This deck was used in the guest lecture delivered by Ganes at the Rutgers Business School, New Jersey, on July 7th, 2021. These slides were supplemented with a live business case that was used for the class discussion.
Transform your Brand's Customer Experience by using AIGanes Kesari
This document outlines 4 steps for using AI to understand customers better:
1. Listen everywhere by collecting direct, indirect, and inferred customer feedback.
2. Understand what customers want by analyzing all available data and asking the right questions.
3. Contextualize the customer by understanding their journey and experiences.
4. Tell data stories to visualize insights and communicate findings in a narrative format to drive actions.
Beyond the Dashboard:Exploratory Analytics discusses how exploratory analytics allows users to go beyond traditional dashboards and reports to test hypotheses, conduct "what if" scenarios, and build predictive models. Exploratory analytics uses visualization, modeling, and interactive capabilities to analyze data in a more flexible way compared to static reports. The presentation highlights how the Quantrix platform supports exploratory analytics through capabilities like pivot and filter charts, enhanced visualization, modeling, and multidimensional analysis for forecasting, planning, and risk analysis. Real-world examples are also provided.
Agile Marketing with Cascade, Analytics & SpectateJoel Dixon
This document discusses using analytics and key performance indicators (KPIs) to inform agile marketing strategies. It emphasizes measuring goals and objectives to determine which content and social media channels are most effective. While data is available, context is needed to understand it. Defining measurable goals and tracking trends can help marketing teams focus content and campaigns on what drives the desired outcomes and returns.
Product Analytics at Web Analytics WednesdayJason Packer
This document contains a series of tweets by Martijn Scheybeler discussing product analytics and web analytics. He talks about analyzing different business models like RV rentals, food delivery, and marketplaces. Specifically, he discusses how product analytics can provide more context than traditional web analytics by tracking things like user interactions, feature usage, and satisfaction across multiple audiences and vendors. The tweets also mention challenges like integrating backend data and the complexity of building holistic analytics solutions.
What’s New In VR Research – And What’s NotRay Poynter
Everyone is talking about virtual reality, but very few of us are doing it, and fewer still are doing it well. Advanced Simulations has been doing variations of VR research for 25 years and has just introduced a new, more realistic and immersive version that works offline or online anywhere in the world. We will talk about what is and what is not important when using virtual reality to conduct marketing research.
This document discusses democratizing analytics by providing self-service business intelligence tools for all employees. It argues that data is now everywhere and insights should be available to everyone, not just data scientists and analysts. The presented solution aims to give self-service analytics and reporting abilities to all user types from employees to customers and partners at scale.
9 Myths That Keep Customer Experience Data Locked in the Server ClosetCalabrio
Eighty percent of companies say they’re collecting enough data to measure business performance, but studies show only six percent are extremely satisfied with their ability to use consumer engagement data. Are you still using spreadsheets? Think it’s too complicated to make the jump to integrated analytics? We think not. Here are the top 9 myths debunked.
Transform your Brand's Customer Experience by using AIGanes Kesari
This document outlines 4 steps for using AI to understand customers better:
1. Listen everywhere by collecting direct, indirect, and inferred customer feedback.
2. Understand what customers want by analyzing all available data and asking the right questions.
3. Contextualize the customer by understanding their journey and experiences.
4. Tell data stories to visualize insights and communicate findings in a narrative format to drive actions.
Beyond the Dashboard:Exploratory Analytics discusses how exploratory analytics allows users to go beyond traditional dashboards and reports to test hypotheses, conduct "what if" scenarios, and build predictive models. Exploratory analytics uses visualization, modeling, and interactive capabilities to analyze data in a more flexible way compared to static reports. The presentation highlights how the Quantrix platform supports exploratory analytics through capabilities like pivot and filter charts, enhanced visualization, modeling, and multidimensional analysis for forecasting, planning, and risk analysis. Real-world examples are also provided.
Agile Marketing with Cascade, Analytics & SpectateJoel Dixon
This document discusses using analytics and key performance indicators (KPIs) to inform agile marketing strategies. It emphasizes measuring goals and objectives to determine which content and social media channels are most effective. While data is available, context is needed to understand it. Defining measurable goals and tracking trends can help marketing teams focus content and campaigns on what drives the desired outcomes and returns.
Product Analytics at Web Analytics WednesdayJason Packer
This document contains a series of tweets by Martijn Scheybeler discussing product analytics and web analytics. He talks about analyzing different business models like RV rentals, food delivery, and marketplaces. Specifically, he discusses how product analytics can provide more context than traditional web analytics by tracking things like user interactions, feature usage, and satisfaction across multiple audiences and vendors. The tweets also mention challenges like integrating backend data and the complexity of building holistic analytics solutions.
What’s New In VR Research – And What’s NotRay Poynter
Everyone is talking about virtual reality, but very few of us are doing it, and fewer still are doing it well. Advanced Simulations has been doing variations of VR research for 25 years and has just introduced a new, more realistic and immersive version that works offline or online anywhere in the world. We will talk about what is and what is not important when using virtual reality to conduct marketing research.
This document discusses democratizing analytics by providing self-service business intelligence tools for all employees. It argues that data is now everywhere and insights should be available to everyone, not just data scientists and analysts. The presented solution aims to give self-service analytics and reporting abilities to all user types from employees to customers and partners at scale.
9 Myths That Keep Customer Experience Data Locked in the Server ClosetCalabrio
Eighty percent of companies say they’re collecting enough data to measure business performance, but studies show only six percent are extremely satisfied with their ability to use consumer engagement data. Are you still using spreadsheets? Think it’s too complicated to make the jump to integrated analytics? We think not. Here are the top 9 myths debunked.
Web Analytics Wednesday April 2020 - Customer Journey MappingJason Packer
Stratos Innovation Group is a consulting firm that helps companies achieve customer centricity through customer journey mapping, service design, and behavioral analytics. They take a holistic approach to understanding customers by mapping their journeys, identifying archetypes based on values and behaviors, designing customer-centric service experiences, and analyzing behavioral data. An integrated approach using both service design qualitative research and behavioral analytics quantitative data provides benefits like designing ideal customer experiences and measuring their impact on business metrics like revenue and retention.
There is no Such Thing as Big Data - Jeremy Waite, StrategySalesforce Exactt...PerformanceIN
The reliance on insights for campaign success is increasing despite many calling for a blend of information and marketer instinct. Data may well be a vital support strut for performance marketing, but does big data actually exist?
