FourKites Innovation, Technology & Agility

How does your team capture customer feedback? 

We have several ways we collect customer feedback, including NPS and CSAT surveys, which measure whether users can meet business objectives, usability and loyalty. Our products and community articles let users give a ‘thumbs up’ or ‘thumbs down’ regarding whether their questions were answered. 

Additionally, we host events to capture feedback — one of which is our Innovation Workshops. Hosted annually, these include up to 10 customers across industries and roles to collaborate in a design-thinking session with our UX designers and a product manager. We host four concurrently and have covered topics like “designing the unmanned gate” or “elevating the end-customer experience.” The output of these workshops accelerates our development of solutions.

Another is our biweekly feedback calls. Again, the audience is composed of customers from different enterprise companies, all leveraging FourKites to achieve their business objectives. On these calls, our product team completes discovery or validation designs before we hand them off to our development team. These are wonderful forums to learn more and build better solutions — they also let customers collaborate with peers and influence our roadmap and product.

Is there a community aspect to FourKites’ customer feedback?

We have a robust online customer community where we host the FourKites Idea Exchange. Customers submit enhancement requests and upvote others’ suggestions for product managers to review when grooming their backlog and building their roadmap. These inputs help prioritization, including de-prioritizing requests that don’t receive wide support.  

We celebrate customers who suggested and partnered with us on solutions brought to market through our Innovation Partner Program, which includes 98 partners. 

Cassie Garrison, supply chain manager at HNI Corporation, is one of those innovators — she suggested additional configurations to our notifications set-up, making them more dynamic. 

“At HNI, we work collaboratively to make sure our customers have a best-in-class delivery experience,” Cassie told us. “Working with the FourKites team to add additional configurations to the business rules ensures our end users and third-party warehouses know where their truck is at and if it’ll be on time.” 

Proactive communication with stakeholders is an objective for many customers — by co-innovating with FourKites, HNI boosted its productivity and helped other customers improve their operations.

What role does customer feedback play in roadmapping for product managers?

While we have many ways to listen to our customers, it’s important for product managers to also be in tune with the macro-environment, be aligned with business objectives and leverage a standardized framework when building a roadmap. We are set up to build customer-centric roadmaps, but prioritization is dynamic — there are times when features or functionality are “not planned” or “not planned yet” and that’s important to communicate to the customer, too. Setting expectations about how customer feedback is being prioritized is key.

How is FourKites leveraging AI right now, and where does your company hope to grow in this area?

We use a mix of enterprise, open-source and custom-built AI tools. This approach gives us the flexibility to meet our business needs while balancing factors such as cost and customization. In our engineering workflow, we’ve integrated these tools to boost quality and ease of use from the start of ticket creation. We use an open-source plugin for Jira to ensure high-quality tickets go into the sprint. Once a developer starts working on a ticket, we use tools, such as GitHub Copilot, to help write code and unit tests. Our testers have created in-house workflows that use ticket descriptions and acceptance criteria to automatically generate test cases and code.

We use these tools in our processes as much as possible, making them easy to adopt while providing increased efficiency and enhanced capabilities. We’re always looking for new ways to expand our AI capabilities, tailoring experiences for each group and addressing specific needs. This ongoing effort not only boosts our internal productivity, but also helps our clients by automating the identification of bug root causes.

What mentorship, training, education and support opportunities are in place for AI technologists at FourKites? 

We have a thorough onboarding and training program for all engineers, regardless of their background. This ensures everyone understands the basics of our tools and development processes for building our own tools. The program includes LinkedIn courses and articles that provide a solid grasp of the tools we use. To cap off the training, each engineer must complete a project, chosen by their team manager, that can be solved using AI. This hands-on experience helps everyone get comfortable with both basic and advanced concepts needed in our AI-driven workplace. 

The rapid progress in generative AI has made creating tools more accessible than ever. Engineers can now build solutions that were once thought impossible or limited to research. Our training helps every team member understand not just the technical side of these tools, but also gives them the confidence to use them in real-world situations. By investing in this training and mentorship, we set up our engineers to contribute to projects from day one, helping them grow personally while driving innovation for the company.

What does continuous learning and project support look like on your engineering teams, and what makes FourKites a good choice for technologists fairly new to AI?

Beyond our structured training and project support, we foster a strong sense of community within our dev teams. We hold monthly group meetings and have dedicated Slack channels where team members share success stories, swap new insights and discuss the latest AI developments. These spaces create a collaborative environment that encourages ongoing learning and helps engineers stay up to date on best practices and new trends. 

We put a big emphasis on mentorship and knowledge-sharing. Each business unit is encouraged to have its own data scientist in addition to our main data science team. This helps them move quickly with AI advancements. Our senior engineers actively guide junior engineers, offering feedback and real-world advice to speed up the learning curve for those new to AI. We also support learning through access to top-notch tools, webinars, research papers and regular AI workshops from our partners at AWS, Azure, MongoDB and others. This mix of community, mentorship and ongoing education makes our company a great place for those early in their AI careers to grow, try new things and succeed.