Should You Be Data-driven, Data-informed, or Data-inspired

Welcome, Introductions & Webinar Setup

Rina Alexin | 00:00:00–00:02:30

Hello everyone, welcome and good morning. Thank you so much for joining us today. Today we’ll be covering another installation in our Product Management Leadership Series. We’ll be discussing whether you should be data-driven, data-informed, or data-inspired.

My name is Rina Alexin and I’m the CEO of Productside. I’ve been leading the company now for the past four years, bringing transformational change to product management teams everywhere. And nowadays, you really can’t emphasize enough the importance of using data to drive insights and decisions. That is why we created the curriculum for Digital Product Management that’s been recently available in a go-at-your-own-pace self-study version. This course goes deep into the topic of data, which we’ll be discussing today.

And I’m so, so excited to be introducing our very own Todd Blaquiere. Todd is a Principal Consultant and Trainer with us at Productside. He has deep expertise in creating product and marketing strategies for companies ranging from startup to enterprise across engineering, media, publishing, life sciences, and the nonprofit sectors. Todd attributes his greatest technology successes to his ability to connect with peers, users, and stakeholders as real partners. He also makes it his personal mission to make product work fun for everyone — which I can personally attest to — though Todd, I’m not here for jokes. Thank you so much for being here with us today, Todd.

Before we get into it, I’d like to first go over a few housekeeping items. After this webinar, continue to stay engaged with the product management community. Consider joining our LinkedIn leadership group, where you can use it as a forum to share best practices and tips with your peers. We’ll be pasting a URL into the chat box shortly.

At Productside, of course, we love interacting with you. And during this webinar, we really encourage you to ask questions. You can use the Q&A box on the bottom of your screen to type in questions at any time. We will be leaving time for Q&A at the end of the webinar, and Todd, with your permission, I’ll even bring a few of those questions while we’re live.

Our most popular question is: “Can we watch this webinar later?” And the answer is yes. All attendees will be receiving a link to the webinar recording after it has ended.

Our agenda for today: First, I’ll be covering a little bit about Productside, and Todd will take it from there to tell you some stories about data, define some data archetypes, and teach you not only how to leverage each of these methods but how to also mitigate bias and use those methods effectively.

About Productside & Digital Product Management Course

Rina Alexin | 00:02:30–00:05:00

So Productside — our mission is pretty clear. We are on a mission to empower product professionals with the knowledge and tools to build products that matter. And what makes us different is that we’re focused on the needs of product professionals everywhere. Whether you need help as an individual looking to grow your career, your knowledge and skills, or you’re a product leader working on improving your team’s effectiveness, we have the expertise and the services that will get you to the next level.

Feel free to check us out at Productside.com. And of course, as I already mentioned, one of our flagship courses — the Digital Product Management course — is available both in our virtual and our self-study go-at-your-own-pace versions. We’ve pasted a URL into the chat to look us up.

Audience Poll: How Do You Use Data Today?

Rina Alexin | 00:05:00–00:07:00

And now we’re going to get into it. So I think we get to start as we usually do with a poll. Can we please launch the poll right now?

Great. So if you can answer — and honestly, I almost wish this was a “select all” because I’m sure in any given day this answer for you might change — but if you can think about what you mostly do when you are using data in your decision-making… right, Todd?

Todd Blaquiere: Absolutely. I love to use my intuition — and I need data, right? Sometimes I don’t have it.

Rina: Yeah. So I guess it’s a little bit of an unfair statement here, but based on the poll results — and it’s no surprise — most people sometimes use data when it’s appropriate. There are a few that have trusted their intuition, and there are even some that say they don’t know how to use data or don’t collect it at all. That’s all right. Wherever you’re starting today, this webinar will share some great tips and best practices for you to start using data more effectively in your career.

