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Farhad Divecha

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Content provided by Kevin Ryan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kevin Ryan 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://ro.player.fm/legal.

Farhad Divecha built an agency from the ground up, has experience in every area of digital, and is making a lot of news lately with his tremendous client base. Farhad came from India, came to do his graduate work in the U.S., and now lives in the UK, running AccuraCast. In this episode, Farhad talks about the things people are doing wrong (and right) in the influencer marketing world, the massive influx of data in the digital world and how it can help us, and real-world examples of AI pulling data together in a way we otherwise wouldn’t have been able to.

Takeaways:

[4:42] Influence marketing is in the limelight now, but if you sit around and wait, you will miss the boat. The whole ecosystem is in flux, and as marketers, we get an inside view from all three angles: the influencers, brands, and what the platforms think of the whole ecosystem.

[10:16] Gymshark is an example of a brand that does influencer marketing right and who lends itself to the influencer marketing ecosystem.

[11:22] When you force influencer marketing on a brand or concept that doesn’t work, that is when the failure starts happening.

[12:03] Influencer marketing isn’t new. Brands have been used to paying athletes and celebrities for what to do, say, and wear for quite some time now. However, the medium has changed and now it is possible for many different people to become influencers and make money from brands.

[16:55] Brands need to do their research when looking at what influencers they want to work with and invest money in. They need to gather the data and really study the influence they have according to their following. For example, some influencers have smaller numbers but more dedicated followers than those with huge followings.

[17:02] Farhad and his team looked at the influence per one thousand followers of many online influencers and found as their actual volume of influence grew, the influence per thousand started declining. Often times there is a mass gathering in followers, but they aren’t actually looking to them for advice on specific purchases.

[29:59] Many times, the people that would be the best influencers are too busy doing their jobs to seek the online attention.

[35:30] Brands are realizing the same principles as previous years need to be applied in this new media, and they use their compiled data to find out which influencer fits with their audience.

[37:58] Farhad and Kevin discuss examples where artificial intelligence stitches data together to form solutions that create a buying funnel with powerful results. Using attribution models, they can target user behavior in a way that creates a specific campaign that makes sense to the whole discovery and purchase process.

Quotes:

  continue reading

61 episoade

Artwork

Farhad Divecha

TMI with Kevin Ryan

published

iconDistribuie
 
Manage episode 236654299 series 2333601
Content provided by Kevin Ryan. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kevin Ryan 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://ro.player.fm/legal.

Farhad Divecha built an agency from the ground up, has experience in every area of digital, and is making a lot of news lately with his tremendous client base. Farhad came from India, came to do his graduate work in the U.S., and now lives in the UK, running AccuraCast. In this episode, Farhad talks about the things people are doing wrong (and right) in the influencer marketing world, the massive influx of data in the digital world and how it can help us, and real-world examples of AI pulling data together in a way we otherwise wouldn’t have been able to.

Takeaways:

[4:42] Influence marketing is in the limelight now, but if you sit around and wait, you will miss the boat. The whole ecosystem is in flux, and as marketers, we get an inside view from all three angles: the influencers, brands, and what the platforms think of the whole ecosystem.

[10:16] Gymshark is an example of a brand that does influencer marketing right and who lends itself to the influencer marketing ecosystem.

[11:22] When you force influencer marketing on a brand or concept that doesn’t work, that is when the failure starts happening.

[12:03] Influencer marketing isn’t new. Brands have been used to paying athletes and celebrities for what to do, say, and wear for quite some time now. However, the medium has changed and now it is possible for many different people to become influencers and make money from brands.

[16:55] Brands need to do their research when looking at what influencers they want to work with and invest money in. They need to gather the data and really study the influence they have according to their following. For example, some influencers have smaller numbers but more dedicated followers than those with huge followings.

[17:02] Farhad and his team looked at the influence per one thousand followers of many online influencers and found as their actual volume of influence grew, the influence per thousand started declining. Often times there is a mass gathering in followers, but they aren’t actually looking to them for advice on specific purchases.

[29:59] Many times, the people that would be the best influencers are too busy doing their jobs to seek the online attention.

[35:30] Brands are realizing the same principles as previous years need to be applied in this new media, and they use their compiled data to find out which influencer fits with their audience.

[37:58] Farhad and Kevin discuss examples where artificial intelligence stitches data together to form solutions that create a buying funnel with powerful results. Using attribution models, they can target user behavior in a way that creates a specific campaign that makes sense to the whole discovery and purchase process.

Quotes:

  continue reading

61 episoade

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