Marketing Analytics Summit 2023 Las Vegas
June 19 - 22, 2023

GA4 isn’t just Universal Analytics with a new coat of paint — it’s a whole new way of measuring website and app engagement. With the Universal Analytics sunset date looming, it’s time to get hands on with GA4. This workshop will teach you not only how to use GA4, but how to rethink your analytics implementations to truly take advantage of everything GA4 has to offer.

Dana orients you to the important differences that make all the difference. A new user interface and a new lens to view your data mean you’ll need this crash course in how to see the sort of reports you are used to, as well as understanding how events, events, events are now the name of the game. Standard reports are out the door and creating custom events for custom reports and dashboards are in the house.

But that’s just half the workshop. Dana helps you acclimate to new types of advanced features and settings that will get you up and running from a stand still. This is where you make the move from GA Universal user to GA4 pilot. It’s time to up your game.

If you’re responsible for managing a team of digital analysts (or want to), Jim offers some practical advice from those who have been there and done that. Jim has interviewed dozens of Digital Analytics Managers, Directors, Vice Presidents – and frontline analysts who wish their bosses had a clue.

Learn the tricks and traps of interviewing, onboarding, and retaining top talent. The department you save may be your own.
What Keeps an Analyst Engaged?Do You Know Their Personal Goals?What Simple Tricks Can Make Your Team Cohesive?How Do You Shift from Managing Them to Coaching Them?
This is very much a workshop situation. Yes, there are some slides to walk through but this will be a working session to talk about your situation. Come prepared to create your own To Do list and walk away with the confidence to help those you work with succeed.

Given the evolution of privacy standards across the industry and the adoption of a consumer-first approach, there will be fewer signals to understand the true impact of campaigns as we move into the next era of advertising. As marketers, we need to have data-driven strategies in place to maximize the return on ad spend. Experimentation and testing is a requirement in order to understand the parameters of the campaign that are working and, as an outcome, carry out investments and optimizations based on data. This workshop will give you in depth knowledge on marketing experimentation and arm you with practical ways to test and implement experiments.

What you will learn:

What are the different types of marketing experiments and testing methods?How to design and structure a successful marketing experiment?How to interpret results and scale learnings from the experiments?What should be done to analyze an experiment that did not have successful results?How to think about an always-on experimenting and testing mindset? And much more…

Who is this for:

MarketersWeb & Digital Analysts
Data Scientists/Marketing Analysts
Growth Managers

A warm welcome, a little housekeeping, and a look at some perennial problems that all the technology in the world has not solved – yet.

Retention matters when it comes to phone subscribers (Verizon), streaming service subscribers (Disney), and analytics team members (all of us). Josephine shares how she learned to be a valuable team player, foster loyalty in others, and fruitfully partner with stakeholders. Understanding data sources, tools, and processes are table stakes; now it’s time to up your game on the people side of the equation from partnering with data engineers, to gaining executive trust, and building a strong team. These are the new metrics for measuring success in analytics.

You could check your email like you always do – OR – you could check out the new tools and services on display in the Exhibit Hall while grabbing a snack and getting some caffeine.

Dojo prides itself on a culture based out of trust. Every quarter, they send out a question to every member of the organization: “Do you trust this person to do their job?” The data organization had some of the lowest scores from each other and from the rest of the business! The next survey asked for feedback on the quality and usability of their data, their visualizations, support, and – most importantly – impact. Lina shares how they built trust up again, became a critical function that everyone relies on, and most importantly, became a TEAM.

Conversion rate optimization is critical for driving sales and revenue. But when your CRO team isn’t delivering the massive growth as promised, it’s time to build and scale experimentation programs. Sheena highlights common CRO mistakes and the data-backed strategies and frameworks that keep them in check. Learn the best way to create a measurement strategy that effectively balances risk and reward and makes you the go-to analyst for the rest of the marketing department.

We experiment to measure, to reduce risk, to optimize, to forecast, and—most importantly—to learn. When a single experiment wins, we know what worked for one audience on one page at one point in time. But the real value of experimentation comes from learning at scale. With proper analysis, your experimentation program can become greater than the sum of its parts. In this talk, you’ll learn to:

•               Design experiments that result in actionable learnings, whether they win, lose, or are inconclusive.
•               Conduct thorough archive analysis to learn from all of your previous experiments.
•               Use archive analysis to run smarter experiments and make better business decisions.

