Leaders of Analytics

As the digital landscape evolves, privacy concerns and regulations are becoming increasingly important for advertisers. With the decline of third-party cookies and the rise of individual data usage consent, measuring advertising attention is more crucial than ever.

One of the biggest challenges for advertisers in a cookie-less world is being able to accurately measure the effectiveness of their campaigns. Without cookies, it's harder to track user behaviour and understand how their ads are performing.

However, measuring advertising attention through alternative methods such as viewability, brand lift studies, and surveys can be helpful, but they provide vague and delayed signals about advertising effectiveness.

How can advertisers measure the attention and effectiveness of their advertising in real-time?

To answer this question, I recently spoke to John Hawkins, Chief Scientist at Playground XYZ. Playground XYZ provides a machine learning-based platform for measuring and maximising attention on digital ads.

The company’s Attention Intelligence Platform is a unique technology that uses over 40 different signals to track user attention as it happens.

In this episode of Leaders of Analytics, we discuss:

• How Playground’s attention measurement platform works in practice
• The importance of attention time in a world without cookies, where privacy and consent are increasingly of mandated importance
• Dealing with the complexities of multi-layered machine learning pipelines and convincing stakeholders of their value
• How data science professionals can foster the right non-data science skills that will make them true unicorns, and much more.

John on LinkedIn: https://www.linkedin.com/in/hawkinsjohnc/

John's book, Getting Data Science Done.

As the digital landscape evolves, privacy concerns and regulations are becoming increasingly important for advertisers. With the decline of third-party cookies and the rise of individual data usage consent, measuring advertising attention is more crucial than ever.

One of the biggest challenges for advertisers in a cookie-less world is being able to accurately measure the effectiveness of their campaigns. Without cookies, it's harder to track user behaviour and understand how their ads are performing.

However, measuring advertising attention through alternative methods such as viewability, brand lift studies, and surveys can be helpful, but they provide vague and delayed signals about advertising effectiveness.

How can advertisers measure the attention and effectiveness of their advertising in real-time?

To answer this question, I recently spoke to John Hawkins, Chief Scientist at Playground XYZ. Playground XYZ provides a machine learning-based platform for measuring and maximising attention on digital ads.

The company’s Attention Intelligence Platform is a unique technology that uses over 40 different signals to track user attention as it happens.

In this episode of Leaders of Analytics, we discuss:

• How Playground’s attention measurement platform works in practice
• The importance of attention time in a world without cookies, where privacy and consent are increasingly of mandated importance
• Dealing with the complexities of multi-layered machine learning pipelines and convincing stakeholders of their value
• How data science professionals can foster the right non-data science skills that will make them true unicorns, and much more.

John on LinkedIn: https://www.linkedin.com/in/hawkinsjohnc/

John's book, Getting Data Science Done.

Inflation is rising, interest rates are up across the globe and cash is king again. How will this impact the flow of venture investments in start-ups and emerging technologies?

While traditional investments may suffer during a recession, the venture capital industry has historically been able to weather the storm and even thrive. One reason for this is that venture capital firms typically invest in early-stage companies that are not yet generating significant revenue.

In fact, some of the most successful companies in recent history, such as Uber, Airbnb and Snapchat, were founded during economic downturns. The downturns created opportunities for entrepreneurs to innovate and create new solutions to problems caused by the economic conditions.

Mendoza Ventures is one such investor, but with a unique approach. Mendoza’s investment strategy is focused on the verticals of AI, fintech and cybersecurity and 80% of their investments go to founders from diverse and minority groups.

I recently caught up with Scott Heyes, CFO at Mendoza Ventures to understand how a venture capital firm works in practice and how he and his colleagues think about investing in the current economic climate and beyond.

In this episode of Leaders of Analytics, we discuss:

• How Scott became the CFO at Mendoza Ventures and what a week in venture investing looks like
• How the firm decides which companies to invest in
• Why Mendoza Ventures specifically back founders from diverse and minority backgrounds.
• Which segments within AI, fintech and cybersecurity will win or lose during a period of uncertainty, inflation, reduced access to funding and higher borrowing costs.
• The trends in AI, cybersecurity and fintech worth watching in the next 2-5 years, and much more.

Scott on LinkedIn: https://www.linkedin.com/in/scottheyes/

Mendoza Ventures: https://mendoza-ventures.com

Learn more about Annual Recurring Revenue in this episode.

