Targeted Ads with Segmento's Psychographic Algorithm
•
0 likes•395 views
Segmento is developing an algorithm to predict psychographics from online data in order to deliver better targeted display ads. They conducted a study of over 300 participants in the automobile industry and found that metrics like risk preference, social comparison bias, and narcissism correlate better to eventual purchase decisions than demographic data alone. Their goal is to build a self-service platform allowing companies to send personalized emails and landing pages based on the algorithm's predictions. They plan to initially generate revenue by selling this service to ad agencies and companies with customer relationship management databases.
Recommended
More Related Content
Similar to Targeted Ads with Segmento's Psychographic Algorithm
Similar to Targeted Ads with Segmento's Psychographic Algorithm (20)
More from Samuel Smith
More from Samuel Smith (6)
Recently uploaded
Recently uploaded (20)
Targeted Ads with Segmento's Psychographic Algorithm
- 1. Segmento Samuel Smith gianna whitver m.a. advertising b.a. advertising b.a. psychology b.a. english B.A. Philosophy a.a.s. comp. sci. with special thanks to our advisors: brian sheehan, former ceo saatchi & saatchi paul morarescu, associate dean, data science bob sollish, lead engineer, synacor sean branagan, entrepreneur
- 2. DISPLAY ADSsimply put, a display ad is any picture ad, on desktop or mobile they're often seen next to content
- 3. Audience targeting behavioral targeting about 18 percentcluster targeting segment targeting retargeting cite: behavioral targeting to grow, adweek two options
- 4. the challenge .10 ?? CLICKTHROUGH RATES ARE THE LOWEST THEY HAVE BEEN IN YEARS .10standard banner .22rich media
- 5. psychographic targeting the solution Segmento is an algorithm that predicts psychographics from scraped data to deliver better targeted ads.
- 7. we did research we sampled over 300 participants from across the u.s. our hypothesis: psychographic targeting is more effective than demographic targeting in the automobile industry. we measured: risk preference social comparison bias narcissism we learned: these metrics correlate better to eventual purchase decisions than demographic data.
- 8. future researchq. How can we possibly determine a random internet user's risk preference? a. perhaps via natural language processing, checkins, and shares q. how do we expand this outside the auto industry? a. every industry will have its own set of psychographic variables to target, and brand managers know what they are. q. how do we find new psychographics that are even more effective? a. haven't gotten this far.
- 9. competitionlots of interest, little competition. 1. Google adWords threats: the elephant in the room. can squash me. weaknesses: targets behaviorally, which is highly unreliable too massive to make monstrous changes in how it targets ads 2. Google ad arts threats: currently working on personalized advertising weaknesses: only customizes select parts of the message, can't select the right message to send to a particular customer
- 10. competition descriptive personalization Varsity ad: "Hey EVAN, HOW'S YOUR TUESDAY GOING? I DON'T KNOW ABOUT YOU, BUT I'M THINKING ABOUT HEADING TO VARSITY AFTER THIS FOR A SLICE OF PIZZA!" BEHAVIORAL TARGETING THE NATURE OF THE INTERNET TAKES CURIOUS PEOPLE TO FARFLUNG CORNERS OF THE WEB. NOT EVERYONE WHO LANDS ON A WEBPAGE WANTS TO BE SOLD THAT PARTICULAR GENRE OF PRODUCT AND IT DOESNT WORK FOR LANDING PAGES OR EMAILS AT ALL. THE DATA'S NOT THERE.
- 11. market size $17 billion and growing potential to disrupt all of display and mobile advertising 2010 $9b 2011 $12B 2012 $15B 2013 $17B 2014 $20b
- 12. deliverable we are prototyping a self service platform for using our personalization technology to send emails and personalized landing pages in case you haven't noticed yet, the magic is in the algorithm. this is a proof of concept.
- 13. biz model Key partners direct mail heroku website key activities market scientist coders key resources code algorithm value props optimized messaging better, more efficient advertising customer relationships self service channels emails, twitter, word of mouth, pr, sxsw, growth hacking, sales team customer segments ad agencies contractors companies with crm databases costs employees heroku revenues selling the service templates
- 14. exit Email and landing page serving could achieve significant profit in its own right Anticipating a pivot from ad serving to using our massive data on sales Opportunities for acquisition at Google, Yahoo, Bing, Salesforce