Our speaker for this session does not think so and he will be detailing why. Jeremy is primed to explain big data mythology and what he thinks it actually is. Attend this if you also want to learn how to provide great experiences for customers, given their average attention span is now less than seven seconds.
How Data Science Builds Better Products - Data Science Pop-up SeattleDomino Data Lab
The document discusses how data science can help build better products. It explains that products are initially built to quickly test ideas through lightweight and imperfect means. Data science helps understand customer value and enables continuous learning through a process of analyzing data, making discoveries, and pivoting the product based on what is learned. This contrasts with the traditional approach where functionality is locked in place. The document advocates for an adaptive software environment that allows for rapid changes based on new insights. It provides tips for building successful data products through iterative improvements informed by data.
Attribution: Weaving the Red Thread of Marketing By Gary VersterMarTech Conference
From the MarTech Conference in London, UK, October 20-21, 2015. SESSION: Attribution: Weaving the Red Thread of Marketing. PRESENTATION: Attribution: Weaving the Red Thread of Marketing - Given by Gary Verster - @the_other_GaryV - Marketing Technologist & Senior Marketing Operations Manager - Trend Micro EMEA Ltd. #MarTech DAY1
How to Present Test Results to Inspire ActionJason Packer
This document provides a template and guidelines for presenting test results in a way that inspires action. It recommends focusing on why the test was conducted, what was tested, the outcome, key learnings, and next steps. It outlines an ideal structure of 3-4 slides that covers the business case, hypotheses, results, insights gained, and actions to be taken. The presentation should avoid jargon and focus on tangible impacts. It also addresses flexing the template for more complex tests and accommodating requests for a shorter high-level summary. The goal is to inspire the audience to take action based on test findings rather than focus on methodology details.
Discover and visualize your critical data and produce actionable facts for better decision making in a fraction of the time. Power BI is a cloud-based business analytics service that gives you a single view of your most critical business data. Monitor the health of your projects using a live dashboard, create rich interactive reports with Power BI Desktop and access your data on the go with native Power BI Mobile apps.
Picnic provides mobile grocery delivery using machine learning models. They face challenges in bulk item recommendations, customer feedback integration, and delivery timing accuracy. To address these, Picnic uses deep learning models combining both large and granular data for improved recommendations. They also use automated classification of customer suggestions and calibration of delivery models to optimize the mobile shopping experience.
Aviso supercharges how enterprises make critical revenue decisions using data science, machine learning and portfolio management frameworks from Wall Street. Aviso's cloud-based application, Aviso Insights, enables sales management, operations and finance executives to forecast sales, quantify risks, predict future outcomes, and have the confidence to exceed quarterly targets.
Join Rich Taylor, Looker’s Senior Director of Operations & Marketing (and a long time SFDC user), as he chats with Kevin Marr, Senior Looker Data Analyst. They’ll discuss the ways we, as well as our customers, use Looker to get the most out of data captured by SFDC.
Better ways to leverage your SFDC Data with Looker:
Snapshots of pipeline: Develop a clear understanding of the business, trends over time, and pipeline vs. target analysis.
Conversion Rates: view them at each step of the sales funnel, and compare them across teams, individuals, and timeframes.
Identifying trends: Project the probability of pipeline closing over time.
Rep Specific Dashboards: Compare a single rep to team and the entire sales org on multiple factors, including customer health for improved and proactive customer retention.
Want to better engage audiences and make an impact? Then consider adding visuals to your content.
Assets like infographics are the visual content you need to add to your content marketing mix – but how can you make yours stand out among the rest?
In this presentation, learn the best practices for creating infographics that will educate and engage your audience.
Discover:
– How to plan for and gather the data and content you need for an infographic.
– 5 best practices for structuring and organizing your content into an infographic.
– How to create an interactive infographic.
– Success stories and results from customers.
Big data and data science will transform enterprises in the future, allowing companies to gain insights from data to find new revenue opportunities. Data science can help enterprises optimize lead generation processes, prevent customer churn, and more accurately predict sales. If enterprises apply data science techniques like consumer companies have, it will fuel large growth by powering personalized recommendations and predictive analytics across various business functions and customer touchpoints.
This document summarizes the growth strategies implemented at Skyscanner over 4.5 years. It discusses transitioning to growth-focused teams organized into tribes. The key aspects that helped drive growth include adopting a lean startup approach with agile marketing principles. This involved highly aligned autonomous teams, frequent experimentation, and customer-focused collaboration across functions. It also emphasizes adopting a growth mindset and culture throughout the organization to support innovative strategies for driving impact.
Gazelle Information Technologies has completed 4 years of helping organizations optimize their supply chain processes. Over this time, Gazelle has helped clients set up sales and operations planning, improve forecasting, optimize inventory, benchmark freight, design supply chain networks, and do dispatch planning, resulting in total combined savings of millions of dollars. Gazelle has developed an end-to-end supply chain management solution that can run on multiple platforms and extract secondary sales data to generate forecasts, conduct S&OP planning, and optimize production and dispatch planning. This full suite of supply chain solutions is now available via Microsoft's Azure platform.
Intelligent Tooling for (Digital) SalesBarry Magee
The document discusses using intelligent tools to help digital sales teams. It notes key seller questions around achieving sales targets and prioritizing clients effectively. It then outlines some of the challenges sales teams face like having too much data and tools, not enough time, and lack of insights. The solution discussed using a cognitive sales advisor that maps territories, provides insights, and helps answer questions to optimize sales processes. It aims to help sales teams prioritize, prepare for client engagements, and find new customers through a data-driven approach.
Intelligent Data - Thoughts on the Analytics of TomorrowSteen Rasmussen
My session from #mesurecamp with thoughts and ideas of what can be done with web and digital analytics data both right now i 2018 but also in the near future to support the business with a return on analytics focus.
"Rebuilding UI at Large Scale" by Monika Halim (GO-JEK)Tech in Asia ID
Monika Halim, or most people call her Momo, believe that being human-centered should also makes us a better person. She's heading GO-JEK's Product Design team that builds over 20 products for consumer, drivers and partners.
She graduated as Bachelor of Design from Bandung Institute of Technology with major in Visual Communication Design, her past experiences including researching and designing for Indonesia Mengajar, led the design & optimization team at ZALORA, and part of the OgilvyOne’s Asia Pacific UX Team.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Watson Analytics provides self-service data analytics capabilities including data acquisition, cleansing, insights discovery, outcome prediction, visualization, and action without requiring data expert assistance. It handles large volumes of rapidly accessible data and automates data preparation, refinement, management, and analysis from the cloud. Statistical analysis, correlations, and predictions help users gain a deeper understanding of their business to see relevant information, take action, and anticipate opportunities.
