Drive Growth with Data-Informed Design
You’ve probably heard the buzz word “Growth” before. While growth is measured in many ways, in the B2C world, growth usually connects with user telemetries, such as user base, usage, transactions, and conversion rate. Meanwhile in the B2B world, sometimes growth is all about how many big sales deals are closed. Product-led growth could be overlooked by sales-led growth. What’s the impact of newly launched R&D projects on enterprise business growth? We are not sure since it’s hard to connect a specific launched feature to a recently closed deal, and we often lack visibility into what product design and strategy have contributed to the business.
At VMware, we aspire to drive more product-led growth with great user experience, utilizing the data-driven design methodology. We will demonstrate a case study in Wavefront by VMware on how we used data to help us increase the free trial activation rate by 30% and increase the dashboard creation rate from 5% to 25%. We utilized data to drive the organic growth of the enterprise SaaS business, from tracking the user data, testing out hypotheses through experiments to see the results, and ultimately accomplishing the goals like expanding the user base and increasing the conversion rate.
The first challenge is to understand what product-led growth means to us.
Product-led growth relies on product usage and customer experience to acquire new users, retain its existing ones, and expand its user base. It doesn’t involve much sales pitch and the process is more data-driven.
We used a framework to brainstorm user metrics to help get clarity about what growth means to us: how is growth reflected as tangible goals; what user metrics represent these goals; and what are the supporting metrics for the representing metrics?
For example:
Wavefront by VMware is a SaaS platform that helps Site Reliability Engineers(SRE) and DevOps to monitor the infrastructure and application.
- What is the business goal: Acquire new customers to generate more revenue.
- What are the user metrics that reflect the goal: Improve the conversion rate from new users to paying customers.
- What are the supporting metrics: Active user engagement, higher product usage such as query usage, dashboard usage, alert usage.
After we defined the metrics we care about, we start to track them with a tool called Pendo. Since Pendo doesn’t require code instrumentation to track the user metrics, it’s easier for non-technical people like product managers and UX designers to set it up by ourselves.
Understand the product holistically before diving into individual data points
To drive product-led growth, we need to have a holistic end-to-end story of our product so we don’t go sidetrack into single data points. We are informed by the data instead of purely driven by the data.
Wavefront by VMware is a SaaS platform with a 30-day free trial for SRE and Developers to try the product hands-on. Here is the end-to-end process of converting from trial users to paying customers:
- Aware: Users will first become aware of Wavefront’s solution.
- Sign up: Users decide to sign up for a free trial to explore the product.
- Try: Users become more interested in our product.
- POC: Users will talk to our salespeople for a proof-of-concept.
- Buy: If they decide to purchase they will be entering in a contract.
In the first three steps “Aware, Sign up, Try”, the growth is more likely to be driven by the product itself; there is not much sales pitching or hand-holding. We want more organic growth in this process.
Do experiments and track the results and continue to learn
Based on the data we tracked and the end to end evaluation of the product, we identified some areas that need improvement. We have a few hypotheses about why the current experience is not working, and we designed the new experience to solve the user pain points and then test the new experience through experiments.
Experiment 1: Improve sign-up form and remove email activation
The first low hanging fruit we found is that the trial sign-up form has usability and accessibility problems. After users sign up they have to go through an email activation, but this out of context action caused friction and ended up increasing the user drop-out rate.
As a collaborative effort with our marketing department, we improved the sign-up form with a better visual design and displayed compelling product benefits next to it. Also, we removed the email activation step that caused friction in the trial activation process. The sign-up activation rate increased by 20%.
Experiment 2: Improve password setup experience
Then, we discovered that when users are trying to set up a password, the system throws a huge error message that leaves the user confused about what to do next. From the back-end, the password requirement is unstructured, which is why the error message is not useful.
To help users easily set up a password, we made the password requirement clear upfront. Password requirements are displayed upfront on top of the password field to help users learn the requirement beforehand, for example: “minimum 8 characters”, “at least 1 upper case”, “1 special character”, etc. When the user enters a password that doesn’t meet a few requirements, the unmet requirements will be highlighted to remind users. We also allow users to toggle to see the password they entered. This error-preventing design provides a delightful experience for our users. After launching this design, the sign-up activation rate increased by 10%.
Because the activation rate increased, our user bases increased and we expanded the top of our sales funnel. We are able to demonstrate that good user experience can actually drive business growth, with quantitative data to prove it. This data-driven design approach saves customer acquisition cost for the SaaS business.
Another benefit of this approach is continuous iterations with data. The more we test, the more we learn, and we continue to build upon it.
Experiment 3: Improve the onboarding flow with clear call-to-action
Now that users have entered the free trial, they will be dropped into an onboarding flow. Again from the end to end evaluation and Fullstory records, which is an app that captures how customers interact with your product, there is too much text on each page of the onboarding flow that nobody reads. Also, the onboarding just serves as an introduction; it’s not very actionable and users don’t know what to do in the onboarding flow. Another problem is that since the flow has 7 steps, we saw many users drop out after each step.
With all this in mind, we made a quick change. We reduced the 7 steps onboarding flow to 5 and got rid of all the unnecessary text, replacing it with images that are easy to understand. More users are able to go through the onboarding flow now.
Another hypothesis we have is that active and engaged users will more likely to turn into paying customers. The more actions that users take within the free trial, the more features they use, the more engaged they are. This is what we did: we built a better connection between the onboarding flow with the product itself. We put actionable buttons on the onboarding flow, for example, “Create a dashboard” will take users directly into the dashboard editor; there are about 15% of users clicking on that button. Users are more engaged by taking more actions in the product.
Experiment 4: Improve Dashboard Editing Experience
Since the new dashboard and chart editor was redesigned, it has a much better user experience. With a shortened and simplified workflow, the users are able to create a dashboard with only a few clicks. Since we removed the technical barriers, the new users don’t need to learn the query language to create a chart or dashboard. The new users are able to visualize their raw data in just a few seconds! After the launch, we saw the dashboard creation rate increase from 5% to 25%, a huge increase.
The benefits of data-driven design and product-led growth are significant
It’s worth mentioning that many of these experiments only cost a few days to design and less than 2 weeks of engineering effort to build. While the investment is small, the return is significant. Also, since it’s agile development, the feedback loop is shortened, and we are able to test out hypotheses faster, delivering business value to our customers faster.
As designers, we want to explain what business value we can bring to the table. By utilizing data-driven design, we are able to use evidence to show the impact design has had on the business.
Continue to read As a designer, what business value do you bring to the table
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Special thanks to Lior Matkovitch and Frank Hattler for partnering in growth hacking, and Grace Noh and Bonnie Zhang for reviewing the article.
