Michael Kaushansky is one of today’s brightest measurement leaders.
He comes on the show and shares the story of how he came to be in the digital marketing space and how he along with other mathematicians came to birth what is essentially known as attribution today, tune in to this episode to also hear what he foresees as its inevitable future!
Michael Kaushansky serves as Chief Data Officer and President of Havas Helia.
He has direct oversight and responsibility for the agency’s data, analytics, and marketing technology plus managing and advancing Helia which is Havas’s relationship marketing CRM agency.
Michael has been involved in the field of data analytics and business measurement for nearly two decades and has held roles of increasing responsibility at GE, Target, and GlaxoSmithKline.
Prior to Havas, Michael led all marketing analytics at Ogilvy where his work spanned leading global brand advertisers including UPS, IBM, Nestlé, CISCO, and SAP.
He has a bachelor’s degree in mathematics and a master’s in applied mathematics and operational research and is an advisor to Rutgers University’s big data graduate program.
[1:49] I introduce today’s guest, Michael Kaushansky, and ask him to walk us through his measurement career trajectory from data set days to today.
[3:42] Michael takes the time to break down three use cases from his time at Fingerhut, in the field of healthcare and in the financial services industry. He explains how he identified which data set points to work with for each, as well as what results these applications yielded, at the time.
[12:35] After the financial crisis, Michael found a way to translate his knowledge of working with data sets to tracking ads, searches, and behaviors and moved into digital advertising.
[15:25] Budgets were getting bigger and bigger for digital, but the way we were allocating our budgets was still based on a cost-per-thousand basis and CTR. Michael shares the work he began to do when he understood the value of the data set available to him with the World Wide Web.
[17:30] Michael touches on the information you can gather about consumers, the relative comparison aspect of marketing and how it ties into the debate on privacy.
[20:03] In 2009–10, nobody knew where to start in order to reach and engage the customer in the digital world. … Enter mathematicians! Michael shares the story of how they built what is now known as the path to purchase tracking.
[24:00] Michael shares his definition of attribution and this leads to an in-depth discussion on the importance of crediting your marketing activities with their success rates in getting consumers to move within your sales funnel. This, in turn, enables you to better allocate budgets and remain competitive in the marketplace.
[31:07] You can’t set it and forget it anymore; how targeting and real-time information gives attribution, data and analytics the ability to keep your decision-making process nimble and your costs under control.
[34:19] Michael speaks to the new frontier — because consumers are spending more and more time on their devices, doing attribution in the digital space for brick and mortar purchases becomes imperative.
[39:10] The failure to adopt advanced analytics and attribution is unfortunately complex; Michael shares what he sees as the three main barriers to adoption.
[42:25] I unpack the last barrier to adoption that Michael highlighted — a previous failure — and offer ways to circumvent those and ensure a successful integration. Michael offers that all advertisers and agencies will have to move towards attribution — it is where things are heading whether they like it or not and the faster they do it, the better off they will be.
[48:56] Despite attribution not being talked about as much in conference circles, there has been an increase in big players integrating the practice. I talk about the progression of adoption we usually see for new practices, and what big enterprises usually drive into a space after they go all in.
[53:01] Michael shares one thing that he knows that no one else knows: always ask for a sample data set. I thank him for coming on the podcast and sharing so much of her experience.
Be sure to tune in for the next episode and thanks for listening!
Connect with Michael:
Michael Kaushansky on LinkedIn