In this new era of Big Data, retailers collect data in ever-increasing volume, variety, and even velocity. In the midst of Big Data, a revolution is taking place in how retailers gain insights about customers, whether they interact with the brand online, in stores, or both.

Dean Abbott is an internationally recognized data mining and predictive analytics expert nearly three decades experience building and deploying advanced analytics algorithms and data preparation techniques to real-world problems.

In his opening keynote to the DA Hub conference Dean will describe the revolutionary transformation that is taking place as retailers transition from reporting to data-driven decisions using advanced analytics. Success requires collecting the right data, creating informative derived attributes, and leveraging scalable computing infrastructure to make this data accessible in a timely manner.

The advent of new computing technologies is transforming machine learning. 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.

If you have had a chance to experiment or do real digital analytics work in machine learning, please attend (we expect a small group). Machine learning is at the cutting edge of digital and this is a chance to swap knowledge, learn about tool experiences, and discuss strategies around machine learning – from the right tools, to structuring the data, to the most interesting problems. Not for beginners.

Setting challenging, but attainable targets, is proven to improve productivity and create a high performance culture. Targets foster engagement and encourage focus on the most important tasks. Furthermore, true data-driven decision-making necessitates clearly-defined targets – you cannot determine the best way to get from point A to point B if you have not yet defined point B AKA the target state.

In this huddle we will discuss techniques for setting effective targets for your KPI. Topics will include:

• Which KPI to consider
• Setting targets that align to broader business objectives
• Discussing the difference between targets and forecasts
• How understanding the difference between targets to forecasts can be used to drive action
• Coordinating action planning with target setting

This huddle will give you the impetus to identify, set and use better targets to achieve better outcomes for your business and customers.

Building and maintaining trust in digital analytics data has always been critically important. The challenge is becoming increasingly more complex in an evolving technology landscape. User behavior data sets are expanding out from simple web traffic to include a diverse array of customer interactions and attributes. This variety in data types places new emphasis on the importance of governance and quality controls.

June Dershewitz is the Head of Data Governance & Analytics at Twitch, the world’s leading video platform and community for gamers (an Amazon subsidiary). Among her responsibilities, she oversees the definition, collection, management and use of business-critical digital analytics data in a custom data warehouse.

In this huddle, June will solicit participants to share their experiences of dealing with an ever growing data set. We will look at:

• Managing quality when your data collection touchpoints extend beyond traditional web sites - mobile devices, game consoles, IoT, etc.
• The role of data curation, data dictionaries and variable maps in a “track it all” world
• Applying safeguards such as 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.

As complex methods and programmatic approaches to data become commonplace, analysts may develop a ‘superiority complex’ towards the seemingly mundane forms of analysis. No matter how sexy big data might be, a great analyst should be capable of producing insightful and actionable opportunities, faster and more efficiently using ‘tried and tested’ digital analytics methods.

Striking the balance between ‘traditional’ digital analytics and data mining is a challenge. So at what point do we shift our resource and focus from one to the other? This is a question Kyle Keller, Director of Analytics at media outlet Vox.com, is having to grapple with regularly.

In this huddle, he will explore questions such as:

• When do you assign personnel to big data initiatives vs the more mundane tasks that drive the business forward and get things done on a daily operational level?
• How do we move an analyst past the somewhat limiting feeling of helping others around the easy but bigger immediate wins, against loftier analyses an individual might wish to embark upon?
• Should we look at transitioning an analyst from traditional digital analytics to data science roles? And if so what does that path look like?
• Are we better off creating mixed teams for digital analysts with data scientists?

This huddle is perfect for analytics managers (and those aspiring to become ones) looking to exchange valuable experiences on effectively managing your analytical output.

Given some KPIs, could you define the best dashboard ever? How would you know it is the best anyway?

Let’s tackle the challenge together - from Stephen Few best practices to the harsh reality of the HiPPO veto, you will manage to learn something new, certainly argue a little bit, and even have fun doing it!

Industry veteran Stéphane Hamel will be the leader of this discussion and you are expected to play an active role in defining the sexiest dashboard ever. Bring your own dashboard templates (ex data) and share what has worked and what has not worked for your organisation.

Personalization is the current hype. Chief Marketing Officers mandate their digital teams to develop and execute personalization programs to enhance customer experience and increase ROI. Personalization might seem pretty intuitive, nevertheless, the application of a solid personalization program requires a structured approach and methodology.

