Program Experience

Highlights and Key Outcomes

In Customer Analytics for Growth, you will:

  • Master the framing of managerial questions around big data and analytics
  • Select the right tools for predicting future customer behavior
  • Explore and understand the latest AI applications, including their pros and cons
  • Discover the companies that are using these new technologies most effectively
  • Gain insights into best practices for recruiting and managing data-science teams
  • Learn methods for rapid, agile experimentation to test and learn from new analytics projects

Experience & Impact

Academic Director Raghuram Iyengar on the “3 Pillars of Analytics.”

Many companies have been swimming in data, and spending millions to collect more. But the unprecedented shifts in the economy and resulting swings in consumer behavior have rearranged the competitive landscape. Customer Analytics for Growth addresses the most pressing concerns of business leaders today who need to understand and utilize the latest methods for collecting and analyzing data.

This program explores the growing need for greater customer centricity and examines data privacy regulations and how to build a compliant analytics program. Participants will learn how to cultivate an analytics-based mindset throughout their organization and gain a deep understanding of emerging AI technologies that are rapidly changing businesses today.

The program examines customer analytics using three foundational pillars:

  • Descriptive Analytics examines the different types of customer data and how they can be visualized, ultimately helping you leverage your findings and strengthen your decision making.
  • Predictive Analytics explores the potential applications of data once collected and interpreted. Modeling tools such as regression analysis and the latest machine learning algorithms can help to predict future end-user behavior.
  • Prescriptive Analytics takes you through the final step: formulating concrete recommendations based on your data. These recommendations can be directed toward a variety of efforts, including pricing and social-platform outreach.

A distinctive highlight of Customer Analytics for Growth is engaging in discussions with expert practitioners from a range of industries who have experience with both business-to-consumer and business-to-business customer models. They will reveal their real-time challenges and best practices, sharing their experience with the three most common hurdles of analytics strategy — tools, talent, and metrics — discussing what tools to use when, how to build analytics teams, and what to track about your customers. Each session also includes a short, highly interactive case study that allows you to explore real-world applications.

Customer Analytics for Growth brings together a powerhouse team of Wharton faculty from operations, information, and decisions; legal studies and business ethics; marketing; and statistics. They guide you through the most current theories and best practices for designing and implementing a data-analysis strategy, while continuously linking the learning to your real-life challenges.

The exceptional multidisciplinary learning journey will also give you a front-row seat to the powerful research and thought leadership of Wharton Customer Analytics (WCA), the world’s preeminent academic research center focusing on the practice of data-driven business decision making. This offers an advantage you will not find anywhere else.


Academic Director Raghuram Iyengar on the live case study


Customer Analytics Capstone Project and Crowdsourced Applied-Learning Project

The Customer Analytics for Growth Capstone and Crowdsourced Applied-Learning Projects gives you two separate opportunities to apply what you’ve learned about how to make data-driven decisions to a real business challenge. Working in groups, you will leverage skills within your group to identify how to successfully use data to create cutting-edge, customer-focused marketing practices.

In the Capstone Project, groups will use real-world data to apply customer analytics to marketing challenges, starting with data collection and data exploration, and continuing all the way to data-driven decisions. You will be challenged to manipulate data and truly translate the results, providing the hands-on experience of becoming a data translator for your organization.

Session topics include:

  • The Future of Marketing Science: Big Data, New Data, Better Science
  • How AI and Machine Learning Are Changing Customer Analytics
  • Building the Analytics Team
  • Customer Value Analysis
  • Business Experiments
  • Storytelling Through Analytics
  • Pricing Analytics

Wharton LIVE Programming

Real-time, synchronous peer learning

The live, virtual version of Customer Analytics for Growth is a five-day program that will be led by the same Wharton faculty who teach in the on-campus program, and it requires a high level of engagement. The sessions are structured to include interactive discussions so that participants can discuss analytics challenges with faculty, guest speakers, and an experienced group of peers. Dynamic small group work helps reinforce the learning and enable networking within the peer community. Guest lecturers and speakers will include Zachery Anderson, chief data & analytics officer at RBS and Neil Hoyne, chief measurement strategist at Google.