Inflation is rising, interest rates are up across the globe and cash is king again. How will this impact the flow of venture investments in start-ups and emerging technologies?

While traditional investments may suffer during a recession, the venture capital industry has historically been able to weather the storm and even thrive. One reason for this is that venture capital firms typically invest in early-stage companies that are not yet generating significant revenue.

In fact, some of the most successful companies in recent history, such as Uber, Airbnb and Snapchat, were founded during economic downturns. The downturns created opportunities for entrepreneurs to innovate and create new solutions to problems caused by the economic conditions.

Mendoza Ventures is one such investor, but with a unique approach. Mendoza’s investment strategy is focused on the verticals of AI, fintech and cybersecurity and 80% of their investments go to founders from diverse and minority groups.

I recently caught up with Scott Heyes, CFO at Mendoza Ventures to understand how a venture capital firm works in practice and how he and his colleagues think about investing in the current economic climate and beyond.

In this episode of Leaders of Analytics, we discuss:

• How Scott became the CFO at Mendoza Ventures and what a week in venture investing looks like
• How the firm decides which companies to invest in
• Why Mendoza Ventures specifically back founders from diverse and minority backgrounds.
• Which segments within AI, fintech and cybersecurity will win or lose during a period of uncertainty, inflation, reduced access to funding and higher borrowing costs.
• The trends in AI, cybersecurity and fintech worth watching in the next 2-5 years, and much more.

Scott on LinkedIn: https://www.linkedin.com/in/scottheyes/

Mendoza Ventures: https://mendoza-ventures.com

Learn more about Annual Recurring Revenue in this episode.

30 years of “corporate social responsibility” has left our planet in dire straits.

Biodiversity loss, climate change, water pollution, micro-plastic pollution, air pollution, species collapse, ecosystem collapse…the list goes on.

What can we all do individually and collectively as business leaders and responsible humans to turn the situation around?

According to Simon Schillebeeckx from Handprint.tech it is possible to create incremental financial value while regenerating the ecosystems we rely on.

Simon and his colleagues at Handprint have written a manifesto for saving the planet, called Regeneration First, that tells us exactly how this can be done.

In this episode of Leaders of Analytics, we discuss:

• The current state of the many environmental issues facing us.
• The “Regeneration First” manifesto and the 7 action shifts needed in our approach to sustainability.
• Whose role it is to deal with climate change
• Promising climate technologies that will help us solve the negative impacts we’re having on the planet
• How we create more short-term environmental incentives to deliver long-term impact
• What we can do individually to contribute to environmental regeneration, and much more.

Links:

Simon on Linkedin: https://www.linkedin.com/in/simonschillebeeckx/

Some promising carbon removal solutions discussed on the A16Z podcast.

The Road to 100 Percent Renewables in Australia via Energy Insiders.

30 years of “corporate social responsibility” has left our planet in dire straits.

Biodiversity loss, climate change, water pollution, micro-plastic pollution, air pollution, species collapse, ecosystem collapse…the list goes on.

What can we all do individually and collectively as business leaders and responsible humans to turn the situation around?

According to Simon Schillebeeckx from Handprint.tech it is possible to create incremental financial value while regenerating the ecosystems we rely on.

Simon and his colleagues at Handprint have written a manifesto for saving the planet, called Regeneration First, that tells us exactly how this can be done.

In this episode of Leaders of Analytics, we discuss:

• The current state of the many environmental issues facing us.
• The “Regeneration First” manifesto and the 7 action shifts needed in our approach to sustainability.
• Whose role it is to deal with climate change
• Promising climate technologies that will help us solve the negative impacts we’re having on the planet
• How we create more short-term environmental incentives to deliver long-term impact
• What we can do individually to contribute to environmental regeneration, and much more.

Links:

Simon on Linkedin: https://www.linkedin.com/in/simonschillebeeckx/

Some promising carbon removal solutions discussed on the A16Z podcast.

The Road to 100 Percent Renewables in Australia via Energy Insiders.

How does a traditional bricks-and-mortar retailer transform itself into an omni-channel business with strong digital and data science capabilities?

In this episode of Leaders of Analytics we learn from Bunnings General Manager, Data and Analytics, Genevieve Elliott, how the company is transforming its operations using data and analytics.

