Curious what a data product manager does on a daily basis? Sweet! I’ve been managing data products since 2012, and in this vid I’m gonna show you the 3 types of work I do on a daily basis.

Be sure to read to the end because that’s where I am going to show you a cool hack for how you can create a rockin’ company-themed data product manager CV that is sure to get you a call back.

YouTube URL: https://youtu.be/5T1MZls8fIo

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As far as why I’m qualified to give advice on managing data products, like I said – I’ve been managing data products since 2012. I have built and managed data science products that have served over 1.3 million data professionals so far. And, I’m actively managing 3 data products right now and I’m bringing them to launch.

If you’re new around here… Hi, I’m Lillian Pierson and I support data professionals in becoming world-class data leaders and entrepreneurs.

What Is A Data Product Manager?

The easiest way to explain this is to show you this Venn diagram.

what does a product manager do

The data product manager is really a hybrid between a product manager and a product data scientist. This means there’s a good bit of data product management; however, there’s also a good bit of data science product management.

Generally, data is the product – either data resources or data expertise. You then use data science and data analytics to actually manage and improve the product overtime.

Caveat: I own a small business so have been running my business for almost a decade. And all of the products that I’m managing are either owned by my company or by a client.

This matters mostly in terms of what I’ve seen with respect to teams and in how much time traditional data product managers spend in meetings and in communications with teams. And because I own my own business and I work remotely, we don’t have meetings in my business, which I like!

What Do Data Product Managers Do?

I’ve broken the work down into three main categories:

  1. Metrics & Strategy
  2. Launch
  3. Products

The metrics inform the strategy, and the strategy drives a growth in both product and product launch.

Below is a pretty extensive mind map which I created that plots out each of the aspects of these three main categories of work. But it’s a little bit more complicated because my business goes in season, so the requirements around these categories shift according to the seasons of our business.

I’m going to break down for you what I’m working on on a daily basis.


I’d love to hear from you! In the comments, tell me a little bit about what you do on a daily basis as data professionals.


What Do I Do As A Data Product Manager?

Looking at what I actually do on a daily basis as a data product manager, it depends on the stage in the life cycle my products are at.

1. Work Breakdown by Product

In this type of work allocation, we are updating our course Python for Data Science, central training, one and two that are owned by LinkedIn Learning and I’m the instructor. That’s an information data product that requires data science expertise in order to create it. I used to do everything associated with developing that course and built it from scratch all by myself.

But at this point, my business has grown to the point that I’m not able to do all the implementation work myself and run the business which I learned this year while rewriting Data Science for Dummies – the second product that I’m managing.

Allocating time for each product

Data Science for Dummies is owned by Wiley and I rewrote it a second time since 2014. It’s done and we are in the launch phase and I hired a launch manager that’s why he takes 5%.

The reason why Python for Data Science is taking 5% of my time is because I hired a data scientist to come in and help me with building out the curriculum and it’s an active development. I had to minimize the amount of time I spent there so I could focus on the Data Creatives & Co. course which is not a data problem. Python for Data Science is a data product as well as the Data Science for Dummies.

Data Creatives & Co. is a course that helps data professionals, supports them to hitting six figures in the first 12 months of their own data business. It’s data intensive but it’s more of a course designed for data professionals to help them with the business. I am spending 90% of my time on that right now – it’s already developed and we’re in the launch phase.

The reason why I didn’t spend much time on Python for Data Science is that I spent the whole year rewriting Data Science for Dummies which required me to actually write it.

Python for Data Science is client work so I have delegated a lot of the work to another data scientist so I can focus on my main revenue generator for my business, the Data Creatives & Co., which is my signature course since it’s owned by my company.

What I work on a daily basis changes according to the seasons of my business and I’m just going to cover two.

2. Work Breakdown by Sales + Leads Season

I’m spending about 40% of my time in launch efforts –  managing the launch and planning the launch. 20% of my time in managing my team, and 15% of my time doing product planning and development.

All of the decisions in my business are governed by data analytics and insights. That’s why beyond data products, I’m using data analytics and making data-informed decisions in all aspects of the product management.

I spend about 5% of my time generating customer feedback and speaking to customers and just getting ideas for how I can improve my products to make them even better, and understand who my customers are and what their needs are.

If you own your business, it’s definitely important to know your customers and keep improving your product on an iterative basis.

Lastly, because I’m an entrepreneur, the other 20% is allocated to “other”.

3. Work Breakdown by Visibility + Nurture Season

When I’m in visibility and nurture season, things are dramatically different. 

We spend about 30% of my time on actual product development and 20% in managing my team.

The 15% is spent on working on the delivery systems for products or delivering services (which is not a product management role). And because the goal of the business during the season is visibility and nurture,  I spend 10% of my time doing collaboration – doing podcast or live events or guest posting.

The 5% then is spent for customer feedback – just speaking with customers and looking for ways to create new products or improve the products I have.

Lastly, 20% is for the “other” – just for running my business.


If you like this post on What a Data Product Manager does on a Daily Basis,  then you’ll probably want to check out the video I did on creating the perfect Data Product Manager Resume.


3 Types Of Data Product Management Work I Do On A (Near) Daily Basis

As you recall, we have broken down the type of work that data product managers do into three categories:

1. Metrics and Strategy

In this part, I’m mostly responsible for all the metrics and strategy. My team only collects the data I use on a weekly basis and I use that in order to inform strategies moving forward. Also, I have a collection of tools that I use to provide analytics so we know what is working and what’s not working.

