The Hidden Ingredient Behind Every Marketing Success: A Conversation on Data Quality with Dr. Prashanth Southekal
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Introduction
Years ago, when I first dipped my toes into the world of marketing, things were simpler. The customer’s journey from awareness to purchase was fairly straightforward. A good campaign was a billboard on the highway, a clever TV ad, or maybe a memorable radio jingle. That was it. Marketers had a gut instinct for what worked, and success was often measured by intuition as much as data.
But times changed. Data became king. It didn’t just help us understand what worked—it became the blueprint for every decision. By the time I developed Galileo, a multi-touch attribution platform designed to trace customer interactions across multiple touchpoints, I was already knee-deep in the data revolution. My tool helped marketers see the entire customer journey, from a social media like to an eventual sale, and determine which touchpoints really mattered.
Yet there was one issue that kept cropping up, time and time again: the data itself. And that’s where my long-time friend and mentor, Dr. Prashanth Southekal, comes in. If there’s anyone who understands data, and more importantly, the quality of that data, it’s Dr. Southekal.
I first met Dr. Southekal while studying in class at the Kellogg School of Management, but in the years since, I’ve come to value his counsel more than ever—especially when it comes to navigating the murky waters of data in marketing.
Data: The New Oil?
“Data is the new oil,” Dr. Southekal tells me over coffee one afternoon. It’s a phrase I’ve heard countless times, often with the implication that data, like oil, is inherently valuable. But Dr. Southekal doesn’t let that metaphor slide so easily. “The truth is, raw data by itself isn’t worth much. It’s what you do with it—and how clean or processed it is—that really matters.” For example, crude oil per-se is not valuable. But when the crude oil is processed or refined, the high-value products such as gasoline, diesel fuel, and jet fuel produced make the crude oil very valuable.
He’s right, of course. Having spent years working with data in marketing campaigns, I’ve seen firsthand how bad data can sink even the best strategies. It’s like having a high-performance car with a faulty engine; everything looks good on the surface, but it won’t get you anywhere.
Dr. Southekal leans in, as if to underscore the point. “Marketers often assume that more data equals better insights. But if your data is inaccurate, incomplete, or outdated, you’re not just running in circles—you’re running in the wrong direction.”
This, he explains, is why data quality matters. It’s not just about having lots of data—it’s about ensuring that data is accurate, timely, consistent, and complete.
The Dimensions of Data Quality
To really understand the importance of data quality, Dr. Southekal suggests breaking it down into its core elements, or as he calls them, the “twelve dimensions of data quality.” These principles are the heart of his work, most notably laid out in his books Data for Business Performance and Data Quality.
“Start with accuracy,” he says. “If your data doesn’t reflect reality, you’ve already lost. Imagine you’re running a campaign with outdated customer addresses or incorrect purchase histories. Every decision you make based on that flawed data is going to lead you further from your goals.”
Accuracy, it turns out, is just the tip of the iceberg. The next dimension is completeness. Dr. Southekal explains this in a way that resonates with me. “Think of completeness as having all the puzzle pieces. If even one piece is missing—say, a customer’s interaction on social media—your entire understanding of their journey is incomplete. You can’t see the full picture.”
I’ve seen this happen firsthand. Galileo can track every touchpoint in a customer’s journey, but if the data feeding it is missing key interactions, the results are skewed. Marketing teams think they’re optimizing for the right channels when, in fact, they’re just optimizing for the ones they can see.
Dr. Southekal continues down the list: consistency, timeliness, validity, uniqueness, integrity, and more. Each dimension, he explains, is critical for turning raw data into actionable insights.
Take consistency, for example. If a customer’s profile is inconsistent across your CRM and your email marketing tool, it’s like trying to piece together two different versions of the same person’s life. “You might be running a fantastic campaign,” he says, “but if your data is fragmented, you won’t know who you’re really targeting.”
Then there’s timeliness, the silent killer of many marketing efforts. If your data isn’t up-to-date, you’re making decisions based on information that’s already out of sync with reality. “In today’s world,” Dr. Southekal says, “timeliness isn’t just important—it’s everything.”
