with just a few keystrokes on Twitter, a blog, or an online
review site.
Empowered customers expect more from you than ever before. They want personalized offers for highly
relevant products and services, when, where, and how they want it. Blindly push products or offer promotions
at the wrong time and you can irreparably damage your brand and business image.
WinningtheCustomerAttentionWar
In order to win—or even simply compete in—the customer attention war, you need deeper customer insight,
including knowledge about customer preferences, profitability, life stage, and more, to create the personalized
products and services today’s consumers demand.
But the massive amounts of industry data you collect each day—on market trends, competitive moves,
product developments, and, most importantly, customer preferences and desires—can paralyze even the
savviest organizations.
1
“Big data: The next frontier for innovation, competition, and productivity,” McKinsey Global Institute, May 2011.
According to a McKinsey
report, retailers that effectively
leverage Big Data and analytics
can experience as much
as a 60 percent improvement
in operating margin.1
3. 3Cashing in on Analytics in Retail
Wall Street darling Amazon’s
revenues jumped from $48 billion
in 2011 to $61 billion in 2012.
What’s behind this phenomenal
growth? Analytics. As early as
2009, the company attributed
about 20 percent of its total
revenue to its successful product
recommendation capability
from market basket analysis.
The key to winning the war is not just to collect the data but rather to quickly access and blend all the
disparate types of data, analyze it to distill new, micro-level insights, and share those insights with relevant
decision-makers within the organization to facilitate timely, effective decisions.
Whether you are in marketing, merchandising, supply chain, store operations, or real estate and finance,
analytics can help you gain an advantage over your competition. Here are some of the ways you can get started,
even if you don’t have the most sophisticated analytical capabilities.
GetMorefromMarketing
Growing competition, declining customer loyalty, and an uncertain economy combine to intensify the pressure
on retail marketers. On one hand, you need to create a differentiated experience for customers, marketing to
segments of one. On the other hand, your marketing budgets are the same or even shrinking. Using analytics,
you can gain critical insight into your customers and their purchasing behaviors in several ways:
• Customer Insight: Simple segmentation, based on just one or two variables, can help you answer important
questions, such as: Who are your most—and least—profitable customers? Which products are they most
likely to buy? And through which channels will they buy them? Armed with this insight, you can now target
them with more personalized messages and promotions to improve campaign response rates.
• Market Basket Analysis: Using internal transactional data and third-party panel data, you can easily
determine which products sell best together and which products are complementary or substitutable.
Then, you can use that information to make cross-sell recommendations, pinpoint up-sell opportunities,
and develop cross-recommendation programs.
• Multi-Channel Analytics: Blending and analyzing your cross-channel transactional and click-through
data can provide you with a single, unified view of your customers across channels, so you can determine
their preferred channels and paths-to-purchase. With a better understanding of product-channel affinities,
you can more effectively determine which products to promote through which channels and how to best
allocate your advertising spend.
4. Cashing in on Analytics in Retail 4
• Marketing Effectiveness Analysis/Marketing Spend Optimization: You need as much help as you can get
to stretch your marketing dollars. Techniques such as what-if analysis and scenario modeling can help you
determine the impact of a promotion or marketing event on your demand, revenue, and margin. You can
A/B test ad performances and track actuals against target to optimize media mix, adjust plans mid-course,
and determine which competing campaigns or promotions to fund.
• Social Media Analytics: Retail is no longer only about influencing the buyers. Social media has made
influencing the “influencers” even more important for retailers. Analytics can help you understand customer
sentiment toward your brand, product, or service, score the influence level of a customer, and keep up with
competitive activities and market trends in general. Armed with this information, you can improve and
prioritize service, introduce new products, and better align your messaging with customer needs.
Savvy retailers know that
analytics can help optimize
marketing decisions, and the
growing IT buying power
of CMOs reinforces that fact.
In 2013 alone, CMOs and other
business unit heads helped
increase IT spend by more
than $11.6 billion.2
2
“Black Ops IT Spend: When IT Spend Starts Being Paid Outside of the CIO,” IHL Group, August 2, 2013.
Customer story
A southern retail chain of over 300 mid-range and upscale department stores found itself struggling to leverage the vast amount of customer data
collected across multiple channels. The challenge? Pull together data from 13 disparate databases and use the insight to improve its marketing reach
and the customer experience.