Dylan Lewis, Director of Analytics & Experimentation at Intuit, has overseen the combination of experimentation and personalization at Intuit. In this huddle he will examine the intersection between experimentation and personalization. We will discuss techniques, pitfalls, challenges and the possibilities of a fully realized customer experience.

You should come away from this huddle with new insights how to improve both your experimentation and personalization programs.

Innovation and testing is where the proverbial rubber hits the road for analytics. Testing has become a part of everyone’s digital culture and provides an ideal vehicle for transforming digital insight and segmentation (nouns) into action and results (verbs).

This is a key challenge every senior analytics team manager must contend with regularly. In this huddle, Rusty Rahmer of investment firm Vanguard, will lead a discussion about how our organizations generate ideas for innovation and testing. We will discuss how companies are aligning themselves around the entire testing lifecycle, from sources of idea generation and organizational models to support innovation, to the processes of prioritization, execution, evaluation and sharing of insights.

You will come away from this huddle with practical ideas for generating valuable insight to inform your organization’s testing, experimentation and personalization efforts.

Our world is changing rapidly. Faster than ever before with digitalization the number one change agent. That means new platforms, new content partners, new competitors, new vendors, new tools etc. For researchers, this also means new data sets to work with, new tools to use, and new questions to answer!

In this huddle, Shari Cleary, the SVP of Strategic Insights & Research at Comedy Central will lead a discussion on best practices for keeping up in this rapidly changing world. We will focus on innovation, partners, talent, and networking. For example, what are some techniques for evaluating new vendors and what do you look for when interviewing candidates.

There is a lot we can learn from our peers by sharing ideas that have worked and pitfalls to avoid. Together we will walk away with ideas on how we can help our own organizations and teams stay ahead in this rapidly changing world.

To keep pace with the speed of change -- business, customer and technology -- we must leverage our community, internal peer groups and external networks. Building an Analytics Community at your company brings together like-minded people across organizational silos to solve business problems. Your external network provides a forum to develop thought leadership, help others and be inspired.

In this huddle, led by Lynn Lanphier of Best Buy, we will examine several approaches for introducing an analytics community and evaluate both the quantifiable and intangible benefits of such a community. By its nature, a community structure is less hierarchical – we will ask what format should it take and how do we keep it moving forward without formal governance.

Join us for a stimulating discussion about a new approach to sharing analytics knowledge, and keeping your talent stimulated and engaged with other analytics functions in your company.

* “A tribe is a group of people connected to one another, connected to a leader, and connected to an idea. For millions of years, human beings have been part of one tribe or another. A group needs only two things to be a tribe: a shared interest and a way to communicate.”
― Seth Godin, Tribes: We Need You to Lead Us

Personalization is one of the biggest buzzwords in our space today. Personalization at the highest level is the ability to deliver engaging customer experiences and meet business goals using data. Businesses grasp the importance of personalization but are yet to execute it well.

Gautam Madiman is responsible for the personalization program at home improvement giant Lowe’s. In this session, he will look to explore with the group different examples of how to drive online personalization and some of the pitfalls in doing so.

We will ask:

• How can one get started down the personalization journey?
• Is there a framework around leveraging customer digital data, segmenting & targeting your customers?
• How should one think about manual personalization vs. automated personalization?
• How should you define segments?

This is a must attend huddle for anyone looking to develop a successful personalization program.

Gartner calls it the Hype Cycle: Innovation Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slope of Enlightenment and Plateau of Productivity. Has Data Science finally emerged triumphantly from that state in your organisation?

Shaping and optimizing the delivery of data science in ASOS is something David Williams has been managing successfully over the past few years; but not without challenges. In this huddle, he will encourage delegates to share stories of success and lessons of failure in building data science teams, ingraining techniques into your company culture and delivering quantifiable business and customer value.

Join a thought provoking discussion on how to optimize your data science efforts.

Last fall, a popular analytics podcast took on the subject of women in analytics. The lively discussion had me arguing aloud in my car with the panelists, and rattling off a list of prominent women in the industry.

Let’s continue the discussion in person. Is there really a lack of women in analytics organizations? Or is that a myth? The data indicates nearly half of all analytics professionals are women. Perhaps it is a marketing issue - how do we help women build their personal brands? What can we do to mentor our younger analysts to ensure we build the next generation analytics leaders? How do we attract and retain more women to our field and our management ranks?