Do you know why your international marketing efforts or websites are less effective? Why some almost-closed deals go awry? Are you paying attention to differing cultures? Perhaps the Cost of Acquisition is too high due to a lack of trust from a potential customer. You can build trust at a very early stage (right on your home page), but this trust is entirely dependent on the culture of the visitor. Geddy shows how to use analytics to reveal the cultural differences of your international web visitors – and the impact on conversion.

From the start (2002) the Marketing Analytics Summit has been the place to discuss and share our common problems. These are your people – they understand your situation. Often rated the best part of the Marketing Analytics Summit, sharing your problems with like-minded professionals is your path to answers, a little empathy, and a stronger professional network. Come prepared with an issue you are facing, a problem you are solving, or a question that needs answering. And then, be ready and willing to help others in this, their hour of need.

All Marketing Analytics Summit attendees are welcome to the DAA Women in Analytics lunch – both women and their allies. Kim hosts a panel of analytics leaders who are striving to support gender equality in analytics profession.

You spend weeks delivering an algorithm, an analysis, or a dashboard only to discover that no one is using it. Not the stakeholders that applied so much pressure, not your peers, not even yourself. We are trained to get to the bottom of difficult issues every day, but how do we create an impact? Anna discusses what last mile analytics are and why they so rarely work. Learn how to assess the impact before getting started, optimize the scope, negotiate with stakeholders, establish appropriate ownership and governance, and organize your teams. This is how we solve business problems and not create new ones.

As the VP of the Consumer Growth team at Trader Interactive, Rachel is on the hook for boosting brand recognition, traffic, and profits. Her Masters in IT from Virginia Tech and 18 years of online marketing experience mean she’s more data and analytics savvy than most business stakeholders. But like them, she relies on data scientists and digital analysts to deliver robust, thoughtful, useful information. It’s not always a bed of roses. Rachel shares the client-side perspective so you can ramp up your game, put your best foot forward, and truly shine as an analyst.

CDPs can be incredible tools to bring together your customer data and drive elevated brand experiences. Setting up a CDP practice requires you to bring together your A-Game, your A-Team, your Class-A data, and your winningest strategies. Sharon gives an honest, sober, sometimes scathing review of what to expect when you challenge politics, silos, and conventions. Learn how to calm internal disquiet and outright dissent so you can have your CDP practice up, running, and improving customers’ and teams’ experience without resorting to Machiavellian machinations.

How do you know when you’re ready to make a role change? And if you decide you want a change, how do you even get started? How can you compare and contrast different opportunities? Riesling has the experience to help you out. In the last 6 years, she has had 7 different data roles across 5 different companies (Microsoft, Capital One, Home Depot, Warner Media, and Atlassian). Riesling talks through the advantages – and disadvantages – of changing roles, the best way to optimize those tradeoffs, ways to build your network to find the best role, and how to build a data focused resume.

Most of us are aware that Google Analytics 4 (GA4) will completely replace Universal Analytics in 2023. The new GA4 brings many new advanced features–but also many easy-to-make mistakes that can lead to bad data and therefore, poor business decisions by you and your team. Mary addresses the top 10 GA4 mistakes people make when setting up, configuring, and using GA4. Get your GA4 error-free with this action-packed session, so you can confidently eliminate disastrous oversight blunders from your GA4 property.

Capturing, cleaning, compiling, and considering data to provide the best insights does not directly translate to solid business decisions. So, how do you determine the value of all the analytics team’s work? How do you connect the effort to the outcome? June describes the creation, delivery, and value of the analytics quarterly reports that go up the chain to where they appraise the headcount, set the strategy, and determine the budgets. These are the highlights and lowlights of reporting on analytics recommendation highlights and lowlights.

Experimentation & CRO have held the crown for the most used buzz words in digital marketing for almost a decade now. Now that we all feel a bit more comfortable talking about experiments, starting up programs , and evaluating platforms, it’s time to align reality and future state to a practical North Star. It’s time to understand data, not just be enthusiast about it. Kenya dives into prerequisites for the robust programs that we all seek to support optimization, personalization, ML, AI, and experimentation.

