Huddle Agenda 2018
How Does It Work?
Simple! Each conference delegate participates in six huddles (discussions) – three on day one and three on day two of the conference.
Each huddle lasts for 90 minutes. There are over 50 huddles to pick from, split into six time slots (round #1 to #6).
No time to pick your huddles now? Not a problem.
You can still register then select your huddles at a later stage. But don't leave it too late as places are limited and some huddles could get booked early.
Welcome Keynote and Analytics Panel, Day 1 - October 18
This keynote shines a bright light on why most analysts and marketer's data presentations are putting their stakeholders to sleep. Chances are their slide design and data visualizations are obscuring their valuable insights. With her special blend of neuroscience-based visualization principles, practical hands-on design techniques, and entertaining "tough love", Lea will equip your team with a fresh new toolbox that will get their data presentations remembered and acted upon.
Huddles Day 1 - October 18, 2018
10:30am - 12:00pm
The advent of artificial intelligence and machine learning is transforming the world of analytics. Whilst some machine learning algorithms have been around for many years, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development.
At investment management giant Vanguard, AI and ML are fast becoming a staple of the analytics process. In this huddle, run by Rusty Rahmer, we will explore how practitioners are experimenting with in-tool and standalone AI and ML solutions within their organizations, the early lessons learned, and the outlook for the future based on their experiences.
Building and maintaining trust in digital analytics data has always been critically important. The challenge is becoming more complex in an evolving technology landscape with an increasing number of data sources.
Does your team have a strategy for data governance? This huddle, one of the most popular huddles of the 2017 conference is still a hot topic. Therefore, was asked Amber Zaharchuk of ESPN to lead this huddle in 2018 taking into account advancements made in the past year. Amber will focus the discussion on how to improve data integrity and stakeholder trust. Questions we’d be looking to answer include:
- How we are using implementation solution design documentation
- Who has the final say when it comes to the data you collect
- The expansion of technology, platforms and number of elements tracked
- Maintaining consistency across products and business units
- The role, benefit and cost of data curation, data dictionaries and variable maps
- Applying monitoring, alerting and anomaly detection to prevent data loss/corruption
If you strive to build trust in an elaborate data environment – this session is for you.
Some vendors swear that the vertical stack of marketing cloud products is the only way to go. Adobe, Oracle, Salesforce, IBM, Microsoft and others offer them. Naturally, the concept of an integrated solution is incredibly appealing to managers.
Yet questions remain - is there real value in letting the vendor bear the strain when it comes to integrated tool sets? And do they really deliver greater-than-the-sum-of-their-parts value to your business? Should you be leveraging best in class tools and integrating them (seamlessly!?!) for first-rate performance.
In this huddle, led by Charles Schwab’s Director of Digital Analytics, Dennis Bradley, will encourage you to share your stories of integration success and challenge – vertical stack victories and failures. We will also ask whether what was hailed as the standard five years ago is still true now and other stories and learnings that we can all benefit from going forward.
Come prepared for a discussion that will cut through the marketing hype and touch upon the real challenges of a single vendor stack in the context of programmatic media.
While analysts once operated in isolation as part of a marketing or product team, in progressive environments they are now working more closely with data scientists and data engineers who have entered the scene along with large and diverse data sets. Undoubtedly, a welcomed development for analysts but it also presents some challenges.
June Dershewitz’s team in Twitch includes both analysts and scientists. In this huddle, June will navigate us through topics and questions such as:
- What’s in a name - is it okay to call a data analyst a data scientist just to attract more candidates?
- Compensation, recognition, clout – everyone wants to do visible, high-impact work. Are data analysts getting the short end of the stick?
- Leveling guides, skill sets, deliverables, career pathways – what are the differences between different data-related roles, and how can people transition between them?
- Organizational models. Where are the data analysts, where are the data scientists? How do they work together most effectively and how do they route work to one another?
- Matching business needs with skill sets – when business leaders say they need a data scientist to tackle a problem, who do they actually need?