We welcome both women and men for what will be an exciting discussion about women development in analytics.

The Internet of Things (IoT) is transforming our lifestyles; giving us more control and better understanding of pretty much everything around us. But IoT also includes a corporate side, enabling organizations to collect and analyze data from sensors on manufacturing equipment, buildings, transport systems, weather stations, even people themselves.

Two years ago, Brandon Bunker of smart home applications and services company, Vivint, changed careers from digital and marketing analytics to IoT. Brandon will discuss how to smooth the transition from traditional analytics to a career in IoT. We will share analytical techniques you already know that have huge value for IoT data and talk about the type of data IoT applications generate and how they differ from web data we already use today. We will look at the different roles that are critical to provide IoT value. Finally, we will discuss how you can position yourself for a leadership role in IoT data.

Data accuracy is a big issue. We are constantly challenged over data quality and accessibility. It is potentially the number one factor holding back our success. So how do we overcome this challenge?

In this discussion, Rene Villa of Verizon Wireless will ask how does great data governance looks like and how can we ensure our organisations adhere to it, to ensure relevant data is available, accurate and accessible when we need to ask questions of it?

We will also consider the following questions:

• Why do so many organisations struggle to maintain useful and accurate data?
• What examples can the group share of organisations that do it better - and what are the key elements which support this?
• How do we ensure measurement is even considered up front in every new initiative - and where should the accountability sit?
• How do we ensure data governance is prioritised, when competing with other uses of resource which might appear to have more immediate customer benefit?

Analytics is commonly used to evaluate the performance of product managers and their success hitting their targets. But the truth is that digital analytics leaders are product managers of their own. Think about it! We manage a solution, working backward from stakeholder needs, to build a program that works best for our organization. So what does that mean to you? What techniques do you use to achieve ABC and XYZ? And how do you measure the people providing the measurement?

In this huddle, Steve Harris, Head of Digital Analytics at Capital One, will stimulate a discussion about the best methods and metrics for measuring your analytics team success. We will consider how to balance your organization’s commercial objectives with your team’s personal objectives and propose tactics to keep your team challenged and invigorated.

Join Steve for a discussion that will challenge some of the analytics team management conventions and offer fresh ideas for improving your team performance.

Tracking and measurement are essential aspects of any marketing campaign activity. However, in most cases the marketers responsible for running campaigns are either unable to define tracking requirements or not responsible for it altogether. This situation leaves the door open to recurring measurement issues due to missing or inaccurate measurement.

So how can marketer and analyst work together to ensure both get what they want? In this huddle, run by Chip Streiff of sports retail giant Adidas, we will examine the processes from conception through planning to execution of successful campaign tracking. We will debate the merits and risks of insisting on detailed data collection vs. simplifying the tracking process. Finally, we will discuss possible approaches for creating a smooth, reliable and repeatable process end-to-end.

Join us for a comprehensive debate around campaign tracking and analysis.

Most organizations aspire to be customer centric. Most companies instrument various forms of “Voice of Customer” data collection, have NPS and CSAT scores and large volumes of customer feedback at their disposal. Some are able to extract significant value from this data, leveraging it for strategy formulation, imbedding into operations, customer service and decision support, while others view it as a “nice to have”, “softer” KPI.

Fashion retailer Abercrombie & Fitch mashes VoC, CRM and clickstream data to facilitate an organizational transition from a brand-led to a customer-focused entity.

In this huddle, Sasha Verbitsky will discuss key factors for value creation and ultimate success of VOC programs, including:

• Starting out with VOC
• Goals and executive and cross-functional sponsorship
• Typical use cases
• VOC data collection and instrumentation (different parts of customer journey; different channels),
• Integration with other data types (transactional, LTV, site/channel behaviors, testing, customer service, operational)
• Actionability (driven by sufficient granularity, flexibility, timeliness, alerts and relevancy to different stakeholder groups)
• Establishing connection between CSAT/NPS and LTV as a key to elevating and operationalizing VOC

You will come away from this huddle with a new found appreciation for how VoC could enhance your analytics and experimentation programs and generate significant business impact.

