A Scientific Approach to Product Sense


Highlights

Wealthsimple recently became the first broker in Canada to offer fractional share purchases. What was it like for your team to work on such an exciting product?

Avrum: I think fractional shares are actually a feature that's really aligned with our mission of democratizing finance. Sometimes buying a single stock of Amazon or of Tesla is actually cost prohibitive.
And fractional shares allows others to participate in the potential upside of those companies and invest in the companies they love and that they use. But with a minimal investment that ultimately aligns with how much they're prepared to risk.
It was a pretty exciting launch. I can tell you that I use it because I'm way too cheap to buy a full share of Tesla. But I want to be part of the journey.

It seems like you’re always delivering exciting things have a strong sense of your customers’ needs. Can you explain how your team thinks of product sense and synthetic thinking?

Avrum: It's interesting because if I contrast my experience at Wealthsimple with my experience at Freshbook– Freshbooks is basically accounting and billing for small service-based business.

I've never run a small service-based business. And so, my intimacy with that problem and that sort of lived experience was always a bit once removed. Obviously, we did tons of research and customer interviews to really deeply understand that customer profile. But because I hadn’t ever worked in that context I was never able to be fully intimate with that space.

Contrasting that with Wealthsimple, I use all the products like a regular client. I think that gives me a little bit of a cheat code when it comes to product management. I’ve learned that if you actually use the products regularly that you’re building, you have an ability to be intimate with it in a way that’s hard to replicate.

Your familiarity with and empathy for the customer is stronger. Now I will caveat that really heavily though, because I think the one danger is that you start to confuse yourself as being the target client.

And I'm certainly not that and recognize the incredibly privileged position that I'm in. We're not the be-all and end-all when it comes to customers.
That said, using your own product is by no means a substitute for talking to customers.

Could you elaborate on the term “synthetic thinking”? What does that term mean to you?

Avrum: Product managers who are early in their career often think that the role of the product manager is to be the idea person, person who sits at their desk and pontificates about the future.

You quickly realize that is not your job. That doesn't mean that it doesn't take a sharp mind to be a product manager. Rather, I think that the real challenge, and where the real genius of some of the best product managers that I've ever worked with shines through, is this ability to synthesize from a myriad of different inputs.

Structured data, unstructured data, customer interviews, market data, business cases, app reviews. This large corpus of basically infinite data at your disposal and synthesize that into a point of view. That synthesis is what I refer to as synthetic thinking.

That is far more difficult than sitting at your desk and pontificating about the future of the world. But you’ll notice that you have even better ideas when you are recognizing patterns in these overwhelming data sets and then synthesizing those patterns into a point of view. This becomes a point of view for your products and your product strategy that you can then pursue.
When you see this done well, it's incredibly impressive. But it also takes a lot of practice to get good at. Anything that requires pattern recognition takes many, many kicks at the can in order to be good at it.

Just start recognizing the common themes and patterns. This is also something that is a sort of a lifelong journey for a product manager. Synthetic thinking and the ability to filter noise into a signal takes time.

How can PMs teach their team about synthetic thinking?

Avrum: When I coach others on synthetic thinking I always encourage them to employ a rigorous scientific methodology. That is something that you never innovate on because it's been around for thousands of years.

It's very, very well-defined process. From this large corpus of data that you have you synthesize the hypothesis, and the hypothesis needs to be falsifiable.

It needs to be built on an educated assumption about how things work or how things could work. And it's falsifiable in so far as you have to be able to prove or disprove it using an experiment. So that's the first thing and that never changes.

Following a rigorous scientific structure at least insures that you're following a systematic process of problem solving. The second piece that I think is really important is how you communicate that hypothesis and that approach in a way that is persuasive, compelling, and really tells a clear narrative. This is really challenging.

And that's where maybe the scientific method is an incomplete process and has to be coupled with some of the communication practices and storytelling practices that product managers are often really good at. You don’t want to be articulating this as a dry scientific hypothesis.

You're trying to tell a story of a customer problem informed by all the data and insight that you have. That ultimately informs a point of view. Getting really good at telling that story and letting others engage in it in a deep and meaningful way is hard.

Ultimately it is really worthwhile because it gets everyone to buy into the approach that you've set out. So, storytelling is another piece of the puzzle that I think is crucially important for product managers.

Can this level of thinking be used by a PM at a startup building a zero-to-one type of product?

Avrum: I actually think it's even more critically important in a zero-to-one context that you're following this rigorous scientific approach.
Now, I’m assuming this is pre-product market fit. You need to have a hypothesis for what you’re building. Being scientific here means that you're open to the idea that you're wrong and that, at a certain point, if you are not succeeding, you actually have the opportunity to pivot.

Be ready to try something else informed by what you've seen in the market. Make sure you don't keep running at the same wall over and over again and expecting different results. This is very important at an early stage context because you only have so much runway.