This huddle is open to both analysts and managers. Attend this session if you see your role as analyst changing and are looking to understand what this change means to you or if you are a manager trying to figure out what is the right mix and how best to utilize each skillset.
Marketers are looking to implement people-based targeting and measurement approaches to optimize the customer experience, increase business performance and drive greater ROI on their marketing investment. According to Forrester, people-based marketing is an emerging approach defined as the ability to perform targeting and measurements at the level of real individuals by resolving consumer identity across digital and offline channels.
In this huddle, led by Lynn Lanphier of US Bank, we will discuss:
- Data integration of first-party customer data, digital identities and online behaviors to create comprehensive consumer profiles, develop audiences, and measure and evaluate campaigns
- The challenges of GDRP and growing consumer privacy concerns have on implementing people-based marketing strategies and closed loop measurement
- People-based marketing use cases that drive business value and marketing benefits
If people-based marketing and closed loop measurement are activities you are looking to conduct or already engaged in then this huddle will give you practical advice on how to do it right.
In 1790 only 5% of Americans lived in urban areas. Prior to urbanization, telecommunication and online, business owners used to have a physical connection to their customers. As society grew in size, organizations gradually lost that connection. Customers became less tangible. Online opened global markets and made customers near anonymous.
So how do organizations connect with their user base in 2018?
One of the biggest obstacles to building a "user-centric" organization are the abstract ways in which we describe our users. They are presented as numbers or charts rather than as living, breathing people. What techniques and methods can we use to make our users real in a way that puts them foremost in our colleagues' minds?
The New York Times strives to make its user base real and tangible to both internal stakeholders and advertisers. In this huddle, James G. Robinson, Director of Global Analytics at the NY Times, will lead a discussion on how best to define your users and customers and how to affectively characterize each unique audience to help the organization continue being user-centric.
Whether your users are readers, fans, customers or consumers, this huddle is relevant to you.
1:00pm - 2:30pm
A successful omni-channel strategy does not focus on a specific end destination. Instead, the customer should have the opportunity to interact or purchase naturally on every platform, syncing perfectly between them.
It is a marvellous vision that is hard to both execute and measure.
Gary Angel has been facing this challenge for many years at Semphonic, EY and Digital Mortar. In this huddle Gary will focus our attention on the unique aspects of omni-channel analytics. We will discuss the techniques for analyzing journeys over time and the methods for integrating different types of channel data. We will then consider how omni-channel affects segmentation strategies. In addition to thinking about the journey itself, we will look at analytics that take advantage of one channel to help drive another: demand signals, assortment optimization and behavioral conjoint analysis are examples.
Expect to come away with meaningful actions for improving your omni-channel analytics strategy.
You have been warned that digital analytics as a standalone discipline is dying. You were told that your resume must include the words data and science, preferably one after the other. You were advised to learn Python. But is it the digital analysts that should fear for their careers or actually the data scientists?
In this huddle, Oppenheimer’s SVP, Ashish Braganza will claim that the market is moving towards interfaced data science solutions that won’t require in-depth coding knowledge. he will also argue that creative thinking cannot be automated and that digital analysts are better at business thinking than their data science peers.
Son this new reality what skills should you develop? How much data science knowledge will be good enough? What areas should you focus on? Those are some of the questions we will answer in this huddle.
- What is voice analytics and how it relates to digital analytics
- What are some of the customer analysis use cases requiring voice and digital data integration
- How can technology such as Hadoop be used to enable analysts easier access to integrated voice and digital
All too often business decisions are driven by internal ‘truths’ that may or may not be reflective of your customers’ real needs. That challenge appears simple, right? Gather customer feedback to guide your business decision making process. However, that process is not that straight forward either – questions about the validity, accuracy, context and representativeness of customer feedback persist. So how can we optimize the business decision process with data?This is a question Alex Destino, Digital Insights Lead at Humana, confronts regularly. In this huddle, he will look to share and exchange views on:
- The biggest customer pain points
- How to combine behavioral and voice of customer data to enable real insight into customer challenges
- How to relay customer pain to internal stakeholders in a way that will prompt them to act
- How to predict customer pain and drive action to fix it
This huddle will deliver an exciting discussion about the best techniques to identify customer pain points and how to use customer interaction and feedback data to uncover (sometimes scary) truths.