Metrics Tracking and Analytics

Once a week I pop in and look at our metrics and analytics. A lot of them are basically leads in sales for the business – like in what marketing channels are producing leads and sales and why and which ones are not performing well and why.

Finance

I also look at finance. I have a team member collecting the data. I’ve got tools and I also got another team member who is doing finance.

Competitive Analysis

I look at all of these metrics and analytics on Tuesday of every week and then I’m continually doing competitive analysis just because we’re always in the process of developing something – whether it be content or products or programs or services that are bringing leads and sales to the business.

I’ve got a variety of tools that I use to basically get information even about partnerships. I use data to inform and make sure I’m making a good decision on everything that I’m in charge of with my business.

A/B Testing

I also do A/B testing on sales pages and my team also does A/B testing for me in email tools. Our A/B testing is facilitated by a variety of tools we have.

Market Research

I also always do market research – that’s very similar to competitive analysis but somewhat different. I have tools to do this so there’s no need to collect the data raw because tools are there to provide those answers for you.

Strategy Development

Lastly, I do strategy development. So by mostly looking at metrics and analytics on a weekly basis, then I update our strategy to be more of what’s working and less of what’s not working and also to do testing to gain traction in new markets or new channels.

In the image, they’re mostly orange and that indicates that these are mostly all data aspects of the role. Strategy development is more like product management.

2. Launch

Launch work is a pretty important part of product management and having a business. We are aiming for two or three launches per year.

Requirements Planning

I do the requirements planning and then I hand things off to my team in terms of launch marketing.

Marketing

We have copywriters and content managers. The subject matter expertise for data and the entrepreneurship expertise comes from me.

I create a source content and then hand it off to my team for formatting, repurposing, and preparing it the way that it needs to be consumed along our channels and also posting it. 

Conversion Medium

Conversion medium would be for launch assets – my launch opt-in, my sales pages, forms and funnels – and I and my team work on this one. It just depends on how much time I have, how many things I’m doing.

Events

For the events, that’s all me because I’m the business owner so I need to show up and show my face.

Data Collection

Data collection is done by the team but they collect the data and then I see how things performed in terms of conversion, open rates, sales, and leads. I then can make improvements in the next launch cycle.

3. Product

Product is the last category of work. Right now, we’ve already covered what products we are actively working on.

Just for this discussion, these products are not new and we’re in version three or higher for all of my products. We’re more in the improvement mode rather than like raw development mode.

Validation

The first thing to do is always validating your product. This is more of a data aspect than a product management task. Validation requires metric analysis and then ultimately sales. It’s looking at conversion rates and stuff, so that’s more data.

Product requirements

Because it’s my business, it’s my vision for the products and then the requirements come from me. But that’s more traditional product management design.

Design

I do not do my own design. I can do some design but I have a Professional Designer and a Web developer. My designer creates the aesthetic, the brand, the colors, the fonts, the layouts. The designer sets it up all for me so I can just replicate what she’s doing if I need to design something. I don’t design because I’m not a designer and I have a web developer that helps implement the tech stuff on the backend. I coordinate with my team – I just tell, for example the designer, what I like and what I don’t like. All the templates and base assets need to be done professionally by a designer. And then my team can use them to populate and create products out of the template.

Testing

I test my products and my team also tests them. In our case, we already have users because this is version three so we get feedback from them on a continual basis and that equals data which we then cycle back through to make improvements to the products on the next round.

Improvements

The majority of my products are data products, data science, information products. Then the improvements in the development work are done by data scientists and that’s me, and I have another data scientist working with me at this point to help me with some things. For my business, mentorship and curriculum – that’s 100% me!

We have a group where I’m bringing in a data scientist because I don’t have enough time to work on all of my data. All of my products and data science are easier to find out than for stuff actually coming straight from my brain and that’s entrepreneurship.

Part 5

Congratulations on making it to the end, because now I’m going to share with you how you can make a company-themed data product manager resume in under 15-minutes…. I talk about this over in the video on the data product manager resume, but basically I created a FREE data product manager template for you over in Canva, so you can just go in and add your details and then change out the colors and fonts so that your resume is branded for the company you’re applying to.

If you want me to do all the heavy-lifting for you, you can get my evergreen analytics strategy framework, that also comes complete with the 44 sequential steps you’ll want to take within that framework in order to build a completely fool-proof data strategy plan for your company. It’s called Data Strategy Action Plan.

Also, I have a free Facebook Group called Becoming World-Class Data Leaders and Entrepreneurs. I’d love to get to know you inside there, if you’d like to apply to join here.

Comment what topic you want me to create a video on next what interests you most about the data product manager role.

Hey, and if you liked this post, I’d really appreciate it if you’d share the love with your peers by sharing it on your favorite social network by clicking on one of the share buttons below! 

 

NOTE: This blog post contains affiliate links that allow you to find the items mentioned in this video and support the channel at no cost to you. While this channel may earn minimal sums when the viewer uses the links, the viewer is in NO WAY obligated to use these links. Thank you for your support!

Lillian Pierson, P.E.

Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she’s helped educate over 1.3 million data professionals on AI and data science. Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She’s supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between. She is a licensed Professional Engineer, in good standing. She’s been a technical consultant since 2007 and a data business mentor since 2018. She occasionally volunteers her expertise in global summits and forums on data privacy and ethics.

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