A highlight of the live virtual program is a crowdsourced, applied-learning project. Participants are encouraged to identify a current analytics challenge that they share within small groups. Multi-level pitching and feedback sessions afford the opportunity to develop unique solutions that may have their origins in different industries, markets, or geographies that are experiencing similar challenges.

Program Duration:

  • Oct. 26 – 30, 2020
    9:30 a.m. to 2:00 p.m. EDT (most days)

Post-Program Webinar

Customer Analytics for Growth also includes a webinar conducted after the program ends to help participants integrate key learnings. Led by Professor Raghu Iyengar, the program’s academic director, this one-hour session allows participants to share the main achievements in implementing concepts and ideas from the course as well as the challenges participants faced implementing concepts. Bringing the cohort back together, this webinar reinforces the importance of peer support as well as faculty insights.


Convince Your Supervisor

Here’s a justification letter you can edit and send to your supervisor to help you make the case for attending this Wharton program.


Analytics, Risk, and the 21st Century Supply Chain

Wharton Customer Analytics InititativeThe business of moving goods from their point of origin to their final destination anywhere on Earth is no small task, and the risks seem to be growing.

Read more on the Wharton Customer Analytics blog.


Wharton Customer Analytics (WCA)

Wharton Customer AnalyticsWCA is the world’s preeminent academic research center focusing on the development and application of customer analytics methods.

Learn more about our academic research center.

Who Should Attend

Senior-level managers in both B-to-C and B-to-B organizations who are responsible for influencing business decisions across marketing, finance, operations, and strategy will benefit from Customer Analytics for Growth. Additionally, executives who are responsible for interfacing with data science and the teams that collect data, those who are beginning to use available data to inform strategy and operating decisions, and those who are new to analytics will benefit from the program.

Participants are not required to have a strong math or technical background. Customer Analytics for Growth focuses on the managerial issues that intersect with analytics, including how best to convey insights from data to decision makers.

Industries that are currently exploiting business analytics include, but are not limited to, consumer packaged goods, financial services, health care/pharmaceuticals, manufacturing, media/communications technology, hardware/software technology, transportation, and logistics.

Job titles may include:

  • Chief Marketing Officer
  • Chief Information and Digital Officer
  • Chief Product Officer
  • Global Director, Pricing Strategy
  • SVP, Data and Decision Sciences
  • SVP, Corporate Research and Analytics
  • VP, Digital Strategy
  • Managing Director
  • Director, Business Intelligence
  • Director, Corporate Sales Operations
  • Director, Digital Marketing
  • Director, Marketing Communications
  • Director, Product Management
  • Director, Products and Services
  • Principal Data Scientist
  • Business Intelligence Analyst
  • Marketing Research Analyst

Participant Profile

Participants by Industry

Customer Analytics Industry Demographic

Participants by Job Function

Customer Analytics participants by job function

Participants by Region

Customer Analytics participants by region


Group Enrollment

To further leverage the value and impact of this program, we encourage companies to send cross-functional teams of executives to Wharton. We offer group enrollment benefits to companies sending four or more participants.

Faculty


Raghura Iyengar

Raghuram Iyengar, PhDSee Faculty Bio

Academic Director

Miers-Busch, W’1885 Professor, Professor of Marketing; Faculty Director, Wharton Customer Analytics (WCA), The Wharton School

Research Interests: Pricing, social influence, social networks


Zachery Anderson

Zachery AndersonSee Faculty Bio

Chief Data and Analytics Officer, Royal Bank of Scotland (RBS)


Eric Bradlow

Eric Bradlow, PhDSee Faculty Bio

The K. P. Chao Professor; Professor of Marketing; Vice Dean, Analytics at Wharton; Chairperson, Wharton Marketing Department, The Wharton School; Professor of Economics; Professor of Education; Professor of Statistics, University of Pennsylvania

Research Interests: Marketing research methods, missing-data problems, psychometrics