Agility is firmly established as one of the important attributes of modern digital businesses. With more teams/companies outside of software development adopting the agile way of working – how do you take the traditional practice of analytics and make it agile where you are working off stories and backlogs?
Veterans’ financial services company USAA is implementing an agile model for analytics. In this huddle, Crystal Martinez Patrick, Director, Enterprise Data & Analytics, will share some of USAA’s learnings. We will seek to answer what are the challenges delegates have encountered around:
- Sizing and defining acceptance criteria for an analytic request
- Frequency of injects, ad-hocs and follow-up questions
- Changing the analyst mindset from working autonomously in the tradition fashion to the breaking up of steps into stories
- Dealing with the time pressures of deliverables and finite iteration
- Ensuring a happy analyst
- What are the positives of working this way:
- improved team dynamics, communication and collaboration
- more structure around the process
- improved focus on customer/business needs
- improved end results to the customer from more tangible and timely deliverables
Come share your agile experiences and learn how others are successfully incorporating agile into their analytics practice.
Technology for digital optimization and personalization is rapidly changing. As the size and scope of challenges to be solved steadily increases, the complexity of the underlying technology is growing. This poses a significant challenge for businesses that are already struggling with turning sporadic experimentation into structured optimization programmes.
In this discussion, led by Paula Sappington, Director, Digital Optimization & Customer Insights at Hilton Worldwide, we will consider some of these challenges and ponder what the future might hold from a strategy and tools perspective. We will also look at the following questions:
- Why personalization is perceived to have failed to deliver on its promise and whether it is a people’s or tools issue?
- How should businesses approach real-time personalization / recommendations?
- What is the case for server-side testing, targeting and personalization?
Come share your experiences and views so together we can tackle some of the fundamental challenges optimization and personalization face in 2018. You should expect to leave with an understanding of how others tackled recent challenge and how they intend to tackle current and future ones.
Deterministic data (aka ‘first-party data) has long been considered the most accurate way of identifying consumers. Probabilistic data, on the other hand, includes either unknowns, or such a wide array of knowns that deterministic models lose their accuracy.
Accuracy has long been the primary concern with probabilistic data. Deterministic data like login info provides more certain identification than the types of data that are used in probabilistic analysis. However, recent research suggests probabilistic data is getting accurate enough to make sound marketing decisions based on the data (granted you wouldn’t use probabilistic data for cancer research).
Just Eat has a significant amount of deterministic data about its customers. However, it also uses probabilistic data to enhance the customer experience. In this huddle, Andrea Mestriner, Head of BI Tech, will guide us through the following questions:
- Are you using probabilistic data alongside deterministic – what are your use cases?
- What are the key considerations for using one or both?
- How concerned should we be with probabilistic data accuracy? Are there specific sources more reliable than others?
- What are the customer experience implications in your decision to use one or both?
- How do GDPR and expected future privacy policies affect use of data particularly probabilistic?
- Should you be considering customer touch points with your brand beyond your product? How would you include them?
This topic may be considered somewhat controversial. Therefore, it is important that we share knowledge and exchange opinions so we are all better informed when coming to make decisions about deterministic and probabilistic data use.
3:30pm - 5:00pm
Today’s consumers are demanding increasingly personalized, relevant communications from the brands they use. The rapid growth in customer data makes it possible for marketers to achieve true personalization at scale for the first time, by harnessing the power of Machine Learning to match the right message to the right customer, in the right context, at the right time.
Microsoft is investing heavily in marketing personalization as it communicates with its over one billion customers worldwide. In this huddle, run by Microsoft’s Senior Director, Customer Data & Analytics, Ian Thomas, we will discuss how to move towards intelligent automation of campaign data, segmentation and creative selection. In addition, we will look at the issues and challenges these present, not just from a technical/data perspective but also from a human perspective – marketers’ jobs will need to change, and marketers will need to become comfortable with working alongside machines for key parts of the marketing workflow.
