Wealthfront's 5-Step Product Development Process
It can be pretty tough for PMs to choose what ideas to explore, which features to roll out, or where to focus their efforts. It’s even trickier when you’re juggling input from multiple sources—customers, executives, or your own gut. That’s why it’s essential to have a well-defined product development process.
Wealthfront follows a 5-step experimentation-based approach to its product development process, treating it like a science experiment. It’ll help you sort through different ideas, prioritize tasks, decide on features, and run feature testing in a data-driven way.
The steps are:
- Step 1: Make an observation
- Step 2: Ask questions
- Step 3: Craft a hypothesis
- Step 4: Test the hypothesis
- Step 5: Iterate
Why this approach?
“At its core, product management is about running experiments to learn about what customers want and what they value,” says Dan.
Dan and his team created this framework to test ideas and uncover the best solution for customers using a three-layered approach. Here’s what it looks like:
First, the product team, customers, stakeholders, and data/research from industry experts contribute insights to drive the process. Then, these insights are fed into the product feature backlog. Finally, product managers put these insights through a step-by-step process to choose the right idea to explore (or feature to build).
Now, let's discuss each step in detail and see how Wealthfront turns them into actionable results.
Step 1: Make an observation
For PMs, an observation simply means identifying a customer’s pain point. Every product (and product feature) is designed to solve a specific problem the customer is experiencing. And the true measure of a product's success is not its visibility but its impact—how well it solves customer problems.
Wealthfront uses a customer development framework to engage with and listen to their customers to determine their needs. Then, they validate the ideas generated through this framework.
So, how does it work?
The framework relies on user insights that come from a variety of sources. Dan's top three go-to customer insights sources are the consumer insights team, data science team, and product support team.
Sprig can help all three teams streamline their processes and gain actionable product insights. As we explore each step, you’ll learn how to use Sprig’s data-gathering and analytics tools for quick, impactful results.
Sprig AI collects and analyses user data to give actionable insights into product improvement.Customer Insights Team
Dan considers the customer insights team as one of Wealthfront’s secret weapons. “The customer insights team is an experienced team that is constantly working ahead of our roadmap using a variety of methods to help us understand what our customers are thinking about next," he says.
The team uses a blend of surveys, qualitative interviews, and traditional methods like user research and usability testing. They generate rich customer insights that reveal customers’ motivations, explain their behavior, and pinpoint what the team should prioritize in the next release.
One example is Wealthfront’s survey of customers who opened an account but never made a direct deposit. They try to understand what roadblocks prevented these customers from doing so. In this case, user research software is used to get insights faster so PMs can make stronger observations and informed product decisions in seconds, not days or weeks.
With Sprig, for example, your customer insights, research, or even your product team can launch targeted in-product surveys to learn, in real-time, why your customers sign up, engage with certain features, and stay loyal or churn.
You can launch these in-product surveys in a few minutes by selecting a survey template that correlates to the product issue you are experiencing and start getting insights within 1-2 days.
Use Sprig Surveys templates to quickly set up and run targeted surveys for your product. Data Science & Product Support Teams
The data science team generates insights based on data in Wealthfront's customer database. The product support team generates insights from daily tickets. Product managers read through these tickets and figure out what customers are asking. The support team categorizes this data, so it's easier to prioritize issues that come up frequently.
"We use these insights to enhance the product and also validate bigger opportunities we have been thinking about. We spot themes in what our customers expect from us next,” Dan said. “That's an incredible advantage when you think about the investing market right now.”
Dan added that the data obtained from customers’ daily inquiries helped the team visualize the monumental shifts in consumer behavior in real-time. It still has a huge influence over Wealthfront’s product development process.
Sprig AI supports this process by automating the analysis of large datasets, identifying patterns, and generating actionable insights.
For product teams, this means saving hours of manual work as triggered studies and AI analysis identify recurring issues or emerging trends to categorize user feedback into themes.
Sprig AI categorizes user feedback into themes so your product teams know what to prioritize.Other Insight Generation Methods
Wealthfront also uses social media to understand why customers choose to use their service. The team tries to identify what they need to do to inspire trust and loyalty in customers and boost retention rates.
Additionally, Wealthfront gets qualitative, visual feedback from a small group of early adopters through video interviews. That way, the team receives unparalleled insight into what is working and what isn't. They also play these videos during biweekly product review meetings for the rest of the team.
"I think one thing you get from those videos is that you can sense the energy people have about the features,” Dan says. “It's one thing to read a customer review on a sheet of paper or a slide. But to actually see them say it. You can gauge it over and over again to see if this is something that people really want.”
