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Design a product for drivers driving in rush hour. I am betting every human stuck in traffic has once thought... “Dang this traffic sucks, I wish I could [insert idea].” The best answer I’ve heard is a tablet-sized visual, that is connected to the internet with key apps such as email, song playlist, podcasts, call functionality; along with the capability for partial self-driving in traffic. Once in rush-hour it kicks in, frees your attention to do other things, improves health of the driver by reducing both physical and psychological strain of commuting in rush hours and is highly scalable to autonomous-capable vehicles. I liked the answer because I’d buy this product 🤪 but also because the answer was (1) optimized for reducing real pain points (2) accounted for the future of driving (3) was a little wild, but not too out there. When I heard this answer I could tell the PM was both imaginative but grounded in solving real problems.
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Yasmin Kothari
Peloton Senior Director of Product Management • May 17
Customer feedback is critical to how we build, and we incorporate it at every step of the product development process. We get customer feedback from a variety of places. When building new products we proactively reach out to customers to learn about their needs and make sure we’re creating the right solutions for them. We have a User Research team that regularly speaks to customers via a variety of methods - everything from interviews and surveys to card sorting and field studies. Along our product development process, we have specific touchpoints where we make sure to utilize user research to get deep insight into the pain points our customers face, and the best solutions to help them. Our customer-facing teams, like sales and customer success, are also talking to customers constantly as part of their daily jobs. These teams rigorously record all of the feedback they hear and compile it into a ranked Voice of the Customer (VOC) list, all managed within Asana. Asana’s VOC program is a critical input into our roadmap process, and helps us prioritize the most pressing needs brought up by customers.
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Tamar Hadar
The Knot Worldwide Senior Director of Product | Formerly Trello (Atlassian) • February 2
As a first PM, you will need to be very judicious with how you allocate your time and resources. In fact, I think that’s true for larger companies as well. There are always going to be more ideas than resources available. As a product manager, you are responsible for translating the company’s vision into a roadmap so your first priority should be internalizing the company’s goals. Is it to drive sign-ups? Increase retention? Increase MRR? Or something else altogether? Narrowing in on that top goal helps to weed out work that may be less relevant. Once you’ve identified the top goal (there may be more than one), filter out any initiatives that do not map to this goal. The exceptions being pressing engineering initiatives (i.e. a platform upgrade, reducing technical debt etc.) or time-sensitive projects. Hopefully, you’ve been able to narrow down your list through this process of elimination. This is where a prioritization framework will come in handy. My go-to is the impact/effort matrix. It is very similar to ICE and RICE but simpler and more visual. For each initiative, assign an estimated impact to a measurable goal and a level of effort. Make sure to collaborate with your engineering and design counterparts when evaluating each initiative. This will reduce the chance of your own bias getting in the way and lead to better prioritization. For those initiatives left on the cutting room floor, think of a way you could still make some progress—is there an MVP you could run to learn something while the teams are working on the selected initiatives? There might be a low-cost way to validate assumptions via user research or data deep dive so that by the time you go through this exercise again, you are able to make a more informed decision.
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Mani Fazeli
Shopify Director of Product • December 14
Let's cover this in two ways: (1) how to think about KPIs, (2) examples of poor ones and how they can be better. I'll also approach the question a little more broadly than Product Managers alone. Remember that Key Performance Indicators (KPIs) are used at all levels of a company (e.g. project, team, group, division, exec team) with different levels of fidelity and lag (e.g. daily active user vs. quarterly revenue). The appropriateness of standard KPIs will also differ by industry (e.g. commerce software will not rely on daily active users the way social networks do). Finally, many people use the term KPI when they actually just mean metrics (whether input, output, health, or otherwise). As the name suggests, only the metrics that are key to success should be elevated to KPIs, and there should be as few of them as possible. When I see more than 1 from a team, 3 from a group, or 5 from a division/exec team, there are good odds that some can be cut, amalgamated, or otherwise improved. KPIs are, after all, meant to drive decision making and accountability. So what are the criteria of KPIs that stand to be improved, and examples of them? 1. Vanity metrics: these look impressive but doesn't actually measure the success of a product. Examples include the amount of traffic to a website, the number of sign-ups a product has, daily active users for marketplaces that monetize through purchases, or the number of likes across posts on a social network. 2. Poorly instrumented metrics: these are not reliably measured, which can lead to incorrect or misleading conclusions about the effectiveness of a product. For example, if the first step of a conversion funnel (e.g. checkout) has many ingress pathways, and the user can transition in and out of that step before proceeding down funnel, how well your instrumentation deduplicates that first step is critical to your conversion calculations. 