How many different types of data are needed to paint a picture of customer experience? Brand affinity research, social media analysis and man-in-the-street surveys can be valuable, but which data sets are the most revealing? When does data become more expensive than it's worth? When does it become un-correlate-able?

The starting point for this discussion will be the mapping of a data taxonomy. What types of data are collected from which sources?

• Do you have a data taxonomy? What does it look like?
• What data do you consider absolutely central to your analytics endeavors?
• What new data sets have been the most revealing/valuable?
• What data collections have been a waste of time?

Can we identify, sort and rank the best/most necessary data elements and attributes to develop a recommendation to the rest of the industry?

A recurrent theme across the analytics and optimization communities is finding the right mix of people, process and technology. There is no one structure that fits all yet most organisations struggled to strike a good balance. This challenge is augmented for multi-nationals – how to balance regional requests for testing and personalization with a globally-managed platform?

As the Global Analytics & Optimization Lead for athletic equipment manufacturer ASICS, Jose Uzcategui is constantly looking to get that balance right. In this huddle he will explore with you the following questions:

• How do you identify the problems worth solving?
• How do you identify the right people, processes and technology mix?
• How do you engage stakeholders in the optimization process?
• How do you collaboratively create/share best practices across disparate team in multiple locations?
• How much freedom do regional teams should have when it comes to balancing personalization and a global brand?

You will come away from this huddle with a set of insights and ideas for moving your program from A/B testing to structured optimization.

The workforce is evolving and more hiring managers are now challenged when searching for great young analytics talent. Gone are the days of simply putting out a “help wanted” ad and filtering through piles of resumes. Today’s workforce entrants come equipped with certifications, specialties, and hands on experience, but how can you tell who is “on fleek” (great) for your company and needs?

In this huddle, Akhil Anumolu of Delta Air Lines will discuss what to look for in potential analytics candidates and how to effectively train them for long term growth of your business. Points of conversation will additionally range from hiring for cultural fit, evaluating if certain schools help or hurt a candidate’s skillset, assessing what millennials find valuable in the workplace for career growth, and how to help retain up and coming talent.

Market forecasts for Internet of Things (IoT) and wearables show a hockey-stick growth - up and to the right. Whether the forecasts are conservative or optimistic, these devices offer the measure community an exciting opportunity coupled with great challenges.

In many cases analytics would be extended from the sales process to the usage of the product. How often is my product used? Where is it used? What features are most applicable? This can aid in product improvement as well as customer understanding. What's more, optimisation now extends beyond the digital sphere into the real world where these devices reside.

Will the frameworks that have helped us organise our digital measurement efforts apply in the IoT data world? Are these just another cross-channel data source or are they inherently different? How will we secure the data streams and ensure we remain compliant with our privacy policies? Join us for a discussion on metrics, consumer expectations, security, privacy and data architecture for the next generation of analytics.

To achieve your vision of what analytics can do for the organization you need a team. Your analysts are your front line – their work reflects on you. They are talking with the business, interpreting data, crafting presentations. They need to understand the customer point of view, to develop the consulting skills to understand and serve the business, and the ability to not only interpret the data but put it together into a compelling story. They need the exposure to develop their careers.

That is a tall order for one job description – consultant, researcher, data expert, visualizer, storyteller. For Carrie Bolton of Vanguard this is a daily challenge managing her team. In this huddle, she will lead a discussion on how to define development opportunities for analysts, help them hone their skills and keep them motivated.

Competition in the digital world is intensifying as barriers to entry keep dropping. With the advent of digital-savvy management the desire to consume data is increasing. Data is quickly becoming the next battleground. Data analysts along with data scientists are the most sought after soldiers. So are we delivering the expected return on investment in analytics or RoA?

Theresa Locklear is constantly challenging her team with this exact question – looking to tackle the challenges of prioritisation and selection of analytics initiatives. The measurement of RoA, as contribution versus cost, is not an easy one. Digital analytics teams commonly serve multiple stakeholders and depend on them for any recommendations’ execution.

In this huddle we will work on examples and experience from attendees to explore the methods and challenges for a RoA calculation. Topics will include:

• How and whether it is necessary to quantify the distinct contribution of the analytics team
• A look at the investment and organizational processes required to enable any RoA
• A review of the desired outcomes and how they would vary between different types of organisations
• Why knowing your RoA can further leverage the strategical position of digital analytics

In addition, we will look to examine the merits and risks of accountability and create an understanding of how focusing on RoA can be used in our daily work to improve our analytics impact on the business.