A mix of surveys, insights from product support teams, and visual feedback gave the team clarity into the core features that resonated with customers. With these insights, they nailed the core use case for that product, expanding its audience and delivering its promise.
Step 2: Ask a Question
After making an observation, the next step is to find your customer's “why.”
It helps you create a compelling roadmap that secures buy-in from stakeholders and enthusiasm from the organization and allows you to prioritize features.
A critical "why" to keep in mind, according to Dan, is the reason your customers hired you in the first place. When you understand why they hired you, you can focus your efforts on solving that pain point. In other words, the core product has to deliver before you expand and sell users on a new feature.
It’s easy for inexperienced product managers to fall prey to the next feature fallacy. They may think building a new feature will solve all the problems their business or product is facing. However, Dan feels, "It doesn't make sense to expand to new product lines if you haven't delighted your customers with the core use case they hired you for. It’s critical to know what your customer is hiring you for on that first use case and make sure you delight them and nail that before moving on to adjacent markets or problems.”
Exploring new features before nailing your core use case sets your company up for failure. “It results in a shifting of resources back and forth between different product lines and the company,” Dan says. It’s like a dog-chasing-its-tail situation—resulting in wasted time, energy, and money.
Customers are rarely interested in adopting new offerings from a company that hasn’t first delighted them and won their trust. So, instead, focus on satisfying the early adopters before expanding to new product offerings.
You can use Sprig Heatmaps and Replays at this point to show you how users interact with new features, which parts get the most attention, and which are ignored. This gives you solid evidence to predict which features will perform better before officially rolling them out.
Sprig Heatmaps and Replays give you solid evidence on what works and what doesn’t. Dan says, "At Wealthfront when we look at building products, we focus on delighting the early adopters. We make sure that the product works well for them. We try to understand the source of the value, and we figure out whether or not we've found a product-market fit before moving onto opportunities to expand further."
Bottom line: Before expanding your product's scope, confirm you have satisfied the early adopters.
Step 3: Develop a Hypothesis
Innovative product teams build on the ideas generated from their customer insights. They don’t indulge assumptions. Instead, they craft a strong hypothesis from the ideas generated and test it before investing in it.
Dan's article, the visionary dilemma, outlines two key elements PMs must consider when deciding whether to expand the scope of a product or focus on improving the product: product performance and resourcing.
Let’s explore each in detail:
Product Performance
Dan believes that a brand “earns the right to explore new product opportunities when the performance of your product and new enhancements surpasses what customers value or are prepared to use.” To understand the concept better, Dan uses a simplified version of Clay Christensen’s product performance framework:
Any product at the far left end of the blue line hasn't earned the right to explore new product opportunities.
Measure your product performance with Clay Christensen’s product performance framework. In other words, when your product hasn't fulfilled its initial promise (the solution it promises), investing resources to create new product lines will be a waste. On the other hand, when you focus on delighting your customer first before rolling out shiny new features, you'll keep progressing up and to the right of the blue line, exceeding customer expectations.
Here, qualitative data gives you the why behind user actions. For example, by using Sprig's AI Explorer, you can generate product recommendations based on feedback and product interactions.
Ask Sprig AI Explorer for Insights into user behavior and identify why and where users get confused. By analyzing inputs from surveys, heatmaps, and replays, AI identifies key user pain points and interests, giving you precise, data-driven hypotheses for targeted testing and development—no guesswork involved.
Resourcing
Wealthfront also uses a framework internally called exploration vs. optimization to determine where to invest resources.
With this framework, Dan and his team identify what the customers need most at a given time and where they should channel their resources. Dan says, “broadening product scope too soon often results in resource shifting from one product to the next, which rarely results in any one product being successful.”
PMs need to answer these questions when deciding when to kick off new product development:
- How much do we need to invest in maintaining dominance in our core product?
- How much do we need to invest to launch a new product successfully?
Evaluating and answering these questions help PMs determine whether or not they have the team resources they need to go in both directions or prioritize one over the other. Here’s how you can tell where to focus your efforts:
To pursue new product opportunities, resourcing should “stack” over time toward new product opportunities so you don’t shift focus from your core product abruptly. If pursuing new product opportunities causes you to divert too many resources from the core product, that’s a sign that you are investing too soon.
Ignoring resource assessment sets you and your team up for failure. You risk taking on too much too soon, failing to delight customers, and decreasing your chances of earning their trust and loyalty.
Based on insights from resource assessment, the team can allocate time on either improving the core product offering or exploring new opportunities. The time allotted depends on the stage of the product’s development, where the company is, and the strategy at a given time. Many of the new opportunities fail once they are tested, while some are shelved for future use. But, overall, the method helps the team invest company resources in the right direction instead of shifting them back and forth, eventually wasting them.