Peter Fader

Peter Fader, PhDSee Faculty Bio

Frances and Pei-Yuan Chia Professor; Professor of Marketing, The Wharton School

Research Interests: Lifetime value of the customer, sales forecasting for new products, behavioral data


Neil Hoyne

Neil HoyneSee Faculty Bio

Chief Measurement Strategist, Google; Senior Fellow, The Wharton School


Jagmohan Raju

Jagmohan Raju, PhDSee Faculty Bio

Joseph J. Aresty Professor; Executive Director, Wharton Co-Sponsorship of Indian School of Business; Professor of Marketing; Vice Dean, Wharton Executive Education

Research Interests: Competitive strategy, pricing, retailing


Lyle Ungar

Lyle Ungar, PhDSee Faculty Bio

Professor of Bioengineering, Professor of Computer and Information Science, the School of Engineering and Applied Science; Professor of Genomics and Computational Biology, Perelman School of Medicine; Professor of Operations, Information and Decisions, the Wharton School; Professor of Psychology, School of Arts and Sciences, the University of Pennsylvania

Research Interests: Statistical natural-language processing, deep learning, mining social media to better understand personality


Abraham Wyner

Abraham Wyner, PhDSee Faculty Bio

Professor of Statistics; Director of Undergraduate Program in Statistics; Faculty Lead of the Wharton Sports Analytics and Business Initiative, The Wharton School

Research Interests: Baseball, boosting, data compression, entropy, information theory, probabilistic modeling, temperature reconstructions

Testimonials


I lead global social listening and measurement at McDonald’s, which includes strategic planning, ongoing tool and capability enablement, measurement of social programs, and deep customer insights work, identifying trends and using customer feedback to improve our business.

I loved the Customer Analytics program. It was energizing, and a nice balance between very quantitatively rigorous and qualitatively engaging. The materials were industry agnostic, and you didn’t have to be an expert on machine learning or modeling to understand the concepts.

Among my most valuable takeaways was the concept of moving from thinking about product-line profitability to looking at customer profitability. We talked about segmenting our customer data based on CLV instead of products, which is a better way to run your business. Another key takeaway was the discussion about how companies need to align to a core set of KPIs across the organization. I live in the world of social where we have so many metrics — likes, shares, retweets, favorites, comments — so narrowing those down to metrics that link with core KPIs will be helpful.

I especially enjoyed the guest speaker Zach Anderson from Electronic Arts. He emphasized that when it comes to customer analytics and results, change to the business doesn’t come overnight. It’s a multi-year journey, and you need to focus your energies on your most important customers in order to realize returns over time.

The faculty was great. Eric Bradlow is larger-than-life. Raghu Iyengar is extremely engaging. I appreciated that the faculty encouraged dialogue among the participants so we would learn from each other and continue our relationships after the program. I also loved the red-carpet treatment we received: we were well taken care of as participants.

Jola OliverDirector, Global Social Listening & Measurement, McDonald’s Corp.


In my role, part of my focus is on environmental and social governance, or ESG, as a criteria for investing. I work with what’s referred to as alternative data in order to identify opportunities and manage risk. I thought Customer Analytics was a fantastic program. It far exceeded my expectations, and I had high expectations going in. It feels like when you’ve finished the program, you almost have a semester’s worth of material that you walked away with in five days.

I was able to start using practical information in evaluating investments right away. Even during the program, in having conversations with colleagues, I was able to pick up some ideas and use them almost in real time.

One of the important things Customer Analytics reinforced for me was to resist the temptation of the next “shiny object” in analytics and machine learning, since there’s so much hype. Simplicity is key, and often it comes down to just finding the right approach to the right problem. At the same time, there’s always new concepts to learn in this space, and different tools you can add to your toolbox to use when you need to.

I especially enjoyed the interdisciplinary nature of the program. Every faculty member and speaker had a different topic or perspective on analytics. One talked about sports analytics, one came from the world of video games, another from Google, and others from traditional technology and marketing. It was a really nice mix and I thought that was a strength of the program. I also appreciated the diversity of industries among the participants. You’d be hard pressed to find two people with similar backgrounds: participants came from biotech, media, finance, technology, and several others.