You need to be really scientific, rigorous, and objective about how you're evaluating your success and your failures. Don’t get precious about an idea or approach. Let the data from your in-market experience dictate what you do next.

Remember– scientific method doesn't mean overly bureaucratic or overly process driven. It just means being rigorous and systematic.
And that means only using the minimum amount of process in order to preserve that rigor is what you need. The most important thing for an early stage company to do is ship and ship a lot. Getting bogged down in cumbersome processes is not necessarily going to help you.

I’ll use Wealthsimple Trade as an example of this process.

We started out as a way to do automated investing. It's automated, passive investing. We realized there was a gap in the market for a simple, client-friendly, self-directed investment platform. There wasn't one in Canada that was really serving the needs of new investors.

Even established investors just didn't have that much in the way of product offerings, especially when you contrast with markets like the U S.
We actually had a brokerage. We had all the backend services, infrastructure, and the platform that would allow us to build a self-directed experience. We could do this without a tremendous amount of additional work. We could actually leverage the asset that we already had and build a really super lean product layer on top of it.

The beginnings of Wealthsimple Trade were you could only open a single account type. There were, admittedly, limited socks even available on the platform. But the fact that we were able to leverage our existing brokerage infrastructure and platform, and relatively quickly add a product layer on top of it allowed us to validate that there a need for this to happen in the Canadian market.

Customers were interested in something simpler, something lower cost, and something that ultimately solves the problem of self-directed investing in a modern way. Our hypothesis was that this product would have a market and have interest. It was validated fairly quickly. Right out of the gate, we had massive interest. Our waitlist was hundreds of thousands of customers long.
The nice thing is that we didn't have to invest that much early in the early days to quickly validate that there was a business here that there was a real opportunity here.

If this hadn't been successful, we had built a layer on top of our existing brokerage. So it didn't jeopardize our existing business.

At that early stage, could you have done an even smaller version of that experiment to test against the scientific method?

Avrum: Wait-lists are a great tool. But they have their limits in terms of what they can demonstrate. And I think one of the key challenges with a wait list is that everything's smoke and mirrors and you basically set up a website.

You haven't actually written a line of code, other than the website, in order to validate whether people are interested in this concept or idea. The problem is less if there's actually a product and a meaningful value exchange between the customer or the potential customer and your business.

The validation only goes skin deep. It's like if you ask the person what features they want, people just keep saying yes to everything. But if they have to pay for that feature, if there has to be a value exchange in order to secure that feature, then suddenly they become a lot more selective about what they want.

And then suddenly, they have to prioritize because you've inserted a constraint. This constraint is something you're going to have to give up. And that isn't always money. It could be your time. It could be like the switching cost of moving from an existing player to you.

But there has to be a value exchange in order for that validation to be really meaningful and start to demonstrate product market fit. Wait-lists are a great tool in the arsenal, but they often don't don't imply enough value such that you can really be super confident in the results.

It's a great vote of confidence. But you need enough of a product where people are exchanging value at scale. And then you can say, you’re on the right track. I’ll also say, I think I’ve misused wait-lists in the past in my career.

If you build this grand vision on a landing page, get people super excited, and then you go dark for months as you build the product, you can actually burn some credibility and some trust with those customers because you showed them a glimpse of something. It wasn't really necessarily even close to being ready.

That excitement kind of fizzles in a way that is ultimately not helpful to your business. And you erode a bit of trust. But you can leverage wait-lists properly. You want to be close enough to the actual realization of that product that it doesn't feel like you're misleading your customers. It’s obviously never your intention, but it can certainly feel that way if there's a big gap.

Tell me about some moments in your career when you really started to connect the dots on this type of thinking.

Avrum: I went through somewhat of a typical product journey that a lot of product managers go through. I came out of university thinking I was supposed to be this “idea person.” But for a little bit in your early career your definitely do play that role.

It’s really humbling for product managers when you've shipped things that you think are great but people don't adopt or they don't have the impact on the business that you assumed that they would. There's a very real, humbling experience when you realize that there has to be a better way.

There is an unavoidable amount of product failure that you need to go through where you learn lessons, the hard way. You want to make sure that you're not putting a business in existential jeopardy to learn some lessons as a product manager.

That was actually one of the great benefits of joining a company like Microsoft. It was bureaucratic enough that there was no danger that my junior PM was going to torpedo the various businesses that I worked on.

Those experiences are humbling in two different ways. One is that the project or the thing you deliver ultimately does not have the intended impact. In fact, it has a null result.

It doesn't achieve anything. And that sucks. What's worse is when it has the opposite of its intended impact or it causes a degradation of the user experience and some unintended, unanticipated way. And that's even more painful. But it's perhaps also more impactful to you as a product practitioner because you never want to feel that ever again– to try to to ship them what you believe has value to the world and have it be just thrown right back at you and saying, no, thanks.

This is terrible. There is no more humbling experience for a product manager, but it's also probably, there's no more elemental experience for a product manager to learn that. Like, well, maybe there's a better way of doing this.

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