Artificial Intelligence: How Enterprises Can Crush It With Apache Spark: Keyn...Spark Summit
Artificial intelligence (AI) is not new. It emerged as a computer science discipline in the 50’s and has been a persistent theme in science fiction. What is new is that enterprises now have the prerequisites needed to create pragmatic AI applications: plenty of data, deep learning frameworks, and blazing fast distributed compute clusters à la Apache Spark. Forrester Vice President and Principal Analyst, Mike Gualtieri will enumerate and demystify nine essential AI technology building blocks that enterprises can use to add a modicum of intelligence to existing and new applications.
How Brands can use AI for Actionable Customer IntelligenceGanes Kesari
This session was delivered on Apr 20th 2020 at the Rutgers Business School. This was a Guest Lecture for the "AI in Marketing" class.
Session Brief:
Today, customers interact with brands continuously, either intentionally or indirectly. They do so on a number of channels, and leave a variety of digital footprints. Unfortunately, enterprises miss out on this opportunity to understand and connect with the customers. This session will show how brands can leverage data and technology to understand their customers.
Brands can harvest both structured and unstructured data from diverse channels. With the help of data analytics, they can build an integrated view of the customer. By overlaying the content with context, they can map every conversation on the customer journey. By stitching all these insights together, brands can use storytelling to help drive the right business decisions.
How Data Science can help Understand your Customers BetterGanes Kesari
This was presented at the AT&T Retirees Quarterly ELATE Luncheon, on Sep 18th, 2019.
SESSION BRIEF:
Most organizations struggle to understand their customers. In a digital world, the power of data and technology is not tapped into. So, customer advocacy initiatives are short-sighted, transactional and unscientific. This session will show how organizations can listen to customers better. It will introduce you to AI techniques that are revolutionizing customer intelligence.
With examples, you will understand how these insights can be translated into business decisions.
LEARNING OBJECTIVES:
1. You will learn creative ways to find what customers are looking for right now
2. You will be introduced to advanced analytics techniques and storytelling with data
3. You will understand how data science can be applied for business decisions
Web Analytics Wednesday April 2020 - Customer Journey MappingJason Packer
Stratos Innovation Group is a consulting firm that helps companies achieve customer centricity through customer journey mapping, service design, and behavioral analytics. They take a holistic approach to understanding customers by mapping their journeys, identifying archetypes based on values and behaviors, designing customer-centric service experiences, and analyzing behavioral data. An integrated approach using both service design qualitative research and behavioral analytics quantitative data provides benefits like designing ideal customer experiences and measuring their impact on business metrics like revenue and retention.
There is no Such Thing as Big Data - Jeremy Waite, StrategySalesforce Exactt...PerformanceIN
The reliance on insights for campaign success is increasing despite many calling for a blend of information and marketer instinct. Data may well be a vital support strut for performance marketing, but does big data actually exist?
Our speaker for this session does not think so and he will be detailing why. Jeremy is primed to explain big data mythology and what he thinks it actually is. Attend this if you also want to learn how to provide great experiences for customers, given their average attention span is now less than seven seconds.
How Data Science Builds Better Products - Data Science Pop-up SeattleDomino Data Lab
The document discusses how data science can help build better products. It explains that products are initially built to quickly test ideas through lightweight and imperfect means. Data science helps understand customer value and enables continuous learning through a process of analyzing data, making discoveries, and pivoting the product based on what is learned. This contrasts with the traditional approach where functionality is locked in place. The document advocates for an adaptive software environment that allows for rapid changes based on new insights. It provides tips for building successful data products through iterative improvements informed by data.
Attribution: Weaving the Red Thread of Marketing By Gary VersterMarTech Conference
From the MarTech Conference in London, UK, October 20-21, 2015. SESSION: Attribution: Weaving the Red Thread of Marketing. PRESENTATION: Attribution: Weaving the Red Thread of Marketing - Given by Gary Verster - @the_other_GaryV - Marketing Technologist & Senior Marketing Operations Manager - Trend Micro EMEA Ltd. #MarTech DAY1
How to Present Test Results to Inspire ActionJason Packer
This document provides a template and guidelines for presenting test results in a way that inspires action. It recommends focusing on why the test was conducted, what was tested, the outcome, key learnings, and next steps. It outlines an ideal structure of 3-4 slides that covers the business case, hypotheses, results, insights gained, and actions to be taken. The presentation should avoid jargon and focus on tangible impacts. It also addresses flexing the template for more complex tests and accommodating requests for a shorter high-level summary. The goal is to inspire the audience to take action based on test findings rather than focus on methodology details.
Discover and visualize your critical data and produce actionable facts for better decision making in a fraction of the time. Power BI is a cloud-based business analytics service that gives you a single view of your most critical business data. Monitor the health of your projects using a live dashboard, create rich interactive reports with Power BI Desktop and access your data on the go with native Power BI Mobile apps.
Picnic provides mobile grocery delivery using machine learning models. They face challenges in bulk item recommendations, customer feedback integration, and delivery timing accuracy. To address these, Picnic uses deep learning models combining both large and granular data for improved recommendations. They also use automated classification of customer suggestions and calibration of delivery models to optimize the mobile shopping experience.
Aviso supercharges how enterprises make critical revenue decisions using data science, machine learning and portfolio management frameworks from Wall Street. Aviso's cloud-based application, Aviso Insights, enables sales management, operations and finance executives to forecast sales, quantify risks, predict future outcomes, and have the confidence to exceed quarterly targets.
Join Rich Taylor, Looker’s Senior Director of Operations & Marketing (and a long time SFDC user), as he chats with Kevin Marr, Senior Looker Data Analyst. They’ll discuss the ways we, as well as our customers, use Looker to get the most out of data captured by SFDC.
Better ways to leverage your SFDC Data with Looker:
Snapshots of pipeline: Develop a clear understanding of the business, trends over time, and pipeline vs. target analysis.
Conversion Rates: view them at each step of the sales funnel, and compare them across teams, individuals, and timeframes.
Identifying trends: Project the probability of pipeline closing over time.
Rep Specific Dashboards: Compare a single rep to team and the entire sales org on multiple factors, including customer health for improved and proactive customer retention.
Want to better engage audiences and make an impact? Then consider adding visuals to your content.
