Ep 185: AKNF - Efficient Amazon Ads Spend Through Deep Segmentation with Clifford and Rob from Pilothouse's Amazon squad episode artwork

EPISODE · Mar 18, 2022 · 23 MIN

Ep 185: AKNF - Efficient Amazon Ads Spend Through Deep Segmentation with Clifford and Rob from Pilothouse's Amazon squad

from DTC Podcast · host DTC Newsletter and Podcast

Subscribe to DTC Newsletter - https://dtcnews.link/signup Rob and Clifford from Pilothouse recently attended a large Amazon vendor show, and the word everyone kept bringing up was efficiency. Everyone's looking for their Amazon Ad Spend to be more efficient. This podcast explains how to achieve Amazon Ads efficiency this through deep product listing segmentation: Work with Pilothouse Amazon ➝ https://pilothouse.co As Clifford details: Recently we've been REALLY segmenting keywords hard - we used to mention this as something to do for Sponsored Brand, but we're leaning into it for Sponsored Products as well. I'll lean into the classic example. Let's say we're Nike - selling a new, red and white basketball shoe.Our approach a year ago for sponsored products would have been something along the lines of: Build a generic keyword campaign ('basketball shoes') Build a competitor keyword campaign ('adidas basketball shoes') Build a competitor ASIN campaign Build a branded keyword campaign Build a branded asin campaign If there was some obvious segmentation we may do some ad groups within those campaigns. But we've now evolved that strategy to segment... everything. Instead of a branded keyword campaign - we'd have: Branded generic keywords ("Nike") Branded generic shoe keywords ("Nike shoes") Branded Nike basketball shoe keywords ("Nike basketball shoes") Branded Nike high-top shoe keywords ("Nike high-tops") Branded Nike Color keywords ("Red Nikes") Branded Nike Material keywords ("Polymer Rubber Nikes") So then the next question is... why? Why put in all this effort and time to segment them? 1st is efficiency - customers shopping for "Nike" aren't as interested in these shoes as a customer shopping for "Nike basketball shoes" - so we'll likely have different efficiency targets for these campaigns, and, thus, move bids differently depending on that. 2nd is for general brand knowledge/data cleanliness - it would be a pain to look inside different campaigns and pull out what keywords are performing and whatnot. This way, it can be seen at a glance really quickly. 3rd is something we came to learn over time - that campaigns with too many keywords, just seem not to perform as well (roughly 50-60+), so limiting it seems to help with delivery. There's a few more reasons, like difference is placement percentages, different negative keywords, etc. So - that's just the branded keywords - we'd do similar segmentation for all the generic keywords, competitor keywords, competitor ASINs, etc. And we'd build that entire suite of campaigns out for each individual product - and also for each ad type (Sponsored Product, Sponsored Brand to Store, Sponsored Brand Video, and Sponsored Display) Subscribe to DTC Newsletter - https://dtcnews.link/signup Advertise on DTC - https://dtcnews.link/advertise Work with Pilothouse - https://dtcnews.link/pilothouse Follow us on Instagram & Twitter - @dtcnewsletter Watch this interview on YouTube - https://dtcnews.link/video

Subscribe to DTC Newsletter - https://dtcnews.link/signup Rob and Clifford from Pilothouse recently attended a large Amazon vendor show, and the word everyone kept bringing up was efficiency. Everyone's looking for their Amazon Ad Spend to be more efficient. This podcast explains how to achieve Amazon Ads efficiency this through deep product listing segmentation: Work with Pilothouse Amazon ➝ https://pilothouse.co As Clifford details: Recently we've been REALLY segmenting keywords hard - we used to mention this as something to do for Sponsored Brand, but we're leaning into it for Sponsored Products as well. I'll lean into the classic example. Let's say we're Nike - selling a new, red and white basketball shoe.Our approach a year ago for sponsored products would have been something along the lines of: Build a generic keyword campaign ('basketball shoes') Build a competitor keyword campaign ('adidas basketball shoes') Build a competitor ASIN campaign Build a branded keyword campaign Build a branded asin campaign If there was some obvious segmentation we may do some ad groups within those campaigns. But we've now evolved that strategy to segment... everything. Instead of a branded keyword campaign - we'd have: Branded generic keywords ("Nike") Branded generic shoe keywords ("Nike shoes") Branded Nike basketball shoe keywords ("Nike basketball shoes") Branded Nike high-top shoe keywords ("Nike high-tops") Branded Nike Color keywords ("Red Nikes") Branded Nike Material keywords ("Polymer Rubber Nikes") So then the next question is... why? Why put in all this effort and time to segment them? 1st is efficiency - customers shopping for "Nike" aren't as interested in these shoes as a customer shopping for "Nike basketball shoes" - so we'll likely have different efficiency targets for these campaigns, and, thus, move bids differently depending on that. 2nd is for general brand knowledge/data cleanliness - it would be a pain to look inside different campaigns and pull out what keywords are performing and whatnot. This way, it can be seen at a glance really quickly. 3rd is something we came to learn over time - that campaigns with too many keywords, just seem not to perform as well (roughly 50-60+), so limiting it seems to help with delivery. There's a few more reasons, like difference is placement percentages, different negative keywords, etc. So - that's just the branded keywords - we'd do similar segmentation for all the generic keywords, competitor keywords, competitor ASINs, etc. And we'd build that entire suite of campaigns out for each individual product - and also for each ad type (Sponsored Product, Sponsored Brand to Store, Sponsored Brand Video, and Sponsored Display) Subscribe to DTC Newsletter - https://dtcnews.link/signup Advertise on DTC - https://dtcnews.link/advertise Work with Pilothouse - https://dtcnews.link/pilothouse Follow us on Instagram & Twitter - @dtcnewsletter Watch this interview on YouTube - https://dtcnews.link/video

NOW PLAYING

Ep 185: AKNF - Efficient Amazon Ads Spend Through Deep Segmentation with Clifford and Rob from Pilothouse's Amazon squad

0:00 23:11

No transcript for this episode yet

We transcribe on demand. Request one and we'll notify you when it's ready — usually under 10 minutes.

No similar episodes found.

No similar podcasts found.

Frequently Asked Questions

How long is this episode of DTC Podcast?

This episode is 23 minutes long.

When was this DTC Podcast episode published?

This episode was published on March 18, 2022.

What is this episode about?

Subscribe to DTC Newsletter - https://dtcnews.link/signup Rob and Clifford from Pilothouse recently attended a large Amazon vendor show, and the word everyone kept bringing up was efficiency. Everyone's looking for their Amazon Ad Spend to be more...

Can I download this DTC Podcast episode?

Yes, you can download this episode by clicking the download button on the episode player, or subscribe to the podcast in your preferred podcast app for automatic downloads.
URL copied to clipboard!