Up until recently digital analytics relied heavily on standard off the shelf tools. However, changes to customer behaviour and advancements in technology necessitate and empower a move towards bespoke and customised solutions. How far are you willing to leap from the comforts of the standard to the benefits and pains of the bespoke?

Tom Betts of the FT has been grappling with this question for the past few years. Two years ago in X Change 2014 he was a lone voice in a big data tech huddle interested in building a self-service digital analytics solution from scratch. Last year at the DA Hub, about a third of delegates in the room were either considering it or had started.

The FT has recently completed building a bespoke solution. In this discussion Tom will share insight for this project but will also solicit the group’s opinions on questions such as:

• What is the business case for building an in-house stack?
• How do you obtain management buy-in?
• How far can we go with off-the-shelf products?
• What are the potential pitfalls you must consider before embarking on this journey?
• How do you continue to grow your solution to address changing conditions?

Whether you at the consideration stage or already into the process of building your own solution this discussion will help shape your thoughts around your next steps.

Dashboards are, for better or worse, essential tools in our business ecosystem. Ideally they should provide a standardized view of the key metrics indicating the health of our organization. Most dashboards are a collection of numerical and graphical metrics and KPIs of historical data. Rarely do they include qualitative interpretations or forward-looking predictions.

In this huddle, Kyle Keller of Vox.com will examine these two fundamental issues with dashboards. First, he will ask whether we should replace some of the numbers and graphs with more qualitative information? Analysts prefer the former but those are often hard to interpret by executives, especially those not well versed in digital analytics terminology.

Then Kyle will look at ways to highlight trends and ideas around where we are headed, as opposed to simply showing the current state of things. In this part we will discuss what are the preconditions to make this work and how could we model scenarios into dashboards to provide actionable insight.

Analytics without a process is doomed. How do you go from an ad hoc, immature, learn as you go approach to a fully-fledged, disciplined, matured set of processes with improved quality and effectiveness? Basically, how do you repeat success?

In this discussion, digital analytics thought leader Stéphane Hamel will argue that we can learn from other disciplines. One such example is Six Sigma, an approach developed in 1986 and put forth by Jack Welsh himself at General Electric. Defined as “a disciplined, data-driven approach and methodology for eliminating defects in any process – from manufacturing to transactional and from product to service” it can readily apply to our field of interest.

You will hear Stéphane repeat the Six Sigma DMAIC mantra - Define/Measure/Analyse/Improve/Control - do you agree? Where does Six Sigma, Lean, Agile concepts, Kaizen and those other approaches with fancy names fit in? What’s YOUR approach? What works or does not work?

All analytics organizations recognize the need to unearth and surface the proverbial “golden nuggets” of deep, actionable insights to their stakeholders. Most want to do it; few seem able to deliver these consistently.

There are many different flavors of "insights”. From simple propositions such as identification and resolution of customer struggles to complex challenged such as connecting the dots of customer journey to optimize each step or deeper understanding of customer types (context, needs & priorities, intent, propensities) that can be leveraged for more relevant marketing, better design of a product or experience or increased customer’s satisfaction and LTV.

Common enablers of our “a ha!” moments are curiosity, experience, critical evaluation of current data vs. prior knowledge, ability to connect current analysis to a bigger picture, and easy access to diverse data sets. Ultimately, it still tends to remain more of an “art” than “science” or “process”.

Sasha Verbitsky’s analytics and testing team at retailer Abercrombie & Fitch, has been rapidly increasing analytics program value and impact on various aspects of marketing, site experiences , operations, CRM and customer NPS over the last 4 years. In this huddle, he will look to exchange views, experiences and best practices for coming up with a systematic approach to drive your "insight discovery rate".

Some of the key discussion topics will include: goal setting , rationalizing time between routine analysis and insight mining, insight deliverables standards, need and ability to collect and connect diverse data types, building and cross-referencing insights repository, separating signal from noise, understanding business levers and insight actionability.

Come ready to share and discuss “insights” techniques, how you got there and how analytics organizations can operationalize and standardize these techniques into a “process”.