I highly recommend the program, and would attend another Wharton Executive Education course without hesitation.

Michael FerrariManaging Partner, Atlas Research Innovations


At Merck, I serve as a data scientist responsible for improving decision-making and business results in our Company’s Global Human Health (GHH) division through innovative uses of data and analytics. I enrolled in Customer Analytics because I want to stay abreast of new developments in customer analytics given the amount of data that are now available, not just in the pharmaceutical industry but every industry. I wanted to learn about industry agnostic novel analytical methodologies that can be leveraged to derive actionable insights from big data. In addition to the course content, Wharton’s reputation was a big factor in my choosing the program.

I loved the program. The faculty was very knowledgeable. Professor Raghu Iyengar and I have remained in touch on LinkedIn. I also really enjoyed the guest speakers, and the opportunity to interact with peers from other industries. I realized that they were facing similar challenges to mine in the pharmaceutical sector, and that the potential solutions are not necessarily unique to pharmaceuticals.

In addition to the technical aspects of the training, I was particularly interested in discovering how to better engage the non-technical individuals in my organization and to communicate insights from analytics in an actionable way. I also wanted to explore how to optimally organize and run an analytical team. The program really focused on all these topics, so that was very helpful to me.

I started applying concepts from the course to my job almost immediately. Two concepts that I found very useful are customer lifetime value and re-defining big data as more columns — unique information — at the unit of experiment as opposed to more rows — units of experiments. I would definitely recommend the course.

Andrew RugaiganisaAssociate Director, Global Innovation Analytics, Merck & Co.


I’m a director of operations for analytics in the U.S. Air Force, which is a relatively new position. We are looking at how we will use big data in order to create new syllabi for our student pilots. We will also use analytics to judge readiness of our operational pilots. I enrolled in the Wharton program because I did not have a strong background in analytics and needed some further academic training. Although I have a number of data analysts and scientists working with me, I did not understand the big picture or have ideas about where we could go with the information we have.

Wharton’s Customer Analytics program was fantastic. Applying what I learned at Wharton is now part of my everyday job. For instance, I’m using the concept of customer lifetime value to create what we are calling pilot lifetime value. We’re also building decision trees based on a student pilot’s ability to perform specific tasks in the jet, in order to transition to personalized training. Moreover, being able to communicate clearly about analytics—to explain it to my leadership and co-workers the same way it was explained to me in the course—is very useful in gaining cultural buy-in.

The faculty was excellent and I also really enjoyed the guest speakers from Google and Electronic Arts (EA). Many of the participants already had a lot of knowledge about solving customer analytics problems for their organizations, and I picked up useful information from them. I’ve already recommended the program, and Wharton, to others. One of my co-workers will be attending a Wharton Executive Education leadership course this spring.”

Matthew RossMajor, Chief Data Officer, 4th Training Squadron, U.S. Air Force


At the Gates Foundation, we seek to end the problems that contribute most to inequality in health and productivity. That means focusing on getting to zero – zero malaria, zero HIV, zero difference between the health of a poor kid and every other kid. To accomplish this, we need to leverage more and more granular information about populations and individuals. I lead an analytics team that brings data expertise and advanced modeling in order to drive more precision in our organization’s decision-making, while also making investments in the field so our partners can more easily do this kind of work as well.

I enrolled in Customer Analytics because I’ve always thought we could learn a lot from the for-profit marketing and e-commerce world that is generating profit by using customer data to drive precision in products and marketing. I wanted to have contact with people outside of the ‘usual suspects’ at the events we go to, who typically work at non-profit and government entities. At Wharton I met people from industries ranging from pharma to restaurants to content distribution, and it was really rewarding and enriching to see how they shaped their business problems and applied the tools we were learning. Although our challenges are different — theirs is business competition and ours is achieving our mission — we were all trying to change our organizations and ecosystems in much the same way.