Assets like infographics are the visual content you need to add to your content marketing mix – but how can you make yours stand out among the rest?
In this presentation, learn the best practices for creating infographics that will educate and engage your audience.
Discover:
– How to plan for and gather the data and content you need for an infographic.
– 5 best practices for structuring and organizing your content into an infographic.
– How to create an interactive infographic.
– Success stories and results from customers.
Big data and data science will transform enterprises in the future, allowing companies to gain insights from data to find new revenue opportunities. Data science can help enterprises optimize lead generation processes, prevent customer churn, and more accurately predict sales. If enterprises apply data science techniques like consumer companies have, it will fuel large growth by powering personalized recommendations and predictive analytics across various business functions and customer touchpoints.
This document summarizes the growth strategies implemented at Skyscanner over 4.5 years. It discusses transitioning to growth-focused teams organized into tribes. The key aspects that helped drive growth include adopting a lean startup approach with agile marketing principles. This involved highly aligned autonomous teams, frequent experimentation, and customer-focused collaboration across functions. It also emphasizes adopting a growth mindset and culture throughout the organization to support innovative strategies for driving impact.
Gazelle Information Technologies has completed 4 years of helping organizations optimize their supply chain processes. Over this time, Gazelle has helped clients set up sales and operations planning, improve forecasting, optimize inventory, benchmark freight, design supply chain networks, and do dispatch planning, resulting in total combined savings of millions of dollars. Gazelle has developed an end-to-end supply chain management solution that can run on multiple platforms and extract secondary sales data to generate forecasts, conduct S&OP planning, and optimize production and dispatch planning. This full suite of supply chain solutions is now available via Microsoft's Azure platform.
Intelligent Tooling for (Digital) SalesBarry Magee
The document discusses using intelligent tools to help digital sales teams. It notes key seller questions around achieving sales targets and prioritizing clients effectively. It then outlines some of the challenges sales teams face like having too much data and tools, not enough time, and lack of insights. The solution discussed using a cognitive sales advisor that maps territories, provides insights, and helps answer questions to optimize sales processes. It aims to help sales teams prioritize, prepare for client engagements, and find new customers through a data-driven approach.
Intelligent Data - Thoughts on the Analytics of TomorrowSteen Rasmussen
My session from #mesurecamp with thoughts and ideas of what can be done with web and digital analytics data both right now i 2018 but also in the near future to support the business with a return on analytics focus.
"Rebuilding UI at Large Scale" by Monika Halim (GO-JEK)Tech in Asia ID
Monika Halim, or most people call her Momo, believe that being human-centered should also makes us a better person. She's heading GO-JEK's Product Design team that builds over 20 products for consumer, drivers and partners.
She graduated as Bachelor of Design from Bandung Institute of Technology with major in Visual Communication Design, her past experiences including researching and designing for Indonesia Mengajar, led the design & optimization team at ZALORA, and part of the OgilvyOne’s Asia Pacific UX Team.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Watson Analytics provides self-service data analytics capabilities including data acquisition, cleansing, insights discovery, outcome prediction, visualization, and action without requiring data expert assistance. It handles large volumes of rapidly accessible data and automates data preparation, refinement, management, and analysis from the cloud. Statistical analysis, correlations, and predictions help users gain a deeper understanding of their business to see relevant information, take action, and anticipate opportunities.
Artificial Intelligence: How Enterprises Can Crush It With Apache Spark: Keyn...Spark Summit
Artificial intelligence (AI) is not new. It emerged as a computer science discipline in the 50’s and has been a persistent theme in science fiction. What is new is that enterprises now have the prerequisites needed to create pragmatic AI applications: plenty of data, deep learning frameworks, and blazing fast distributed compute clusters à la Apache Spark. Forrester Vice President and Principal Analyst, Mike Gualtieri will enumerate and demystify nine essential AI technology building blocks that enterprises can use to add a modicum of intelligence to existing and new applications.
How Brands can use AI for Actionable Customer IntelligenceGanes Kesari
This session was delivered on Apr 20th 2020 at the Rutgers Business School. This was a Guest Lecture for the "AI in Marketing" class.
Session Brief:
Today, customers interact with brands continuously, either intentionally or indirectly. They do so on a number of channels, and leave a variety of digital footprints. Unfortunately, enterprises miss out on this opportunity to understand and connect with the customers. This session will show how brands can leverage data and technology to understand their customers.
Brands can harvest both structured and unstructured data from diverse channels. With the help of data analytics, they can build an integrated view of the customer. By overlaying the content with context, they can map every conversation on the customer journey. By stitching all these insights together, brands can use storytelling to help drive the right business decisions.
How Data Science can help Understand your Customers BetterGanes Kesari
This was presented at the AT&T Retirees Quarterly ELATE Luncheon, on Sep 18th, 2019.
SESSION BRIEF:
Most organizations struggle to understand their customers. In a digital world, the power of data and technology is not tapped into. So, customer advocacy initiatives are short-sighted, transactional and unscientific. This session will show how organizations can listen to customers better. It will introduce you to AI techniques that are revolutionizing customer intelligence.
With examples, you will understand how these insights can be translated into business decisions.
LEARNING OBJECTIVES:
1. You will learn creative ways to find what customers are looking for right now
2. You will be introduced to advanced analytics techniques and storytelling with data
3. You will understand how data science can be applied for business decisions
This document provides tips and guidance for effective storytelling with data. It discusses why storytelling is popular, such as short attention spans and overwhelming amounts of data. It also covers basics of storytelling in business, including knowing your audience, asking questions from their perspective, and providing closure. Tips for storytelling with data include working "on" the data, using the right amount of data, adding context, and always ending with actionable next steps. The overall message is that data is just the beginning, and the key is using insight and storytelling to separate yourself and add value for your audience.
The governments online future in the age of persuasive designEmagination ®
The document discusses 3 challenges facing government organizations in managing their online presence and goals: 1) having a jumble of data, tools, and pages that don't meet goals, 2) failing to provide good usability and accessibility, and 3) missing opportunities to influence decisions through persuasive design. It recommends listening to audiences, using data visualization to tell compelling stories, and applying persuasive design techniques to help audiences make better decisions.
Data Informed Product Management by Eventbrite Sr PMProduct School
The document advertises courses offered by Product School to help individuals and companies build product management skills. It provides information on courses in product management, coding for managers, data analytics for managers, digital marketing for managers, UX design for managers, product leadership, and corporate training. The courses are designed to teach practical skills through part-time online learning to help land jobs or advance careers in product management and related fields.
