Last Thursday, October 12, the Digital Analytics Summit 2023 was held at Pakhuis de Zwyger in Amsterdam. A knowledge and networking event created to bring specialists and managers, who work with digital analytics on a daily basis, up to date on data, analytics and digital marketing. Digital analytics from head to tail, in other words. From collecting data to reporting insights, but also about the various techniques and regulations that may apply to it.

In the three rooms of the impressive building on ‘t IJ, which incidentally used to serve as a cold storage warehouse, there was room in the program this day for some very interesting speakers from home and abroad. Analytics Power Hour podcast creator and self-proclaimed “analytics dinosaur” Tim Wilson was one such. But there were more interesting speakers... I made a personal selection, and because of the extensive program, I made the most of it and that's exactly 50% (saw 8 out of 16 speakers). Or do I now have a 100% score? :). It's just how you look at the data. Let that be just about the thread of the day. What exactly is analytics? How do you look at it as a specialist, but more importantly, how does your client look at it? And what questions are asked? 

Sometimes some of the stories sounded like old wine in new bags, but that's exactly what it wasn't. The analytics community has tried a lot, failed a lot, learned a lot (GA4 not to forget!) and some interesting insights were therefore shared with us today. For example, that we always fall for the fact that data collection is very important and that there would be business value in it too! Nope, it's much more about its potential value. In addition, we still have much more to gain from that human, creative brainpower of the analyst.

Read on quickly and get the potential value from the take aways of the 6 speakers I saw and heard.

7 KEY METRICS TO MEASURE THE VALUE OF ANALYTICS

Ibrahim Elawadi, Global Director, Marketing Analytics (Philips)

Ibrahim Elawadi bit the bullet. As Global Director of Marketing Analytics at Philips, he addressed two questions: “How do you know analytics works?” and “How do you measure its value?”. This also kind of stems from the following: in fact, there are estimates that only 20% of analytics insights actually drive a particular business outcome.

Takeaways:

• You can only get value from analytics if you take action on it. To determine how long this takes after insights are gained, you can use metrics such as ‘action rate’ and ‘time to action. 
• In addition to tangible values such as ROI and Cost of Ownership, non-tangible values should not be underestimated. Consider, for example, insights with strategic value, saving time, costs and decision-making based on qualitative insights.
• Not a tech stack but the organizational culture, which consists of people and processes, is often seen as the main barrier to being data-driven. Therefore, at the coffee machine, don't start talking about data and technology but what keeps someone engaged.

DECATHLON: MAPPING OUT THE PATH TO DIGITAL ANALYTICS MATURITY

Peter O'Neill, Head of Digital Analytics (Decathlon)

In addition to his new position as Head of Digital Analytics at Decathlon, Peter O'Neill is best known as founder of MeasureCamp, the world's largest analytics unconference. Since joining Decathlon only 3 months ago, Peter has been mapping the current digital analytics maturity of the organization. In his talk, he made it clear that Decathlon is not making enough impact at the moment, but he also explained how he plans to improve this over time in order to make an impact. 

Takeaways:

• Using its own maturity model, it was determined that the situation at Decathlon appears to be unbalanced on several issues. The biggest challenges appear to be putting data quality and everything concerning data ownership in order.
• A plan is in place with clear steps to address maturity. In addition to data quality, this includes data activation, documentation, consistency, training and culture.
• Need at this time is for time, people, recruitment and having 1 analyst per team.

INVESTIGATING DRIVERS BEHIND ONLINE ENGAGEMENT

Director of Data & Consumer Analytics (DPG Media).

With 14 million unique visitors per day, the network of DPG Media in the Netherlands and Belgium has an incredible reach. Good content on websites like AD.nl or Nu.nl is important and this figure shows that, but what drives visitors to read even more and what success metric do they look at?

The key KPI is the number of returning days per visitor in the past 28 days. At least, that has been the main engagement metric for the past 2 years. Through the conduct of an experiment, they have come to interesting new insights that need to be explored further.

Takeaways

• By working data-driven and adopting an experiment mindset, possible drivers were explored and researched using hypotheses established in advance.
• An experiment with an email campaign to encourage app usage showed 2.5 more app engagement, but this did not result in more app downloads. The approach and especially the key metric(s) are being reconsidered.
• Stay focused on the relationship with key KPIs. Research hypotheses and do experiments. Dare to dig deeper if your plan doesn't work!

ARE WE DANGEROUSLY OBSESSED WITH DATA COLLECTION?

Tim Wilson, Co-Host Analytics Power Hour (analyticshour.io)

Tim Wilson is an analytics veteran or an “analytics dinosaur” as he also calls himself. He has worked for Fortune-500 companies for more than 20 years, advising them internally at various levels. In this talk, which he told me he spent months tinkering with, his message is very clear: “Why do we spend so much time collecting data and so little on actually using that data meaningfully?” Like Ibrahim Elawadi earlier in the day, Tim's talk is also about working with data, what you do with it next and exactly what value you get out of it. The latter in particular is something that has bothered Tim for years. So in his view, this is not being done enough.

We seem to get caught up in thinking time and again that data collection and data management are about business value, but it's more about potential value. This is an important difference and it is very easy to get sucked into this thinking. According to Tim, we need a framework for the different ways we use data.