3. Lack of attribution to effort: any metric who's fluctuations cannot be explained by the combination of efforts from the team/group using it as a KPI, plus seasonal and random variability, is going to be ineffective. For example, if a common funnel in the company has multiple teams trying to improve its conversion, each team needs to define a KPI that does not overlap the others or they won't know if their efforts resulted in an outcome versus another team's efforts. Note that if all those teams are in the same group (e.g. a growth org), then that group could effectively use the conversion rate as their KPI. When in doubt, or if you're unable to isolate your efforts with lower level metrics, run an A/B test against every major change by each team to get a better (but imperfect) indication of relative contribution. This criteria covers many grey areas as well. Revenue is a prototypically difficult KPI for individual teams to use because of attribution. However, you can find relatively small teams or groups that build add-on products that are directly monetized and expansion revenue can be an excellent KPI for them (e.g. a payroll add-on to an accounting system). 4. Unclear tie to next level's KPI: companies are concentric circles of strategy, with each division, group, and team needing to fit its plans and focus into that of the prior. This includes KPIs, where you'd expect a well modeled connection between lower level KPIs driving higher level ones. For example, say a SaaS invoicing platforms sets an X in Y goal as an activiation hurdle to predict long term retained users (i.e. 2 invoices sent in first 30 days). It would be reasonable to assume that onboarding will heavily influence this. But what about onboarding, specifically, will matter? If a team concots a metric around how many settings are altered in the first 7 days (e.g. chose a template, added a logo, set automatic payment reminders) and wants to use that as their KPI, they'd need to have analyzed and modeled whether that matters at all to new users sending their first 2 invoices. 5. Lagging metrics at low levels: the closer you get down to a team level, the more you want to see KPIs defined by metrics that are leading indicators of success and can be measured without long time delays. Bad KPIs are ones that just can't be measured fast enough for a team to learn and take action. For example, many teams will work to increase retention in a company. But larger customers in SaaS may be on annual contracts. If features are being built to influence retention, it's better to find leading activity and usage metrics at the team level to drive behaviour and measure them weekly or monthly. These can tie into a higher level retention KPI for a group or division, and keep teams from getting nasty delayed surprises if their efforts weren't destined to be fruitful. The only caveat for this criteria is how platform and infrastructure teams measure themselves. Their KPIs are typically more lagging and this topic is deserving of its own write-up. 6. Compound or aggregate metrics: these are made up of multiple individual metrics that are combined using a formula in order to provide a more comprehensive view of the success of a product without needing to analyze many individual numbers. Examples include effectiveness scores, likelihood indicators, and satisfaction measures. Arguably, many high level KPIs behave this way, such as revenue and active users, which is why (3) above is important to keep in mind. However, its formulas that are particularly worrisome. They inject bias through how they're defined, which is hard for stakeholders to remember over time. You find yourself looking at a score that's gone down 5% QoQ and asking a series of questions to understand why. Then you realize it would have been simpler to look at individual metrics to begin with. In my experience, these KPIs lead to more harm than good. 7. Lacking health metrics or tripwires: having a KPI is important, but having it in isolation is dangerous. It's rare for lower level metrics to be improved without the possibility of doing harm elsewhere. For example, in commerce, we can make UX changes that increase the likelihood of conversion but decrease average order value or propensity for repeat purchases. Therefore, a KPI that does not consider tripwires or does not get paired with health metrics is waving a caution flag.
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I love this question! It happens a lot and working through it is part of our role as PMs. There are a few layers to my approach here: First, start with building the relationship. (I hope this theme is clear by now ;-). While your goals may conflict, at a higher level you are playing for the same team, and having constructive, trusting relationships is a key for any team’s success. You don’t need to agree, but at least seek to understand and show empathy. Second, focus on higher level framing, rather than your own goals - You both want the company to succeed, and if you start double clicking into what success means, you will likely be in agreement for the first few clicks. As you go deeper, call out the framing e.g. “We want to grow revenue, but also want to ensure good customer satisfaction. We may disagree on the relative importance of those factors”. I specifically recall a leader I worked with with whom I philosophically disagreed on the overall direction of my product, but could still have very productive conversations about how to think about the space. We were not trying to persuade each other, but rather use those conversations to enrich both of our thinking. Third, As you lay the framework and get to the crux of the disagreement, try to think of the “what needs to be true” statement. If two reasonable, capable groups of people look at a problem and get to a different conclusion it may be because they put different “weights” on different considerations. You can then enumerate “A is better than B if X, Y and Z are true. Otherwise B is better than A”. Example: Driving revenue up by X is more important than driving customer satisfaction up by Y if we believe that the change in customer satisfaction will lower attrition by XX and drive increased spend fro existing customers of YY”. Then the discussion can be about the conditions, not the goals. Fourth, when the discussion does move to goals, look at counter metrics. “Grow metric X while keeping metric Y within certain guardrails”. I’ve seen this technique used a lot at Meta. Last - Escalate. I encourage my teams to escalate disagreements so we, as a leadership team, can unblock them. If the work above does not solve the challenge, at least it allows for a very structured discussion among the leaders of the conflicting parties.
