A Data-Driven Approach to Strengthening Your Online Presence

Resource Bank Meeting March 28, 2014

Objectives

1.  Help you learn from our mistakes 2.  Identify a new approach 3.  Be useful!

Common mistakes

•  Deciding by HiPPO •  Deciding by committee •  Deciding by expert

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The answer?

Decide using data.

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“We  basically  found  our  guts  were  worthless.”    

-­‐Senior  Obama  Campaign    Digital  Team  Member    

How optimization can transform your organization

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Let’s test your gut instincts

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Version A?

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… or version B?

Here they are side by side

Version B outperforms version A 44.4% increase in conversion rate 95.14% confidence

3.3% increase in average gift 95.14% confidence

49.3% increase in revenue per visitor From $4.76 to $7.11; 95.14% confidence

4 steps to optimization

1.  Identify what to improve (email, page, etc.)

2.  Identify the goal for #1 (donations, content reads, etc.)

3.  Identify the best measure of success 4.  Develop hypothesis to improve that measure

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Case study: Adding a renew button

•  What: Top navigation on Heritage.org •  Goal: Increase revenue on main donation page •  Measure: Revenue •  Hypothesis: Adding a second donation button

saying “renew” will increase revenue 19

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The two-button version wins

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83.95% increase in site conversion rate 0.05% to 0.09%; 99.9% confidence

62.5% increase in revenue per site visitor $0.06 to $0.09; 98.8% confidence

Testing isn’t about redesigning

•  Testing is what you do before redesigning to avoid costly mistakes

•  Testing allows you to improve your site incrementally, at lower cost

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Case study: Heritage report pages

•  What: Heritage online policy report pages •  Goal: Communicate Heritage’s message to

more people •  Measure: Number of people reading to the end •  Hypothesis: Reduce clutter to boost reads

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Version A

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Version B

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Version B drove more reads

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11% increase in page reads

104% increase in social sharing

Test to learn, not to win

•  Not every test yields a win •  But every test allows you to learn what to do •  … and what not to do

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Case study: Event invitations

•  What: Event e-mails and registration pages •  Goal: Boost event attendance •  Measure: online RSVPs •  Hypothesis: More personalized messages

conveying more value will drive more RSVPs 3/26/14 28

Version A

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Version B

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Version B drives more RSVPs

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126.2% increase in RSVPs From 12% to 19%; 100% confidence

How to put all this in place

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What are the challenges?

•  Technology •  Culture

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Google  Analy+cs   Op+mizely  

Cost   4 Free  

3 $17/month

Ease  of  tes+ng   3 4

Support   0 3

Long-­‐term  suitability   1 3

A Culture of Optimization

•  Focused on learning •  Characterized by humility •  Leads to process change

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“The  core  of  the  campaign  was  not  Alashy  or  even  particularly  innovative  except  in  the  willingness  of  senior  staff  to  listen  to  numbers  people  rather  than  consultants  acting  on  old-­‐fashioned  political  intuition.”    

-­‐TechPresident  

4 steps to optimization

1.  Identify what to improve (email, page, etc.)

2.  Identify the goal for #1 (donations, content reads, etc.)

3.  Identify the best measure of success 4.  Develop hypothesis to improve that measure

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Where you can start testing right away

•  Your donation page •  Your e-mail newsletter

Use the handout to guide your initial testing.

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Follow-up Webinar

http://heritage.org/RB-digital

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Case study: Thermometer vs. countdown

•  What: Donation e-mails •  Goal: Generate more revenue •  Measure: Number of gifts; revenue •  Hypothesis: A thermometer will drive more

donations than a countdown timer 40

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The timer drove more gifts

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11.8% increase in gifts

7.5% increase in revenue