The faculty was exceptional. I was absolutely floored by the quality of their instruction, their ability to drive engagement, their command of the subject matter, and their ability to tie together the many different perspectives in the room. They made the course both academically eye-opening and fascinating, as well as practical and actionable.

Professor Eric Bradlow’s initial session was transformative for me. He talked about how to view problems and the data associated with them in a way that pivots from a product-oriented view to a customer-oriented view. It made sense for a foundation like ours — which is organized around disease verticals and the products that cure them — to figure out how to incorporate this perspective.

This course is a great introduction to, and framing of, data analytics that you can take back to your organization to work more effectively with data and data scientists. It helps you learn to ask good questions that are answerable with data, and to cut through the clutter and hype around analytics techniques. I highly recommend it.

Ben PiersonSenior Program Officer, Bill and Melinda Gates Foundation


Christine WilliamsDirector, Customer Analytics, Anthropologie


I'm responsible for the data our sales organization uses to manage business KPIs and our primary applications of CRM and Microsoft Power BI. I enrolled in Customer Analytics because our organization is looking to invest in understanding how we can better leverage our data sets to drive business insights. Traditionally we’ve mostly been reactive, but in growing as a business, you realize you need a more strategic methodology around how you’re pulling data and presenting it to solve problems. We also want to get more into predictive analytics.

The program was great. The academic director, Raghu Iyengar, was awesome, and all the faculty and speakers were very informative, interesting, and engaging. The staff that helped coordinate the program and answer questions was very nice and accommodating. The week went really fast; the days were long, but they didn’t seem long.

The very first presentation, on the first day, hit the nail on the head for me. It was about segmenting your business and customers, and running customer lifetime value data to understand who’s contributing the most to your company and why. And just a couple of weeks prior, my colleagues and I had been talking about the need to figure that out. So it really resonated with me and was immediately applicable to what we were working on. I took a ton of useful insights from the program that I have applied and continue to apply.

My background is in sales and I was concerned there would be a lot of participants with statistical or mathematical backgrounds, but there were plenty of business leaders there as well. I discovered that many other companies have the same issues as we do, which was interesting and helpful to know. I would absolutely recommend the program to anyone looking to take it who is in a similar role to mine."

Todd IngenitoDirector, Corporate Sales Operations, SHI International Corp.


I am CBC’s strategy manager for Guatemala and Jamaica, and that basically involves three pillars: consumer pricing; customer pricing, including the trade terms we give our customers; and demand planning. We’re playing a quick game of catch-up with technology because we are based in Central America, and with Customer Analytics for Growth we recognized a great opportunity to see what they’re doing in the U.S. and around the world in advanced customer analytics.

I enjoyed the program very much. The high academic standards of the professors, guest speakers, and classmates really challenges you to a new way of thinking. It was very holistic in that it had a pricing module and an analytics module. I particularly liked the pricing module and also the speakers from Google and EA Sports. The program offered insights into what the future holds — such as blockchain management — as well as many quick wins, or low-hanging fruit, that we were able to apply to the business very fast. From the program, we discovered a new way to understand consumers better and to segment our customer base. We’re now directing our discounts more specifically to certain customers in a way that will add value to our business and not just give the same thing to everyone.

Moreover, when I returned from the course, I had exposure with my CEO, my executive president, the general director, and the VP of marketing to present my insights. It’s not easy to get time in their agenda, yet a 30-minute meeting turned into almost two hours because the discussion was so enriching. I think it also contributed to the next step in my career, my recent promotion from revenue management to strategy manager.

I would totally recommend the program. On a scale of 1 to 10, it’s a 10. I have a very strong interest in continuing my professional leadership development at Wharton.”

Alfredo CastanedaStrategy Manager, Central America Bottling Corporation, Guatemala


At Cubic, we have a philosophy of ‘winning the customer.’ As part of this philosophy, it’s important that we understand our customers and their needs, both today and in the future. We believe that one way we can achieve this level of customer commitment is through the use of customer analytics.

To help further develop my knowledge in analytics, I enrolled in Customer Analytics for Growth. The program is fantastic. I enjoyed every minute of it. I can’t speak highly enough of the team at Wharton; they have created a program that is well structured and relevant to any business.