B2BCamp: ANNUITAS Technology First SyndromeB2BCamp
Brought to us by, Sarah Shelnut, ANNUITAS
Pick the right technologies and you will have a successful Demand Generation programs, right? Wrong. As tempting as it may be for marketers to be enticed by the latest and greatest technologies, we need to always think about what will best enable our existing strategy before we double down on a technology, especially one of the critical platforms like marketing automation or CRM.
Find out how to avoid the “technology-first syndrome” and make choices that drive results because they fit your organization, your needs and match your goals. It’s never technology first.
Companies can get stuck trying to analyze all that’s possible
and all that they could do through analytics, when they should
be taking that next step of recognizing what’s important and
what they should be doing
This document summarizes a presentation on how companies can succeed in the new digital market context.
The presentation discusses key trends companies cannot ignore, such as the importance of having the right data in the right place at the right time. It also discusses factors for success in the digital economy, such as mastering a fast feedback loop to quickly iterate products/services based on customer data insights.
Data is emphasized as more important than ever, with both massive opportunities and challenges to get it right. Leaders are said to strive for excellence across mobile/digital strategies, using data insights to transform customer experiences, and accelerating their overall digital businesses.
The presentation concludes that transformation can happen at all levels of an organization and that
CWIN17 New-York / keynote - The ten tenets of digital innovationCapgemini
The document outlines 11 tenets of digital innovation:
1) Innovation solves problems for both businesses and consumers.
2) Examine the underlying nature and opportunities of your business beyond current offerings.
3) Customer expectations are rising globally and without limits.
4) View customer service as a two-way relationship that empowers customers.
5) Use digital tools to make customer interactions asynchronous and available at all times.
6) Data should be earned through good experiences, not just collected for marketing or sales.
The document provides guidance on how to create an effective pitch deck for funding. It outlines 11 steps to tell a compelling story: 1) Define the problem and solution, 2) Tell a story with a sample company, 3) Describe the market size and opportunity, 4) Explain how the solution solves customer problems, 5) Provide proof through testimonials and data, 6) Prove the business model and revenue streams, 7) Show the capable leadership team, 8) Address the competition, 9) Specify the financial requirements and use of funds, 10) Outline the roadmap, and 11) End with a clear call to action. The overall goal is to open the investor's mind to the vision and get them
How artificial intelligence (AI) can help maximize customer intelligence ROIVincent de Stoecklin
This document discusses how artificial intelligence can help maximize customer intelligence ROI. It provides an overview of customer intelligence and discusses how AI is enabling more data, more predictive analytics, and more automation in customer intelligence. Specific use cases discussed include churn prediction and next best action recommendations for a large European bank, product recommendations for a B2B software vendor, and large-scale consumer insights for a global CPG company. The document concludes with best practices for AI projects, emphasizing defining processes, including business stakeholders, exploring and iterating on features, combining supervised and unsupervised machine learning, and robust deployment.
This document discusses transitioning a company to follow lean principles. It describes how the company Infochimps originally hypothesized products related to social media data and Foursquare data derivatives. However, customer interviews revealed the real problems customers wanted solutions for: finding the right data and having systems to access "big data" insights. The document discusses evaluating whether to build a new product for digital agencies seeking social media analytics tools based on learnings. It emphasizes that the lean canvas strategy framework can help diagnose whether to pivot the product or persevere with the original vision. Pivots involve changing the strategy, while staying focused on solving customer problems.
Trying to figure out if embedded analytics are for you?
According to Gartner Research, more than 90% of business leaders view content information as a strategic asset, yet fewer than 10% can quantify its economic value. Read this guide to learn why you should be leveraging an asset you already own--data--to build relationships, increase retention, and drive revenue.
Keynote Lavacon 2016 - Content as a Strategic Asset Aaron Fulkerson
Several macro-trends in business and emerging technologies have turned content into a strategic asset for businesses. Disintermediation, new conversational user interfaces, internet of things, and the move to customer success are some of these trends.
For more information on trends, read: http://mndt.ch/selfservnow
Presentation on "A PREDICTIVE ANALYTICS PRIMER" made as a task for the internship on "DATA ANALYTICS WITH MANAGERIAL APPLICATIONS" under Professor Sameer Mathur, IIM Lucknow. Submitted by TARANG JAIN,DTU
Customer Experience: A Catalyst for Digital TransformationCloudera, Inc.
Customer experience is a catalyst in many digital transformation projects. It is why many businesses invest in new technologies and processes to more effectively engage customers, constituents, or employees. The goal of putting digital tools to work in a transformative way is to ensure that data and insights connect people with information and processes that ultimately lead to a better experience for customers. Yet, it demands a modern approach that considers all of the platforms, processes, and data across the customer journey. The goal for many organizations is dynamically maintaining a single source of truth about each customer to drive personalized experiences based on individual preferences and behaviors.
However, businesses today have primarily invested in systems of record. While these systems are critical for managing internal operational processes, they are typically not effective for today's pace of business change. Insight-driven experiences require customer intelligence platforms that can finally create a customer 360. The deeper data and improved algorithms now available let users factor in individual affinity, segment, and a myriad of growing data sources. The result is greater relevance and effectiveness to deliver a differentiated experience that in today’s competitive landscape is not a luxury, but a necessity for survival.
In this session we will address:
3 things to learn:
•Leaders and Laggards of digital transformation
•How to create data-driven customer insights
•The importance of machine learning to uncover hidden insights
Introduction to Lean Analytics for Lean Startup Circle SFLean Analytics
An introduction to Lean Analytics for the Lean Startup Circle SF event. Covers the basic topics of analytics, Lean Analytics framework, and a number of case studies from companies such as Circle of Friends, Localmind, Static Pixels and more.
Product Strategy for Startups (english) #GoogleLaunchpadBenno Lœwenberg
Countless numbers of products are put out in the wild, that nobody asked for. Building something, that people actually need or want is enabled through a well shaped product strategy.
This talk illuminates how a propper product strategy looks like and what the crucial success factors are. How it helps translating business goals & vision into product design and business model, that take customer needs and market affordances into account.
#ProductStrategy, #ProductMarketFit, #MinimumViableProduct, #MVP, #JobsToBeDone, #JTBD, #LeanStartup, #LeanProductProcess, #ProductLifecycle, #RiskiestAssumptionTests
Chris is the Director of Consultancy for Aquila Insight, focussing on driving business growth through strategy development and alignment of Big Data, Analysis, Tech and Customer Experience.
