AOL posts

Jul 16th 2014

Adap.tv's Patented Conversion Tracking Brings Accountability and Measurability to TV Advertising

Conversion attribution on the Internet is ubiquitous, and many methods – including "last click" and cookie-based matching – are used to match a conversion event back to the initial search or banner ad that the user saw or clicked on.

This technology is seamless, automated, and taken for granted: marketers just drop a conversion tracking script onto their websites, and, presto, they have conversion counts and rates for their various ads.

The widespread availability of conversion data has arguably led advertisers to be able to confidently optimize their ads online with a greater degree of granularity than ever before. Different ad creative, devices, mediums, keywords and times of day can all be used in optimization using conversion data that has been collected on them. Indeed, one could argue that conversion-tracking systems – with their incredibly fine measurability – have been the engine that has powered the online advertising revolution.

In contrast to online, conversion measurement in TV is nothing short of an unsolvable labyrinth for advertisers. When an ad airs on TV, conversion events can happen on the Web, over the phone and even retail stores; and there's no way to know whether those sales were driven in part to the original TV ad, let alone what particular TV airing caused it.

With the goal of bridging that gap, Adap.tv has been hard at work in aligning television closer to digital within attribution modeling. Today, we are happy to share the news that the US Patent and Trademark Office (USPTO) has granted Adap.tv an important patent for TV conversion tracking.

This patent validates our work in solving a critical problem for marketers: Online advertising systems have a problem with over-attribution. They tend to be very good at taking credit for – well – everything! TV has the opposite problem; TV tends to take no credit at all.

For example, because online advertising systems are often designed to attribute everything that is last click, it is not uncommon to see branded search keywords (eg. Verizon.com) with an amazing cost-per-acquisition in the pennies thousands of conversions. At this kind of incredible cost-per-acquisition, shouldn't a marketer just shut off all other marketing campaigns on TV, radio, etc. and pour those budgets into online keywords?

Experienced marketers know that such an approach is likely to result not only in a bloated keyword campaign, but could also spell the end of their business by shutting off one of the most important parts of the sales funnel – people who need to learn about and be exposed to the product for the first time.

The reality is the people who typed in the brand's name into the search box overwhelmingly already know the product's name and what it does. The paid keywords are being used as navigational links to reach the site. To put it bluntly, keywords can receive credit by simply being in the right place while a user's navigating to the site. It'd be like a promoter going up to fans waiting in line to get into a concert, giving them a coupon, and then claiming credit for the fans walking through the door. (Recent reports corroborate this phenomenon.)

This dichotomy between over-attribution in digital and lack of quantitative data in television makes it extremely difficult for marketers to calculate how much budget to apply towards TV. Further increasing the difficulty, the lack of granular conversion tracking also makes it impossible to do things like optimize TV media towards the media that is producing the highest number of conversions. In a media environment where every dollar counts, this can be incredibly wasteful.

This patent describes one of Adap.tv's automated conversion tracking systems for television, designed to go beyond last click-type attribution to credit assignment based on properties of the conversions and media event.

US 8,768,770 "System and Method for Attributing Multi-Channel Conversion Events and Subsequent Activity to Multi-Channel Media Sources" describes a process where a machine-learning system is trained to recognize conversions that come from TV, based on cases which are clean enough for deterministic attribution – often about 1% of the cases. The system then estimates the probability of conversion for the larger set of TV airings based on those learned patterns between airing and conversion. The technique makes it possible to probabilistically separate organic Web activity from Web activity driven from TV.

This kind of signal source separation is similar to the "cocktail party problem," where one tries to segment specific conversations out of several conversations happening simultaneously within a room. The system can also report on conversions that are due to marketing events that were not TV; for example, it would be equally bad to over-assign credit to TV for understanding which TV airings have been more effective. In order to do this, not assigning credit is just as important for optimization purposes as assigning credit.

Adap.tv has worked diligently to disambiguate, measure, and report on TV's impact and make it possible to budget TV in a rational way. Adap.tv and Convertro, the leading multi-touch attribution platform recently acquired by AOL, have years of experience running television campaigns and measuring television sales response. In general, our results suggest that TV effects are extremely large, distributed across multiple channels, extended in time, and are woefully under-reported.

With better measurement techniques, we believe that it will be possible to bring hard ROI measurement to TV and put it onto a similar footing as online advertising. That's good for everyone, not only in television, but also in online advertising too. Optimizing your marketing campaign using keywords only is equivalent to looking for your keys by only searching under a street lamp – just because there is some light there, doesn't mean that's where you should be focusing.
The objective should be to cast light on all parts of your marketing campaign.

Further Resources
Read the patent contents here: http://bit.ly/1oCejXA
A scientific paper on the algorithm was published at IEEE International Conference on Data Mining, along with attribution results from various television advertisers. You can read that paper here: http://bit.ly/1zpDXEE

Conversion attribution on television, radio, offline, and digital channels, is performed by Convertro who use a multi-touch attribution (MTA) algorithm to measure effects across channels. You can learn more about Convertro's technology at www.convertro.com.