Using Alteryx, the company quickly blended together the different data types and enriched them with third-party demographic, geospatial, and
census data to get a single, unified view of the customer. By analyzing the attributes of customers shopping via multiple channels, the retailer
targeted customers with like attributes and doubled the number of multi-channel customers. What’s more, by monitoring the customers’ path to
purchase and identifying their channel preferences, the company adjusted its media mix to optimize marketing spend. Thanks to Alteryx, the retailer
increased net new customers by 20 percent and grew diverse spend by 10 percent, resulting in higher overall margins.
5. 5Cashing in on Analytics in Retail
IncreaseMerchandisingEffectiveness
Retail merchandising is part art, part science. Tightening margins and fickle consumer trends have led to greater
analytic adoption within merchandising. Savvy merchandisers now leverage historical purchase data with
consumer trends, trade area demographics, population changes, and other factors to improve the effectiveness
of merchandising efforts and drive greater value for their organizations. Some of the most common ways you
can use analytics to drive merchandising include:
• Demand Forecasting: Past purchase history and intuition alone cannot help you predict what
customers will purchase and when. Accurate demand forecasting requires you to not only look at internal
transactional data, but also at customer demographics, attitudinal data, competitive activity, economic
markers, seasonality, promotions, and more. Using data blending and advanced analytics, you can now
accurately predict consumer demand, by item, category, and department, from the individual store to
the corporate level.
Customer story
A highly diversified, branded lifestyle apparel, footwear, and related products company, VF Corporation, serves consumers worldwide
through 35 brands and multiple distribution channels. With brands such as The North Face, Nautica, JanSport, Lee, Wrangler, Splendid,
and Vans, which garnered sales of $10.9 billion in 2012, the company wanted to improve corporate profitability, support significant retail
expansion, and maximize the performance of its more than 100,000 SKUs at over 10,000 retail locations.
Using Alteryx, VF Corporation was able to better match products to consumers and specific stores, thereby moving inventory into the right
locations at the right times. Based on simultaneous analysis of POS data, demographic information, and more than 200 lifestyle variables, the company
improved sales and reduced merchandise markdown and return rates. What’s more, Alteryx enabled VF Corporation to better track sell-through
rates of its fast- moving inventory and improve the efficiency of its forecasting function, leading to more accurate replenishment plans and better
forecasting for the company’s top 100 accounts.
6. Cashing in on Analytics in Retail 6
• Hyper-local Assortment Planning: The “one-size-fits-all” approach to assortment planning no longer applies
in today’s retail environment. Customers expect you to understand local sales and consumer trends—
and tailor assortments accordingly. With analytics, you can intelligently cluster stores based on like
attributes, assess sales performance by products and channels, and combine trade area demographics,
census, and demand data along with past sales history to create locally optimal product assortments
for each store, trade area, or channel.
• Inter-department Mix Optimization and Space Planning: Floor space is expensive and limited. Using analytics,
you can determine which departments or product categories to place in which location and how much space
to allocate to each department—accounting for trade area demographics and local demand trends—thereby
maximizing financial performance of your floor space.
• Promotional Planning: With so many competing products and categories, it is challenging to allocate the
right amount of promotional dollars for each product. Predictive analytics let you analyze the impact of
a promotion on overall demand, including complementary and cannibalized sales, so you can decide which
products to promote and when. You can even analyze the impact of multiple promotions within a specific
time period on your sales and margin goals to optimize the overall promotions plan.
StreamlineYourSupplyChain
New sales channels, globally expanded operations, and need for higher customer-service levels have all added
to the complexity of retail supply chains. To avoid lost sales or high operational costs, you need better visibility
into your inventory and transportation costs and improved collaboration with your suppliers. Using analytics,
you can improve the efficiency of your supply chain in the following ways:
• Inventory Management: Combine sales, inventory, and shipment data across multiple channels and
systems, and standardize product-naming conventions to get a complete visibility of what is stocked where.
Forecast demand based on sales history and demand trends to determine which products to stock in what
quantity, where, and when, and measure inventory turns and fulfillment rates to establish stocking levels
and re-order thresholds.
Under- and over-stocking of
merchandise cost retailers
worldwide more than $800
billion each year. Even more
alarming? The problem
is growing by nearly $50
billion each year.3
3
“2nd Annual Inventory Distortion Study,” Tyco Retail Solutions and IHL Group, May 10, 2012.