Before Aquila, Chris spent 18 years working for Boots, Egg, Capital One, National Express, and most recently, as the Global Director of CLTV (Customer Lifetime Value) Strategy & Planning for Sony Mobile.
Starting life initially as an analyst of customer behavioural data, before ultimately moving to lead major CRM teams, Chris’ focus has always been on understanding both the business and customer need, and delivering an approach that blends these to create commercial growth.
Within his most recent role at Sony, Chris and his team led a joined up cross channel customer life stage programme, supported the development of a big data architecture, implemented commercialised customer satisfaction modelling and focus area development, and integrated a full end of end analytics unit. He was also responsible for One Sony Europe, looking to create a more joined up customer experience across the Sony group.
Similar to RBS Guest Lecture - Actionable Customer Intelligence with Journey Mapping (20)
Project Management Careers in Data ScienceGanes Kesari
This document discusses top career opportunities for project managers in data science. It outlines the typical roles and responsibilities of a data science project manager, including managing teams, translating business problems into data solutions, and driving organizational change and adoption of projects. The document emphasizes that while AI can perform many tasks, most organizations struggle to achieve business value from AI projects due to challenges like measuring impact. It provides tips for project managers to succeed in data science careers, such as learning both technical and domain skills, adapting frameworks to workflows, and owning change management.
How AI Can Help Anonymize Clinical Trial DataGanes Kesari
The document discusses the challenges of anonymizing clinical study reports to comply with increasing privacy regulations while maintaining transparency. It proposes a human-in-the-loop analytics approach using natural language processing and iterative risk scoring to transform structured and unstructured data in clinical studies. By leveraging domain expertise and user feedback, the solution aims to balance privacy, transparency and regulatory compliance for anonymizing sensitive clinical data.
Penn State Guest Lecture: Business Forecasting in Real LifeGanes Kesari
This deck was used in the guest lecture conducted at the Penn State College of Information Sciences and Technology. The session was delivered by Thanoj Kattamanchi and Ganes Kesari on November 30th, 2021.
Session Abstract:
What are the most common applications of forecasting techniques? This talk will share several industry case studies on forecasting. It will dive into the details of how a large agricultural conglomerate adopted price forecasting to achieve a revenue uplift of 3.2%. The session will cover the step-by-step approach adopted by the client, from business problem definition, data identification, variable selection, model evaluation, to deployment. It will conclude by sharing the top lessons learned and guidelines for aspiring data scientists considering a career in building machine learning applications.
500 startups cognitive bias in decision making - ganes kesari - nov 2021 - finalGanes Kesari
What are the most common cognitive biases that impact leaders? How can early-stage startups lay a foundation for data-driven decisions?
In this fireside chat for 500 Startups, I addressed startup founders on how to champion good data stewardship, embed it in product development, and ensure organizational ROI from data.
The session was conducted on November 10th, 2021.
The document discusses both the promise and risks of artificial intelligence through three examples of how AI is being used for social good. It describes how AI is being used to help save rhinos in Africa by detecting them in aerial images, track penguin populations in Antarctica by counting them in thousands of camera photos, and help control mosquito populations and reduce human deaths by predicting optimal places to release genetically modified mosquitoes. While AI shows potential to help solve problems, it also has risks like generating fake news or deepfakes that need to be addressed. The document advocates being curious about what AI can do but also watching out for its impacts and risks.
5 Steps to Transform into a Data-Driven Organization - Ganes Kesari - Gramen...Ganes Kesari
This session was presented on May 27th, 2021, in a Webinar organized by Gramener.
https://info.gramener.com/5-steps-to-transform-into-data-driven-organization
Session Details:
Today, organizations struggle to get value from data despite significant investments. Did you know that there's one factor that influences the outcomes of all your data initiatives?
This webinar will highlight how an organization's data maturity influences its performance. It will show how you can assess your data maturity and plan the five steps for data-driven business transformation.
Pain points we would be discussing:
Most organizations stagnate midway in their data journey.
Gartner says that over 87% of organizations in the industry are at lower levels of data maturity (levels 1 and 2 on a scale of 5).
Just doing more data science projects will not improve your capabilities or outcomes. The fact is that the top challenges reported by CDOs fall into five common areas.
This webinar will show what they are and how you can tackle them.
Who should attend
- Executives, Chief Data/Analytics Officers, Technology leaders, Business heads, Managers
What Will You Learn?
- What is data science maturity, and why does it matter?
- How do you assess data science maturity and limitations of the assessment?
- How can data science maturity help your organization level up (explained with an example)?
How AI can Save Lives with the Help of Satellite ImageryGanes Kesari
1) AI and satellite imagery can help count populations and detect building footprints to more efficiently plan mosquito release sites for controlling dengue-carrying mosquitoes.
2) A deep learning model is used to extract building footprints from high-resolution satellite images. Additional data layers like vegetation and statistical population distributions are then overlaid to estimate populations in small grid areas.
3) The resulting gridded maps showing population densities and unpopulated areas can help identify optimal locations to release genetically engineered mosquitoes, reducing planning time from weeks to hours and improving outcomes.
Saving lives by applying AI to Satellite imageryGanes Kesari
1) The document describes how AI and satellite imagery can be used to count populations and help defeat dengue by more accurately targeting mosquito release sites.
2) A 3 step method is outlined that involves detecting building footprints via deep learning, estimating population distributions using geospatial data layers, and producing gridded population maps.
3) The results were improved accuracy of release sites, reduced planning time from 3 weeks to 2 hours, and more efficient post-release monitoring. This solution is being implemented in multiple countries.
What Really is AI and How will it Shape our Future?Ganes Kesari
This document provides an overview of artificial intelligence (AI) and how it may shape the future. It discusses the history of AI and how recent trends in data, processing power, and other technologies are fueling the current AI revolution. The document explores what AI is capable of today, such as writing articles, generating images, predicting prices, and detecting fraud. It also examines scenarios for how AI could impact the future, ranging from gaining scary effectiveness to becoming disillusioning after an initial hype cycle. The document outlines the major players in the AI ecosystem, including companies producing and using AI technologies.
How AI can help you make your Audience Sit up and take NoticeGanes Kesari
This session was delivered in the IABC World Conference 2020, on June 15.
https://wc.iabc.com/sessions/
Session Abstract:
How do you cut through the clutter and connect with your audience? Can data make your message more credible? Can analytics help you craft compelling content? How can AI help understand your audience’s response? Today there is an over-abundance of information and a paucity of meaningful communication. Data and analytics can be invaluable aids in communication.