As the world of analytics and marketing grows, so does the complexity of the tools and tracking required. Do the silos of marketing and IT still haunt your organization? Are you concerned over implementation and understanding if the pricey tool you paid for is truly working correctly? Is your team too one-sided into analysis with no focus on implementation and improvements?

Akhil Anumolu of Delta Air Lines will lead this engaging huddle as we assess how to break down barriers of marketing and technology to build a unified solution for analytics in any organization with the right personnel. Converse with other leaders over leveraging technical hires in marketing, differentiating a marketing technologist from a marketing architect, the space of MarTech in the industry and its growing influence, and how best to expand the technical and marketing skills of your team to make them more hybrid marketers.

Come learn how some of the top companies are redefining roles in analytics to grow faster.

Creating a high impact analytics program is challenging. It takes significant time, investments and effort as well as pulling all the pieces of the puzzle together around technology, people and processes. Nevertheless, if done correctly it would yield a significant return to your organization.

So how do we make this happen? Well, sitting down with other analytics managers to discuss what works for them would be an invaluable step in reaching that goal.

Gautam Madiman has established high impact analytics programs at Dell, Autodesk and Lowe’s. In this huddle he will investigate the key foundations for establishing a great analytics team. We will look to answer questions such as:

• How do you know you have a high impact analytics program?
• What are some of the traits of a high impact analytics program?
• What are some of the pieces of the puzzle needed to bring together a high impact analytics program?

You will come away from this huddle with fresh ideas to take your analytics program to the next level.

Digital analytics tools can provide excellent insight into how customers move from one web page to another. However, they struggle with in-page insights such as which parts of the page customers focus on, do they scroll down and do they encounter any technical issues preventing them from completing forms.

Enter Customer Experience Management (CEM) tools such as ClickTale, IBM Tealeaf and Decibel Insight. In this discussion Chip Streiff of Adidas will look at the most recent use cases of CEM. We will also explore how CEM should be integrated with digital analytics and A/B testing to create a comprehensive view of customer experience.

In the increasingly flexible world of web development, content delivery and personalization the old paradigm of a page visit being synonymous with viewing a specific piece of content is gone.

From images to videos, banners to blogs, they all play a key part in a customer’s journey and we should be measuring and valuing them appropriately. But how should we go about it? Join Rusty Rahmer of investment management giant Vanguard at this huddle to find out.

We will discuss appropriate methods for measuring content impact with Rusty sharing his experiences of both the good and bad. We will also discuss the challenges, approaches, emerging techniques and successes in adapting analytics to personalized experiences for the benefit of measuring effectiveness and optimization of content in the “liquid web”.

Ecommerce Conversion Rate, Ave. Order Value and Revenue are the most common performance metrics used to measure ecommerce sites. But are those the right KPIs to evaluate the health of your ecommerce site? More importantly – are they effective indicators of future performance (short or long term)? Join Jose Uzcategui, Global Analytics & Optimization Lead at ASICS, in this exciting huddle where we will be looking to identify forward looking metrics the inform business stakeholders rather than just provide them with a rear view mirror of past performance. Unshackle your reporting image and unleash your advisory aura to become your commercial team’s best friend.

Marketing clouds are all the rage. 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? Or should we take the name at face value – ‘Marketing’ Clouds.

David Williams, Digital Experience Director of fashion retailer ASOS invites you to share your experience, views and predictions. He will discuss success and horror stories, the build/buy/borrow dilemma and whether this gets us any closer to delivering data-driven personalisation for our customers.

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 personalization.

Growing your role into an analytics services advisor requires a change of behaviour on your part in order to effect a change in the behaviour of your organisation. How we represent ourselves determines how the rest of the enterprise sees us.

Leading the discussion form the perspective of senior management, Jim Sterne will look to unearth ways an analyst can present their occupation so that the rest of the company sees them as specialists and authorities instead of sentient calculators.

What does an analytical statement of work look like? How does an underfunded analytics team properly prioritise the tasks they can accomplish? What can we do and what should we avoid doing in order to gain respect?

Our output might include a list of positioning guidelines for analysts or advice on helping one’s company become more data driven.

In recent years we have seen an explosion in video and audio consumption via online channels; from marketing videos through socially-shared video content to full streaming services such as Netflix. While the shift in consumer behavior is clear, most organizations still struggle to measure streaming activity successfully.