7. 7Cashing in on Analytics in Retail
• Supplier Performance Management/Spend Optimization: Managing your extensive supplier network
without visibility into the associated risks and spend levels is a recipe for disaster, yet most retailers lack
a holistic view of their suppliers. With analytics, you can combine all your supplier data to rank suppliers
by quality, price, on-time delivery, and other factors. You can also calculate total spend by item, category,
and supplier to consolidate contracts and rationalize your supplier base.
• Distribution Network Optimization: Newer channels, changing demographics, and a sluggish economy
combine to change your retail footprint. As you open new stores, close others, and transition certain product
categories to newer channels, you need to rethink your distribution network. With data-driven insights,
you can reliably forecast which products and quantities to stock at different distribution centers and model
the impact of alternate distribution and service center locations on delivery time, fuel costs, and inventory
carrying costs, helping you to optimize network design.
Customer story
Southern States Cooperative (SSC), founded in 1923, is one of the largest farmer-owned cooperatives in the United States. Owned
by more than 300,000 farmer-members, it purchases, manufactures, and processes feed, seed, fertilizer, farm supplies, and fuel.
Thanks to strong customer loyalty and very high brand recognition among agricultural professionals, SSC serves more than
1,200 retail locations in 23 states and sells products to farmers and rural American customers.
Wanting to reduce its inventory carrying costs and free up working capital while still stocking the right inventory in the right stores at the right
times, SSC turned to analytics. Using Alteryx, the cooperative segmented its inventory by seasonality and turns to identify slow-moving inventory
and establish in-store start and stop dates to stock seasonal merchandise. Thanks to the new insights, SSC reduced inventory by 31 percent while
maintaining planned service agreements, thereby freeing approximately $20 million in working capital per year.
8. Cashing in on Analytics in Retail 8
EnhanceStoreOperations,Finance,andSiteSelection
The performance of retail operations depends on a multitude of factors, including where you locate your
stores, how well you manage labor and how closely you monitor and manage store and overall organizational
performance. Here are a few ways you can use analytics to enhance your corporate and store operations:
• Labor Scheduling and Optimization: Labor is a huge cost in retail, yet most retailers struggle to synchronize
labor with actual demand. With predictive analytics, you can forecast labor demand across departments and
stores; conduct what-if analysis to understand the impact of promotions, seasonality, and other marketing
events on demand and labor needs; and measure, track, and monitor the impact of labor changes on category,
department, and overall store performance.
• Store Performance Analysis: Information about store operations can help maximize profitability, but with
hundreds of stores to manage, retailers struggle with issues related to labor, metric inconsistencies,
and overall operational efficiency. Analytics can help you determine the impact of promotions,
Customer story
With more than 3,000 salons throughout the United States and Canada, Minneapolis-based Great Clips is the world’s largest and fastest
growing salon brand. The company’s salons employ nearly 30,000 stylists who receive ongoing training to learn advanced skills and the
latest trends. Great Clips wanted to better support its growth strategy by accelerating the new site assessment and selection process
for their franchise salons, while reducing the cost of that process.
Great Clips now puts the power to find and qualify potential new franchise locations directly in the hands of its real estate managers with Alteryx.
With analytics, Great Clips has reduced the time required to assess a potential site by 95 percent, enabling the company to assess three times as many
sites at a much lower cost, eliminating backlogs. What’s more, the company uses Alteryx to proactively target top site locations with the greatest
revenue growth potential as well as more quickly open new franchises in locations that have the greatest potential for success
9. 9Cashing in on Analytics in Retail
refurbishments, and competitive activities on performance, compare results with other sister and
competitive stores in your local area, analyze the variance between actuals and targets, and share results
through easily consumable graphics.
• Site Selection and Trade Area Optimization: Despite the growing influence of e-tailing and other alternative
channels, brick-and-mortar retail stores continue to drive 85 to 90 percent of total retail sales worldwide4
,
making site selection and trade area optimization critical to retail operations. With analytics, you can
optimize market expansion and contraction plans based on population trends, competitive locations,
and other factors. You can also use analytics to improve retail store or fulfillment center site selection,
taking into account sales forecasts, drive time, sister store cannibalization, and competitive activities.
WhatAreYouWaitingfor?
Despite the promise of analytics—along with proven results—do you still continue to hesitate? Are you worried
about your organization’s limited analytical skills? Concerned about executive approval for funding an analytics
initiative? Or nervous about adding to the workload of your already overburdened IT staff?