Details:
This session will cover four ways to enable this:
Sourcing data to develop your idea: An idea becomes credible when backed by data. But where do you find the data? We’ll see how to get creative with public data sources.
Taking the help of AI to build your narrative: AI needn’t be terrifying. With the open tools available, it can be a powerful aid in discovering insights and building a narrative
Adopting storytelling to craft your message: A set of simple yet powerful principles can transform ordinary messages into powerful stories.
Using content analytics to establish a feedback loop: Analyze your content and audience response in the form of text, video, and audio to get vital clues for improvement.
This session will have live polls for audience feedback and there will be short exercises to absorb the content from each module.
You’ll learn:
How to find data to support your idea.
Which AI tools and techniques can help develop your idea.
How to establish a content analytics feedback loop to learn and improve.
'Recession-proofing' your Business with DataGanes Kesari
This session was presented on May 7th 2020, in a Webinar organized by Gramener.
https://info.gramener.com/recession-proofing-your-business-with-data
COVID-19 has disrupted every industry and precipitated a recession. With the virus still in the early stages of progression, the only certainty is that the pains to the global economy will be prolonged.
Is your business ready for the long haul? Data is your best ally to navigate the crisis and come out stronger. This webinar will show you how.
What will I learn?
Which areas of your business can benefit most with a data-driven response.
A framework to identify use cases that will deliver the biggest bang for the buck.
How to identify new market opportunities and customers through creative approaches with data.
AGENDA:
- Relevance of data in the current crisis
- How data science can help you stay prepared to navigate the recession
- Industry case studies from Gramener's work to help clients respond to COVID-19
What's the Value of Data Science for Organizations: Tips for Invincibility in...Ganes Kesari
This session was delivered as an Open Colloquium on Apr 30th 2020 for the Master in Information program students. It was organized by the Rutgers School of Communication & Information.
The session covers 3 themes:
- How do enterprises and not-for-profit organizations gain value from data science?
- What are the biggest challenges in data science that professionals are unaware of? How can students translate that into learnings, to make themselves indispensable in the industry
- What's the impact of COVID-19 and the recession on data science industry? How will the data jobs be impacted?
These are the slides from the Gramener webinar conducted on 16-Jan-2020.
- What skills & roles will help you deliver your analytics and data visualization projects?
- What skills do most teams miss to hire for?
In a Gartner survey, CIOs reported 'team skills' as their biggest barrier ⚠️ to data science. They have trouble deciding the skill mix ⚗️needed or in finding the right people for the job.
This webinar will show the skills and roles you must plan for. You will learn how to tailor this based on your organization's data maturity. It will help you decide whether to upskill teams or hire externally. The session will show you how and where to find talent.
Throughout the webinar you will learn:
- Critical skills & roles needed in your data science team?
- Tips for data science hiring. What aspirants should know about the jobs?
- Insights presented using real-world examples
Why is it difficult to achieve strategic differentiation using AIGanes Kesari
This deck was presented at ICC 2019, the ISACA Chennai Conference, by Ganes Kesari.
Session Abstract:
Today, every organization is trying to make their business AI-ready. However, industry reports claim that “80% of data science projects will not deliver value”. While the destination is clear, the path to be taken isn’t obvious.
Companies struggle with several questions: How to lay out a robust data science roadmap? What skills do you need to hire for? How do AI models translate to business value? How to sustain a culture of innovation and insight?
This session will answer these questions and show how organizations can apply AI at scale. It achieves the following learning objectives:
* How to align data science with the organization’s strategic objectives?
* How to setup and scale teams?
* What organizational structures help deliver business value with AI?
AI for Social Good - Saving the Planet with Data ScienceGanes Kesari
This document discusses how AI and data science can help protect biodiversity by detecting, identifying, and counting animals using computer vision models. It provides examples of projects that use deep learning to identify salmon from underwater videos, classify species from photos shared on iNaturalist, estimate penguin counts from images, and detect elephants spotted via aerial surveys to help conservation efforts. The document emphasizes the importance of having adequate training data and combining automated methods with human inputs and validation to accurately protect threatened species.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
Analysis insight about a Flyball dog competition team's performanceroli9797
Insight of my analysis about a Flyball dog competition team's last year performance. Find more: https://github.com/rolandnagy-ds/flyball_race_analysis/tree/main
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Open Source Contributions to Postgres: The Basics POSETTE 2024ElizabethGarrettChri
Postgres is the most advanced open-source database in the world and it's supported by a community, not a single company. So how does this work? How does code actually get into Postgres? I recently had a patch submitted and committed and I want to share what I learned in that process. I’ll give you an overview of Postgres versions and how the underlying project codebase functions. I’ll also show you the process for submitting a patch and getting that tested and committed.
Global Situational Awareness of A.I. and where its headedvikram sood
You can see the future first in San Francisco.
Over the past year, the talk of the town has shifted from $10 billion compute clusters to $100 billion clusters to trillion-dollar clusters. Every six months another zero is added to the boardroom plans. Behind the scenes, there’s a fierce scramble to secure every power contract still available for the rest of the decade, every voltage transformer that can possibly be procured. American big business is gearing up to pour trillions of dollars into a long-unseen mobilization of American industrial might. By the end of the decade, American electricity production will have grown tens of percent; from the shale fields of Pennsylvania to the solar farms of Nevada, hundreds of millions of GPUs will hum.
The AGI race has begun. We are building machines that can think and reason. By 2025/26, these machines will outpace college graduates. By the end of the decade, they will be smarter than you or I; we will have superintelligence, in the true sense of the word. Along the way, national security forces not seen in half a century will be un-leashed, and before long, The Project will be on. If we’re lucky, we’ll be in an all-out race with the CCP; if we’re unlucky, an all-out war.
Everyone is now talking about AI, but few have the faintest glimmer of what is about to hit them. Nvidia analysts still think 2024 might be close to the peak. Mainstream pundits are stuck on the wilful blindness of “it’s just predicting the next word”. They see only hype and business-as-usual; at most they entertain another internet-scale technological change.
Before long, the world will wake up. But right now, there are perhaps a few hundred people, most of them in San Francisco and the AI labs, that have situational awareness. Through whatever peculiar forces of fate, I have found myself amongst them. A few years ago, these people were derided as crazy—but they trusted the trendlines, which allowed them to correctly predict the AI advances of the past few years. Whether these people are also right about the next few years remains to be seen. But these are very smart people—the smartest people I have ever met—and they are the ones building this technology. Perhaps they will be an odd footnote in history, or perhaps they will go down in history like Szilard and Oppenheimer and Teller. If they are seeing the future even close to correctly, we are in for a wild ride.