During the five-day program, we worked through a wide range of analytics, including pricing analytics, customer value, and much more. I was worried I was going to spend days looking at mathematical formulas, but that wasn’t the case. The program offered great variety, and any time we did spend working through formulas was in groups and focused on understanding how our calculations related to real-life business challenges.

The guest speakers from a wide range of industries were insightful and informative. They shared with us their experiences of implementing customer analytics, answered our questions, and presented the positive results their businesses have seen.

The program has opened my eyes to new possibilities for analytics. Since returning from the program, I’ve presented two ideas to the leadership team at Cubic on how we can use customer analytics. The business has welcomed the ideas, and we’re now partnering with the Wharton Customer Analytics initiative on two projects.

I highly recommend Customer Analytics for Growth to anyone who wants to use data to create a stronger and healthier relationship with their customers.”

Zoe YatesDirector of International Marketing and Customer Analytics, Cubic Mission Solutions, United Kingdom


Customer Analytics for Growth was fantastic. It covered best practices for thinking about data, machine learning, and analytics. I'm not a marketer by background but I am quite data driven, and the course was very helpful in providing an understanding of how the role of analytics is changing in decision making. It also explored how managers should be shaping their organizations to use these techniques.

The course was not overly technical so it should not deter anyone who is uncomfortable with quant. The number of industry-based guest lecturers was very helpful in providing a real-world view of the challenges.

I think that every business is becoming a data-driven business and becoming data-centric these days. And a huge part of what we're doing at my company carsales.com is to think about — as a technology company — what data do we need to be able to improve the customer experience, and to maximize our ability to wrap all of our services around the customer? So the course was really useful.”

Stephen WongChief Strategy Officer, carsales.com


I do independent consulting and I’m currently working with an international communications and marketing agency. I decided to enroll in the Customer Analytics for Growth program because I have worked for 14 years in the consulting industry and wanted to better understand what my clients wanted and needed.

The Wharton program helped me integrate most of my past work experience into one coherent set of skills and gave me a foundation to expand my capabilities. My appreciation for what customers might be looking for has been shifted quite a bit, and I really gained great insights into what it means to work with customers.

One major insight that I got from Customer Analytics for Growth was that even though human beings can be infinitely complex, their behavioral patterns are actually not that complex when it comes down to the moment of deciding whether to buy something or not. There are a lot of great tools that can help you understand customers’ underlying propensities and past behaviors.

Another takeaway was that because there’s so much freedom and reach in what you can do in the online digital space, ethics matter. It’s important not just for people in my role but for users, site operators, and ad agencies. I also gained a better understanding of the larger customer analytics community — marketers, consumers, corporate managers, scientists, and developers — and the part each one plays in this field.

The faculty was excellent and the program was well designed. I felt that they delivered the program at their best. I also had a great time getting to know the other participants during the classes and at lunch and dinner. We ended up building a collective view, a coherent understanding, of a given subject. That kind of thing never happens in a regular work environment, so I really liked that aspect of being in the program. I strongly recommend the course. I would give it a 10 on a scale of 10.

As a Wharton alum taking this class, I almost forgot what it would be like to be back at Wharton. It was a reminder of the quality and style of the faculty, and I realized I missed that environment very much: an environment where you get to access the intellect and rigor of those researchers. I also enjoyed being around the staff members and of course the students who come to take the courses.

So it was great to be surrounded by the kind of place where you can appreciate what academia has achieved over many years, where you can access resources to really understand what’s happening around you, in your own way and on your own terms. I really want that kind of message to be sent out there: for people to understand what it’s like to be back in school once in a while.”

Takashi YoshizakiFounder, Takashi Yoshizaki Consulting, New York City


Everything that was covered in Wharton’s Customer Analytics for Growth program — from understanding baseline decisions about data to different types of analytics — is relevant for my company. When I came back and presented some of what we learned, my boss said the program already paid for itself several times over.