And don’t get him started on uniqueness. “Duplicate data is like having two maps of the same place, but each one leads you in a slightly different direction. It’s confusing, it’s inefficient, and it can sabotage your entire strategy.”
The Hidden Story of Multi-Touch Attribution
I know the power of multi-touch attribution (MTA) better than most. I built Galileo to solve a problem that’s plagued marketers for years—understanding how various channels contribute to conversions. But as Dr. Southekal and I both know, even the best MTA model can’t function if the data feeding into it isn’t clean.
“MTA is brilliant,” Dr. Southekal says. “It’s one of the most powerful tools marketers have today. But it’s also fragile. If the data isn’t high quality, you’re going to get skewed or biased results. You’ll end up over-crediting certain channels and undervaluing others.”
He’s seen it happen, as have I. A company might be spending millions on paid advertising because the raw data tells them it’s the best performer. But what if the data is incomplete? What if organic search is driving the initial engagement, or if another offline interaction is the key factor to revenue – but those are not being captured?
Dr. Southekal looks at me knowingly. “Without clean data, you’re misallocating your budget. You think you know where the value is coming from, but you’re just following a distorted map.”
He’s right, of course. We’ve both worked with companies that have realized, too late, that they’ve been funneling money into the wrong channels because they trusted dirty data.
The Importance of Data Governance and Cleaning
This is why data governance matters so much. Dr. Southekal has been preaching this for years, and it’s one of the most important lessons I’ve learned from him. “You need a strong data governance framework,” he says, “to ensure that your data is accurate, consistent, and reliable across all departments.”
Data governance isn’t sexy—it doesn’t grab headlines like a viral campaign or a new social media strategy—but it’s the foundation that makes everything else possible. “If you don’t have a process for cleaning and validating your data,” he says, “you’re setting yourself up for failure.”
I think back to the early days of Galileo, when I was working through some of these very challenges. It wasn’t enough to build a platform that could track customer journeys across multiple touchpoints; we had to make sure the data coming in was pristine. I’ve spent countless hours ensuring that the data feeding our platform met the standards Dr. Southekal laid out. Without clean data, the platform wouldn’t be able to tell the full story.
The Tale of the Retailer Who Got It Right (Eventually)
Dr. Southekal tells me a story that feels all too familiar. He worked with a retailer that relied heavily on last-click attribution. Their data told them paid search was driving the bulk of their conversions, so naturally, they poured more money into that channel.
But when they switched to MTA, things didn’t improve right away. “Their data was a mess,” he says, shaking his head. “Duplicate profiles, missing touchpoints—it was a disaster. Their model was giving them bad insights because their data wasn’t clean.”
But this is where Dr. Southekal’s expertise in data quality really shone. He worked with them to implement a robust data governance framework, cleaning up their data and filling in the gaps. Only then did they realize the full customer journey. Social media was driving awareness, email was nurturing leads, and paid search was simply closing the sale.
“Once they cleaned up their data and implemented MTA correctly, their whole marketing strategy changed,” he says. “And within six months, they saw a 31% increase in ROI.”
It’s a familiar story to me—one I’ve seen play out with other clients. The lesson is clear: data quality isn’t just a technical detail. It’s the secret weapon behind every successful marketing campaign.
The Future of Data-Driven Marketing
Looking forward, I ask Dr. Southekal about the future of data in marketing. He reflects for a moment before answering.
“Data isn’t going anywhere,” he says. “If anything, it’s becoming more important. But as the amount of data grows, so does the need for data quality. The companies that invest in data governance, cleaning, and validation will be the ones that thrive in the future.”
It’s the prevailing concept I hear today. After decades in marketing, and years working with multi-touch attribution, I’ve learned that it’s not enough to have data. You need to have the right data—clean, accurate, and complete. Only then can you truly understand the customer journey and make data-driven decisions that lead to success.
As we finish our conversation, I leave with a renewed appreciation for the work Dr. Southekal has done, and for the critical role that data quality plays in marketing today. If there’s one thing I’ve learned from him, it’s this: great data is the invisible force behind every successful campaign.