As Australia and New Zealand’s largest retailer of home improvement products, Bunnings is a highly complex organisation with a large physical footprint, a wide product range and an elaborate supply chain.

Bunnings is almost 130 years old and has undergone tremendous growth over the last three decades. The company’s well-known strategy of “lowest price, widest range and best customer experience” is increasingly being driven by the company’s growing data and analytics capability.

In this episode we discuss:

• Genevieve’s career journey and how she ended up in data and analytics
• How Bunnings uses data to create operational efficiencies, improve customer experience and optimise pricing
• How the team prioritises projects and engages with the organisation
• How the Data & Analytics team is driving a data-driven culture through the company
• Genevieve’s advice to other analytics leaders wanting to drive strategically important results for their organisation, and much more.

Genevieve Elliott on LinkedIn: https://www.linkedin.com/in/genevieve-elliott/

How does a traditional bricks-and-mortar retailer transform itself into an omni-channel business with strong digital and data science capabilities?

In this episode of Leaders of Analytics we learn from Bunnings General Manager, Data and Analytics, Genevieve Elliott, how the company is transforming its operations using data and analytics.

As Australia and New Zealand’s largest retailer of home improvement products, Bunnings is a highly complex organisation with a large physical footprint, a wide product range and an elaborate supply chain.

Bunnings is almost 130 years old and has undergone tremendous growth over the last three decades. The company’s well-known strategy of “lowest price, widest range and best customer experience” is increasingly being driven by the company’s growing data and analytics capability.

In this episode we discuss:

• Genevieve’s career journey and how she ended up in data and analytics
• How Bunnings uses data to create operational efficiencies, improve customer experience and optimise pricing
• How the team prioritises projects and engages with the organisation
• How the Data & Analytics team is driving a data-driven culture through the company
• Genevieve’s advice to other analytics leaders wanting to drive strategically important results for their organisation, and much more.

Genevieve Elliott on LinkedIn: https://www.linkedin.com/in/genevieve-elliott/

Is your company good at customer success and retention? Chances are that you could be better.

For most businesses with a recurring revenue model, customer churn is a very costly affair. Whenever a customer leaves, you lose out on recurring revenue, forgo the opportunity of expansion (cross sell) revenue and have to pay for another round of acquisition costs to cover the loss.

In my personal experience, customer retention is both art and science. Machine learning and other data science techniques can be used to identify customers who are likely to churn, but it is equally important to craft meaningful and delightful interactions throughout the customer lifecycle.

So, what’s required to become a lean, mean retention machine?

In this episode of Leaders of Analytics, I speak to Sami Kaipa to learn the best practices of data-driven customer retention.  Sami is an experienced technology executive, serial entrepreneur and start-up advisor. He is co-founder of Tingono, an AI-driven customer retention platform.

Listen to this episode as we discuss:

• Sami's journey as an entrepreneur and corporate technology executive
• The core elements of customer success and retention that every business should master
• A deep dive into the concepts of customer retention, expansion and NRR
• The economics of customer retention and expansion
• How data science and machine learning can help with retention, and much more.

Connect with Sami on LinkedIn: https://www.linkedin.com/in/samkaipa/

Tingono's blog: https://www.tingono.com/blog

Is your company good at customer success and retention? Chances are that you could be better.

For most businesses with a recurring revenue model, customer churn is a very costly affair. Whenever a customer leaves, you lose out on recurring revenue, forgo the opportunity of expansion (cross sell) revenue and have to pay for another round of acquisition costs to cover the loss.

In my personal experience, customer retention is both art and science. Machine learning and other data science techniques can be used to identify customers who are likely to churn, but it is equally important to craft meaningful and delightful interactions throughout the customer lifecycle.

So, what’s required to become a lean, mean retention machine?

In this episode of Leaders of Analytics, I speak to Sami Kaipa to learn the best practices of data-driven customer retention.  Sami is an experienced technology executive, serial entrepreneur and start-up advisor. He is co-founder of Tingono, an AI-driven customer retention platform.

Listen to this episode as we discuss:

• Sami's journey as an entrepreneur and corporate technology executive
• The core elements of customer success and retention that every business should master
• A deep dive into the concepts of customer retention, expansion and NRR
• The economics of customer retention and expansion
• How data science and machine learning can help with retention, and much more.

Connect with Sami on LinkedIn: https://www.linkedin.com/in/samkaipa/

Tingono's blog: https://www.tingono.com/blog