I’ve been through many training programs, but this program was by far the best. The interactions with the professors, all of whom I got to know, and the rest of the class made for a lot of opportunities to learn more, make connections, and network. My company will be sending more people next year."

Crystal Bray, PhDSr. Data Scientist and Head of Advanced Analytics, Tailored Brands


Wharton really goes in depth, not only in the theory but also in tools and strategy. It’s the right combination of the theoretical and the tactical, and you start implementing what you are learning in real time.

Many times programs like this take you from A to H. You learn some of what you need but not everything. Customer Analytics for Growth goes from A to Z. The professors are fantastic and cover every aspect of the subject. There is no other way to learn this much about customer analytics without going back to school."

Kati StratosDirector, Analytics, Comcast


When you go to a program 3,700 miles away, you must be very sure that it’s going to be a great program in a great business school, and you go with many questions in your mind. Some of my questions were broad, including why we need to change from a product-centric model to a customer-centric one, and why customer lifetime value is a key if you want to be successful in your business. I also came to the program wanting to know more about specific metrics topics such as regression and deviation.

Customer Analytics for Growth answered all of my questions, and the program has been key for my future in this new world. It was worth every one of the 3,700 miles of travel to study at a great business school with the best teachers and highly engaged classmates."

Salvador Muñoz PatiñoSales Manager for Spain — Portugal, Teradata Iberia


Everyone reads about Netflix and Amazon doing amazing analytics and making great strides. But they’ve been doing it for a long time with big budgets. Now after attending Customer Analytics for Growth, I am confident that as a small company there are things we can do to nudge up to them if we are focused. We don’t have to replicate what they’re doing. By creating our own analytics strategy we can address our challenges and save hundreds of thousands of dollars because of what we are learning. My company is already looking at our offerings and pricing in a new way, and starting to make changes.

You can’t get the level of learning and instruction anywhere else. The professors take complex concepts and make you comfortable with them. You leave ready to start using what you learned."

Steve GebhartChief Technology Officer, Western Veterinary Conference


I started using what I learned in the program almost immediately. The course helped me realize that I needed to readjust a couple of people on my team to becoming more informed in certain areas. The learning curve is almost vertical. Every day they can do more things, and I’m seeing dividends already.

I particularly enjoyed the program’s discussions of applied solutions, including the presentation on sports and the talk by Zach Anderson, Chief Analytics Officer of Electronic Arts. Seeing those models in action, and learning how they were built, was very interesting. I also liked that they allowed us to look under the hood a little to show us the actual algorithms. Overall, the caliber of the faculty and guest speakers was world-class.

Exchanging ideas with the other participants was very valuable, whether they were people with the same role as mine but a different industry, or different roles within my industry. The various perspectives really made me think. I also appreciated hearing experts and peers talk about AI and the problems they’re trying to solve with it. It’s a complex area, but I now feel I can speak more authoritatively on the subject.”

Patrizio CernettiStrategy Advisor , Sapient Industries

FAQs

What does customer analytics mean? What does customer analysis mean?

Customer analytics involves both understanding the customer journey and then recommending what firms should do based on those insights. There are three parts to customer analytics.

  • The first part is descriptive analytics — visualizing the customer journey using the data that a firm has.
  • The next part is predictive analytics — forecasting what customers will do in the future based on the marketing mix.
  • The last step is prescriptive analytics. This step offers actionable decisions that the firm can make based on understanding the customer journey.

Customer analysis can be broadly categorized under predictive analytics.

What is consumer behavior analysis?

Customer analytics typically involves a deep dive using data on transactions that a customer may have with a particular company. Consumer behavior analysis is a much broader term. For instance, one type of consumer behavioral analysis may focus on customer emotions before and after any purchase.

What are the stages a customer goes through when buying a product?

The typical framework for describing any purchase decision is the AIDA model – Awareness, Interest, Desire, and Action. The stages a customer goes through when buying a product are very distinctive. The first one is when a customer becomes aware of your product – the awareness stage. This is where advertising can play a role. The next two steps involve consumer learning, wherein the consumer learns about the product and may form a positive disposition towards it. The final stage is making a decision about the purchase – after they’ve looked at all the different products, they decide to purchase one.