Join us for a fascinating discussion about the latest applications of ML for marketing personalization.
There is a certain irony that there has never been more data in the world before yet understanding cross platform media consumption is still so difficult.
With media consumption fragmented across devices and experiences, the measurement challenge is not trivial. Many research companies look to solve this challenge but none seem to offer a single comprehensive solution.
In this huddle, Greta Shafrazian, Director of Digital Research at Warner Brothers Studios, will lead a discussion about why this is still a challenge and what can we do about it. We will look at questions such as:
- What are some hurdles that we face in telling our brand story when audiences are fragmented across multiple media touch-points, and the measurement firms have been slower to track multifaceted consumption?
- What do participants think of the progress being made by the more traditional syndicated measurement providers (Nielsen, etc.) in the cross-platform space? What are some of the limitations of the existing product(s)?
- What is holding back the adoption of all cross-platform data providers in improving the measurement of fragmented consumption, and also making ads more relevant to their audiences?
- What are the opportunities and challenges of companies creating their own independent data sets or “currencies” to define the success of content and advertising in reaching intended audiences? For example, Google, Facebook and others often use their own data for advertisers and content providers.
While mainly a media, advertising, and marketing vertical challenge, other delegates are welcomed and will find interesting, practical and relevant take-aways.
Following the implementation of GDPR there is a growing interest in ‘Data Governance’. Specifically around the handling of personal consumer and patient data. Imagine what would happen to your data collection, personalization strategy, CRM and targeted marketing if the US passed broad sweeping legislation around data governance. This would be a forced transformation.
We all have a responsibility to ensure we are prepared for this transformation and we act in an ethical manner in the absence of US legislative governance. Sometimes the boundaries become opaque as we come close to a breakthrough or under pressure from the business to deliver.
In this huddle, Matthew Wolf of Dignity Health will use the group’s collective experience to explore the question of data governance and ethics in analytics. This ranges from how we collect data, to what we find out about customers, how that is communicated internally and how we should act upon the insight.
It is a pretty wide-ranging area that touches on many aspects of digital analytics from split testing to predictive analytics. We will start by trying to answer questions such as:
- What are the main areas in digital analytics where we are likely to be confronted by ethical issues and potential legislation?
- What are the main areas in digital analytics where we are bound (voluntarily or otherwise) by ethical standards?
- Where is the line drawn between practicality and ethical best practice?
- How do we manage our obligation between the needs of the business and the rights of the customer / visitor / data owner?
If you don’t attend this discussion you are either a well prepared saint or you have no moral compass with a flair for risk.
Your analytics tool is running like a well-oiled machine, your reports are automated, and you’re generating tons of actionable insights. Now it’s time to move up to an executive role, but what skills do you need to make that transition? Oftentimes it is the softer skills that make a great leader. How do you find time to hone those skills while you’re managing your day-to-day work?
The analyst transition is a favorite topic for Amy Sample of PBS. Still relevant to her today from a manager’s perspective. In this huddle, we will share our experiences and pitfalls. For those that have made the transition, what advice can you offer to others? How have you dealt with having less time to do actual analysis? What are the biggest challenges you make? How do you keep your technical skills sharp while honing your management skills?
For those that are looking to make the transition, how can experienced executives help? What resources have others found helpful in making the transition?
Whether you’ve made the transition or are just getting started, you will leave this huddle with some ideas and practical tips to shape your career path.
The ability to track individual user information on respective websites (e.g. cookie-ing users post login) and across digital touchpoints (e.g. email, app, website) are the necessary fundamentals that can facilitate a laser-targeted customer outreach program.
Mining such data at the individual customer level unlocks exciting opportunities to promote cross-sell, deepening, and customer satisfaction (e.g., email, alert to sales person, service etc.). Examples including notifying sales staff that a prospect has read an email, visited three product pages, and spent the lion share of their time viewing the specifications of a particular products. Sales staff can then reach out to this prospect to share more about the product and/or close the deal.
