Editor’s note: Susan will be pitching Mavatar on February 14 at Women 2.0 Conference as a PITCH SF 2013 Startup Competition finalist!
By Susan Akbarpour (Co-Founder & CBDO, Mavatar)
When I entered Stanford Graduate School of Business in 2009 at the age of 40, it didn’t take me long to notice that my closet was not configured for student life. No matter how hard I tried, I showed up to my classes overdressed! I didn’t have the time and the interest to go shopping.
I was comfortable in my own style, and I knew that the moment I’d step into a mall, I’d end up buying the same brands and looks that I loved. So instead, I went online and purchased seven pairs of jeans in one sitting! Each around 50 bucks!
To my surprise, all of the sudden, after this drastic shopping behavior, I started receiving hundreds of emails from various retailers to buy even more cheap jeans!! Promotions were chasing me everywhere, online and offline. My browser was flooded with banners imploring me to buy more jeans! It was a constant, unbearable reminder, screaming at me, “YOU BOUGHT SEVEN PAIRS OF JEANS IN ONE SITTING!”
As I sat in the Data Modeling course, I was in awe of the power of data analysis and optimization – fascinated by its potential and application. Being right-brained, I found myself looking for everyday scenarios where these analytical techniques could be applied. So during the last semester, I found myself drawn to a course called Social Data Revolution offered by Amazon’s former Chief Scientist. Two topics kept coming up: user privacy and qualified data.
Privacy is increasingly becoming an important issue for online shoppers. Marketers collect large amounts of user’s personal information after every purchase or on simple search inquiries she makes. Following this mostly surreptitious capture of private data, marketers bombard the user with direct and indirect purchase recommendations and advertisements. More often than not, the intent of the shopper or her evolving shopping habits are missed.
At the peak of the social data revolution, we are stuck with the emergence of “noise” – a result of using unreliable data collection methods such as past shopping and consumption behaviors, user’s trusted network’s behaviors or search inquiries which cause an even higher degree of unwanted and inaccurate targeting. Our needs, wants, tastes, moods and relationships differ from day to day, driven by the collection of haphazard data. Advertisers are most likely feeding suggestions and products unrelated to our real-time needs. It’s not surprising that as much as 88.5% of the time people don’t pay attention to pay-per-click ads.
A few years ago, seeing banner ads for a Chanel bag that you were just searching for, seemed like a miracle. But given the affordability of retargeting, more advertisers now have access to cheap and redundant data. Hence the reason you see so many banner ads following you online even months after you have searched and bought that Chanel bag!
According to the Gallup survey in 2010, 6 out of 10 participants reported that they have noticed targeted ads based on websites they had previously visited. Further, 9 out of 10 said that they pay little or no attention to these online ads and recommendations.
Remembering my compulsory jeans nightmare, it occurred to me that data and privacy can’t be mutually exclusive. The fact is that the user doesn’t have direct control over her data, nor does she receive a reward for unwittingly sharing her data, all ends up as unwanted and unproductive noise.
I asked myself, “What if she were in charge of her data and rewarded for sharing her data?” What is her incentive for this sharing? Marketers are already spending hundreds of million dollars every year to issue discounts and perks with a mediocre redemption rate of 2 to 3%. Why? Because these discounts don’t work, and are definitely not delivered to you when you need them.
Does anybody wonder, with so many emails, discount codes, and endless fine print, who is capable of finding the needle in the haystack?
I also realized that the industry’s focus on the user’s data, rather than on the macro trend, does not truly serve the industry or the consumer. Push advertising models proved inefficient. This is the same model that my father used when he started the first advertising agency of my home country, Iran, 50 years ago: “We have this offer. We hope you buy it!” The optimal solution needs to be user centric and based on the pull model, which allows users to be in charge of their exchange with the market.
This gave rise to Mavatar, a user-centric smart shopping cart that keeps the user’s data in a private sandbox while shopping but analyzes a vast amount of data (offline and online promotions, recommendations, discounts, coupons, offers, etc.) for her automatically to help her process her smartest shopping decisions.
For the past two years, this solution has become my obsession, and together with my co-founder, Dr. Brom Mahbod, a former Oracle VP of e-business platform, and an amazing team of senior developers, user experience scientists and researchers, we have created Mavatar to introduce a platform that breaks through the friction and creates a true personalize shopping experience for hassle-free and organized online shopping: Mavatar, shop better.
Women 2.0 readers: How can we improve online shopping?
About the guest blogger: Susan Akbarpour is a co-founder and CBDO of Mavatar. She co-founded the company in January 2010 along with Dr. Brom Mahbod; entrepreneur and an Internet visionary, and a former vice president at Oracle Corporation. A visionary and globally focused executive and entrepreneur, Susan has 15 years of hands-on experience in building successful and innovative businesses in media, management consulting and investment. Follow her on Twitter at @MAVATAR10.