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Using AI to advertise mobile games - Günay Aliyeva (Gamelight)

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Manage episode 430194198 series 3587809
Contenu fourni par Remerge. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Remerge ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Günay is the co-founder of Gamelight, a user acquisition platform for app developers and a game and app recommendation platform for users. Gamelight’s success can be attributed to its powerful AI algorithm. Learn how UA managers are leveraging tech to pair users with mobile games that they’ll love.

Questions Günay Answered in this Episode:

  • How does Gamelight work?
  • What technology are you leveraging to run your platform?
  • Has Gamelight had this technology from the start?
  • What is your background and how did you come to start Gamelight?
  • What have you learned from building this AI algorithm?
  • How does that change the role of a UA manager?
  • What have you seen that works really well for the games that advertise on your platform?
  • How do you convince games to advertise on your platform?
  • How do you acquire users to your recommendation platform?
  • What do you see coming ahead in the industry?

Timestamp:

  • 1:53 What is Gamelight?
  • 3:27 The AI technology behind Gamelight
  • 6:58 Günay’s story
  • 9:18 What we’ve learned from building our AI algorithm
  • 11:23 The role of the UA manager
  • 15:27 What draws publishers to advertise our platform?
  • 17:23 How our recommendation platform works
  • 21:38 How I become a mobile gamer
  • 24:52 What’s ahead

Quotes:

(5:08-5:27) “We let the algorithm decide because it’s way more granular and can analyze more data points than a human. This is how it brings much better UA results for our advertisers because it can pick every single user that could be the best fit for them instead of taking average gender or age for users.”

(13:04-13:13) “[Humans] are more creative. They can have better ideas on what to do and how to plan UA campaigns in a more strategic way.”

Mentioned in this Episode:

  continue reading

199 episodes

Artwork
iconPartager
 
Manage episode 430194198 series 3587809
Contenu fourni par Remerge. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Remerge ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

Günay is the co-founder of Gamelight, a user acquisition platform for app developers and a game and app recommendation platform for users. Gamelight’s success can be attributed to its powerful AI algorithm. Learn how UA managers are leveraging tech to pair users with mobile games that they’ll love.

Questions Günay Answered in this Episode:

  • How does Gamelight work?
  • What technology are you leveraging to run your platform?
  • Has Gamelight had this technology from the start?
  • What is your background and how did you come to start Gamelight?
  • What have you learned from building this AI algorithm?
  • How does that change the role of a UA manager?
  • What have you seen that works really well for the games that advertise on your platform?
  • How do you convince games to advertise on your platform?
  • How do you acquire users to your recommendation platform?
  • What do you see coming ahead in the industry?

Timestamp:

  • 1:53 What is Gamelight?
  • 3:27 The AI technology behind Gamelight
  • 6:58 Günay’s story
  • 9:18 What we’ve learned from building our AI algorithm
  • 11:23 The role of the UA manager
  • 15:27 What draws publishers to advertise our platform?
  • 17:23 How our recommendation platform works
  • 21:38 How I become a mobile gamer
  • 24:52 What’s ahead

Quotes:

(5:08-5:27) “We let the algorithm decide because it’s way more granular and can analyze more data points than a human. This is how it brings much better UA results for our advertisers because it can pick every single user that could be the best fit for them instead of taking average gender or age for users.”

(13:04-13:13) “[Humans] are more creative. They can have better ideas on what to do and how to plan UA campaigns in a more strategic way.”

Mentioned in this Episode:

  continue reading

199 episodes

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