Mohammed Aaser, VP of Marketing Strategy & Analytics at Ameriprise, has extensive experience running such programs. In this huddle, he will encourage participants to share their experiences on:
- Techniques for customer data mining (gathering)
- Tools and methods to store the data (storage)
- Using the data for effective customer profiling (analysis)
- Building a data-driven outreach program (strategy)
- Targeting customers based on the data (operationalization)
Join Mohammed for a frank and informative exchange of experiences and opinion about what works and what does not for targeted outreach programs.
Digital analytics is a critical tool to help improve online performance. However, it also has tremendous value for product managers and alike looking to understand the strengths and weaknesses of their products from a customer perspective and to help them make savvy merchandizing decisions.
In this discussion, Julie Albers, Senior Manager of Advanced Analytics at retailer Urban Outfitters, will examine creative approaches to product analytics. This will be a valuable and exciting session for those looking to discuss:
- What alternative data sources can be used to supplement traditional analytics to better merchandize the customer experience? (retail metrics, customer feedback, reviews etc.)
- How can these additional data sources be leveraged to support personalization?
- How to automate this optimization in real time for category sorts or recommendations?
- How to leverage text analytics from reviews and social media and incorporate this feedback into our merchandising algorithms
Huddles Day 2 - October 19, 2018
9:30am - 11:00am
Since our last conversation, the Women in Analytics movement has marched on. 2018 has been the year of the woman around the world. In the analytics world, Columbus, Ohio hosted the Women in Analytics conference, the DAA launched a formal mentoring program, and networking groups are popping up in organizations across the industry.
Let’s continue our conversation. What success stories do you have to share with the group? What techniques have you applied in your organization to attract and retain more women analysts? How do we address the differences in equity perceptions among men and women? How do we achieve a better gender balance in senior leadership positions? Where do we need to focus our energies for the next year?
We welcome both women and men for what continues to be an exciting discussion about our profession.
Creating a real-time analytics system that is both functional and visually-appealing is an art form. We want to be able to make changes to improve performance as quickly as possible while avoiding any needless high anxiety.
How can we fuel our nimble and reactive development and marketing teams without spreading panic through real time analytics?
In this huddle, led by Julie Albers of Urban Outfitters, we will exchange experiences and opinions about the key features and design elements necessary for an engaging and actionable real-time analytics dashboard.
We will discuss two arms of real-time analytics – one to inform and one to drive action. We will consider more advanced methods for using real-time analytics such as feeding our targeting and personalization program or generating automated alerts for when things go awry.
In a saturated digital landscape where brand blindness is the norm marketers have their work cut out for them. We have reached a point where targeting at the individual level is potentially the only way to resonate with an audience.
Automated personalization driven by AI and ML appear to provide a sensible solution to the challenges above.
Dennis Bradley, Director of Digital Analytics at financial powerhouse Charles Schwab has faced this challenge over the past few years. In this huddle, he will be looking to share stories of how the buzz translates into action in daily business life. We will also answer questions such as:
- Are you using AI/ML applications for acquisition, cross-sell, retention, winback and call center deflection? Or there other noteworthy use cases?
- How are your marketing, data science, analytics, technology and operations teams partnering to make this work?
- What technologies are delivering the most (or least) value?
This will be a practical discussion and debate on how to make personalization more effective through the use of advanced technology.
What gets measured gets managed, thus, KPIs serve as the cornerstone for any strong analytics program…or any management program for that matter. But are you sure you are using the measures that matter most? The wrong KPIs will likely drive your organization in the completely wrong direction.
In this huddle, Alex Destino, Digital Insights Lead at Humana, will explore the processes organizations take to set KPIs. Alex will argue that gaining alignment for your KPIs is the key challenge; once gained, the subsequent steps are amazingly easy. Do you agree?
We will also tackle the following points:
- How to identify the indicators that lead to value
- Finding the sweet spot for:
- Leading vs lagging indicators
- Customer vs internal
- Actionable and impactful
- Standardized vs customized
- Short vs long term
- how to set actionable metrics that connect to strategy
- How to build organizational buy-in for the metrics we recommend
- Setting KPIs using data-driven techniques
Naturally, KPIs divide opinions. Let us have a stimulating conversation, even a debate, and share views on what works and does not work in establishing KPIs that lead to business action.