You’ve proven that a red button is better than a blue button? Great; here’s your trophy. Convinced the Powers That Be to authorize a full-on program of controlled experimentation by showing them how to quantify the impact of Test and Learn? Gold star! What’s that? You haven’t yet? Then listen closely as Val shares how to get your entire org aware of all the learnings and actions taken, seek to improve the health of your program, and – ultimately – invest more in experimentation.

Do you feel limited by your toolset? Do you suffer from tool FOMO? While it’s true that if you only have a hammer, everything looks like a nail. But the flip side is that if you have all the tools in the world, you’ll spend more time learning and choosing that using them. That turns analytics teams into cost centers rather than profit generators. How do you scope a reasonable tech stack? How do you trim the fat and shore up the weak points? Jenn steps through the critical criteria for choosing – and loosing – the tools that make or break the analytics value proposition. Spoiler: It’s not about shiny, new tool. It’s about return on investment.

Together, we’ll lead to a toast to Universal Analytics and revel in how its growth and features led to GA4. What are some of UA’s Greatest Hits you may ask? How are they already at parity in GA4 or will they get left behind in the in the deprecation rapture?

Customer Data Platforms are incredibly powerful tools when implemented properly. That, however, is no mean feat. The fundamental structuring of data within a CDP is different than the majority analytics and data management platforms that have come before and that requires a new way of thinking about data. This is not lift and shift. Emily explores the calamity of over-eager data ingestion into a CDP, the possible impacts to data quality, and the necessity for strong business requirements in foundational data design for CDP’s.

Digital analytics is so wonderfully granular and revealing! But it’s not the whole story. Yes, there’s a lot of ground to cover from campaign analysis through web analytics, email, and social media to testing. But there are other types of metrics to fold into your analysis that can stretch your brainpan and help you arrive at insights that are even more informed. Jessica maps the landscape of metrics including qualitative/attitudinal research, marketplace research, mix modeling, Business Intelligence, competitive research, customer lifetime value, etc., and offers hard-won lessons about how to broaden your horizons. Her two-decades of experience show how to deepen your conversations with business partners and become even more valuable to your organization.

It’s a poorly kept secret: marketing analysts are among the most critical roles to fill and have the most vital perspectives to include. But when given the microphone, too many analytics rockstars fumble because they’re not communicating the value of their measurables in terms that are impactful with owners, the C-suite, or other decision-makers. As a result, campaigns, product features, and customer outreach can fly blind without the input and insight of critical analytical findings. A Gartner Survey in 2022 found that marketing analytics influenced just 53% of decisions across those polled. You don’t need complicated data visualization, expensive tools, or an appendix of spreadsheets to get the attention of your decision-makers and overcome cognitive bias, but Alex hares the ten things you do need to stop doing when presenting your findings.

You have data literacy from here to the moon and back, naturally. And some of your clients (internal or external) have some grasp of where the data come from and what it can do for the organization. But data literacy isn’t enough for an organization to successfully take action. Even the strongest findings can be left behind if your organization lacks data fluency. Data fluency connects employees across roles through a set of standards, processes, tools, and language. You can make a huge impact by building a data-fluent organization, but there are pitfalls to avoid on the journey. Ali identifies the major hazards, how to overcome them, and a few social engineering tips and tricks to get everybody on board.

Everyone agrees that data is a necessary part of any business, but clients may have expectations that current workstreams and budget cannot support. Why is it so hard to get adequate resourcing to provide the best data? It’s time to think outside the box and put your coaching shorts on along with your project management hat. You may not fix everything overnight, but here are some practical steps – and the mindset shifts necessary – to begin improving your analytics workstreams and creating a more nimble team without overwhelming yourself! 

Deborah dives into three common data analysis pitfalls and how to avoid them in this interactive session. Based on real-life A/B test case study examples, you will fully understand problems with statistical significance and how this so-called gold-standard metric can be “gamed.” Next, Deborah explains the importance of statistical power and why it’s so important to calculate sample size requirements ahead of time. Finally, learn what the “winner’s curse” is and what data-driven marketers should be striving for instead. Come away with a stronger understanding of how to recognize, navigate, and overcome these common data analysis issues in order to make more informed, accurate data-driven decisions.