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Ravneet Uberoi
Uber B2B Products | Formerly Matterport, Box, McKinsey • August 31
One way I like to prioritize problems is based on the level of risk these will pose to the final solution. Which are the riskiest assumptions or riskiest bets that will affect the success of your product? (Risk can be defined crudely in terms of Low, Medium, High or in some cases you might have a model with some sensitivity analysis built in). Regardless, if you can quantify the risk (and thus impact) of the problem to the final solution, you have a clear blueprint of where to begin. A related method is to consider one-way vs two-way decisions. One way decisions are challenging or impossible to reverse - these have multiple downstream effects on the solution. Two way decisions can be reversed easily or adjusted over time once you have more data. I prefer to focus my time and energy on one way decisions first, as these will build the pillars of the product. If there is considerable time or effort spent by your team on a two way decision, you can make the argument to come back to this once you have more information or once all the one way decisions have been made.
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Rodrigo Davies
Asana Director of Product Management, AI • May 17
* I get frustrated whenever I hear business outcomes and customer outcomes described as two forces that are in tension, and that it’s necessary to choose between either building a fantastic product or having a fantastic business. It’s certainly possible to have a highly profitable business with a shoddy product, but I believe that the advantage that organizations gain by going that path is short term, and that eventually a poor product experience will erode trust and lead customers to move on to better products. * This is especially common in new product / technology areas, where some companies optimize everything around being the first to launch something in order to capture the so-called first mover advantage and build a moat. Looking back on the last few software innovation cycles, there are many examples of where the second, third or even fourth product to market was the eventual winner, by prioritizing nailing the customer experience and learning from others’ mistakes, over pure speed.
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Clare Hawthorne
Oscar Health Senior Director, Product Operations • March 22
My “north star” vision for the Product Operations team is to “unlock Oscar’s ability to ship more product, better and faster.” While this is a pretty broad statement, I want to highlight a few elements. 1. Product Operations is not a function to make the life of a Product Manager better or easier. We do not “support” Product Managers. Our focus is unlocking Oscar’s capacity to ship software. In our context, this means that Product Ops focuses on the goals and delivery of our engineering pods. If there are opportunities to increase efficiency of engineering or design, those are on the table. 2. Product Operations adds value in a few different ways. Here are a few examples: * Ship more product - We can maximize the time each member of the pod is spending at their “highest and best use.” This may mean that Product Ops takes on execution oriented work while we advocate for automation or create an operational process. * Ship product better - We can improve product quality by ensuring that we follow necessary testing protocols, or ensure downstream teams are fully enabled before product releases. * Ship product faster - We can create efficiencies by building repeatable processes and playbooks, both for ourselves and for other stakeholders. In real life, this might manifest as a Product Ops Manager taking on the product launch process for a particular pod, which frees up capacity from the Product Manager and the Tech Lead (ship more product). Product Ops can ensure that their operational counterparts have visibility into the feature work and are communicated about launches in a timely manner (ship products better). Product Ops then codifies this improvement by creating a product launch checklist for themselves and other feature teams, thus avoiding “recreating the wheel” for each team (ship products faster).
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I would say there is no substitute to real user data. User research is table-stakes. But in my experience, not always representative of "actual" usage, so don't overindex on specifics. Rather validate if the problem statement is indeed important for the user segments. Because if it is, then they might be more patient with your iterations towards solving their needs. Else they are very likely to abandon very early on and never return. A good way to test is whether they are willing to pay for the solution. Paper mocks UXR is helpful once you have narrowed themes and want to develop MVP scope. Then go build MVP and ship to a small user segment to learn and iterate. This step is the journey. Scale up only when you see hockey sticks for atleast one feature. Also retention loops should be naturally showing up by then.
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Boris Logvinsky
Vanta VP Product • December 12
Start by showing interest and taking steps in your existing role. Work with your engineering manager or the PM on your team to take on PM work. You can listen to customers calls, gather insights and turn those into a feature or investment proposal, or perform competitive research and synthesize that into an action plan for your team. The best place to make the transition is at your existing company, where you have already built trust and there is someone who's willing to work and invest in your development.
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