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Robot

Unlocking the value of AI in Slack

Context

Research Objectives

Insights informed

In this exciting project, I set out to understand how Sales professionals (Slack's biggest customer segment) use AI in the context of Slack (either through app integrations or outside) and by extension, how AI could be used to bolster the UX. Cross-functional stakeholders included product designers and product managers. 

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  • Understand the current AI usage of Sellers

  • Identify where Slack AI can improve the process

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AI support for specific stages of the sales life cycle (developing and pitching a customer, nurturing the deal pipelines, and closing a deal)

Research Questions

How are sellers currently using AI in their workflows?

How does Slack AI play a role in the seller workflow?

What would sellers like to use AI for, ideally?

What should AI prototypes look like in Slack, specifically for sellers?

Methodologies

In-depth interviews

Concept Test

Process & Challenges

10 Sellers of various Slack products

Inclined towards using AI for work

Mix of current users and interested users

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Google Meet

I recruited participants personally via Slack using the data from the internal warehouse. Answers from the interviews were transcribed and I used thematic content analyses to derive insights. Based on these insights, the design team came up with prototypes which were then tested in quick-follow concept test sessions with the same participants.

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Challenges:

Potential for digression: AI has been making waves in the tech industry, so the topic was definitely exciting for all participants. The challenge was to ensure that participants stay on track and provide insights about the questions on hand, rather than talking about the industry/AI in general.

Impact

  • The insights clearly outlined what sellers are currently using AI for, and how they would like to use AI in the future, helping the product team prioritize what AI support should be developed

  • Concepts were created based on insights from the interview, which were tested in quick-follow sessions with the same participants.

  • The design team had clear recommendations to refer to, while developing the next iteration of AI concepts.

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