Step 4: Test the Hypothesis
After crafting a hypothesis, the next step is to test it.
Depending on the product, Wealthfront uses a clickable prototype to get concrete evidence that customers will use the new feature (or product). They also try to understand how customers will get value from the update.
How do they get the answers they need?
According to Dan, relying on the words and enthusiasm of customers when it comes to rolling out new product features isn't a great way to go. People’s actions don’t always align with what they say. So, PMs shouldn’t prioritize everything a customer demands. That's why testing is critical.
Here's how Wealthfront tests a hypothesis:
When testing an idea, Dan and his team take a core insight and formulate a point of view. Then, they try to figure out if that insight is a problem for their customers. This part is critical because that’s where they determine if customers truly need the product or it’s a mere desire with no real, long-term value.
Next, they try to envision what the solution might look like. The result of this process is a clickable prototype presented to the customers. The goal is to figure out if these customers would use the product if it existed. If the answer is no, they don’t throw in the towel. Instead, they push to understand why.
Sprig can also refine this process for you and make it more data-driven. Sprig’s automated studies collect user feedback through triggered surveys to capture user sentiment at critical moments.
Then, you can set up triggered session replays and heatmaps based on specific customer attributes to see how users interact with the prototype. Leverage AI to analyze the data, identify issues, and find potential solutions, like relocating a button to a place with more activity for better engagement.
Set up specific studies with Sprig, learn user pain-points and get actionable steps on improvement. This way, you can validate hypotheses using real-time data directly from your user to minimize reliance on assumptions and make data-driven decisions on feature development and market readiness.
According to Dan, it's usually in the process of understanding “why” that you uncover insight about the true nature of the problem, and it allows the team to iterate their point of view. For example, most customers don't realize the cost of developing a product feature. So, if you ask if you should build a new feature, they'll say yes. The way around spending too much on a feature no one might use is to get some sort of commitment from them.
Dan and his team assess whether or not they should pursue a new product by asking customers if they are willing to pay to be a part of an early access program. Gauging their commitment level is critical to Wealthfront’s overall health, given the timelines and complexities of the products.
“If we're going to spend six months to a year bringing a new product to market, we want to know that we're pretty darn confident that it's going to have the impact that we expect," Dan says.
The trick is to make sure that the scales are in your favor. Aim to be right more often than not, and the magnitude of success should be high.
Let’s Explore Two Contrasting Examples Wealthfront's Hypotheses Tested:
In late 2018, Wealthfront rolled out a free financial planning product to give customers access to world-class financial advice.
The team hypothesized that before clients could invest, they needed to do financial planning. Existing customers signaled that their financial planning offering was valuable and resonated with them. So, Wealthfront launched the product as a way to generate leads and convert them into investment clients.
The outcome wasn’t as anticipated. Even though it drove customer acquisition, the conversion rate wasn’t impressive.
On the flip side, they observed that customers had lots of cash sitting in low-interest-bearing accounts. So, in early 2019, they launched their high-interest cash management account for customers saving for short-term goals such as rent, a new car, etc.
The company partnered with FDIC-insured banks to hold customers’ deposits. The product performed far better than the financial planning feature tool, nearly doubling Wealthfront’s ARR that year.
So, even though both hypotheses passed the test, only the high-interest cash management account yielded more than the desired outcome.
Step 5: Iterate Outcomes
In this phase, the goal is to use the results to make new hypotheses and take a step back to evaluate your process. Are there loopholes or signs you overlooked? What could you have done better?
This requires timely and relevant feedback, which calls for creating a continuous feedback loop for a steady stream of insights for product iteration.
Sprig’s built-in tools, triggered at key interaction points, can automate the collection and analysis of up-to-date user sentiment.
Use Sprig tools to quickly build and launch custom surveys to get constant feedback on any page you want.
Whether it's new features, UX, or layout, instantly create targeted surveys using tailored templates to always integrate user feedback into your product development loop.
According to Dan, a product's success relies on a blend of validated insights and the PM's judgment. That's why product managers need to be intellectually honest with the data they gather from customers to avoid building the wrong things—it’s also why AI analysis of user feedback can play such an important role in developing effective product strategies.
Conclusion: Embrace Customer-Centricity To Build Products People Love
Creating products that people love starts with a healthy customer obsession. And without customer insights, it’s impossible to know what your customer thinks, how they feel, and how they make decisions.
Instead of being laser-focused on the competitor's playbook, Dan and his product team at Wealthfront use customer insights to understand how they can deliver optimum customer value. Thanks to a robust experimentation framework that allows them to improve and learn continuously, Wealthfront is always working to serve customers better.