Lotame

At Lotame, we are constantly striving to stay ahead of the curve and innovate. Since our inception, we have aggressively sought out and developed new, valuable metrics to measure the success of individual online advertising campaigns, as we do not believe (and have never believed) that clicks and conversions tell the complete story.

After much exploration, research, and analysis over the past few years, we have also realized there is no “magic metric”. In other words, there is not one individual metric that has the capability of measuring success for all campaigns. A key reason for this is due to each advertiser or campaign having a different goal. Some advertisers just want users to become familiar with their brand; others want users to purchase their product; while others want users to watch their television show or movie. One metric cannot accurately accomplish measuring each of these goals at the same time.

A year ago, we created our own single, unified metric for every campaign. It was a combination of every metric we look at in measuring the success of the campaign. However, there was an issue with creating such a metric – how does an advertiser compare the performance of their campaign by media buy/site? If only one buy/site uses the metric, then you cannot compare it across all buys/sites. Since the metrics we use incorporate our technology, it is not always easy to reproduce for other buys.

As a result, we measure the performance for each campaign individually, which also allows us to customize what we measure and report on for each campaign/advertiser. At Lotame, we have always prided ourselves on being 100% customizable for advertisers. We create completely customizable targets – no buckets. Therefore, creating completely customizable performance measurements seemed like a natural progression. While there are typically only a few possible end goals of a campaign (awareness, conversions/purchases/intent to buy, intent to view, buzz generation), many advertisers have smaller, intermediate goals. These smaller goals are fairly unique to each campaign. Therefore, we measure each of these goals as well as analyze the other metrics we deem to be valuable for their end goal. We want to stress that the smaller goals only exist as a means to measure the larger, end goals. And that is where our knowledge and experience at measuring the end goals comes into play. For instance, an advertiser may run a campaign asking users to upload photos for a contest. The likely reason behind running such a campaign is to generate awareness of the product/brand. We will not only measure the performance of the contest entries, but also various other metrics (i.e. Lotame’s patented Time Spent metric, the amount of time a user spends on the micro-site and/or the number of pages consumed on the micro-site, the responses to one-question in-banner surveys, and various engagement metrics with the creative) to get a more complete picture of awareness. The advertiser should understand that their contest is only one small portion of measuring the awareness of their product/brand. Lotame will complete the story with our knowledge, technology, and customized performance metrics.

We will continue to strive to identify and evangelize the best metrics possible to enable our clients to set appropriate goals for their campaigns and gain optimal insight into campaign performance. In doing so, we may find our way back to some uber-metrics, entirely new metrics or most likely, combinations of metrics which can be customized to match the specific requirements of each campaign. We’re fortunate to have great partners in this quest – our forward-thinking brand, agency, and publishing partners and companies including Vizu and Dimestore. Ultimately, the continuous development of new and scalable metrics will provide our clients with the best approaches for guiding and measuring their online advertising campaigns.

Written by: Doug Pollack is a Senior Business Analyst with Lotame Solutions. Doug has been responsible for the development of leading, and innovative Key Performance Indicators as well as new metrics for digital media. Prior to Lotame, Doug worked for a division of the Army where he leveraged his statistics background to analyze the aging of tanks operating in Iraq and Afghanistan. Doug is available at doug [at] lotame [dot] com.

one-question in-banner surveys: Surveys have gotten a bad reputation recently – mainly due to poor response rates and inaccurate results. However, the surveys we run are not affected by these issues. The types of surveys that are affected are the long surveys that force users to stray away from the website they were on. Users, especially those on social community sites (like Facebook, MySpace, and Bebo), do not want to be taken away from the websites they are on. These long, in-depth surveys do just that. They take the user away from the sites for a very long time, as they typically have 10 to 20 pages of questions. Therefore, the response and completion rates of the surveys are quite poor, leading to limited responses. With limited responses, results are typically inaccurate. However, the quick, in-banner, one question surveys we run solve these problems. Users can quickly take the survey without leaving their community. This leads to higher response rates, more responses, and more accurate results. In fact, Lotame has just finished a study testing the accuracy of the results of the surveys. We ran a survey measuring intent to view, which asked users if they planned on watching the season premiere of a popular TV show. We then re-surveyed the users who responded with a 2nd survey asking if they actually watched the premiere. 83.3% of users who responded to the 1st survey saying they would “Definitely” watch the premiere, did tune-in and watch the premiere. 74% of users who responded to the first survey saying they would either “Probably” or “Definitely” watch the premiere, did tune-in to the premiere.

