November 08, 2012
Case Study

Offer Relevance: How achieved an 18% increase in price quote requests through personalized targeted marketing

SUMMARY: Since it began as a paper guide in 1966, Edmunds has focused on providing customers with accurate and relevant automobile buying information. Through, the company aims to offer the same focus, by utilizing technology that allows it to remain current. But, with a reach of 15 million,'s issue lied in constructively using data from these visits to connect those who would benefit most with partner-related price evaluations.

This case study covers the process implemented to optimize its price quote suggestion and create the most valuable website experience for its consumers.
by Courtney Eckerle, Reporter


According to Seth Berkowitz, President and Chief Operating Officer,, the constant challenge that led to re-evaluating the's partner-related price evaluations system was to provide the best website experience for its consumers.

"We have a website that is visited by north of 15 million people, and we experience in the neighborhood of 200 million page views a month. Even in that context, there is actually a finite amount of space to promote various partner-related opportunities on the website for our sponsors, advertisers, or for our dealer partners.", an auto buyer’s resource, wanted to bring in a level of personalization to its offers that would be an asset to its relationships with both partners and the consumer.

"We want to make sure that the consumer experience is as good as possible, and yet we also want to ensure that consumers have the opportunity to see what our partners and sponsors and advertisers have to offer," Berkowitz added.

He said the challenge became finding a way to "strike that balance in the right way. … It has been determined that the answer lies in understanding people’s propensities better, that if we know which sub-segment of our audience is most interested in a specific opportunity, that we will be better off."

To provide that service to its consumers, strove in this effort to ensure opportunities to receive price quotes that would reach the people most likely to appreciate the suggestion. It was important to not to burden the entirety of its visitors "by using real estate on the website that will be a bother to them," said Berkowitz.


"The particular product that we decided to focus on was what we would call, ‘Free Price Quotes,’" said Berkowitz.

In this process, the consumer would be prompted to submit their first and last name, email address and, in some cases, their phone number. This would lead to having a dealer respond with price quotes for the product they were viewing.

"Some people want and desire that service because they think that getting quotes from three or four dealers will enable them to get the car at the best possible price. Other people just don’t want to deal with that hassle," Berkowitz explained.

The issue with that service, he added, is "if you present that opportunity to 100% of the audience, you are over targeting because you are showing it to people that want it, but also showing it to a lot of people that don’t."

To solve this issue with the service, began collecting behavioral data to enable them to only offer the price quotes to consumers who would be most likely to want them.

Step #1. Take a subsegment of the audience to test consumer reaction

Berkowitz said began testing by randomly offering the free price quote to a small percentage of its audience, without factoring in behavioral data.

By initially offering price quotes randomly, Berkowitz says could better gauge how factoring behavioral data into whom to make the offers to would improve results and service, as opposed to the random offers.

Offering to a random group initially, was able to slowly test. Berkowitz said this also allowed the company to understand, "if you show this offer, how are people going to respond? We did that for a very short period of time, just to understand the math of that."

Searching to increase upon the results seen from the random sample, began applying behavioral data into its process.

Step #2. Gather behavioral data

With this campaign, strove to "to get a better understanding into … what are the types of behaviors that people demonstrate on our website that indicate that they are actually desirous of using a free price quotes service versus those that aren’t interested," Berkowitz said.

To begin accomplishing that, "years’ worth" of click stream data had to be analyzed, according to Berkowitz, in order to assess which consumers would most likely take advantage of a dealer price quote:
  • Repeat vs. non-repeat visitor

  • Make and model of the vehicle

  • Time of day

  • Day of the week

  • Geographical location of the user

  • Pages viewed

All of these behaviors were looked at to determine the likelihood of a visitor to the site being interested in receiving a free price quote. For instance, it was discovered that 13% of mobile visitors to, if they agreed to location-sharing, were within 600 feet of a car dealership.

According to Berkowitz, when someone visits the website, "We basically make a determination based on their behaviors as they look on each page. Are they more or less likely to respond to a free price quote or not?"

Step #3. Continue testing and expand

The necessity of becoming more discerning in suggesting price quotes became apparent, especially to achieve’s goal of ensuring that "we are really doing a service by our users by only showing the offer to those that are most interested," said Berkowitz.

The results showed "an increasing number of people responding to the offers over time as a result of showing it to the right people, and leaving everybody else alone who would be less interested in it."

Berkowitz said testing is a part of’s regular process as a whole, and is necessary to consistently improve the consumer experience.

"We do give ourselves the liberty to carve off anywhere between 10-15% of the audience at any given time for a short period to do testing in the interest of improving the consumer experience for everybody as a whole. We are now doing that on a continuous basis with all kinds of tests to figure out what are the right offers, and whom do we need to be showing them to."


Berkowitz spoke of the results his team has seen from testing its offers on a small percentage of its audience.

"So now, after going back and forth for a good three months and a fair amount of trial and error, we are at a point where we are seeing an average of an 18% increase in the amount of people responding to Free Price Quotes," said Berkowitz.

This increase through the personalization has also led to a better relationship with advertisers, according to Berkowitz.

"We are providing more value to our partners as a result of this implementation, and we have seen our sales rate pick up and also our cancellation rate drop," Berkowitz said. "Our dealer body appears to be happier that they are seeing more value as a result of this … amongst other changes that we are continually making to the experience."
  • 18% lift in conversions

  • No negative impact on page views or dwell time

Berkowitz said that one of the biggest takeaways from this effort has been the desire to utilize personalized data in more areas of the website.

"We now need to do this with everything. … I think everybody on all sides of the equation is looking for an experience that is more tailored to what they are looking for. Both the customer, in terms of offers, and the advertiser, in terms of the right audience, and I think that these types of efforts show us what is possible in the future."

Creative Samples

Free Price Quotes


Mintigo – vendor for

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