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From Product to Page One: How a Data and UX Mindset Accelerates SEO Results (with Neha Khanna from ZipRecruiter) | Ep. 17

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Content provided by ResultFirst. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ResultFirst or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

On Performance SEO Unpacked, host Ruchi Pardal is joined by Neha Khanna to explore how product thinking is transforming SEO at scale. Drawing from her experience at ZipRecruiter and Wayfair, Neha Khanna shares how moving away from technical checklists and toward user-centered problem-solving creates lasting growth.

Instead of chasing keywords, she focuses on systems that scale—measuring outcomes like conversion and engagement rather than impressions and rankings. Ruchi Pardal and Neha Khanna discuss AI not as a content factory, but as a storytelling co-pilot. They also break down how prioritization frameworks like RICE can bring clarity and confidence to enterprise SEO decisions, especially when getting stakeholder buy-in or forecasting results.

Whether you're facing stalled traffic, ineffective keyword strategies, or just looking to build SEO into product loops, this episode delivers tested strategies straight from the field.

👤 Guest Bio

Neha Khanna blends SEO and product management, with experience at organizations including Wayfair and ZipRecruiter. Known for shifting teams away from traditional SEO tactics and toward integrated, outcome-focused strategies, she prioritizes relevance, user intent, and business alignment.

Connect with Neha Khanna on LinkedIn.

📌 What We Cover

  • Why Neha Khanna stopped asking “what keywords should we rank for?”
  • A real example of solving post-click friction instead of expanding long-tail content
  • How SEO success changes when you integrate UX, data science, and engineering
  • Why traffic metrics without conversion are just vanity numbers
  • The AI-assisted content engine Neha Khanna helped build at Wayfair—and why human QA still matters
  • How to design AI prompts that scale storytelling, not just content
  • Using the RICE framework (Reach, Impact, Confidence, Effort) to prioritize SEO work
  • Why writing product-style briefs helps SEOs align cross-functional teams
  • The power of thinking like a user instead of optimizing for search engines

🔗 Resources Mentioned

  • RICE Prioritization Framework (Reach, Impact, Confidence, Effort)
  • ResultFirst: Visit for more SEO tips and strategies.
  • Connect with Ruchi Pardal on LinkedIn for a conversation about SEO.

If you enjoyed today's episode and found valuable insights for your business, be sure to subscribe to Performance SEO Unpacked for more expert discussions. Don't forget to leave a review and share this episode with your team or fellow marketers! Let's keep the conversation going—connect with us on LinkedIn and join the community of enterprise SEO enthusiasts.

  continue reading

18 episodes

Artwork
iconShare
 
Manage episode 490760714 series 3639269
Content provided by ResultFirst. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ResultFirst or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

On Performance SEO Unpacked, host Ruchi Pardal is joined by Neha Khanna to explore how product thinking is transforming SEO at scale. Drawing from her experience at ZipRecruiter and Wayfair, Neha Khanna shares how moving away from technical checklists and toward user-centered problem-solving creates lasting growth.

Instead of chasing keywords, she focuses on systems that scale—measuring outcomes like conversion and engagement rather than impressions and rankings. Ruchi Pardal and Neha Khanna discuss AI not as a content factory, but as a storytelling co-pilot. They also break down how prioritization frameworks like RICE can bring clarity and confidence to enterprise SEO decisions, especially when getting stakeholder buy-in or forecasting results.

Whether you're facing stalled traffic, ineffective keyword strategies, or just looking to build SEO into product loops, this episode delivers tested strategies straight from the field.

👤 Guest Bio

Neha Khanna blends SEO and product management, with experience at organizations including Wayfair and ZipRecruiter. Known for shifting teams away from traditional SEO tactics and toward integrated, outcome-focused strategies, she prioritizes relevance, user intent, and business alignment.

Connect with Neha Khanna on LinkedIn.

📌 What We Cover

  • Why Neha Khanna stopped asking “what keywords should we rank for?”
  • A real example of solving post-click friction instead of expanding long-tail content
  • How SEO success changes when you integrate UX, data science, and engineering
  • Why traffic metrics without conversion are just vanity numbers
  • The AI-assisted content engine Neha Khanna helped build at Wayfair—and why human QA still matters
  • How to design AI prompts that scale storytelling, not just content
  • Using the RICE framework (Reach, Impact, Confidence, Effort) to prioritize SEO work
  • Why writing product-style briefs helps SEOs align cross-functional teams
  • The power of thinking like a user instead of optimizing for search engines

🔗 Resources Mentioned

  • RICE Prioritization Framework (Reach, Impact, Confidence, Effort)
  • ResultFirst: Visit for more SEO tips and strategies.
  • Connect with Ruchi Pardal on LinkedIn for a conversation about SEO.

If you enjoyed today's episode and found valuable insights for your business, be sure to subscribe to Performance SEO Unpacked for more expert discussions. Don't forget to leave a review and share this episode with your team or fellow marketers! Let's keep the conversation going—connect with us on LinkedIn and join the community of enterprise SEO enthusiasts.

  continue reading

18 episodes

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