What are the factors that influence consumer behavior?

Managers have to consider many decisions that customers make in terms of whether or not to buy a product. There could, for example, be the social aspect – what are other people buying? Or it could be based on the marketing interventions that a firm carries out to make the customer aware of a product.

What are actionable insights? What is actionable intel?

One of the biggest things in customer analytics is understanding what decisions managers have to make — which is different from the results of a predictive analytics exercise. Any set of results becomes actionable — actionable analysis — when it has an impact on the decision a manager has to make. The phrase “actionable intel” is interchangeable with “actionable insights.”

What is insight in data analysis?

There are two big aspects that everyone thinks about in predictive or descriptive analytics. One is the actual analysis of the data itself, or data analysis. And the second is the more important step: how one can relate the results to actionable insights. Put differently, what can an individual do differently as a manager with the results? Thus, after analyzing the data, the critical step is generating insights and putting them into action.

What is descriptive data analysis?

Descriptive data analysis is one of the first steps in understanding the customer journey. It’s getting a sense of what the data is like and what it is telling you about customers. An example: one may perform a descriptive analysis of customer transactions in a firm’s database. This analysis might tell you what the most popular products are, which types of customers are buying them, and where they are buying them.

What are the outcomes of descriptive analytics?

Successful use of descriptive analytics starts with the decision. For example, if your decision involves targeting the most valuable customers, the descriptive analytics outcome should be in “describing” who your most valuable customers are, and the next step would be determining how to find them. In some sense, outcomes are not as important unless they relate to a business decision.

What is descriptive analytical method?

This is interchangeable with descriptive analytics — broadly speaking, the methods that would help you visualize data.

What is the difference between predictive and prescriptive analytics?

Predictive and prescriptive analytics are two major aspects of the analytics journey. Predictive analytics follows after descriptive analytics. After you have broadly understood what the customer data is suggesting, the next step is to try to forecast what customers will do in the future. This is the step where one builds a forecasting model. After completing the predictive analytics component, the next step — from the firm’s point of view — is what should they do? In other words, prescriptive analytics basically prescribes optimal actions that a firm should take once it understands what its customers will do in the future.

How is predictive analytics used in business?

Predictive analytics forms the core of what a business wants to do, which is to be able to forecast what customers are going to be doing in the future. Then the firm can start thinking about many issues, such as customer lifetime value and resource allocation. Thus, predictive analytics forms the backbone of making decisions that rely on understanding how a customer’s journey will proceed in the future and how the firm will be able to shape it, given its marketing resources.

What is the goal of prescriptive analytics?

The goal of prescriptive analytics, as the word implies, is basically to prescribe actions for firms. To give a concrete example, prescriptive analytics around pricing would include how much a product should be priced.

What are predictive modeling techniques?

Similar to prescriptive analytics, predictive modeling techniques are a framework that one can use in understanding what customers’ needs will be in the future. The workhorse for predictive modeling technique is a regression-based analysis, which quantifies historical data to make predictions for the future.

What is prescriptive modeling?

Prescriptive modeling is a method for ultimately prescribing optimal actions for firms.

What is the prescriptive approach?

The prescriptive approach is thinking carefully about how one can come up with an outcome that is a very clear action that a firm should take. So, for pricing it would be optimal price, and for advertising it would be optimal level of advertising. It’s any approach that helps firms understand what they should be doing for certain kinds of marketing decisions.

What is customer value analysis?

Customer value analysis is thinking carefully about the customer’s lifetime value, or a monetary value for the customer. Some questions of general interest are: How does one put a monetary value on the customer base and determine how much each customer is worth? Such valuation can, in turn, help firms understand who their most valuable customers are.

How do you increase customer value?

The answer to this depends on whether one can link different marketing actions to eventual lifetime value of customers. For a media company, it could be about trying to curate content to appeal to customers and make them more engaged with your company. For other companies, it will revolve around other kinds of marketing actions they engage in.

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