If you have to improve the adoption rate of a SaaS product, where would you start?

I'd start with the data! This may mean tapping your data analysts, marketing analysts, basically anybody who is knee-deep in the metrics. What I would do first is attempt to map out the funnel for the product in question (if this doesn't already exist) - figuring out how people get to your website, what they do once they arrive, and where any significant drop-offs may be occurring. 

In this case, if you are more focused on retention then I'd look at what users are doing once they are in the product, how long they are sticking around (or not), and try to pinpoint any significant data points for these users - for example, if you notice that users with a certain team size are more likely to remain active after two weeks, you may decide it's worthwhile to encourage inviting teammates as an initial step in product onboarding. 

Once you discover something like that ^ it's all about figuring out where to encourage these types of behaviors, what channels do you have access to? Email? In-app? Direct mail? The way you reach these people may vary based on your offering and platforms you have access to, but one thing is for sure, you first need to understand the behavior and characteristics of the users that ARE taking your most desirable actions - and then try to map that into getting more people to take those some behaviors. 

At Asana, customer empathy and experimentation are not only how we build our product, but who we are. I would start with deeply understanding the customer - what are their needs and motivations? What problems are is your product solving for them? 

I would then connect with data science and user experience teams to review product usage data. When comparing highly engaged users to those who drop off, can you identify any demographic/firmographic differences or product usage trends among each segment? Can you identify opportunities across different stages of the customer journey, as adoption can apply to signup, onboarding, engagement, etc? Hone in on the right metrics to move and form experiment hypotheses based on your customer research. 

Oh, man, big question! It really depends on the product and company. But if I have to generalize...

First, I’d try to get crystal clear on what we mean by adoption rate. Is that net-new free signups? Is that activation of those signups? Let’s say it’s it’s activation of those signups for discussion purposes.

The second thing I recommend is sign up for free (if you're PLG) for your company’s product using a burner email and record your screen going through the first-time user experience. What screens do you see? What emails do you receive in the first five days? First 30 days? What in-app messages do you receive when you return? Is someone in customer success hitting you up right away to schedule a call? Sometimes, it helps to take screenshots of everything and throw it in InVision Freehand or another whiteboarding tool to analyze the process.

Step back and think like a family member of yours who is checking out where you work. Is the experience helpful? Do the emails urge you to try the right features? What are the right features? Where’s the friction? Is the friction helpful for you the marketer, but not the customer?

Next, I dive right into Mode or Amplitude, and I start looking at the cohorts who are active. What Top 20 people are using this product? What’s their job title, what kind of company do they work for, what industry are they in? I even grab their photos from LinkedIn and create a whiteboard of them sometimes. Here’s the account's first user, the champion, the most active, etc.

I then like to interview some of these most active customers to find out why they’re active, what they like about the product, and what marketing communications, in-app experiences, and third-party content they’ve benefited from.

I’m all about focus, so I generally double-down on that cohort (say, product managers in medium-sized collaboration-software SaaS companies) and try to do more of whatever marketing tactic worked to reach their lookalikes until I exhaust that method and cohort.

• Partner with digital marketing to understand the source that drove the user to your property, the actions they took before converting, and the page they converted on (or where they dropped off).
• Map out the customer journey from when landing on the website to sign up to active/conversion. Look for the biggest drop-offs and partner with the growth team to A/B test the experience and messaging.
• Measure time to conversion. For example, if 10% of new signups are converting to paid in the first week, take what you learned from digital marketing and isolate where these folks are coming from, then follow them through funnel analysis and use their successes as a foundation for your upcoming a/b tests.

A common pitfall when trying to improve feature/product adoption is to jump straight into tactics. This often results in emails and in-product messaging that doesn’t have the intended impact, and annoys users.

I like to start by better understanding the users that have adopted a feature/product. Ideally, I can look at product usage data in addition to talking to users. I want to know who they are, how often they’re using the feature, what they use it for, and what they like/dislike about it.

In addition to understanding the users that have adopted a product/feature, I find it helpful to talk to users that have not adopted. In my experience, this has largely been qualitative — via sending out a survey and talking to users directly. When reaching out to these users, I focus on understanding on whether they know about the feature or not, and if they do, why they haven’t tried it yet. Is there a workaround they prefer? Another product where they’re doing this activity instead?

Lagging adoption can be the result of many things (e.g. poor discoverability, lack of product-market fit) — taking a step back to first understand the root cause allows you to tackle the right problem and be targeted in who you reach out to.

Example: Recently at Figma, we launched a new product, FigJam, so I’ve been thinking a lot about how to drive adoption. When we first launched in beta, we wanted to better understand adoption from our existing user base, so we surveyed active users and users that had abandoned after trying it. One learning we had was around templates —active users loved and relied on these, while abandoned users identified these as a feature gap. We realized our problem was discoverability, and took action by prioritizing changes to the product UI and creating a template-focused re-engagement campaign.

1. Get a good handle on your funnel metrics
2. Identify areas in the funnel where there is disproportionate dropoff
3. Once you’ve narrowed in a bit on where in the funnel you want to focus, talk to your customers. Get feedback on what hurdles exist and what might overcome those hurdles.
4. Brainstorm, scope, and prioritize experiments. I usually like to have some small quick wins complimented by bigger bets.
5. Measure, learn, and iterate. Keep going until you see an impact :)

The first thing I would do is ensure I have a solid understanding of my target audience and their needs, pain points, and expectations of the product. You can start by gathering feedback from your existing user base to identify areas for improvement and/or features that can enhance adoption. Surveys are great for that. ;) This, in combination with analyzing existing user data to identify friction points will likely guide your initial focus. Other likely areas to look at next (in order of logical progression):

• Onboarding flows: Do users have a smooth experience right from the start? Do they know where to begin?

• UX analysis: Are there usability issues, points of friction or clear drop off points?

• Customer education: Is your product difficult to get started and use? Would users benefit from kickstart guides or walkthrough videos?

• Feature highlighting: Are there specific features that could greatly enhance adoption but are not being utilized? Are they being appropriately featured in the right place in the customer journey?