the beauty of continuous discovery is that there’s no single right way to do it. this is why teresa often talks about guiding principles and core concepts, but encourages everyone to find what works best for them.
for example, while teresa recommends creating a product trio that includes a product manager, engineering lead, and a designer, she acknowledges that some product trios might be made up of slightly different members. the job titles of each participant matter less than the fact that you’re creating the smallest possible decision-making unit that still includes all essential perspectives.
similarly, the opportunity solution tree can be an incredibly powerful tool for keeping track of your desired outcome, the opportunities you learn about during discovery, the solutions you’re considering for each opportunity, and the experiments you’ll run to assess your ideas. but again, there’s no rule that requires you to use the opportunity solution tree. you might find there’s another tool that works better for your team—and there’s nothing wrong with that.
when it comes to the tools that support your continuous discovery, the same philosophy applies. it’s not about finding the right tech stack; it’s about finding the tech stack that works for your team.
when it comes to the tools that support your continuous discovery, it’s not about finding the right tech stack. it’s about finding the tech stack that works for your team. – tweet this
in the tools of the trade series, we talk with different product professionals to explore how they approach continuous discovery and which tools facilitate this process for them. find all of the posts in this series here.
please note that this post is intended to be educational and does not constitute an official 瑞士vs喀麦隆水位分析 endorsement of any of the tools that are mentioned.
meet the continuous discovery champion, product manager steve cheshire
steve is one of the product managers for pendo feedback, a product that enables other software as a service (saas) companies to centralize, analyze, and prioritize feedback while keeping visitors in the loop—all within their own app. according to steve, “the problems that come with that are capturing, organizing, and prioritizing feedback at scale, so that without too much time investment product managers can distill raw data into actionable insights which inform discovery and ultimately drive roadmap decisions.”
at a tactical level, steve works with two fantastic engineering teams whose goal is “to make sure we’re building the right product and building the product right.” he also works with design and leadership on the medium-term strategic space, helping decide and define future initiatives that will unlock value for their customers and prospects.
the main persona they serve is product managers and other people in product roles such as chief product officer, vp of product, or product operations. this can create a false sense of familiarity, so steve says they need to be intentional to avoid making assumptions about their users. “whilst serving those with familiar problems to you is nice, it’s easy to become biased, believing everyone does product management the way you do.”
whilst serving those with familiar problems to you is nice, it’s easy to become biased, believing everyone does product management the way you do. – tweet this
describing his experience with continuous discovery, steve says, “fortunately, i’ve always been in environments where i’ve spoken to customers fairly frequently, which helps train your personal understanding of the problem space.”
at pendo, steve and some of his peers participate in weekly rolling research. he also regularly looks for opportunities to jump on sales or customer success calls with customers who have new use cases.
steve believes his team has adopted the right mindset, striking the balance between targeted learning and exploring new opportunities in the same customer call. “engineers are also onboard and really enjoy the raw customer context it provides, as well as validation that what they’re building makes a difference,” adds steve.
one of the biggest challenges they’re currently facing is keeping up with synthesis and maintaining the latest system of record for the problems, opportunities and other key learnings. “this is mostly because we haven’t booked enough dedicated time in to review immediately after the sessions and have changed tooling around,” says steve.
when it comes to their continuous discovery activities and the tools that are associated with them, steve says there are a few main categories: recruiting, interviewing, synthesis, and experiment design/execution. let’s look at each one in more detail.
for recruiting existing customers to participate in interviews, they use a combination of pendo in-app guides (pop-up windows that prompt users to take a specific action) and calendly (an automated scheduling tool). “this allows us to target a specific segment of our visitors in-app, inviting them to schedule a call right there,” says steve.
when it comes to using pendo in-app guides or something similar, steve says, “the main tip i have is be punchy and direct with content when trying to recruit, using a known pain point as a headline to get a bite. for example, ‘need better search results?’”
when trying to recruit customers through a pop-up or something similar, be punchy and direct with content, using a known pain point as a headline to get a bite. – tweet this
once a user clicks on the “schedule a call” button, they’re taken to a calendly calendar that allows them to schedule a call at a time that works for them.
for interviewing, the pendo team uses zoom. “its main advantage over similar tools is everyone’s familiarity with it, meaning no time is lost while finding the screen share button or turning on video,” says steve. “it also has integrations for importing recordings to other tools for onward analysis.”
zoom calls are stored in the cloud, so the product team can share the url immediately after the call with anyone who’s interested. the ux research team also pulls recordings into tetra insights, a research analysis and repository tool.
synthesizing what they’ve learned
once the recordings have been imported, they can tag key insights in tetra insights and easily curate a play reel of video snippets from different interviews that all surface the same themes. this is really powerful when trying to give context to engineering or convince executives that a product investment is needed to solve a problem.
logging feature requests from discovery calls in pendo feedback is a great way to get validation from the wider audience, since all their customers can see them, add their vote, and provide their unique context in a comment. customers can create their own requests, and the tool surfaces things that are organically gaining momentum. “yes, we use pendo on pendo!” says steve.
designing and running experiments
the pendo team creates prototypes and designs in whimsical (lo-fi) and figma (hi-fi). leveraging low-fidelity mockups helps them understand if participants can grasp new concepts or easily discover new parts of the ux, whereas high-fidelity prototypes enable them to test full user flows and information architecture.
when they need more quantitative techniques to validate solution ideas, they use userlytics to run unmoderated tests with a quick turnaround time. they would usually take this approach after hearing a common theme emerging across a small sample of interviews. this would then prompt them to test some assumptions/solutions with a wider scale study.
“the click test shown here allowed us to very quickly get quantitative data on how discoverable features were on our new design as well as how quickly users found them,” says steve.
according to steve, “the key to getting good results out of these tools is providing good context and adding steps to make sure participants have fully read and understood tasks before they embark on them.”
adding new tools and advice for other teams
before adding any new tools to your toolbox, steve says, “push the tools you’ve already got in house to the limit first. the tools you already have will be easiest to get colleagues to look at and don’t require budget or security signoff.” he also recommends prioritizing sharing and collaboration when evaluating tools. “try to avoid tools that require an expensive license for users who just want to view content.”
before adding any new tools to your toolbox, push the tools you’ve already got in house to the limit first. – tweet this
reflecting on what he might do differently, steve says he’d think a little more carefully about where interview notes are archived for future reference. “we’ve used a mix of miro and figjam so raw data is spread about a bit.”
while trying to limit the number of tools is a good rule of thumb, steve also recommends not getting too coupled to any one tool. “this space is moving fast and there’s a good chance a new tool could come along and shake part of the process up at any time.”
finally, steve says that being transparent with customers can really pay off. explain to them that you’re listening to lots of perspectives and there will be future opportunities to get involved in research as solutions are developed. “turning customers with pain points into reference customers who help you build the future product is a massive win,” says steve.
turning customers with pain points into reference customers who help you build the future product is a massive win. – tweet this
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