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Hyper Geo-Targeting in AdWords Campaigns: How to Drive Store Traffic to Nationwide Locations

When a well-known, furniture retailer and manufacturer contracted Lever Interactive to manage their paid search campaign, they had several goals they wanted to achieve. Besides the most common goal we hear from all of our clients (please make our campaigns more efficient!), they wanted to make sure they were spending money in the right locations. Their unique challenge is that they are in 26 different DMAs across the United States with over 100 corporate store locations, and their goal is driving foot traffic to a store; not an online purchase or lead.

Previous to contracting Lever, this furniture retailer was working with another agency that targeted all 26 DMAs within each Google AdWords campaign. While it is great that they were targeting each of the markets, there were several problems we isolated right out of the gate.

  1. With all DMAs combined, the retailer had limited insight into which markets where driving conversions or cost.
  2. They were unable to control budget by DMA; one of the client’s ultimate goals.

DMAs are different shapes and sizes depending on the area. We discovered the previous agency was targeting DMAs without consideration of store locations. In one market, for example, they were targeting a huge metropolis but their store location was actually on the very outskirts of the DMA. The DMA spanned over 100 miles from one end to the other…which is a long way to drive to see furniture!

AdWords GeoTargeting Map

So, after digging into their historical data and identifying their “pain points” and objectives, we started outlining our process for restructuring the account with the following goals in mind:

  1. The retailer needed comprehensive, DMA level performance data so they could make better informed decisions on where to allocate their media spend based on in-store and web traffic.
  2. They needed to know that the users they were targeting geographically were qualified, and most likely to translate into store traffic. (Conversions were tracked based on visits to the store locator page).

In the end, Lever decided to restructure the account based on DMA, with a new account for each DMA, all housed under one MCC. This extensive campaign restructuring, that focused on store specific campaigns and included geo-targeting adjustments, help achieve our client’s goals. In just a few months, we were able to:

  • Decrease CPAs between 15-30% month over month since the account restructure.
  • Allocate budget amongst all 26 DMAs with budget goals that are dependent on in-store traffic. For example, if one market has been having slow foot traffic, then DMA budget is readjusted so that market can drive more web traffic in an effort to increase in-store traffic.
  • Reduce spend 44% month over month in their most troubled DMA that was producing unqualified traffic. This also reduced the DMA’s CPA by 54%.
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