Mar 30, 2014
Site Retargeting scenarios: Episode #1—JC Penney
JC Penney has been in the news a lot lately, and for all the wrong reasons. In 2011, the famed retailer was caught breaking the rules in attempt to boost its Google rankings. More recently, the company forced out CEO Ron Johnson after 17 disastrous months on the job.
So, what can JC Penney do to right the ship? There are a lot of good answers to that question. But you’ve got to start somewhere, and, for JC Penney, a new marketing technique known as Programmatic Site Retargeting (PSR) is an obvious place to start.
PSR is the more sophisticated version of a marketing technique known as Site Retargeting. With Site Retargeting, a brand can show display ads to users who have visited its site with the hopes of luring them back for conversions. The problem with this basic form of Site Retargeting is that it doesn’t do a very good job of distinguishing among the different types of users who visit a site. After all, some users are much more valuable to a brand than others.
PSR, by contrast, makes use of far more data, allowing a brand to score each (anonymous) visitor to its site based on how likely that visitor is to convert. These scores are then used to determine how high a brand should bid to serve an impression to the user in a real-time auction.
So, how could JC Penney put PSR to work? Let’s look at some examples.
Example 1: The Jobs Page Visitor
Let’s start by looking at someone who arrives at the jobs page on the J.C. Penney site. With simple Site Retargeting, this user might end up seeing a lot of J.C. Penney ads as she browses the web. But PSR takes into account the search term that brought the user to the site as well as the page the user looked at. With that data at hand, JC Penney would know to not serve this user an ad for products, since someone searching for a job at Penney’s does have intent to purchase a product.
Example 2: The Serious Shopper
Now let’s look at a user who arrives at the J.C. Penney site after searching for short-sleeved sweaters on J.C. Penney's site. Let's say this user looks at short-sleeved sweaters in a number of different styles and spends several minutes on each page. The user also clicks to see additional images of the sweaters before leaving for another site. This user is revealing very clear intent to purchase a short-sleeved sweater. if JC Penney was using PSR, they would place a high bid to serve the user a display ad for its sweaters.
Example 3: The Potential Conquest
Most of the time, scoring a user isn’t as straightforward as the above examples suggest. Take the user who arrives at the diamond ring section of JC Penney’s site but only browses for a very short period and doesn’t click on any of the products. This user hasn’t shown a strong intent to purchase, and without any additional data, this user might only justify a low bid. But, with PSR, there’s always more data. Let’s say this same user had also searched Google for “Kay Jewelers diamonds.” Now. JC Penney has another valuable signal and a chance to steal away a competitor’s customer. It’s time to raise that bid.
Example 4: The Redundant Ad
Let’s take one last example, just to illustrate the range of data available with PSR. In this example, the user visits the page for a short-sleeved sweater, which might indicate intent to buy. But CRM data reveals that the user purchased the very same sweater only a few days ago, and thus has little-to-no value for retargeting. That CRM data just saved JC Penney a little bit of money. Multiple that money by millions of visitors each week, and you begin to see why PSR could help turn JC Penney around in a hurry.