Agenda 2024

GenAI changes our relationship with technology. It’s a step-change from computation and automation to inspiration and innovation. Time to take the biggest leap in technology since the advent of the Internet. Using it as a tool to crank out text and images is all the rage but is like using an 18-wheeler to go to the grocery store. It’ll get the job done, but this is a tool for improving your imagination, creativity, and analytical thinking. Time to shift your thinking about computers from data retrieving and calculating to brainstorming, strategizing, and critical thinking.

• Learn to think outside the content generation and automation box
• Get your LLM to be your prompt engineer
• Elevate your strategic, innovative, intellectual capacity

You know the steps of data maturity from data and analytics engineering and reporting, through creating data products and becoming a trusted advisor. But toward what end? Lina paints a picture of the ideal, data-forward organization as a target, a goal, an aspiration. But more than just a daydream, she offers handy templates and tactics you can use to move your team forward and define what the 3rd generation CDO and data team could look like. Every small step you make today can get you closer to the ideal.

So, you’re collecting data server side, or maybe it’s next on your strategic roadmap?  Great work already!  The advantages of server-side data collection are well documented: Good for data quality, user privacy, user experience, and you’re a step closer to regulatory compliance. And then what?  Join Doug for this this exploration of business scenarios where server-side data collection unlocks potential, provides answers, and delivers competitive, commercial value. You’ll be able to take the business case to the board – and they’ll ‘get it’. Doug shares a plethora of use cases across industry verticals to incorporate into your data roadmap. 

More data and more technology to wrangle it than ever is driving stakeholder expectations through the stratosphere. The result? A growing Value Gap. And now comes the prefiltration of AI technologies exacerbating a trying state of affairs. Neil shares his Really Offensive analytics strategy that focusses on the Last Mile of turning data into wise counsel and actionable recommendations.

Or, as ChatGPT would have it:

In a world of endless data streams, tech and numbers fuel our dreams,
Expectations soar on high, yet the Value Gap is nigh.
Stakeholders’ hopes rise like dawn, real results often lag and yawn,
Businesses yearn for data’s might, visions struggling to take flight.
To Close The Gap, adopt bold ways, focus on the Last Mile phase,
Transform insights into action, fulfill data’s true attraction.
Join Neil Mason, learn the way, lead with data, seize the day.

Juliana shows how she created a Small Language Model top determine if search queries are linked to real visitor issues or purchase objections. By applying natural language processing and textual entailment (if the meaning of one text can be inferred from another) her model can improve landing pages, product detail pages, and category pages based on the content visitors search for. Learn practical strategies to apply these insights in your workflows…almost immediately. Spoiler alert: not using commercial Large Language Models!

Phil presents learnings from a study of the top 1000 sites in UK that use Google Tag Manager. Using a combination of BuiltWith, GTMgrader, and ConsentModeMonitor Phil’s team built an automatic scoring system to assess which companies had the best technical set-ups. They clustered site`s by vertical then looked at common tags & technologies. For the top 5 best and top 5 worst, they did a deep dive into their technical set-ups using GTMspy. The winning sites were not what you would expect and the split between high quality set-ups vs paid tools varied WILDLY between brands. Phil spills the beans.

Generative AI offers incredible potential for marketing analytics, but it also comes with a host of challenges and considerations. Martin explores the good, the bad, and the AI of using generative models. The potential for personalization and optimization must be balanced with the risks of bias and overreliance on automation. Martin offers up real-world examples of successful and responsible generative AI campaigns and discusses strategies for navigating potential pitfalls.

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.

Craig’s been using GA since Urchin days and has been sharing tips on Device Mining for 6 years.  After analysing hundreds of websites for device experience opportunities, coupled with device lab testing, Craig has mapped device reality to the GA data model, in ways that will help us all improve UX and Conversion.  All this Device Mining knowledge is now available in a free Looker Studio dashboard.  In this session, Craig will explain how to use the reports, read the data and what to look out for.  You’ll learn where the flaws are in the GA4 data model.  Most importantly, you’ll learn how to identify and fix gaps in the device experience for your product.

Scarlett was obsessed with digital behavioural tracking when the light bulb went on and she became obsessed with driving revenues with data products and services at the core. There is often an opportunity to take your data craft and apply it to a business problem that’s run in Excel/gsheets. Scarlett talks through her journey and how it created a new career for her. Lessons learned and things to not get hung up on as a data person included. This is how to get from maths to money.

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.

Digital analytics exists to support the entire marketing team and that requires the team to be data-ready. Salman shares his approach to transforming the marketing teams into data enthusiasts starting with the establishment of an internal baseline through surveys. Survey results are essential for creating appropriate and effective training programs. He outlines his method of fostering a data-aware culture through informal training, formal workshops, and casual office hours. If you are not dedicated to internal marketing of initial success stories, this plan cannot succeed. Salman offers a few tips, tricks, and traps for turning data skeptics into data fanatics.

Google Consent Mode is supposed to help businesses manage user consent for Google’s advertising and analytics tools. This API allows you to control consent preferences, especially regarding cookies and data collection – a variety of options that make it more common to botch the implementation than not. Robert covers the technical and the marketing/business side of using Consent Mode to properly collect the data needed for modelling, which can later be used for AI-augmented smart audiences.

The course of true Omnichannel never did run smooth. Yael shares lessons learned while attempting to cover 360 degree Omnichannel by triangulating dynamic attribution, Media Mix Modeling and incrementality testing. Like all of us, she still has a long way to go, but can share some of the challenges and insights already generated along the way. Learn what she would do to speed things up next time.

After many false starts and delays, it looks like third-party cookies will finally disappear at the end of 2024. This change will have a huge impact on marketers’ ability to target, measure and optimize their campaigns, but many companies are woefully ill-prepared for the coming storm. Fortunately, salvation may emerge from an unlikely quarter: AI. Ian explores how a trinity of AI techniques (deep-learning based contextual targeting, automated creative generation, and continuous optimization) can come together to save the day and protect campaign performance and insights in a post-cookie landscape.