Jul 14th 2014

Julie Jacobs Named in Profile Magazine's "Top General Counsel of 2014"

We're thrilled to announce that AOL's General Counsel and Corporate Secretary, Julie Jacobs was featured in Profile Magazine's 2014 Top General Counsel Issue. Responsible for all legal, regulatory, compliance and public policy matters for AOL, Julie also oversees AOL's Corporate Services function.

Each year, Profile Magazine showcases those who are raising the bar for in-house counsel. This year's picks know how to be true partners to the business. They are risk mitigators, voices of reason, and sounding boards for the CEO. The piece focused on Julie's assistance spearheading the growth of AOL, citing her as "the catalyst for one of the most lucrative deals that set the comeback company on a path to make history."

You can read the full article here.

Jul 11th 2014

Ran Harnevo Featured in eMarketer Digital Video Streaming Report

Digital video is more exciting now than ever before. In the last few years, streaming has come into its own, bringing a unique ecosystem with it. Between an evolving content landscape, the challenge of curating and maintaining audiences, and a deluge in new devices on which to stream content, there are significant opportunities available for content creators, distributors, and consumers alike.

With the increased influence of mobile devices and connected TVs in today's market, the industry has been forced to expand in order to accommodate the growing demand for ubiquitous entertainment across all digital platforms.

"We're getting to a point where being screen-agnostic is the only way to approach consumers because they watch more videos on every platform," Ran Harnevo told eMarketer in an interview for their Digital Video Streaming Report. "At the same time, when it comes to creating video, length and format are highly influenced by the distribution method at hand."

"There's an appetite for all lengths of content. Usually, time spent is dictated by screen size," continued Harnevo. "The smaller the screen, the smaller the attention span. If you go with connected TVs, play with longer forms. With mobile, be short."

Visit eMarketer to sign up and access the report.

Jul 11th 2014

The Missing Page To The Most Powerful Women Engineers In The World

Kicking-off the week, Business Insider published a great, forward-leaning piece outlining 22 of the most powerful women engineers in the world. At AOL, we've known all along that women in tech are an impressive and powerful constituency, and applaud BI for highlighting those who often fall under the radar.

In the spirit of celebrating women tech leaders, we think BI's headline meant to say: "Top 27 of the Most Powerful Women Engineers in the World." Luckily, just ahead of the weekend, we've located the last page of the article. Meet five bright and powerful women engineers from AOL.

No. 23: AOL, Yumei Tung

Job Title: Chief Architect

Team: AOL Advertising Technologies

Location: Dulles, VA

Why she's powerful: Yumei currently leads the team that designed and developed several tools critical to monetizing advertising revenue. Using her team's proprietary Stream Analysis Framework (SAF), which shortens the processing loop for data integration and analysis, she led the team that designed systems like real-time ad log impression/click/conversion, real-time predictive segments and real-time advertising reporting. Yumei believes that a curious mind -- coupled with the desire to take on challenges and constantly learn -- is critical to succeed in the industry.

No. 24: AOL, Christa Stelzmuller

Job Title: Chief Data Architect

Team: Gravity

Location: Santa Monica, CA

Why she's powerful: Christa brings nearly twenty years of experience to the field of Big Data. She began her career in startups -- one of which was acquired and integrated into Yahoo -- and built content integration systems from the ground up. She co-invented an enhanced text-matching method in which she holds a patent, and has a patent pending for her work on music playlist recommendations.

Christa went on to become Chief Data Architect at MySpace during its peak years of traffic, where she oversaw the data architecture of the storage systems and drove the development of a high-volume messaging system that brought transactional integrity to disparate data stores. She currently works at Gravity, architecting and managing the petabytes of data that flow from Gravity's recommendations systems.

No. 25: AOL, Jade Chu

Job Title: Technology Director of Infrastructure Development

Team: AOL Infrastructure Development

Location: Dulles, VA

Why she's powerful: Jade is responsible for crystallizing the application of AOL's internal cloud. After working as a software engineer for an ad serving and advertising campaign management application, and then a small government contracting shop, she realized she preferred the fast-paced Internet environment.

What inspired Jade to enter the industry? After her mother, originally from Taiwan, traveled to the U.S. to obtain a masters in computer science, Jade says "Mom showed me that a woman can be a needed, valued and highly recruited resource in technology."

No. 26: AOL, Jing Wang

Job Title: Senior Principal Software Engineer

Team: AOL Platforms

Location: Palo Alto, CA

Why she's powerful: Jing is the technical lead on AOL's Predictive Segments and Real-time Predictive Segments on the R&D team in Palo Alto. Under her technical leadership, Predictive Segments continues to be a growing success. Jing leads a team of highly trained and highly technical engineers who require only a top notch tech lead to have maximum impact.

Jing has been with AOL for almost 7 years – starting out as an individual contributor developing data mining and machine learning programs to architecture and subsequently, engineering lead.

No. 27: AOL, Miria Grunick

Job Title: Technology Manager, Search & Geocoding

Team: MapQuest

Location: New York City

Why she's powerful: Miria oversees the technical decisions made for the back-end systems and interfaces with business and product to ensure that products meet the specifications. She is currently pursuing a master's degree in computer science part time at NYU.

In addition to school and work, Miria belongs to NYC Resistor, a "hackerspace" in New York City and creates things on the Arduino platform, like heart-rate responsive running jackets and programmable children's toys that can evolve as the child grows older.

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