PLA 2.0: Strategies to Improve Your Program and Your Performance

By — 11.17.16

PLA 2.0

The growth of Google’s Product Listing Ads (PLAs) over the last few years has been fueled by the growth in mobile. With the majority of searches taking place on smartphones, Google reported that 30% of all purchases are now being sourced by these devices1. Just last year, we saw PLA’s overtake text ads in terms of click share, and in the first half of this year they account for 54%2 of paid search clicks and 53%2 of wallet share, and we expect this figure to grow as the holidays approach.

While you’d have a hard time finding a retailer who isn’t investing in PLAs, even large multichannel retailers, who are heavily invested in PLAs, struggle to fully optimize their existing programs. Adlucent has found huge performance opportunities when taking over PLA account management and after implementing our unique methodology we are able to make significant performance gains.

By implementing these strategies we have grown PLA revenue by as much as 3.7x and quadrupled (4x) traffic for accounts.

Because of this we partnered with Google to develop strategies that retailers can use to take their PLA program to the next level. Introducing: PLA 2.0. Working with Google we have developed these advanced strategies to take product ad programs to the next level of performance. Read our latest white paper to learn tried and true ways to reduce wasted ad spend and identify new growth opportunities in your PLA program.

Download our latest white paper to learn:

  • How restructuring your account to be as granular as possible will help uncover important insights and drive needed performance gains.
  • How to improve your bid management to minimize wasted ad spend and ensure you’re growing efficiently.
  • How to use consumer, product, and feed data to understand the intent behind a consumer’s search and then match it to products with the highest probability of leading to a conversion.

Click here to learn how to take your PLA program to the next level with PLA 2.0 Strategies to Improve Your Program and Your Performance!

 

1 Google data Sept 2014 vs Sept 2015

2 Adlucent data 01/01/16-06/30/16


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