June Dershewitz is the Head of Data Governance & Analytics at Twitch, the world’s leading video platform and community for gamers (an Amazon subsidiary). As such, understanding streamed content is a core focus of her role. In this discussion she will examine some of the challenges with measuring streaming video.

Topics will include:

• Instrumentation and data collection - what makes streaming content unique? We must contend with multiple platforms and players, a wide array of metadata, and edge cases galore
• Blending technical performance metrics with traditional user engagement ones
• Opportunities for reporting and analysis of streaming video

If streaming is a key part of your content strategy then this discussion is where you should be.

Experimentation programs have been operating within many companies for nearly a decade now. That is a sufficiently long enough period to exhaust most if not all of the “low hanging fruit” of testing and targeting potential. There are new opportunities with the introduction of new technologies such as mobile, apps and increasingly wearables. However, in most cases the fundamentals remain the same.

So what’s next for experimentation? Where is the next growth area? In this huddle, led by Dylan Lewis of Intuit, we will explore the opportunities for getting better results, driving more informed decision making, enhancing customer experiences, and avoiding common mistakes. This conversation will be focused on practical ideas and concepts aimed at improving our experimentation programs to ensure continuous success.

Over the years you have developed extensive analytics experience. You progressed through the ranks from analyst to senior manager. You are now at (or nearing) the top of the digital analytics ladder. You must be asking yourself – what’s next? Can I become the next Chief Data/Information Officer? Is there room moving up or do I need to shift to another commercial role to expand my options?

In this huddle, Steve Harris of Capital One will lead a discussion around the perpetual personal development questions we face as our career develops. Is there any road left in digital analytics? Should we skill up into other areas of analytics? How do we manage the dialogue with senior management over the jump to a CDO/CIO role?

Join us for what is sure to be an illuminating discussion about career progression at the top of the digital analytics pyramid.

Lynn Lanphier, heads Best Buy’s digital intelligence and optimization team. Driving decisions via innovative communications is a daily challenge her team thrives on.

In this huddle, Lynn 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. We will also look at what are the key features of a ‘good story’? How to define and support our expertise through storytelling? What are the most common mistakes and pitfalls? What is the balance between data simplicity and data sufficiency? And should suggestions and recommendations be a part of our stories?

Within any large group of fans/customers/users, there are segments that have similar characteristics. Some customers will use the same device to consume your content; others will engage with your brand in similar frequency or display a certain level of brand advocacy on social media.

Segmentation is a valuable way to evaluate your audience. With today’s tools and capabilities, segmentation has many use cases and a variety of practical approaches. Defining the various segments and building strategies for each is not an easy feat. But it is an essential task if you are to move the needle on key metrics.

In this huddle, Shari Cleary, the SVP of Strategic Insights & Research at Comedy Central, will lead a discussion on best practices for defining segments and the tools to help us do so. She will also share a recent case study and will encourage participants to provide their success and fail stories.

This huddle will inspire you to use your customer data more effectively through new ways of segmenting audiences.

Platform owners like Facebook, Google, Apple, Snapchat and Wechat all have something in common – they are all competing for our time and attention. To do so, they are reshaping mobile customer experiences and building new ways of bringing media and commerce into the confines of their own walled gardens.

The motivation is simple – improved experiences for their users help them compete in this battle for attention. This exciting movement could fundamentally change the dynamics of mobile usage and consumption. And while exciting, this movement poses significant challenges to analysts. It risks creating siloed data sets and a fragmented data ecosystem making the sought-after holistic view of customers much more challenging to obtain.

This has all of the hallmarks of our experiences in the rise of mobile platforms. Except this time the change is likely to be quicker and platform providers hold the keys to the data.

Join Tom Betts, Chief Data Officer at the Financial Times, for a discussion about data ecosystem management in a world where distributed platforms rule. We will look at key challenges and successes with accessing and integrating data from distributed platforms. We will also examine how best to leverage this data.

We all have a responsibility to ensure we act in an ethical manner. Sometimes the boundaries become opaque as we come close to a breakthrough or under pressure from the business to deliver.

In this huddle, Theresa Locklear of the NFL will use the group’s collective experience to explore the question of ethics in digital 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?
• 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 discuss you are either a saint or you have no moral compass at all.

Most enterprises have struggled with digital. As much money, time and resources as they have invested, traditional businesses often feel – and really are – slower, less accomplished, and less adept at digital than their pure-play competitors. Is that fixable? Are there ways big companies can adapt their culture, their organisation, and their capabilities in ways that make them truly competitive?