We all focus data narratives on what is known from the data. This practice is a key baseline for success but too often, we ignore what we don’t know and how that can inform the narrative. Whether it is cookie-based measurement omitting iPhone users, look back windows that are too short for a buying cycle, or needed data that was never captured, Zamira and Brianna discuss how to change your approach to data stories to catch these blind spots … and what to do when you find them.

Every company has the need to be data driven. We’ve worked across industries and always face the challenge of making the data digestible to the audience. How do we achieve this? What tools do we use to enable the audience to see, touch and make decisions based on their data. Audience is everything! What do they want? What do they need? Marketing analysts and data scientists can see it but can their audiences see it? In this talk we will walk you through 3 real world examples of facing this challenge and the solutions we utilized.

If your audience is a set of power users or a C-suite executive who wants an at a glance view of how the company’s metrics are performing right now – these audience types should be the defining factor in how you visually communicate the data.

You’ve collected all the data – now it’s time for the analysis. Having heard from our amazing speakers and getting a direct dose of the Analytics Power Hour – now it’s time to share the things that captured your imagination, gave you a grasp of some topic you didn’t quite get, and the To Do list you’ve made for yourself. This is a chance to learn from each other; a chance to find out what was said in the parallel track you missed. It’s hugely valuable to find out what others thought were the most important learnings.

Bringing it all together, tying a ribbon around it, and putting a nice bow on top.

We are at the threshold of new computing era. While everybody speculates about how Generative AI tools like ChatGPT and DALL-E will change, well, everything, now is the time to understand how to bend them to your will.

Yes ChatGPT is cool. Yes, GPT4 and then 5 and then 6 are sending shockwaves around the world. But what does it mean for analytics in general and marketing analytics in particular? 

A significant advantage goes to those who learned how to use

• Computers in the 1980’s
• The Internet in the 1990’s
• Analytics in the 2000’s
• Smartphones in the 2010’s
• Generative AI in the 2020’s

Asking a machine to write copy and draw pictures is like asking a recent graduate to do the same and represent your company in public. Talented though they may be, they lack the deep knowledge about your marketplace, your customers, and your products. They have no reason, no common sense, no grasp of truth vs. fiction. A recipe for disaster.

While others are diving deep into the technical aspects of how Generative AI is being created and understanding its internal workings, this workshop focuses on using Generative AI for practical applications – in marketing.

These sophisticated tools give rise to a different user experience calling for a fundamental understanding of how to get the most value from them.

More structured questions produce better (more relevant and accurate) results. Asking good questions reduces the time and effort required to train an AI system. That’s where Prompt Engineering comes in. Prompt Engineering is as important to understand and leverage today as word processing, spreadsheets, and email were decades ago.

• Using a payroll app = driving a car
• Using a spreadsheet = modifying your car
• Writing code = building your own car
• Using Generative AI = building your own spaceship

We will cover/ You will learn

• What is Generative AI really?
• Common applications for Generative AI
• Technical applications for Generative AI
• Introduction to Prompt Design
• Introduction to Prompt Engineering
• Top tips for getting the most out of Generative AI
• Supercharging your Generative AI efforts
• The One Secret to Success with Generative AI
• Q&A/Exercises

You are encouraged to bring your device of choice for hands-on Generative AI exercises.

Instructor

Jim Sterne, Founder, Marketing Analytics Summit

Jim Sterne has been in data processing since 1979, an online marketing consultant since 1993, and an online marketing analytics consultant since 2000. Sterne focuses on proving the value of digital communication as a medium for creating and strengthening customer relationships. He is the founding president of the Digital Analytics Association and producer of the eMetrics Summits. Sterne was named one of the 50 most influential people in digital marketing by the United Kingdom’s premier interactive marketing magazine and one of the top 25 Hot Speakers by the National Speakers Association, to which he credits his degree in Shakespeare. He has consulted to some of the world’s largest companies; lectured at MIT, Stanford, USC, Harvard, and Oxford; and sat on a plane to Las Vegas grading the CRM strategy plans of a Nigerian mobile phone company for a course he taught in Singapore produced by a training company in Shanghai. Sterne is the author of 12 books on online marketing and analytics including his latest, “Artificial Intelligence for Marketing: Practical Applications” (Wiley, August, 2017)

“No matter how big your data, you must master storytelling and visualization to influence business decisions.”

