An Interview with XPETO’s Yuli Shumsky

AAEAAQAAAAAAAAIZAAAAJGRmMmNjZGU0LTIyMTgtNDQxMy1hZDU0LTUwNjc5MzU5MmMxZQ

Yuli Shumsky is Director, Programmatic Systems at XPETO, and his professional background is in performance marketing and brand engagement media buying.

Back in 2004 while I was still in school he landed a job as a performance media buyer for one of North America’s largest affiliate networks at that time. Shumsky had the opportunity to learn from and work with some of the brightest minds and visionaries in the digital media world.

With extensive exposure to a number of successful digital business models, as well as hands on experience across a variety of media buying platforms, techniques and pricing structures, Shumsky quickly learned how each link in the value chain works together in order to bring forth the best digital results for clients while establishing long term relationships and revenue streams.

What have you learned about RTB?

With the rise of RTB, in 2010 I’ve made the transition to the premium network side of things working as the programmatic product manager at Mediative/Yellow Pages Group. Working closely with the Chief Operations Officer I was tasked with building out the infrastructure, process and performance products composing of Yellow Page’s first party data for industry’s first all-Canadian trade desk.

In late 2013 I had joined the team at Media Experts, Canada’s largest independent agency, to take on yet another journey of building and launching an in-house trade desk to service Media Expert’s list of blue chip clients.

Alongside a few industry friends and colleagues we launched the Toronto Ad Ops initiative in November of 2014.

Toronto Ad Ops focuses on creating a localized support network and a streamlined communication forum for all members of the Ad Ops ecosystem in the Greater Toronto Area and beyond. It is a not-for-profit organization aimed at bringing together Advertising Operations professionals from all corners of Digital Advertising industry.

What are some common issues with attribution?

I think the idea of attribution is still evolving.

With the advent of new technologies and ways to analyze the delivery of online advertising, we keep discovering new factors and insights that influence how we think about attribution.

I believe a more complete attribution model should be inclusive of some additional ad delivery analytics as well as consumer behavior.

Inclusion of viewability/time in view, number of ad exposures, time on site and even social media interactions for example, would yield an improvement over most current attribution models.

Inclusion of viewability/time in view, number of ad exposures, time on site and even social media interactions for example, would yield an improvement over most current attribution models.

Can you talk about the implications of the ‘last touch’ model?

The last touch model is where click takes precedence over an impression are commonly used.

Following the traditional logic in terms of ‘action’ leads us to believe that the click is what drove the final conversion.

However, if you consider previous interactions and the time spent on advertiser’s site, or number of pages per visit following those ‘pre-last click’ interactions, that very last interaction might not be considered as the most valuable or having 100% causal effect on the final conversion.

This also holds true for any attribution model where an “X” number of interactions are either assigned the same or some sort of a sliding scale value.

An attribution model needs to exist which can dynamically adjust to account for the effect of each ad exposure and interaction on consumer behavior, consumer’s entire brand journey, not just the final purchase/conversion.

An attribution model needs to exist which can dynamically adjust to account for the effect of each ad exposure and interaction on consumer behavior, consumer’s entire brand journey, not just the final purchase/conversion.

What are some trends for mobile advertising over the next 12 months? What excites you the most?

The biggest trend is more and more people are using mobile devices to do research regarding a purchase whereas the actual purchase itself happens on a desktop device.

Depending on which point in the funnel a consumer has reached, the use ratio of a mobile device vs. desktop changes.

Initially, consumers tend to use their mobile devices more, while researching and considering a product or a brand.

As a consumer moves through intent and evaluation stages, mobile usage declines while desktop usage increases.

This makes sense when you think about things like price comparison, payment option analysis, etc.

The biggest trend is more and more people are using mobile devices to do research regarding a purchase whereas the actual purchase itself happens on a desktop device.

Finally, at the conversion point you generally see 90% or more desktop usage.

Mobile seems to be the channel of choice when consuming one stream of content at a time – general news, video and music content, etc.

On the other hand, desktop become predominant when two or more sources of content are consumed at the same time.

Be it brand/retail content (product comparison between two or more retailers, room availability between two or more hotels), work/professional content (research, education) or user generated content (product reviews and general discussion).

What are some opportunities for mobile marketers?

The opportunity for mobile marketers is to track a user’s physical location during specific browsing behaviors.

When a person is checking out product availability for a specific brand or retailer, where are they? Are they at home? Are they near retail location where these products are sold? Are they near a competitor’s retail location?

Knowing where someone is could be the next level of creative A/B testing. See how responsive a user is to a given creative based on their physical location. Or as a user moves from one location to another.

Knowing where someone is could be the next level of creative A/B testing. See how responsive a user is to a given creative based on their physical location. Or as a user moves from one location to another.

Another opportunity I see is, what I call, group tracking.

Marketers should start creating pools/audiences based on frequent visitors to a given physical location. From here comes also comes the ability to target users based on their duration at a physical location, like a coffee shop, a grocery store or an amusement park.

Knowing where someone is, how much time they spend there and who they are surrounded by can paint a user behavioral profile that goes beyond any web site visits or ad serving analytics.

0 Comments

Leave a reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>

Log in with your credentials

Forgot your details?