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Expert Insight: Brian Balfour - Learn Your Domain and Differentiate Yourself
An insightful look into the world of data analysis and what makes a great team in this interview with a product expert.
If you are working in the fields of tech products, marketing, data, design, and engineering you probably know about Reforge. As someone who has been working with product growth methodologies for many years, I can’t highlight enough how important and useful Reforge frameworks are for deep dives, guides to help you improve retention, running experimentation, or monetization. If you have been reading my journal over the last few months, you might have noticed I often highlight Regorge concepts and insights in my newsletters (Benchmark traps, Adjacent user, the Word of Mouth Coefficient).
I am so honored and excited to reach Brian to interview him for my journal and get his view on what common challenges data analysts are dealing with and how to navigate through them to develop your career.
1. What qualities must a good data analyst have?
Different companies put various meanings for this role - data analyst, product analyst, data scientist, and they often overall. A couple of qualities set apart from the average ones:
The ability to explain and communicate a function, how to put data into a story. How do you communicate something you spent so many hours, years in your career to someone who doesn't know much?
Don't take a question or a request on a surface, but discover, shape, and define real problems.
Ability to merge product, market, or other knowledge with their day to day work. Upfront problem discovery.
And of course, everything else is very important - technical skills, must have curiosity.
2. What are some common mistakes that you notice data analysts sometimes make?
First, understand the project. What is the decision you are trying to make, and what is the impact of this decision? Is it small or medium? I often see over analysing, under analysing.
Your job as an individual contributor is to go out and gain the information you need to do your job - get the right insight, knowledge. If you feel you are not included in the discussions, you have to earn it. And, the way you earn your way into those conversations is by showing the ability to ask the right questions, provide the right insights, understand the context, connecting all pieces together, etc. Strong communication is very important. Be connected with other teams, because you can’t know every little piece of information or knowledge.
... and for that, you have to develop partnerships and work with multiple stakeholders or teams to access the right information.
I think the best organizational structure (or the hub), once you get to the right size, should follow a hybrid model where there is a centralized data team that is managing infrastructure, systems, applications, and then there is some form of an analyst sitting on a cross-functional product or marketing team. You can do it when (1) a company is at a certain stage and (2) they actually take data seriously enough to invest in it. It is still a rare thing these days... Most organizations do not have that. They are either running a very small centralized model, or there is an analyst sitting on a random team.
Ideally, you are part of a truly cross-functional team working alongside product managers, engineers, designers, and not an order taker when a question or request comes up.
3. I think a Product Analyst is the most challenging role. It lives at the intersection between product, growth, and marketing. There are high expectations for analysts to comfortably navigate between all these domains and know their metrics and specifics and have enough statistical knowledge to back up their testing, monitoring, analysis, and insights. How can someone navigate all of this and not get lost?
These expectations are high for marketing or product managers as well. PMs need to know all the core products managing stuff, growth, datasets. This is a common problem across all functions.
In a sense, PMs and Data Analysts are two probably the least specialized functions. If you are looking at Design, for example, designers went through this wave of specialization. There are now Product Designers, UX, UI, Content Designers, Strategist, Brand Designer, etc... And, there is only one type of Product Manager. There is now a growing specialization around Growth PM, for example. It seems like there is a little that specialization going on for Product Analyst, and maybe some others as well. My hypothesis is that these functions will grow over time.
I think it also sets a trap you are getting into when people feel like they have to be experts at everything. It will take a lifetime for you to learn everything. It’s an impossible task. My encouragement would be to pick a path:
Try to find a way to make it specialized in one area - Marketing Analyst, Growth Analyst, Financial Analyst, and understand the analyst function from that perspective and that domain. The depth you build there for your career will push you into a much more interesting position.
Many people pick a generalist side and do a little bit of each. The problem with that is it’s difficult to go deep, and as a result, you end up looking like all other analysts. Career management is Economics 101 - supply-demand. How would you put yourself in a situation where you are very low supply, and there is very large demand. And that’s how you get the roles and the job opportunities faster than others do.
It’s like a product strategy - how you differentiate yourself. The fastest way to differentiate yourself in your career is to go very deep. This is common advice I give to not just this function, but others as well.
4. What values do you try to foster within your team?
I’ll answer your question in a slightly different way. I read a lot of these blog posts about the XYZ values and principles a team should have. I think over time what I learned throughout my career is that values and principles are meaningless unless they are specific to your team, product, and mission.
A good example of this is the story from Fareed Mosavat (a Reforge EIR and was formerly a Director of Product at Slack). Many growth teams used to move and iterate very fast, building tons of Minimum Viable tests, and launching them in an extremely scrappy phase. At Slack, one of the core principles was Craftsmanship. It helped the company become successful in the early days. Fareed developed a principle on his team that merged the concept of Learning Fast with Craftsmanship. The tradeoff was that the tests they run had high design fidelity, which means that they would run fewer tests by putting more work into user research. This is an example of taking something that is important and molding it in the right situation.
Just copying and pasting generic values from another company isn’t going to work. You can use them as good inspiration points, but you really need to answer questions like who is your target audience, what is your differentiating strategy, what are the core behaviors, and things we need to do inside our company to achieve and execute that strategy. By the end of the day, if you make them more unique, they will mean more to you and your team.
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