This week Alan Levy, CEO of Blog Talk Radio, will be joining me in a open conversation about how podcasting and online radio can help brands in their marketing effort.

Besides being a super guy, Alan, along with Bob Charish founded BlogTalkRadio in August 2006. The concept for BlogTalkRadio was developed by Levy as he mourned his father’s passing. Levy maintained a blog, to update his family and friends on his father’s health - and later as a memorial to his life. Levy thought by combining blogging and telecommunications, a true immediate two-way interactive online platform could be established. This led to the birth of BlogTalkRadio.

Please join us as we explore how to effectively use this new platform for marketing.

Join us @11:30 EST on Thursday 4/30 over at Blog Talk Radio.

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In his blog post over at GigaOm entitled “One Size Doesn’t Fit All When It Comes To Online Recommendations,” Darren Vengroff writes about 4 different product recommendations approaches, all deeply rooted in the smart use of data. This is very similar to some of the processes that can be employed when it comes to making decisions about which advertisement to show, and whom to show it to, with the aid of a data driven ad targeting platform:

• Segmentation, which divides users into groups based on characteristics like age, gender, and geographic location;
• Collaboration, which starts with an individual and attempts to locate others like them;
• Personalization, which relies on a user’s prior actions to determine what they are likely to do next; and
• Similarity, which starts with products, rather than users, and models relationships between them to drive recommendations.

In our business at Lotame, we have found that ad campaigns don’t have to be reliant on a single approach, and at times it may be best to combine different approaches simultaneously. Additionally, we have found that other approaches to use data that revolve around some of the unique social data that Lotame collects.

Darren is chief scientist at richrelevance. Previously, Darren was CTO and co-founder of Pelago, principal engineer at Amazon.com, and a vice president at Goldman Sachs. The entire article, with deeper definitions of each of the four approaches, can be found here.

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• One Size Doesn’t Fit All When It Comes To Online Recommendations (gigaom.com)

I was just blown away by this statistic published by Andreas Weigend, over at the Harvard Business Blog.

He states that “In 2009, more data will be generated by individuals than in the entire history of mankind through 2008. Information overload is more serious than ever.” WOW

Andreas should know, he is the former Chief Scientist at Amazon.com and an expert in data mining and computational marketing. He currently teaches the graduate course Data Mining and Electronic Commerce at Stanford University.

He goes on to explain that we are in the midst of a second data revolution. “The second data revolution brought about a new dimension to data creation: users started to actively contribute explicit data such as information about themselves, their friends, or about the items they purchased. These data went far beyond the click-and-search data that characterized the first decade of the web.”

At Lotame, we are at the epicenter of this revolution, our core DNA is about turning these mountains of data (all different kinds) into value for publishers, marketers, and consumers. All our technology offerings, have been built with Andreas’ vision of the second data revolution in mind. If you haven’t had the opportunity to see our suite of products first hand, then you are missing out on a presentation that will have you thinking about the possibilities of using Lotame in daily lives.

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• The Social Data Revolution(s) (blogs.harvardbusiness.org)

A recent study on users with Travel interests within our publisher partners showed that 61% of travel-interested users were female, and over one third (37.3%) were between the ages of 25 and 35. Additionally, 3 out of 4 travel users have interests in arts & culture-related content, such as art, crafts, dance, literature, and theater.

Additional Findings can be found by viewing the full report on Frequent Travelers. (Download the PDF here for free) We sampled approximately 67,000 individuals in our Co-Op who fit the description “Travel Enthusiasts,” users who reported interests in travel or demonstrated interests by sharing, posting or discussing travel related content.

An archive of additional reports can be found here.