Let me tell you what we see.
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataKiwi Creative
Harness the power of AI-backed reports, benchmarking and data analysis to predict trends and detect anomalies in your marketing efforts.
Peter Caputa, CEO at Databox, reveals how you can discover the strategies and tools to increase your growth rate (and margins!).
From metrics to track to data habits to pick up, enhance your reporting for powerful insights to improve your B2B tech company's marketing.
- - -
This is the webinar recording from the June 2024 HubSpot User Group (HUG) for B2B Technology USA.
Watch the video recording at https://youtu.be/5vjwGfPN9lw
Sign up for future HUG events at https://events.hubspot.com/b2b-technology-usa/
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
End-to-end pipeline agility - Berlin Buzzwords 2024Lars Albertsson
We describe how we achieve high change agility in data engineering by eliminating the fear of breaking downstream data pipelines through end-to-end pipeline testing, and by using schema metaprogramming to safely eliminate boilerplate involved in changes that affect whole pipelines.
A quick poll on agility in changing pipelines from end to end indicated a huge span in capabilities. For the question "How long time does it take for all downstream pipelines to be adapted to an upstream change," the median response was 6 months, but some respondents could do it in less than a day. When quantitative data engineering differences between the best and worst are measured, the span is often 100x-1000x, sometimes even more.
A long time ago, we suffered at Spotify from fear of changing pipelines due to not knowing what the impact might be downstream. We made plans for a technical solution to test pipelines end-to-end to mitigate that fear, but the effort failed for cultural reasons. We eventually solved this challenge, but in a different context. In this presentation we will describe how we test full pipelines effectively by manipulating workflow orchestration, which enables us to make changes in pipelines without fear of breaking downstream.
Making schema changes that affect many jobs also involves a lot of toil and boilerplate. Using schema-on-read mitigates some of it, but has drawbacks since it makes it more difficult to detect errors early. We will describe how we have rejected this tradeoff by applying schema metaprogramming, eliminating boilerplate but keeping the protection of static typing, thereby further improving agility to quickly modify data pipelines without fear.
2. 2
INTRODUCTION
Ganes Kesari
Co-founder & Head of Analytics
“Simplify Data Science for all”
100+ Clients
Insights as Stories
@kesaritweets Help start, apply and adopt Data Science
8. 8
G O A L S A U D I E N C E A C T I O N S
Goals: Why am I
creating this?
Who are my users and
what do they want?
What actions should I
enable for them?
9. “Is purpose defined in sufficient detail?”
“ Show the manufacturing delays. ”
“ Show the manufacturing delays:
Ø over the last 12 months,
Ø across different products,
Ø by stages of production
Ø and highlight the bottom 10%. ”
vs
10. “Is my coverage complete?”
What’s excluded...
…is often more important than
what’s included
12. 12
L O O K O U T F O R 3
T Y P E S O F F E E D B A C K
Review websites, social
media
INDIRECT
Website clickstream
data, contact center
INFERRED
Voice of Customer
surveys, Interviews
DIRECT
Source: Gartner Market Guide for Voice-of-the-Customer Solutions
19. 19
S A M P L E T H I S C U S T O M E R
F E E D B A C K F R O M A V O C S U R V E Y
“I loved the product features and super-quick onboarding, but the great experience
did not continue while using your product. Your support teams have been helpful,
but I’m not sure whether I’ll buy again.”
20. 20
T A G T H E C O N T E N T T O
J O U R N E Y S T E P S
Identify Customize Use Product
Deal with Issues
Reorder
“I loved the product features and super-quick
onboarding, but the great experience did not
continue while using your product. Your
support teams have been helpful, but I’m not
sure whether I’ll buy again.”
“I loved the product features and super-quick onboarding, but the great experience
did not continue while using your product. Your support teams have been helpful,
but I’m not sure whether I’ll buy again.”
21. 21
L E T ’ S N O W A S K T H E
Q U E S T I O N S
Approach to data Benefits
AI / ML models with recommendations What actions will help me convert my
detractors into promoters?
Simple ML models What will be my promoter score
next quarter?
Statistics What led to lower
satisfaction in EMEA?
Simple summaries
Did I improve on
customer satisfaction?
22. 22
INTEGRATE THE FEEDBACK
SIGNALS
“Your summer collection
didn’t interest me”
Store Survey
“Drop in market share by
2.5% last month”
Market Report
“Disappointed with Brand
‘A’. Anyone still buying?”
Social Media
“Brand ‘B’ has more
‘vibrant’ colors than you”
Competitive Survey
Our summer collection didn’t work. We los 2.5% market share
with a projected revenue dip. We must improve our product.
“
“Predicted dip in Monthly
revenue by 11%”
Financials
24. 24
O V E R 5 0 % O F D A T A S C I E N C E
P R O J E C T S N E V E R G E T
D E P L O Y E D .
B A D S T O R Y T E L L I N G I S A K E Y
R E A S O N F O R T H I S F A I L U R E .
G A R T N E R
Gartner: “How to use Storytelling to sell your Data science projects”, Apr 25 ‘19
“
25. 25
Gartner: “How to use Storytelling to sell your Data science projects”, Apr 25 ‘19
27. 27
ADD CONTEXT & NARRATIVE TO BUILD THE STORY
Sales grew 40% in 2018, despite competitive product launches
Gartner: “How to use Storytelling to sell your Data science projects”, Apr 25 ‘19
28. 28
STORYTELLING CHANGES IN
CUSTOMER SATISFACTION
Hig
h
Impact
on
Satisfaction
Low
High impact CX
Negative Positive
Low High
Customer Sentiment
Q2’20
Identify
Buy
Q2’20
Service
Q2’20
Reorder
Q2’20
Use
Q2’20
Customize
Improve on ‘Service’
Maintain ‘Identify’ & ‘Buy’
‘Customize’ is less important
Q2’20
29. 29
RECAP: 4 STEPS TO ACTIONABLE
CUSTOMER INTELLIGENCE
• Define customer persona
• Ask the right questions
UNDERSTAND
1
2 • Direct, Indirect, Inferred
• Analyze all data types
COLLECT
4
STORY-TELL
• Visualize the insights
• Drive actions with stories
3
ANALYZE
• Understand their Journey
• Roll-up for the headline