Transformed LinkedIn Sales Navigator by integrating AI to automate key tasks, enabling sales professionals to be more effective (doing the right things) and more efficient (doing things right) which shape the future vision of the product.
Workshop / Sprint
Sketch and wireframe
Interaction and prototype
Visual design
User research with UXR
5 designers
1 PM
1 Eng lead
1 UXR
Design and research: 6 months
Main feature BETA released late 2023
Successfully integrated into the product roadmap in 2024
Some features from this vision exploration were initially released in a BETA version to a select group of users. The BETA release allowed us to gather valuable feedback and make necessary adjustments before a full rollout.
The early feedback from the beta users has been positive. Users appreciated the intuitive nature of the AI Assist Search, noting how it simplified the process of finding relevant leads and information. The Account IQ feature was particularly well-received for its ability to provide comprehensive and actionable insights, which helped users feel more prepared and confident in their interactions with clients.
This positive reception has validated the team's efforts and the chosen direction for the product. The successful BETA release has set the stage for further development and refinement of these features, as well as the introduction of additional AI-driven capabilities in the upcoming roadmap.
Users appreciated the intuitive nature of the AI Assist Search, noting how it simplified the process of finding relevant leads and information. However, users expect “AI Assisted Search” to be much more powerful and go beyond existing filters and taxonomy.
The Account IQ feature was well-received for its ability to provide comprehensive and actionable insights about an account, which helped users feel more prepared and confident in their interactions with clients.
Would like to skip the design process? Check out the final design and recap directly.
LinkedIn Sales Navigator is a specialized tool designed for sales professionals. They leverage the platform to identify potential accounts and leads, receive personalized lead recommendations and insights, and reach out directly to prospects via InMail.
For instance, a sales representative might use Sales Navigator to identify key decision-makers within a specific industry and initiate conversations that could lead to valuable business opportunities.
"Sales Navigator is like a Formula 1 – an incredibly powerful car that very few people know how to drive" - Customer quote
On a weekly basis, 75% of our users are not getting a Qualified Lead (ideal customer with the intent to buy) and 98%1 are not taking full advantage of the product. Users often struggle with information overload due to the vast amount of data available, making it difficult to prioritize leads effectively. Additionally, the manual effort required to analyze prospects' profiles and engage with them can be time-consuming and inefficient.
1: As of May 2023, only 2% of all Sales Navigator seats (~30K seats) are using our 4 core features weekly (Search, Save, InMails /Message and positive alerts engagement)
To solve the problem, and considering AI as a new technology, the team would like to Transform Sales Navigator by automating the majority of tasks, enabling sales professionals to be more effective (doing the right things) and more efficient (doing things right). With that, we aim to transform the entire product with the following goals:
For this project scope, the team decided to focus on B2B account-centric sales rep in hunter roles (eg: SDR, Account Executive), farmer roles (eg: Relationship Managers, Account Managers), and hybrid. This approach was selected because these roles represent the greatest business opportunities and value, with the potential to later expand insights to broader user personas.
Since AI is a new technology, we also align on unified AI principles to ensure design quality and consistency, while fostering trust, transparency, and ethical use in all aspects of our AI-driven solutions.
During the exercise, we first looked into the entire sales journey and aligned on what part of the process can be the most valuable and easiest to automate are also the activities that we are most uniquely positioned to help with.
Then during brainstorming sessions, we encouraged open and unrestricted thinking, pushing the boundaries of conventional approaches to address the core Jobs To Be Done (JTBD). We explored the potential of leveraging artificial intelligence (AI), generative AI (GAI), and large language models (LLMs) to envision a bold and transformative future for Sales Navigator.
There were a lot of great ideas generated from the brainstorming session. Taking these ideas:
Together with the PM and UXR, we synthesized and prioritized ideas based on value to users, Sales Navigator most uniquely positioned to help with, and achievability. This process also involves actively presenting and getting feedback from XFN leadership.
Incorporating a narrative framework, the team collaborated to develop a comprehensive user narrative that captures the overall user flow. This narrative served as a storytelling tool to illustrate how users would interact with LinkedIn Sales Navigator, incorporating the new AI-driven ideas.
When exploring potential models for integrating AI into LinkedIn Sales Navigator, I considered two distinct approaches:
Each model presents unique benefits and challenges. The conversational interface-dominated model offers a more intuitive, hands-on experience, ideal for users who prefer a natural language-driven approach. On the other hand, the JTBD-driven traditional interface provides a more familiar and structured experience, catering to users who appreciate clear, task-specific workflows. The inclusion of conversational elements in the latter model enhances its flexibility and responsiveness, allowing for a blend of traditional and innovative interaction methods.
Taking the design with narrative, we got feedback from internal and external users, aiming to surface top risks and provide direction for next design and strategic steps. We also present our progress to the XFN leadership on a weekly basis to make sure leadership buy-in and alignment. Here are a few top feedback from user research and Beta release that we further iterate and address:
After careful consideration and multiple rounds of review, we decided to proceed with the second option: a JTBD-driven traditional interface with integrated conversational features. To further refine this approach, we expanded the user narrative to illustrate how this model would function for a typical user persona, highlighting key interactions and benefits.
Through a rigorous and iterative process, we were able to craft a user narrative showcasing the forward-looking product vision, which not only aligns with typical user flows but also ensures that interactions are intuitive and essential information is readily available.
Would like to learn more about specific iteration process in this vision project? Let's talk!
Clear communication about how the AI functions and the data it uses fosters understanding and trust. Providing users with control over their experience enhances their sense of agency, while feedback mechanisms allow them to contribute to improvements. Addressing ethical considerations, such as potential biases, is crucial for building confidence in the system. Additionally, offering educational resources helps users grasp AI capabilities and limitations, further reinforcing trust in the technology.
By framing the solution in terms of the user's experience, needs, and journey, narratives can highlight the real-world impact of an idea and demonstrate how it solves specific problems. They are especially useful in UX design and product development because they help stakeholders visualize how the product will be used in context.
It can also help the team to see the holistic picture of how the entire product work when there are multiple ideas involved.
First, defining clear objectives and scope ensures alignment across all stakeholders, at the beginning of the project we set the foundation for success by clarifying goals, deliverables, and boundaries. To maintain cohesion, fostering collaboration and alignment among cross-functional teams is crucial; so I lead workshops and open discussions to create shared understanding. Effective communication is key to keeping everyone on the same page—I ensure regular updates, transparent reporting, and stakeholder check-ins help address concerns and adapt to changes. Finally, a comprehensive plan provides a roadmap for progress. Along with the team, we break down complex tasks into manageable milestones while prioritizing flexibility to accommodate unexpected challenges.
In order to get stakeholder buy-in, we engage key stakeholders from the outset and keeping them informed throughout the process can create a sense of ownership, increasing their likelihood of support.
In every stakeholder review, we create a working prototype of the user narrative with strong visual aids, which help stakeholders better understand the vision and potential of our idea. It turns abstract concepts into something tangible, also, during the presentation, we try to highlight the business and user impact with data. In this project, I also got a chance to directly present our innovative ideas to CEO in the same room!
Another effective way is to demonstrate small-scale success through Beta testing. It can show quick wins and increase stakeholder confidence.
