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How to Harness the Power of Google Analytics and Vanity

How to Harness the Power of Google Analytics and Vanity. Nooshin Latour Communications and Marketing Anirvan Chatterjee Data Strategy. What is UCSF Profiles? Profiles.ucsf.edu. Hard to find the right expert. Photo by CTSI at UCSF, used under CC, https:// flic.kr /p/ k2Dkp3.

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How to Harness the Power of Google Analytics and Vanity

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  1. How to Harness the Power ofGoogle Analytics and Vanity

  2. NooshinLatourCommunicationsand Marketing Anirvan Chatterjee Data Strategy

  3. What is UCSF Profiles?Profiles.ucsf.edu

  4. Hard to find the right expert Photo by CTSI at UCSF, used under CC, https://flic.kr/p/k2Dkp3

  5. for biomedical researchers

  6. What is UCSF Profiles? • Every UCSF researcher has a profile • Every profiles automatically includes publications and research topics • Researchers can log in to add a photo, bio, awards, etc.

  7. What is UCSF Profiles? • Users can search UCSF Profiles to find an expert on a topic, enabling collaboration • Profiles data is publicly available via APIs, and used in 30 UCSF apps & websites

  8. What is UCSF Profiles? • Lots of traffic from on and off campus • 2,800 visits per day • 1 million visits per year • 75% of traffic from search engines • We actively mine web analytics data to provide insights into site usage

  9. Phase 1: LaunchJan 2010 – Dec 2011

  10. How do you launch a brand new campus-wide resource? Photo by Diane Yee, used under CC, https://flic.kr/p/e48bHL

  11. Tactics • News article on UCSF.edu • Executive Vice Chancellor emails ~8000 people • Send postcard to the 2500 people profiled • Free iPad contest for users who update their profiles • Get major campus websites to link to the site • e.g. UCSF.edu, Library, School of Medicine • In-person outreach at faculty event

  12. Results

  13. Phase 2: GrowthJan 2012 – Jun 2013

  14. How to understand, increasewebsite traffic and usage? Photo by Thomas Sauzedde, used under CC, https://flic.kr/p/admtKw

  15. 1. Search engine optimization

  16. 2. Advanced Google Analytics

  17. 3. Pretty URLs profiles.ucsf.edu/ProfileDetails.aspx?Person=276329999 profiles.ucsf.edu/deborah.grady

  18. 4. Get incoming links from all over ucsf.edu cancer.ucsf.edu directory.ucsf.edu ctsi.ucsf.edu neurology.ucsf.edu meded.ucsf.edu immunology.ucsf.edu postdocs.ucsf.edu osr.ucsf.edu ind.ucsf.edu osher.ucsf.edu accelerate.ucsf.edu familymedicine.medschool.ucsf.edu microbiology.ucsf.edu humangenetics.ucsf.edu id.medicine.ucsf.edu endocrine.ucsf.edu medicine.ucsf.edu anesthesia.ucsf.edu epilepsy.ucsf.edu globalhealthsciences.ucsf.edu surgery.ucsf.edu radiology.ucsf.edu ucsfhealth.org open-proposals.ucsf.edu anp.ucsf.edu epibiostat.ucsf.edu stemcell.ucsf.edu diabetes.ucsf.edu globalresearch.ucsf.edu pharmacy.ucsf.edu addiction.ucsf.edu bms.ucsf.edu pharmchem.ucsf.edu ohns.ucsf.edu mountzion.ucsfmedicalcenter.org healthvalue.ucsf.edu tobacco.ucsf.edu ari.ucsf.edu surgicalmovementdisorders.ucsf.edu medschool.ucsf.edu dgim.ucsf.edu pharm.ucsf.edu pediatrics.ucsf.edu multiplesclerosis.ucsf.edu transplant.surgery.ucsf.edu cardiology.ucsf.edu studentlife.ucsf.edu globalprojects.ucsf.edu mphd.ucsf.edu psych.ucsf.edu pibs.ucsf.edu whcrc.ucsf.edu cfar.ucsf.edu nephrology.ucsf.edu experimental.medicine.ucsf.edu fellows.ucsf.edu urology.ucsf.edu cvri.ucsf.edu general.surgery.ucsf.edu officeofresearch.ucsf.edu dahsm.ucsf.edu gi.ucsf.edu odonovanlab.ucsf.edu coe.ucsf.edu dermatology.ucsf.edu ccb.ucsf.edu sfghres.ucsf.edu acrc.ucsf.edu lomvardaslab.ucsf.edu hcgne.ucsf.edu geriatrics.ucsf.edu top.ucsf.edu ita.ucsf.edu nursing.ucsf.edu hospitalmedicine.ucsf.edu nic.ucsf.edu plastic.surgery.ucsf.edu memory.ucsf.edu prds.ucsf.edu pulmonary.ucsf.edu

  19. 5. Syndicate Profiles data tocampus websites and apps

  20. Results

  21. Phase 3: EngagementJul 2013 – Jul 2014

  22. The challenge Only 28% of users had edited their own Profiles pages (as of August 2013)

  23. Regular Email Doesn’t Work Source: YouKnowWhatSpamEmailis Source: YouKnowWhatSpamEmailis

  24. Key Strategies • Measure: Establish benchmarks • Partnerships: Easier to work together • Automation: Tech trumps manual labor • Vanity: Tap into user motivations

  25. Case study 1 Co-Branded Personalized emails

  26. Email open rates for these campaigns, vs. industry averages • UCSF Profiles News Email: 41% • UCSF Profiles UCTV Email: 39% • Our department newsletter: 26% • Nonprofit industry avg.: 25% • Education industry avg.: 23% • Social networking avg.: 22% • Software / web app avg.: 22%

  27. Case study 2 AutomatedOnboardingEmails

  28. Automated onboarding email • User added to Profiles • Daily process checks new user logs • New users get a customized welcome email,delivered via Mandrill email service provider

  29. Automated onboarding email

  30. After two weeks…if they didn’t edit their Profile

  31. A/B tested subject lines “Reminder: Mary, take a few minutesto update your UCSF Profiles page”vs. “Mary, here are three ways toenhance your UCSF Profiles page”

  32. After two weeks…if they did edit their Profile

  33. Email open rates • Welcome email #1: 39%Click-thru rate #1: 32 % • Welcome email #2A (didn’t edit): 26% • Welcome email #2B (did edit): 31%

  34. Case study 3 Customized Engagement Emails

  35. Default vs. Customized Profile

  36. Customization rates As of November 2013, before this round of emails: • 18% had added a bio and photo • 20% had added only a photo • 3% had only added a bio • 59% had added neither

  37. Ask users to fill out their Profiles • We sent a customized emailto 3,072 Profiles page owners • Emails were customized by segments: • missing photo (3%) • missing bio (20%) • missing photo and bio (59%)

  38. Users gets a custom pitch • Specific call to action (e.g. “add photo”) • Share average pageviews to motivate users

  39. Results • “Add bio” email 12% made edits • “Add photo” email 11% made edits • “Add both” email 10% made edits

  40. Case study 4 UCSF ProfilesAnnual Report 2013

  41. What do researchers care about? Academic reputation Funding Status

  42. Google Analytics tells us which networks looked at which user

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