Stories: Data-driven Dan, Data-informed Inga, Data-inspired Imogen

Todd Blaquiere | 00:07:00–00:13:00

I love it. And we’re going to start off with some stories. We’ll dig deep into how we’re using data, as Rina said, and some different ways to make sure we’re using data the right way. But I love stories — I think everybody loves a good story — and as product managers we have to be good storytellers. So let me take you through some stories that help illustrate what we’re going to talk about today.

I’m going to introduce you to three people from my career. The first one is Data-driven Dan. Dan loves to make decisions using data. He loves data. He loves to find the thing that is objective. He wants to find — if possible — a silver-bullet piece of data. He’s really fascinated with artificial intelligence and machine learning because he loves the idea that you can get data down to a number that can make a decision, because he believes numbers don’t lie. He believes facts speak for themselves.

I worked with Dan when I was at Tribune Publishing. Tribune Publishing — if you don’t know — is the group that has many publications underneath it including the LA Times, the Chicago Tribune, New York Daily News, Orlando Sentinel, and many more. And Dan’s role was to create videos and add those videos to stories across the Tribune network. So he had to know which stories were performing well, which were interesting, and which ones had a high view velocity — so, trending stories — so he could create a video and attach it to those stories.

Dan was really successful. He was able to drastically increase video consumption and video ad revenue. And the way he did this was by using a dashboard. He had a dashboard that showed him what the most popular stories were and those that were trending upward. So he used data — the data made the decision for him. Whatever the dashboard said: that’s what he did.

Rina: And Todd, wouldn’t you say Dan was working with a very well-defined problem?

Todd: Yeah — so his objective was very clear. And so he could leverage data because the data was telling enough of the story for him to make that decision. Very clear objective and very clear KPIs.

Now this is Inga — Data-informed Inga. She loves using data to make decisions. In fact, she can never have enough data. She likes both qualitative and quantitative data. She wants user observation; she wants interviews; she wants dashboard metrics; she wants product KPIs; she loves learning from experience. And she believes her superpower is combining her experience with data to find the best answers.

I worked with Inga at IQVIA. She needed to improve a user experience and tighten a funnel for one of the software products. So she interviewed users, created prototypes, ran surveys, and she relied on her background in design heuristics. And she was successful — she developed a new UX that delighted users and improved frequency and funnel completion.

And finally: Data-inspired Imogen. She loves data when it’s available, but doesn’t always have it. I worked with her at a nonprofit called Fight the New Drug. She’s an intuitive thinker and wants to challenge the status quo.

She had to come up with a new way to promote a product designed to inspire people to overcome challenges. She brainstormed with her team, had some data showing teens love video, but she was also a rock climber. So she created a video of a climber conquering a mountain as a metaphor. And it worked — it created tons of buzz.

So what do these three people have in common? They all found success. But — and Rina pointed this out — they all iterated. Even the data-inspired person didn’t make one decision and stop. They had to test their way forward.

What Is “Data”? Qualitative vs Quantitative

Todd Blaquiere | 00:13:00–00:15:30

So now, what is “data”? Just very quickly — qualitative data describes. It’s gathered through observation, recorded in words: empathy interviews, shadowing, focus groups, spot-leader articles.

Quantitative data counts. It’s numerical: surveys, statistics, product metrics, financial records.

Rina: And Todd — there are ways to code qualitative data so it becomes more quantitative. There’s a whole process around that. And if anyone wants to learn more, reach out to us and we can point you to a webinar where we cover coding qualitative data into measurable themes.

Defining Data-driven, Data-informed & Data-inspired

Todd Blaquiere | 00:15:30–00:20:00

Let’s define each archetype. First: data-driven. The data tells you where to go. You follow it. In a data-driven approach, the data itself makes the decision. My metaphor: a GPS. It tells you to turn left — you turn left.

Data-informed means data helps you make the decision, but you still make the call. You weigh your experience, your context, your intuition alongside the data.

Data-inspired means you may have little to no data and must rely on intuition, creativity, or proxy data. You don’t always know where you intend to end up. The goal is discovery.