The North Star Metric (NSM) is a fairly new concept predominantly used by start-ups. It is a metric designed to captures the core value that your product delivers to customers. Optimizing your efforts to grow this metric is key to driving sustainable growth across your entire customer base.
NSM helps teams move from driving short-term growth to focusing on the generation of long-term retained customer growth.
Just Eat is one of Europe’s biggest technology start-ups. In this huddle, Andrea Mestriner, Head of BI Tech will share how Just Eat employs NSM. We will address the following questions:
- Is one metric really enough?
- What are the practical barriers you would face and how to overcome them when looking to implement NSM?
- How do you determine your NSM? Is there a single metric, easy to understand and report that supports the results of all your product, technology, marketing, experimentation and development effort?
- Can you create a relationship tree that connects your NSM to the metrics used daily by the various teams?
- What are the traits and attribute of a good NSM?
- How does NSM help you drive sustainable growth?
Join us for a pragmatic discussion about one of the emerging themes in business measurement. Expect to leave with a better understanding of how NSM could work for you.
GDPR is transforming the world of digital data and analytics, forcing organizations to fundamentally rethink their strategies around retention and use of customer data collection, as well as their use of third-party data.
This huddle, led by Ian Thomas of Microsoft, will focus on strategies and tactics that organizations can deploy to fill the gap left by new GDPR rules and related restrictions (e.g. Facebook’s restriction on third-party data brokers), such as gathering more first-party customer data, moving towards contextual targeting and other approaches.
Come share and learn how to manage and best utilize your customer data in an era of intensifying privacy regulation.
For many organizations, big data is an untapped resource of intelligence that can support business decisions and help provide customers a better service. As data volume and types continues to increase and change, more and more organizations are embracing predictive analytics, to take advantage of data at scale.
In this huddle, led by Mohammed Aaser, VP of Marketing Strategy & Analytics at Ameriprise, we will share successful use cases of digital data-based predictive modelling. We will then dive deeper into questions such as:
- How to select the right predictive model for particular challenges
- What is the role of machine learning
- How can we move predictive modelling from the world of the mathematician into the world of the business analyst
You will come away from this huddle with practical examples and a better sense of direction on how to utilize predictive modelling in the digital environment.
12:45pm - 2:15pm
Syndicated data sources such as comScore and Nielsen are relied upon as the main ‘currency’ in media to buy and sell advertising, to contextualize our performance versus our competitors, and to help us understand the demographics of our audience.
Although these tools can be quite valuable in terms of competitive intelligence and deepening our understanding of our audience, they have both strengths and limitations.
In this discussion, Greta Shafrazian of Warner Brothers Studios, will look at the various new and existing vendors within the space and the methodologies employed by them. We will also examine the ways that the data can be leveraged for various purposes including ad sales, gaining a deeper understanding of brand performance, and helping us to create the right messaging / user experience for our consumers.
We will look to answer these questions:
- How do we leverage syndicated data tools to tell cohesive, well-rounded stories about our brands?
- How can we make more insightful decisions about our brands based on the data we can glean from these tools?
- Who are the main data vendors within the space, and what are the strengths and limitations of each data vendor?
- How truly “standardized” are the data sets?
Competitive intelligence analysis is more than a nice to have. Find out new ways to leverage this data and drive more actionable insights in your organization.
Customer centricity, machine learning and digital transformation are arguably the three most discussed themes in digital at the moment. So what is the part of the digital analyst in all of this?
Join Ashish Braganza, SVP at Oppenheimer Funds, in this huddle where we will explore the role analytics plays in supporting each of these themes. We will ask:
- What are the analytical drivers of digital transformation?
- Should we pursue professional training in machine learning?
- How can analytics put our customers at the heart of our digital strategy?
Looking to take the initiative and support key digital programs in your organization? Take part in this huddle and get some practical advice on how best to do so.
