AI forecasting is HubSpot's AI-driven predictive forecasting solution. I worked with the team to develop this feature from zero to one in time for launch at HubSpot's INBOUND conference in 2023.

PROJECT TYPE - B2B SaaS APP
MY ROLE - SR. CONTENT DESIGNER
MY CONTRIBUTIONS - CONTENT STRATEGY, PRODUCT STRATEGY, TERMINOLOGY, NAMING, UX WRITING

The challenge

Customers need accurate forecasting to effectively manage their businesses. But fewer than half of the customers paying for HubSpot’s Sales Hub adopt the forecasting tool today.

Many customers rely on spreadsheets and other analytics tools that force them outside of HubSpot to help them hit their goals. This disconnected experience means they're getting less value out of their paid sales seats and are less incentivized to adopt other deal management tools in Sales Hub.

The outcome

AI forecasting uses past sales data to predict future performance. It enables teams to view a forecast prediction with no added manual effort, increasing efficiency and time to value. Since the accuracy of the AI forecast relies on quality deal data, it also incentives sales teams to adopt downstream deal management tools in Sales Hub.

The process

📚INTERNAL + INDUSTRY AUDIT - GETTING RAMPED UP

To understand what we needed to communicate and when, I had to ramp up fast. I reviewed:
- Existing terms and concepts in the tool
- Competitive benchmarking
- Writing for AI best practices
- Conversations with PD, PM, and our data modeler
- Product docs and existing research

🗣 NAMING - LEADING WITH CLARITY

Next, I ran a naming workshop for alignment, getting all core stakeholders invested and accountable early. I also led a formal naming process with the broader marketing and framework teams.

I provided periodic updates using Loom to stay lightweight and async while keeping everyone informed.

📝 MESSAGING - BUILDING TRUST AND CONFIDENCE

I also developed an information matrix outlining important information we needed to convey to customers and when. Messaging was anchored in customer research and industry expertise from our product team.

📚 TESTING AND ITERATION - REVIEW AND RESPOND WITHOUT LOSING MOMENTUM

Based on customer feedback, I worked with my design partner to design:
- Coaching tips to improve onboarding and better explain how predictions are calculated
- Empty states to educate customers on loading times and ways to improve accuracy
- Simplified metrics to work for a wider range of customers

😎 WHAT WENT WELL?

I was brought in on this project fairly early and the team quickly saw the value of content design. I was a true co-owner on the work, collaborating in real time with my design partner in Figma and leading wherever it made sense based on our individual strengths and interests.

We also designed with components, which was super helpful when we needed to pivot quickly with last minute string changes or unexpected asks from our legal and marketing teams.

🎢 WHAT WOULD I CHANGE?

I didn't anticipate that the naming of this feature would impact our framework team, so I didn't bring them in early in the process and the project was blocked (very briefly) while we worked with their information architect to resolve it. I updated my naming process to include that team as "informed stakeholders" in my DACI matrix so I don't bump up against that again going forward.

Up next:

Integrated Analytics System product hubs

The challenge

The outcome

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