
engineering.linkedin.com/ab-testing/xlnt-platform-driving-ab-testing-linkedin
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XLNT Platform: Driving A/B Testing at LinkedIn
A/B testing is an indispensable driver behind LinkedIn’s data culture. We run more than 200 experiments in parallel daily and that number is growing quickly. We realized early on that ad hoc testing would only take us so far. We needed to change our approach to allow us to quickly quantify the impac
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XLNT Platform: Driving A/B Testing at LinkedIn
A/B testing is an indispensable driver behind LinkedIn’s data culture. We run more than 200 experiments in parallel daily and that number is growing quickly. We realized early on that ad hoc testing would only take us so far. We needed to change our approach to allow us to quickly quantify the impac
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XLNT Platform: Driving A/B Testing at LinkedIn
A/B testing is an indispensable driver behind LinkedIn’s data culture. We run more than 200 experiments in parallel daily and that number is growing quickly. We realized early on that ad hoc testing would only take us so far. We needed to change our approach to allow us to quickly quantify the impac
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12- titleXLNT Platform: Driving A/B Testing at LinkedIn | LinkedIn Engineering
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5- og:titleXLNT Platform: Driving A/B Testing at LinkedIn
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- og:urlhttps://engineering.linkedin.com/ab-testing/xlnt-platform-driving-ab-testing-linkedin
- og:descriptionA/B testing is an indispensable driver behind LinkedIn’s data culture. We run more than 200 experiments in parallel daily and that number is growing quickly. We realized early on that ad hoc testing would only take us so far. We needed to change our approach to allow us to quickly quantify the impac
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- twitter:urlhttps://engineering.linkedin.com/ab-testing/xlnt-platform-driving-ab-testing-linkedin
- twitter:titleXLNT Platform: Driving A/B Testing at LinkedIn
- twitter:descriptionA/B testing is an indispensable driver behind LinkedIn’s data culture. We run more than 200 experiments in parallel daily and that number is growing quickly. We realized early on that ad hoc testing would only take us so far. We needed to change our approach to allow us to quickly quantify the impac
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