Advocates of self-service analytics maintain that it can fill the gap caused through a shortage of trained analysts by allowing business users to make data-driven decisions in real time without having to revert to the analytics team. Critics maintain that only a trained data analyst can reliably understand the meaning of certain data correlations and if the analysis process is mismanaged, it can lead to potentially incorrect decisions.
In this huddle we will debate the merits of self-service. Led by June Dershewitz, Head of Data Governance & Analytics at Twitch, we will look to answer the following questions:
- Who are the different customers of self-service analytics, what motivates them, how do their needs differ, and how can you best enable self-service for each group?
- Information sharing - data catalogs, knowledge bases, wikis, BI tool add-ons. There are many ways to organize, manage, and share your company’s data-related lore. What’s out there, and how do you choose the right tools for the job?
- What are the dangers of self-service? What could possibly go wrong once you empower everyone to become their own analyst? Or, to put a positive spin on it, how do we make data literacy pervasive?
- The future of self-service analytics – voice assistants, chatbots, what else is next?
If your analytics resources are overwhelmed, you are wrestling with your organization over the adoption of self-service analytics or you are in self-service nirvana then this is your opportunity to share and learn how to maximize analytics ROI via self-service.
Campaign attribution is a marketing challenge as old as marketing itself. Despite our superior ability to measure digital channels (in comparison to most offline channels), attribution is still one of the most hotly contested areas of marketing today. Intriguingly it is a people as much as a tech problem (call it the politics of attribution).
Lynn Lanphier has faced this challenge many times previously at Best Buy and currently at US Bank. She has both the retail and financial angle of campaign attribution.
In this huddle, Lynn will start us off with a discussion about the goal of attribution models and who they serve. We will then ask:
- What are the key factors to consider when building your attribution model?
- Which model should you use? Can you use more than one simultaneously?
- How to gain consensus across the organization and how to socialize results?
- The pros and cons of inhouse vs outsourced solutions?
Following this huddle, you will be able to attribute your marketing analytics success to the moment you decided to join this discussion (that is if you’re using first touch!).
Developing a truly effective analytics program requires a good balance between people, processes and tools (in this order!). In addition, the team must develop a high level of credibility with other parts of the organization in order to (a) be heard and (b) given the necessary funds and support to implement and run the program.
Matthew Wolf, Head of Analytics at healthcare provider Dignity Health has built his team from scratch and is constantly working hard to make it even greater. In this huddle, he will encourage delegates to share their views and experiences of what makes an analytics program great. We will discuss how to structure the program and develop it over time. We will ask what skills and roles are essential from day one and which could be added as the program evolves? And how should the digital analytics team be integrated into the larger organisation?
Join us to explore the critical intersection of people, process, and technology and how they impact your own measurement success.
You have grown from one part-time A/B testing resource to an optimization program of X team members running both quantitative and qualitative testing. You had lots of growing pains! You manage a governance team which sets your roadmap and priorities. And yet you feel that optimization is not delivering to its full potential.
This is exactly the challenge Paula Sappington of Hilton Worldwide faced. In this huddle we will examine how to drive more out of our optimization programmes. We will look at examples of effective prioritization processes, how to measure your program’s health, the role of analytics and executive reporting and scaling the program up.
Time permitting, we will touch upon the role of agile and a product-centric approaches to delivering ‘lean learnings’ to multiple product groups in a timely manner.
2:30pm - 4:00pm
Marketing clouds are common place these days. Adobe even has a few of them. The concept of a SaaS integrated solution is incredibly appealing to businesses. Cloud solutions offer greater flexibility and accessibility alongside better processing powers – data could be actioned faster and more efficiently. However, cloud solutions throw new challenges for analytics professionals.
In this huddle, led by Gary Angel, we will look at all the aspects of building an analytics system in the cloud – from selecting a cloud vendor (e.g. Amazon vs Azure) to discussion around appropriate configurations (e.g. memory vs. compute) to tools to maximize governance, data intake, ETL, and analytics.
Come prepared for a discussion that will cut through the marketing hype and touch upon the real challenges of a single vendor stack in the context of delivering superior analytics insights and driving ROI.
