Airtable AI for Product teams
Airtable
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Airtable
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Airtable AI for Product teams
Product development is a challenging process to get right. From analyzing customer feedback to creating product requirements documents, there are a slew of operational subprocesses, tasks, and actions that guide the product process.
Our end-to-end product workflow consists of four phases: Discovery, Planning & Prioritization, Execution & Delivery, Measurement. In this article we will dive into how AI can fit into each of those phases.
Discovery
Prioritize features effectively by summarizing and categorizing customer feedback. Streamline resourcing by automatically routing plans to the right teams.
The more customer insight you can infuse in your product development life cycle, the more informed you will be about finding the right solution. Here are a few ways to leverage AI in the discovery phase:
Collect feedback from a wide variety of sources. Whether you have data from social media, the app store, feedback forms, customer calls, or review sites, quickly translate feedback into a common language for analysis. Extract key customer pain points from long customer call transcripts or from extensive data that would take too long to review.
Categorize feedback to ensure it gets to the right person for review. Start by summarizing long or poorly-written feedback for clarity. Then have AI apply categories or tags by product area or team for quick analysis or routing to the right group for review. Or try having AI determine sentiment of the feedback so you can filter more effectively.
Make better product development decisions, faster by using AI to help tag, categorize, and summarize customer feedback, giving you more insight with less time spent.
Planning & Prioritization
Automate translations and localization for every market on every product or new feature you launch, without the manual lift. Quickly determine product development prioritization using customer data.
Spend less time prioritizing and more time executing by assigning customer value to product features by pulling out clear insight. Here are some ways to use AI in the planning and prioritization phase:
Prioritization of key product opportunities. Make more informed decisions about what features to prioritize and give visibility into the priority of product opportunities by automatically matching customer feedback to features.
Align your product work to company or team goals. Write goals at the individual, team, or organization level before you kick off your work. Determine which product priorities map to strategic initiatives.
Prioritize feature development using customer data. Match features to the interested customers or pain that is identified in customer feedback building a business case for your product feature with key stakeholders.
By using AI to link features to customers or directly to a revenue opportunity, you can make quicker, more effective prioritization decisions and highlight the impact of the feature.
Execution & Delivery
Multiply your outputs. Automatically transform your Product Requirements Docs into support articles, FAQs, team training and more.
Leverage AI to supercharge execution and delivery of responsibilities like determining project tasks or generating documentation. Here are ways to use AI during the execution and delivery phase:
Report up the chain on project progress over time. Summarize the content from engineering tickets, standup reports, or other project tracking tools to determine project status. Automatically send a summary to leadership on a given timeframe or at key project milestones.
Generate a list of project tasks. Break down projects into digestible tasks that product development needs accomplish for launch.
Launch products faster by generating draft launch materials. Generate drafts of launch materials using launch documentation. Give key stakeholders like support, marketing, and sales the materials they need for launch.
AI can improve visibility into the product development process, automate time-consuming tasks like writing different versions of documentation, and help you launch faster by generating drafts of launch materials.
Measurement
Find hidden insights and make sounder decisions by summarizing feedback and sharing with key stakeholders in one workflow.
Quickly track key product metrics to gauge product performance or determine sentiment from customer feedback. Here are ways to use AI during the measurement phase:
Track product metrics to gauge awareness, adoption, retention. Summarize core metrics and product outcomes, extracting core insights. Automatically share insights with the team on any cadence.
Track product sentiment and make improvements. Categorize support tickets, social media posts, customer feedback, etc. by product area. Summarize the feedback and determine appropriate next steps.
Track business metrics like sales impact from products. Find linkages between features deployed and customer purchase patterns. Use these numbers to set future revenue targets and forecasts.
By automatically tagging and categorizing data, you can analyze metrics faster, making better product decisions and iterating more quickly.
Try it now
There is no shortage of ways to incorporate AI into your end-to-end product workflows. Don’t waste time on manual, everyday tasks. Instead, leverage AI directly within the tools that manage your product process and customer data to make smarter, more informed decisions.
About the author
Airtableis the digital operations platform that empowers people closest to the work to accelerate their most critical business processes. Across every industry, leading enterprises trust Airtable to power workflows in product operations, marketing operations, and more – all with the power of AI built-in. More than 500,000 organizations, including 60% of the Global 2000, rely on Airtable for digital operations and citizen development to help transform how work gets done.
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