The Magic of Machine Learning in Real Time
Part of the magic of real-time bidding is found within machine learning. This involves using sophisticated algorithms to “learn” complex patterns based on large amounts of data in order to make optimal advertising decisions. The importance of machine learning is cost avoidance and value creation. Cost avoidance is simple to understand: data-driven optimization strategies help reduce waste by identifying the most relevant impressions while selecting the best ads (better creative message, better offer, etc.), which in turn improves performance and ROI (define). Value creation, on the other hand, happens when buyers and sellers of commoditized offerings are more efficiently brought together for a transaction. To create machine learning magic, two ingredients are required: scale and prediction. Scale speaks to the need to make more users/impressions available through the auction marketplaces, and increase the number of advertisers bidding on these users. The bigger the scale, the more sophisticated the data-driven prediction can be. The second ingredient refers to the idea that prediction needs to be “accurate enough.” Amazon and Netflix have demonstrated that when you provide an accurate prediction of what consumers want, the business grows in two ways:
- Better inventory control and more purchases/utilization.
- Better targeting becomes a custom delight feature when it’s perceived to be quite accurate by average consumers.
The ability to deliver relevant choices in real time based on what consumers reveal about themselves creates a virtuous cycle:
Ads/recommendations become more accurate → consumers are willing to share additional information about themselves → the machine learning algorithm for ads/recommendations becomes even smarter
In digital advertising, the machine learning prediction ultimately boils down to two parts: identifying your target audience and reaching them efficiently. The first part requires machine learning at the user level to learn the most optimal audience segments to target; the second requires machine learning to drive real-time bidding strategy with precision. For instance, demand side platform technology allows advertisers to have global control over how many times each user sees the ads (i.e., frequency capping) and how they see them. This begs the obvious question, “what is the optimal number of ad repetitions?” The answer might be an average of five times over a period of seven days. Problem solved? Not quite.
Read More: ClickZ
BrightRoll Launches Video Ad Exchange
Earlier this year, video ad company Adap.tv launched a video ad exchange in partnership with Gannett Co. and Publicis Groupe’s VivaKi digital unit. Now, its OneSource platform will have some competition from a rival video ad marketplace started by video ad network BrightRoll. As with the online exchanges that have emerged in recent years for display and other types of advertising, the goal is to bring increased efficiency to the video sector by giving publishers a way to unload unsold inventory and media buyers an automated system for reaching particular audiences across a wide range of sites. “What we’re essentially releasing is a video advertising business in a box for buyers of online advertising,” said BrightRoll CEO Tod Sacerdoti, who added that the new exchange dubbed BRX is an outgrowth of the company’s efforts to further automate its own ad network over the last 18 months. BrightRoll is the third-largest U.S. video ad network based on streaming video ads viewed — at 333,492 in June, according to comScore. “We realized everything we were building was applicable to other media buyers and sellers,” said Sacerdoti. A BrightRoll study earlier this year found that half of publishers surveyed reported that at least 20% of their online video advertising inventory is never sold, suggesting the potential for an automated, auction-based marketplace for pre-roll ads.
Read More: MediaPost
Forbes Sells Investopedia To ValueClick For $42 Million
After less than two months on the block, Forbes Media has sold financial education site Investopedia to lead gen provider ValueClick (NSDQ: VCLK) for $42 million. In June, Forbes retained the Jordan, Edmiston Group, Inc. three years after it bought the Canadian-based site. The announcement comes a few weeks after Forbes purchased freelance journalism site True/Slant, which was shut down last week and will remain live as an archive site only. Forbes had been an investor in True/Slant and before the purchase, it had hired site’s founder, Lewis DVorkin, as consultant to help restructure its digital offerings. The quick sale of Investopedia is a the first step in the struggling publisher’s latest digital reinvention. Despite the fact that Forbes was eager to sell the Edmonton, Alberta-based Investopedia, the company claimed that the site’s profits and users have grown in the past three years since it was acquired. In a release, ValueClick CEO Jim Zarley said that Investopedia gives the company “great content, organic traffic and established advertiser relationships in the important financial services advertising vertical.” He also believes that the addition of Investopedia will be able to help build up its ValueClick Brands and ValueClick Media offerings.
Read More: PaidContent.org