In this discussion, led by Gary Angel, we will look at how analytics can/should be integrated into the enterprise to achieve deeper organisational transformation. Topics covered will include:

• Why analytics fails
• What capabilities need to be integrated
• What is the role of Agile
• How to transform enterprise culture around analytics

In an attempt to better understand our customers and to quantify and qualify their experience, we have deployed a multitude of tools that collect copious amounts of data. With digital analytics, customer satisfaction, session replays, usability testing and ethnographic fieldwork data, one could claim to be capturing the full customer experience.

But how do we make sense of all this data and what measurements are appropriate for gauging the success of our efforts?

In this huddle, led by Rene Villa of Verizon Wireless, we will explore the question above. We will share experiences, good and bad, of using diverse data sets to augment traditional digital analytics data. We will look at techniques to harvest that data effectively and to use our limited resources efficiently.

You will come out of this discussion with a new sense of focus on how to improve the tracking and consequently the understanding your customer journey.

If your career is not in transition, it should be. This does not mean you need to change jobs but without growth and change - we stagnate. And then it is only a matter of time before change will be brought upon us. Why not proactively seek it out?

This discussion, led by David McBride of Intel, will focus on topics like detecting early-warning signs that it is time to re-engage, deciding if you need to make a career change, finding the right way to seek additional responsibility, seeking opportunities at your current company, cultivating a network and starting out in a new role on the right foot.

Note: Attending this discussion does not mean you are looking to change companies or that you do not like your job. All who seek to optimise their work experience are welcome and encouraged to attend.

Getting exposure for the digital analytics experience (and for yourself) means telling a compelling narrative and visualizing data to support it. Are you telling a memorable story? One that is forward looking, coherent, and represents the business opportunities that digital can offer your business?

Carrie Bolton of Vanguard will lead this discussion on how to get business leaders to share what they really need, and how to interpret their needs into compelling work that keeps them interested in what the digital channel has to offer. She will invite participants to share their expertise – how do you consult with your business partners to understand what they are trying to accomplish? How can you translate your work into a story they can absorb and act upon?

Join this huddle and come away with fresh ideas about how to communicate with senior management and improve your storytelling techniques.

Just as baseball scouts try to build and cultivate dynasty teams, we analytics managers seek to develop and optimize high performing organizations. In a market that is exploding with opportunity and a shortage of analysts, are there lessons and strategies we can learn from these scouts? What tools can we use to identify and recruit for skill gaps in our teams? When do you build a bench of talent and when do you look for veteran stars? What can you do to help your rookies become stars?

In this huddle, led by Amy Sample of PBS, we will explore strategies to creating top-notch teams. We will share what has worked for us in our own organizations from interviewing techniques to writing good job descriptions. We will explore what tools are available to help define a career path for our analysts. And we will discuss ways to help our analysts get the skills they need to move to the next level. This huddle is ideal for those already managing a team and those aspiring to do so.

The recent explosion of data, and the tools to handle the data, has created huge opportunities for savvy business. It is no longer enough to simply use data to optimize or course-correct your business. Your data can be used to create digital products that provide value to consumers and businesses.

Vivint, the smart home applications and services company, employs digital analytics insight regularly to inform its product development. In this huddle, Brandon Bunker, Director of Analytics at Vivint, will share experiences and investigate how to integrate analytics into digital product development to create value for both customers and companies. We will discuss how to identify valuable data opportunities. We will examine the requirements and demands of digital goods and the changes we must make to our analytics processes to support those changes. We will ask how to get organizational buy in to create these products or services. Finally, we will talk through some of the technologies that are making this journey possible.

We rarely have all necessary data in the data-to-decision supply chain. Our business is constantly making assumptions, many of which trigger questions to the analytics team. Which of those questions should be prioritized? Which ones should be modeled, and which ones deserve new data to be captured?

In this huddle led by Alex Destino of Humana we will discuss making the shift from ad hoc to a planful, demand-driven analytics system centered around choosing the "right" questions to be answered using data. Topics will include managing learning agendas, shifting the analyst mindset, and aligning stakeholder expectations.

Following our conversation, you will be better equipped to design a service-first analytics practice that will ultimately help your organization make better decisions.