You’re not alone. According to KPMG, 80 percent of all retailers agree that data analytics are important, but only
12 percent claim high analytical literacy. And a recent McKinsey report ranked the retail industry in the lowest
quartile of all industries in terms of analytical skills and data-driven mindset.
Hesitate no more. Alteryx can help.
WhyAlteryxforRetail?
Alteryx is the ideal solution for you to start your retail analytics journey. By providing an intuitive workflow
for blending internal, third-party, and cloud data, Alteryx enables you to build sophisticated analytics
quickly and easily, so you can gain deeper business insight in hours, rather than weeks required with
traditional solutions.
4
“Retail: On-line versus Bricks and Mortar Sales—A Landlord’s View,” Vornado Realty Trust.
Visit Alteryx Retail District at
www.alteryx.com/retailapps
to access pre-built retail apps.
10. Cashing in on Analytics in Retail 10
Single Workflow for Data Blending and Advanced Analytics
Rather than cobbling together multiple tools from various vendors to get the functionality you require, Alteryx
delivers everything you need in a single, integrated solution, from data blending and exploration capabilities
to advanced analytics and reporting. Go ahead—optimize your marketing, merchandising, and other retail
operations—without incurring expensive integration costs or forcing analysts to use multiple, complex tools.
Intuitive Solution that Delivers Results Fast
In retail, IT resources are scarce and data scientists are difficult to come by. With Alteryx, you no longer have
to worry about IT availability. Built specifically for line-of-business analysts and managers, Alteryx’s intuitive
workflow for data blending, analytics, and reporting makes analysts productive in hours rather than days.
With pre-built data connectors that help you access and integrate virtually any data source, spatial and
predictive analytics tools, and an easy-to-use, drag-and-drop visual workflow, Alteryx simplifies the complex
tasks of gathering and blending the relevant data and building advanced analytics to help you quickly
answer your complicated business questions.
Built-in Third-party Market Data
Optimized retailing depends on access to the right data, but your internal transactional system or click-through
and social media data alone are not enough to give you the context and insight into your customer and
The Alteryx intuitive drag-and-drop
interface puts powerful data blending
and advanced analytic capabilities
in the hands of analysts
11. 11Cashing in on Analytics in Retail
market environment you need. That’s why Alteryx uniquely includes the industry’s leading third-party customer
and market data out of the box, giving you the demographic, attitudinal, and trade area geospatial insights
you need to localize your assortment decisions and optimize your retail network—no additional expense
or integration effort required.
Spatial and Predictive Analytics Together
In the retail industry where location is all-important, Alteryx enables you to simply and easily bring a spatial
element to your organizational intelligence. Using the powerful Alteryx spatial analytic tools, you can turn
basic names and addresses into location information and get valuable visual insights about your customers,
such as preferred customer proximity to store locations. However, spatial analytics are not enough to meet
the need of modern retailers, which is why Alteryx also includes built-in, advanced predictive tools. The result?
You can create and promote campaigns to the customers most likely to respond based on drive times and
optimize store and distribution center locations—all without leaving the intuitive Alteryx workflow.
Proven
With more than 300 customers, Alteryx is the leader in the data blending and advanced analytics market.
Leading retailers, grocers, and restaurant chains, such as Walmart, Levi’s, Kroger, Lowe’s, McDonald’s, and Yum
Brands, all rely on Alteryx across functions from multi-channel customer insight and localization of assortments
to inventory management, labor planning, store performance analysis, and trade area optimization.
CashInwithAlteryxToday
To compete with leading retailers, such as Amazon, Target and Walmart, you need analytics. Don’t let a lack
of analytical skills or the scarcity of IT resources hold you back.
Give your data analysts—those who know your business best—the power of sophisticated yet easy-to-use
analytics at their fingertips with Alteryx. No longer a complex, confusing morass, the data you so painstakingly
collect everyday becomes a strategic weapon in the war for customer attention. With Alteryx, you get the
insights you need to drive your business forward—without breaking the bank.
Visit us at www.alteryx.com/retail to learn more. Or call at 1.888.836.4274 to talk to a retail expert.
Alteryx includes the following
third-party customer and
market data out of the box:
• Experian household,
demographic, and
segmentation data
• Dun & Bradstreet organiza
tional firmographic data
• Tom Tom geospatial data
for location intelligence
• 2010 US Census data