USAA’s centralized Enterprise Data & Analytics (D&A) Hub was facing a customer support challenge.
USAA descended into siloed D&A teams that performed separate specialized functions such as data collection, report building, analytic request, governance support, model building etc. This resulted in a bad customer experience for internal business partners. Often customers did not get the support they required.
To meet this challenge USAA piloted a support model that created a single point of contact for the customer termed the Engagement Manager (EM). This person functions as a go between contractor who knew enough about all D&A services and capabilities offered and could then serves customers as their D&A consultant. Once the EM understood the needs of the customer they would assemble an agile team of D&A specialists to fulfill the request.
Two years on – this program is a huge success. But not without teething problems. In this huddle, led by Crystal Martinez Patrick, Director, Enterprise Data & Analytics at USAA we will discuss the opportunities and challenges of such programs. We will also ask – is this the ideal model for every company?
Digital analytics job descriptions continue to expand, making it near impossible for any one person to meet the criteria. This presents a challenge for both the hiring team and the applicants. In this huddle, led by Amber Zaharchuk of ESPN, we will discuss the difficulties we face when staffing digital analytics teams, including:
- The state of the analytics talent pool
- The causes of skill deficiencies
- How to prioritize essential skills to improve recruiting
- Where we feel deficient in our own skills and why
- How to improve tenure of analytics teams
This discussion will benefit both team managers and analysts. Together we will form a complete view to help managers attract and retain the best talent. For analysts this will be an opportunity to share their viewpoint and find out how to get the most of their career.
Analysts have a thing or two to learn from journalists. Their jobs are remarkably similar -- to investigate interesting questions, uncover and confirm what’s really happening, and communicate important information and insights in clear and accurate prose.
Led by James G. Robinson, Director of Global Analytics at the New York Times and an adjunct professor at Columbia University’s School of Journalism, this huddle explores what analysts can learn from the practice of journalism to become better storytellers, engage audiences and drive action.
How does one tell compelling stories with numbers? What are the key features of a ‘good story’? How does one translate the nuance and complexity of analytics into simple and clear insights? And should suggestions and recommendations be a part of our stories?
In this huddle, James will examine some of the techniques which we can deploy to convey our insight and knowledge more effectively and share experiences on how to integrate storytelling into our analytics practices. He will also draw on his latest research project investigating how journalists think about the specific audiences they serve and how that could apply to digital analytics.
As data and reporting requirements evolve so should analytics implementations. Most changes should be applied under business as usual procedures. However, at times a more comprehensive reimplementation project is needed.
Julie Albers, Senior Manager of Advanced Analytics at Urban Outfitters, has recently completed an analytics replatforming project and bears the scars. In this huddle she will take us through the considerations, pitfalls and challenges of selecting a new tool and conducting large-scale implementations.
Some of the questions we will answer include how to:
- Get management buy-in and how to quantify the business benefit?
- Deliver the project efficiently, timely and to scope?
- Govern the project and who should do that?
- Set stakeholders expectations and managing them through the project
- Pick the right partner to support the switch
If you are considering a change of analytics tools, your analytics implementation requires a major upgrade or you are simply interested in exchanging implementation experiences then join this huddle where we will focus on solutions rather than venting frustrations of past experiences.
Are you experiencing increasing pressure to quantify the value of your analytics team and its deliverables? Are you delivering the expected return on investment in analytics or RoA?
Join this huddle, led by Rusty Rahmer, Manager of Enterprise Web Analytics & Digital Intelligence at Vanguard, to find out how others are solving the challenges of quantifying the value of the strategic insight, consulting, and reporting solutions produced by analytics teams in the spirit of maturing data-driven insight and decision making.
Questions we will look to answer include:
- What opportunities exist to enhance our understanding of the value of digital?
- Is it necessary to quantify the distinct contribution of the analytics team?
- How do you measure RoA?
- Why knowing your RoA can further leverage the strategical position of analytics?
- What are the merits and risks of accountability?
You will leave this huddle with practical advice on how to focus on RoA to improve both your team and your own efficiency and impact on your business.