Machine Learning Algorithms & Intelligent Recommendations [Innovation Blog Series Part 01]
March 3, 2017
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The letter “I” in “Vizury” stands for Innovation! Well, we haven’t coined any such fancy initialism, but if we did the “I” would surely expand into nothing else but Innovation –it runs in our DNA here at Vizury. Innovation is one of our core values and symbolizes the way of work for us.
While we offer performance marketing solutions to brands and help them realize their ROI, we are constantly innovating in the background . These innovations could be centered around bidding optimization, sharpened recommendations, delivering meaningful analytics, optimizing spends and so on. But the end goal always is delighting our clients.
Beginning with this one, we present a series of blogs that talk about our super-successful product innovations and how they have impacted our clients’ businesses.
Do shoppers always buy the last seen product from your website? Not all the time! Any visitor on your website does not necessarily follow a sequential purchase path. He might look at tee shirts, drop off, come back for shoes and then look at tee shirts again. The challenge that remarketing partners like Vizury face, is choosing the right product recommendations while showing ads to such users.
Do we show the shoe or the tee shirt or both?
Intelligence that helps us choose:
As complicated as the shopper is, the machine learning algorithms that fuel the right recommendations are more so. The key here is to get a larger perspective of the user which is possible by understanding the user’s actions and behavioral trends across devices, channels, offline as well. Our product specialists have been constantly optimizing and experimenting with Vizury’s recommendation algorithm. We now have over 50 parameters including “last –seen” helping us decide the best suited product recommendations for every user on both desktop and mobile devices.
All campaigns running with the renewed recommendation algorithm have delivered 10% higher ad-clicks and conversions.
Nishant Kadian takes care of content marketing for mFaaS. He is passionate about sharing his learning on the ad technologies, mobile ad fraud preventions, and more. Drop him a 'Hello' on LinkedIn or Twitter to start a conversation with him.