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From Retrospective to Prospective Analytics - Ikechi Okoronkwo

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Ari Kaplan sits down with Ikechi Okoronkwo of Mindshare for this episode to discuss using predictive analytics to make key future decisions.
Mindshare is a global media agency dedicated to forging competitive marketing advantage for global clients like Unilever, General Mills, and Ford. Ikechi Okoronkwo heads Mindshare’s Business Intelligence & Analytics team, which is lauded in the industry for their fresh approach to analytics.

His mission is to simplify and refine decision-making processes using data and analytics to drive good growth: growth that is ethical, unbiased, and beneficial. His team builds tools that shift the focus of analytics from retrospective to prospective–from looking backward to looking forward.

“People think of analytics as reporting or dashboards charting progress against a target ROI. But the best types of insights are those that influence an imminent decision, whether that's a budgeting decision, an optimization problem, or any question about how to move forward.”

Their analytics do, of course, have a quantitative aspect: using the scientific method to test and validate assumptions is critical. But Ikechi challenges his team to continually find ways to drive a balance between data and the creativity that empowers clients to push their boldest ideas.
“Our job is to provide our clients simple frameworks to help them make smarter data-driven decisions in everything from creative to content to strategy.”

They begin with qualitative consultative conversations, from which they build an outcomes framework and define successful key performance indicators (KPIs). Only at that point do they start to talk about the data that will be needed to serve as indicators of performance against their articulated outcomes.

They then apply machine learning technologies to collect relevant data, leveraging proprietary methodologies to determine which types of data should be fused into each aspect of a client’s outcomes framework.

While the industry has been focused on collecting as much data as possible on people's behaviors–what they're clicking on, which sites they're visiting–Ikechi’s team invests in AI and machine learning to understand what’s behind those rational signals. For example, neurological studies in a neurolab might validate the self-reporting in surveys. They might observe participants and their subconscious reactions to a specific format or moments of higher receptivity when ads are viewed.

At the same time, data privacy and ethics are paramount to their solutions. They firmly believe clients should own their own data, and they’ve led the industry in their work to recognize bias in data. Their ethics tools enable continuous monitoring of how data is being collected, from where, and how it is used. In the end, this helps clients make objective decisions.
“It's not a question of how much more data we can collect to be better at our job. It's really more about what outcomes our clients want to drive and how we can empower them as business partners.”

Learn more about Ikechi’s innovative approach to analytics in this episode of More Intelligent Tomorrow. We’ll cover:

  • How to define exactly what data is needed to make critical decisions and how best to protect it
  • How to identify bias and know when you’re collecting the wrong data
  • How to use data to test feedback in the creative process
  continue reading

69 episodes

Artwork
iconShare
 

Fetch error

Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on February 26, 2024 14:53 (4M ago)

What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.

Manage episode 320023413 series 2842356
Content provided by DataRobot. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by DataRobot or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Ari Kaplan sits down with Ikechi Okoronkwo of Mindshare for this episode to discuss using predictive analytics to make key future decisions.
Mindshare is a global media agency dedicated to forging competitive marketing advantage for global clients like Unilever, General Mills, and Ford. Ikechi Okoronkwo heads Mindshare’s Business Intelligence & Analytics team, which is lauded in the industry for their fresh approach to analytics.

His mission is to simplify and refine decision-making processes using data and analytics to drive good growth: growth that is ethical, unbiased, and beneficial. His team builds tools that shift the focus of analytics from retrospective to prospective–from looking backward to looking forward.

“People think of analytics as reporting or dashboards charting progress against a target ROI. But the best types of insights are those that influence an imminent decision, whether that's a budgeting decision, an optimization problem, or any question about how to move forward.”

Their analytics do, of course, have a quantitative aspect: using the scientific method to test and validate assumptions is critical. But Ikechi challenges his team to continually find ways to drive a balance between data and the creativity that empowers clients to push their boldest ideas.
“Our job is to provide our clients simple frameworks to help them make smarter data-driven decisions in everything from creative to content to strategy.”

They begin with qualitative consultative conversations, from which they build an outcomes framework and define successful key performance indicators (KPIs). Only at that point do they start to talk about the data that will be needed to serve as indicators of performance against their articulated outcomes.

They then apply machine learning technologies to collect relevant data, leveraging proprietary methodologies to determine which types of data should be fused into each aspect of a client’s outcomes framework.

While the industry has been focused on collecting as much data as possible on people's behaviors–what they're clicking on, which sites they're visiting–Ikechi’s team invests in AI and machine learning to understand what’s behind those rational signals. For example, neurological studies in a neurolab might validate the self-reporting in surveys. They might observe participants and their subconscious reactions to a specific format or moments of higher receptivity when ads are viewed.

At the same time, data privacy and ethics are paramount to their solutions. They firmly believe clients should own their own data, and they’ve led the industry in their work to recognize bias in data. Their ethics tools enable continuous monitoring of how data is being collected, from where, and how it is used. In the end, this helps clients make objective decisions.
“It's not a question of how much more data we can collect to be better at our job. It's really more about what outcomes our clients want to drive and how we can empower them as business partners.”

Learn more about Ikechi’s innovative approach to analytics in this episode of More Intelligent Tomorrow. We’ll cover:

  • How to define exactly what data is needed to make critical decisions and how best to protect it
  • How to identify bias and know when you’re collecting the wrong data
  • How to use data to test feedback in the creative process
  continue reading

69 episodes

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