A Day in the Life of a Data & Analytics Product Manager

As a primer, I am a Senior Product Manager currently working at an agency, so my day involves working with several different clients and helping them with their data and analytics issues. As a Product Manager, I get a lot of questions around what a typical day looks like. I also field a lot of questions from folks wanting to get into Data and Analytics as a Product Manager in particular as to what it means to be a Product Manager in this space. Naturally, this is my experience and this is not meant to speak for all.

Depending on the day, I do anything from managing the implementation plan of a new analytics tool, helping clients building meaningful analytics Dashboards that they can use on a day-to-day, training clients on growth processes like A/B testing or talking to potential new clients about what we offer and how we might help them solve their data problems. I work in an arm of the business that is primarily in the Product Analytics and Product Growth space, so most if not all of the clients are looking for help with Analytics and Growth specifically. This is meant to be one experience in Product Management, but is certainly not meant to account for everyone’s experience. I love what I do, and am happy to work with so many different clients with pretty exciting problems to solve. So, here is a walkthrough of a day in the life of a Senior Product Manager in Data and Analytics.

7:30 am

I get up and have coffee and check my emails, follow up on anything I can right away and write down what I need to do some digging on. I also like to write down a list of my daily to-dos and start my day slowly by either watching an episode of something or meditating. Usually, I am drinking coffee and hanging with my partner who gets home from work late. So, I get a few tasks done before she gets up and then I chill with her for a bit.

9 am

My first meeting is presenting to a group of partners and stakeholders about our overarching product growth & data analytics practice and how it might dovetail to their businesses with the goal of enabling them to dig a bit deeper in their engagements. This is the third meeting like this and my colleague and I have spent a week or two prepping the deck so we are already well-versed in how to deliver it. We end up having a lively discussion.

9:30 am

I am on an email thread with an IoT Client to get me access to JIRA so I can QA their data and going back and forth to make sure I can access the tickets I need. I respond async while listening to the rest of the meeting. The thread ends with a list of tickets they want me to QA, so I write it on my to-do list.

10:00 am

After my first meeting, I continue building analytics dashboards for an arts based product on the events we recently implemented and realize a few events haven’t been triggered yet so I message them so they can trigger events on their end. Once they have confirmed they will trigger the events, I write it on my to-do list to circle back and finish the Dashboard.

10:45 am

I get an ask to add more numbers from a past engagement to a deck my colleague and I have been using as the base for conversations with potential clients. I am able to locate the documentation easily so I keep the tab open and plan to go back to it once I have a minute.

11:00 am

I attend a webinar for a customer data platform about a brand new product they are launching and take notes to send to people who had to miss the meeting and also to reference with clients who are currently using the platform. I order lunch while watching the webinar. During the webinar, I get a message from a coworker looking for some help with a data problem, so I look over the chart they made and start a conversation asynchronously helping them through how to best serve up the data to their client.

12:00 pm

I have a meeting with my IoT client to go over some issues with their data. There was an issue with access keys, so we dig into the code while screensharing and we cross reference so we can get the issue sorted. I also spend a good portion of the meeting fielding some questions about their data and how to connect certain user behaviours to each other. I leave the meeting with a few asks including creating new projects for the tools and following up with a few folks about next steps.

1:00 pm

I jump into an exploratory call with a potential client and we talk in depth about their data needs, our offerings and how we might be able to help them. I leave the meeting with a few asks around coming up with a solid 6–8 week plan based on the client needs so we can formalize the engagement and get the ball rolling. The client seems to be excited about working with us, so I want to get this done sooner rather than later.

2:00 pm

I have some time before my next meeting so I build out my first pass at the 6–8 week plan utilizing materials I have already created, so this doesn’t take too long. I also chose to do this while the conversation is still fresh so I can make sure to retain the nuances of the conversation. I send it off to a colleague so he can look it over and we can work on it async.

2:30 pm

I revisit the documentation from the numbers ask earlier and the day and create a slide to tell a story based on the numbers. I spend time going into the original chart to make sure the numbers line up with the metric I documented previously. I also copy the link to include in the slide for reference. I make a note to myself to double check it tomorrow so I can make sure it looks good before I send off. Also, I want to make sure that if the ask comes in sooner, I can prioritize sending it off easily while also being confident in the numbers.

2:50 pm

I look over a slide deck created for an elearning client ahead of a meeting coming up at 3 and make sure that everything is clear and I can easily recall all of the necessary details ahead of presenting them to the client.

3:00 pm

I have a client meeting with an elearning client where I am presenting the findings of a recent audit. I present and lead discussion around what we found, the results of our gap analysis and we facilitate a discussion of next steps. The clients express that they are pleased with the results and I am feeling good about the work we put into the deck and the engagement.

4:00 pm

I circle back to the Dashboards I was making for the arts based client at 10am and update it based on the data that was triggered by the client in the morning. I reference the questions the client had requested be answered by the data and make sure all of the charts line up. Since we have previously done the work to name events with these questions in mind, this task is straightforward.

4:30 pm

A part of my job is leveling up other product managers around product growth and analytics engagements, so I meet with a colleague and they go through some of their challenges on the project and I walk them through possible solutions as well as send them templates to help guide their work.

5:00 pm

I start QA’ing the list of tickets my IoT client has given me. This requires looking at the event names, property names, etc. and making sure that I can see the data firing properly in their analytics tool. From there, I tag the client in the tickets with any issues.

5:45 pm

I have finished QAing the initial tickets. I check my to-do list and rate each item in terms of priority — in this case, any remaining tasks can wait until tomorrow.

6:15 pm

I close my computer for the night.

There you have it, a day in the life. One thing I want to note is that I typically work with 2–3 clients at a time and do other oversight work on the side, which I recognize is not the same experience for folks who work on a single product or within a single company. Personally, I enjoy the variety as well as being able to use past experience to solve current client problems — it feels rewarding to offer value right out the gate simply by utilizing experience. I am always open to talking more about this, so feel free to comment or asks questions etc.

Data and Analytics Strategist and Consultant. Product Manager at TWG

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