Take aways

• There is no fixed business value attached to analytics measurements, only a potential business value. 
• Data collection and management is too promising and often prompted and promoted by software vendors and agencies. It's more about mental models and creative thinking than what specific technology you deploy. We need people to think!
• Use a framework that helps you focus on data use in your organization in the areas of performance measurement (what is the expected business value from the present to the future?), hypothesis validation (how can you use data to reduce uncertainty?) and operational activation (what if data is part of a process? what do you do then?).

BREAKING THE CHAINS OF DATA TRADITION: CRAFTING A FRESH MEASUREMENT STRATEGY FOR SUCCESS

Jill Quick, Analytics Consultant and Trainer (The Coloring in Department)

Jill Quick is a colorful and versatile analytics jack-of-all-trades. As a consultant for ‘The Coloring in Department,’ she helps organizations with all things tracking. These have recently been many GA4 implementations, but she also does data visualization. This is report generation and BigQuery. In her talk, she discussed breaking what she describes as a “data tradition” and had some fun anecdotes from her clients' practices:

“We have migrated but it doesn't feel right. Make GA4 like UA! All our reports are broken and nothing matches what we had as a baseline in UA”. 

Takeaways

• Data maturity is often done from an internal perspective and that is still about creating beautiful, colorful dashboards and less about how you use data. Dashboards are still useful to make, for example to get hold of a budget. Tip: dashboards can also be worked out first as a wireframe with pen and paper.
• It is important to keep asking stakeholders the why question. After all, they often don't ask what they really want to know. For example, ask if they trust the data (problems they experience are often not even technical in nature) or what their most and least favorite metric is. Distinguish between need to haves and nice to haves.
• Use post-it note reporting. This is a simple approach to working out points for Read, Act, Convert and Engage from the RACE marketing model. Jill herself learned from a client to work out points on a post-it first (otherwise she wouldn't get a budget).

THE BEAUTY OF SELF-SERVICE

Yael Farkas, Head of Digital Intelligence (Douglas)

Yael Farkas' passion lies in creating value from data, reflecting her ongoing commitment to shaping the digital landscape at Douglas. During her talk, she dwelt on how it all started: with an infinite number of tickets to answer simple data questions that provide absolutely no value. She also showed how she transformed Douglas' organization into one that is largely self-sufficient in data.

Takeaways

• To be more profitable and efficient using data, 3 pillars have been defined:
  1) Off to a great start 2) You are not alone and 3) Actionable insights
• The first pillar is actually about trust, and one can gain it by, for example, using automated video onboarding and creating reports on specific topics and walkthroughs (this explains, among other things, what a metric means and how to deploy it). 
• The second pillar is about grabbing momentum. Use weekly drop-in sessions to spar with analysts. Should no one show up, the analysts can still spar together. With Slack, simple requests were handled the same day using an SLA.
• The third pillar is about scaling up and further automation: it's business as usual!

SCALING AN EXPERIMENTATION PROGRAM IN A REMOTE FIRST WORLD

Ashit Kumar, User Growth Lead (Spotify)

Ashit and his team are responsible for running 100 experiments a year on Spotify's website. Meanwhile, the platform has 220 million subscribers (50% is Premium) and 551 million active users. By the way, these figures are from June this year. With a team of 11 people, they work together intensively remotely, so the team is also highly dependent on each other when it comes to development, data analysis and designing the experiments. 

The tooling used consists of a mix of Google Analytics, BigQuery, Conductrics, Airtable, Github, Figma and Jupyter. The team is now running well but this was difficult to organize at first because how do you scale up in a world where almost all team members work in different time zones?

Take aways

• It's hard to empathize with people in a remote-first environment, but you'll just have to embrace asynchronous working. Create trust inside and outside the team first.
• Set up a workflow that automates a lot for the team. In this case, a combination of Airtable and Slack where the latter tool provides implicit transparency because comments and emojis make people feel heard and seen. Email threads are much harder to track in that respect.
• Setting focus time is useful for not getting distracted. Notification fatigue is real!
• Use moments to look back (“remote retrospectives”) and be as honest with each other as possible. Engage in team building by engaging in 2-weekly health checks and water cooler conversations, for example.
• Celebrate successes, as well as failures. Carrots work better than sticks!

The final speaker of Digital Analytics Summit 2023 was Parvathy K. Krishnakumari, Chief Technology Officer of the Analytics for a Better World Institute. Her talk was very inspiring to everyone in the room. The institute combines capabilities of nonprofit organizations, academia and businesses to contribute to the United Nations Sustainable Development Goals (SDGs). 

It gave an impressive insight into how analytics can also be used, namely to make the world a little better again. A good reminder for myself and also for many organizations in the room. Perhaps analysts should devote their knowledge and power to a sustainable project. Analytics, for a better world!

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Conclusion

The interest in the talks during this edition of the Digital Analytics Summit was probably very personal for everyone. Want to take away more knowledge about GA4 and BigQuery? Or hear about Privacy by Design? It was all covered because the program was well balanced and therefore very well put together by the DDMA commitee. My compliments! 

What potential value I got out of this day? That a good digital analytics maturity scan always provides good insight into what an organization needs. That analytics itself has no business value, but at most a potential value. That your customers or stakeholders are not machines but people, just like you, the analyst. People with creative ideas and these ideas you have to keep exploring and finally, therefore don't talk data but ask what is on someone's mind. Ask the why question more often. Why? Well, why...

Want to know more about GA4? Click here for our GA4 Training.

Want to learn more about BigQuery? Click here for our BigQuery Training. 

Photos: https://digitalanalyticssummit.nl

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