Visualization is the new communication medium – not the activity of making charts! Learn how to apply the foundations of visual language, evoke what people really want from their data, and unleash your creativity.

Develop leadership in the processes, people, and culture around visualization. To make big data successful requires you to build new skills in visualization and change how teams work together.

This workshop is more than amazing ideas you can put into action immediately. The exercises build your confidence with practical ways to improve your visualizations and make it easy to see insights.

Are you ready to transform how your organization makes decisions and takes action?

LANGUAGE OF VISUAL STORIES

The building blocks of visualization

• An introduction to your brain
• Understanding the six core traits
• Deep dive on properly using color

Stories you may need to tell

• Trends and Relationships
• Comparisons, Range of Values
• Differences, Targets vs. Actuals
• Contest:@Ninja

DEVELOP YOUR ANALYTICS STORY

• Step 1: Ask the Magic Question™
• Step 2: Transform to Action-oriented
• Step 3: Develop the main ideas
• Step 4: Arrange the storyline
• Contest: the Gauntlet

COMPOSE YOUR ANALYTICS STORY

• Storyboards: Learn the three secrets
• Exercise: Yes, you are creative!
• Exercise: Viz Listener’s Worksheet™

DecisionViz helps you become a great communicator of data

Companies spend a tremendous amount of money and time on big data and visualization technology – then the investments have limited success or completely stall. They don’t give much thought to how people will use these new capabilities to drive decisions and take action. To make big data successful requires elevating teams with new skills in data visualization, turning data into stories, and changing how business and IT teams work together.

Instructor

Lee Feinberg, Founder and President, DecisionViz

Lee Feinberg is the Founder and President of DecisionViz, a management consultancy that helps companies build leadership in the processes, people, and culture around data visualization. He invented the Blue Ocean for Visualization™ Framework and the DRAW-ON™ Method and is a thought-leader on building decision-driven organizations. DecisionViz is a Tableau Software Alliance Partner and Alteryx Solutions Partner.

Industry leaders frequently ask Lee to address domestic and international audiences, including Tableau Software Conferences, O’Reilly Strata, TDWI, and TechTarget. He is the author of the BeyeNETWORK column “HD Visualization: Driving BI and Analytics,” founder/ leader of the NJ and NY Tableau User Groups, and served on Tableau’s Customer Advocacy Board. Lee also serves on the Board of Advisors, Stevens Institute of Technology, Business Intelligence and Analytics program.
Prior to founding DecisionViz, Lee led Nokia’s Decision Planning and Visualization practice. He received a B.S. and M.S. from Cornell University and has been awarded a US patent in telecommunications.

BigQuery is one such data warehousing system provided by Google. Google Analytics now sends data to BigQuery and once it is there you can use SQL. Anil dives into the latest GA has to offer, some insights about navigating BigQuery, and the ins and outs of SQL that every analyst should know.

What you will learn:

• What BigQuery is and how to set it up
• How to send Google Analytics 4 data to BigQuery
• The structure of data in BigQuery
• BigQuery vs. relational databases like SQL Server, MySQL etc.
• Common queries to pull the required data from BigQuery
• How to bring data from various sources into BigQuery
• How to send data to Google Data Studio for further analysis.

Who is this for:

• Marketers
• Web & Digital Analysts
• Marketing Analyst
• Business owners
• Business development managers

Instructor

Anil is a seasoned Digital Marketing and Analytics consultant with 15 years of experience. Anil has worked with companies ranging from Fortune 50 to startups and has helped their Digital channels improve business results. Anil’s customers include Microsoft, SmartMoney.com, ESPN, T-Mobile, Hoovers, RealNetworks, Starbucks, and TheStreet.com. Anil holds a B. Tech in Electronics and Communication Engineering from India and an MBA from University of Washington, Seattle.

He has taught and trained several Digital Marketing and Analytics folks in the past 9 years of teaching at UBC, University of Washington, Bellevue College and speaking engagements at various conferences as well as his blog, http://webanalysis.blogspot.com. He also served on the Board of Digital Analytics Association (DAA) and was instrumental in starting the DAA Symposiums.