Rina: And the key here is that innovation often requires a data-inspired approach — like Ford. If he asked people what they wanted, they’d say “a faster horse.”

Pros & Cons of Each Approach

Todd Blaquiere | 00:20:00–00:24:00

Data-driven: Pros — fast, certain, scalable. Cons — rigid, myopic, prone to bias if data is incomplete or flawed.

Data-informed: Pros — holistic, contextual, creative. Cons — complex, time-consuming, uncertain, can lead to analysis paralysis.

Data-inspired: Pros — innovative, freeing, collaborative, good for blue-sky ideation. Cons — directionless, fuzzy, hard to articulate rationale, highly bias-prone.

Cognitive Biases & How They Sneak Into Our Decisions

Todd Blaquiere | 00:24:00–00:29:00

Humans can be irrational — and bias shows up everywhere.

Confirmation bias: We trust data that supports our belief and reject data that challenges it.

Recency bias: We overvalue the latest data — like when a salesperson tells you “This feature will close the deal!”

Authority bias: The hippo — highest-paid person’s opinion — dominates.

Anchoring bias: Jumping to conclusions too early based on early feedback.

Survivorship bias: Looking only at successful cases and ignoring failures.

Rina: And remember — our brains are wired for shortcuts. Biases aren’t going away. We manage them by becoming aware of them.

Mitigating Bias & Balancing Outcomes, Buy-in, and Constraints

Todd Blaquiere | 00:29:00–00:33:00

To mitigate bias:

• Seek opposing data.
• Retain older feedback.
• Treat the hippo’s opinion as a hypothesis.
• Slow down — avoid anchoring.
• Look at pessimistic data, not just optimistic data.

As product managers, we balance outcomes, buy-in, and constraints: time, resources, and data availability. The goal is to make optimal decisions efficiently while gaining alignment.

Choosing the Right Archetype & Picking KPIs

Todd Blaquiere | 00:33:00–00:38:00

Choose the archetype by evaluating:

• Your desired outcomes
• Your constraints: time, resources, data
• Your frequency of decision-making
• Your experience level

Then choose KPIs. Usage is not a metric — user engagement is. Six key dimensions:

• Depth — which features they use
• Breadth — number of active users
• Frequency — how often they use it
• Paths — what steps they take
• Sentiment — how they feel
• Feedback — real-time insights

Rina: And leadership is motivated by real stories. Bring them the story of what’s happening to users when the product isn’t working as intended.

Q&A: Career Positioning, Scaling Data & Internal Products

Rina Alexin & Todd Blaquiere | 00:38:00–00:43:00

Rina: All right — let’s take questions.

Q: “How do I describe being data-driven on my resume?”

Todd: Don’t just say “data-driven.” Describe what you achieved with data. Tell stories. Show outcomes.

Rina: Yes — show business impact or key learnings. That’s what stands out.

Q: “How do you scale data gathering?”

Todd: You often need less data than you think. You don’t need 20 interviews — five to seven often reveals themes.

Rina: And there are ways to automate scraping and coding, but clean data always takes effort.

Q: “Internal product: usage is high, but users aren’t using it as intended. Leadership thinks it’s successful.”

Todd: Classic vanity metric problem. You need user observation and data on outcomes — not just usage.

Rina: And get leadership thinking about the long-term view. Today’s success won’t get them where they want to be in three years.

Upcoming Courses, Webinars & Closing

Rina Alexin | 00:43:00–00:45:00

If you’re interested in learning more, our Digital Product Management course is available both live and self-study. There’s a coupon code for $500 off as a thank you for attending.

We also have upcoming webinars — including our International Women’s Day AMA and “Modern Budgeting for Today’s PM World.” Links are in the chat.

Thank you all so much for joining us. Todd — great presentation. I learned about Charlie balls, so I hope everyone else learned something valuable today.

Todd: Thank you everyone!

End of webinar.