The rise of ecommerce probably has had two effects on your day-to-day life. For one, ecommerce has made it easier to reach customers throughout the country and the world. Fellow evidence-based marketer,
But second, every product you’re selling, every goal you have now exists in a brutally competitive market where your potential customer can quickly and easily leave your website and choose anyone from the behemoth Amazon to an eBay seller operating out of a garage instead of your company.
So how do you compete? How do you increase your conversion rate and sell more products? I can’t give you a specific answer.
But I’ll tell you who can — your customers.
With A/B testing, you can discover what really works on your brand’s website, in your brand’s email, and in your brand’s ads with your brand’s prospective customers.
To give you ideas for tests on your website, we put together this swipe file of 25 ecommerce experiments that MECLABS Institute analysts conducted in Research Partnerships with ecommerce companies to help them learn about their customers and improve conversion rates.
There’s a lot of information here, and different people will want to go through this swipe file in different ways. You can scroll through the webpage you’re on and use the anchor links. Or use the form on the page to download a PDF with all of the experiments, including a table of contents and internal anchor links to help you navigate.
If these experiments inspire your own tests, we’d love to see the results — just drop me a line at d.burstein@meclabs.com.
Here’s to higher-converting ecommerce websites,
Daniel Burstein
Senior Director, Content & Marketing
MarketingSherpa and MECLABS Institute
P.S. If you need help improving conversion, just drop me a line as well. MECLABS analysts can work hand-in-hand with you to apply our patented methodology to your conversion challenges.
Experiment #1: 46% more conversions for furniture company by changing credibility approach
Experiment ID: TP11009
Background: Mid-sized furniture company selling mattresses
Goal: To increase the overall number of mattress purchases
Research Question: Which credibility approach will produce the highest rate of mattress purchases?
Test Design: A/B variable cluster split test
Experiment #1: Control
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Experiment #1: Treatment
Experiment #1: Side by Side
Experiment #1: Results
46% Relative Increase in Conversions
The treatment significantly increased conversions by 45.69%
Design | KPI | % Rel. Change |
Control without GreenGuard copy | 0.65% | - |
Treatment with GreenGuard copy | 0.94% | 45.69% |
What You Need to Understand: The increased clarity around an exclusive source of third-party credibility increased the value exchange and appeal of the product driving more sales.
Experiment #2: 37% increase in conversions for travel agency by simplifying and sequencing the cart options
Experiment ID: TP1294
Background: B2C company offering package vacations to global consumer audience
Goal: To increase cart completions
Research Question: Which cart page will generate the highest completion rate?
Test Design: A/B split test (variable cluster)
Experiment #2: Control
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Experiment #2: Treatment
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Experiment #2: Results
37% Relative Increase in Conversions
The treatment significantly increased total cart conversions by 101.40%
Design | KPI | % Rel. Change |
Control | 12.94% | - |
Treatment | 17.66% | 36.50% |
What You Need to Understand: By moving the secondary CTAs to the relevant cart sections and putting emphasis on a single CTA to move the customer forward friction was reduced and conversion increased.
Not This, But This…
Options Selection
Protocol ID: TP1294
Experiment #3: 12% increase in conversions for multimedia retailer by strategic placement of testimonial and credibility indicators
Experiment ID: TP1070
Background: A national computer hardware multimedia retailer with a significant online and offline presence
Goal: To increase total cart conversions and revenue per cart
Research Question: Which treatment will generate the highest conversion rate and revenue per cart?
Test Design: A/B variable cluster test
Experiment #3: Control
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Experiment #3: Treatment
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Experiment #3: Side by Side
Experiment #3: Results
12% Relative Increase in Conversion
The treatment significantly increased revenue per conversion by 11.6%
Design | KPI | % Rel. Change |
Control | 49.14% | - |
Treatment | 54.84% | 11.60% |
What You Need to Understand: By addressing anticipated anxiety at the critical decision through the use of testimonials and clear trusted payment options, the treatment generated 3.69% more sales in addition to 11.6% more revenue per cart, resulting in a projected $53,000,000+ annual increase in revenue.
Experiment #4: 87% increase in conversions for online printing company by re-sequencing product and process information on product page
Experiment ID: TP1568
Background: An online printing company that specializes in delivering printed marketing materials with minimal turnaround
Goal: To increase number of purchases online
Research Question: Which product page will result in the largest purchase rate?
Test Design: A/B Variable Cluster Test
Experiment #4: Version A
Experiment #4: Version A
Experiment #4: Version B
Experiment #4: Version B
Experiment #4: Side by Side
Experiment #4: Results
87% Relative Increase in Conversions
The treatment significantly increased conversion by 87.40%
Design | KPI | % Rel. Change |
Version A | 4.03% | - |
Version B | 7.55% | 87.40% |
What You Need to Understand: By resequencing the page to put the form first and better match motivation and clarify the eye path, the new product page template achieved an 87.40% increase in conversions.
Not This, But This…
Eye path
Protocol ID: TP1568
Experiment #5: 20% increase in conversions for Italian cosmetics website by adding an interactive element to product page
Experiment ID: TP1283
Background: Italian ecommerce website offering cosmetics. The researchers were focusing on testing different approaches to the "body" category page.
Goal: To increase rate of conversion
Research Question: Which page will generate the highest rate of conversion?
Test Design: A/B Variable Cluster Test
Experiment #5: Control
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Experiment #5: Treatment
Treatment 1 seeks to make the page easier to use by adding an interactive configurator that enables the visitor to customize the products that show up below.
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Experiment #5: Treatment
Treatment 2 seeks to make the page easier by removing the category links and simply featuring the main categories with images. |
Experiment #5: Treatment
Treatment 3 is a radical approach that seeks to make the process easier by removing the “body” category page altogether, enabling the visitor to choose their category within the navigation of the homepage. |
Experiment #5: Treatment
Treatment 4 is similar to Treatment 3, only it integrates a more visual approach to the categories within the navigation. |
Experiment #5: Side by Side
Experiment #5: Results
20% Relative Increase in Conversion
The configurator treatment significantly increased conversion by 20.00%
Design | KPI | % Rel. Change |
Control | 1.04% | - |
Treatment 1 | 1.25% | 20.00% |
Treatment 2 | 1.10% | 6.00% |
Treatment 3 | 1.10% | 5.00% |
Treatment 4 | 1.10% | 5.00% |
What You Need to Understand: By adding an interactive element, the new product page achieved a 20% increase in conversions.
Experiment #6: Projected $500,000+ increase in revenue per year for retail/wholesale collector items website by testing which version of a second step in the conversion funnel will produce the highest conversion rate
Experiment ID: TP1305
Background: A website that sells retail and wholesale collector items
Goal: To increase rate of conversion
Research Question: Which version of a second step in the conversion funnel will produce the highest conversion rate?
Test Design: A/B variable cluster split test
Experiment #6: Background
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Experiment #6: Control
What might be causing the fallout?
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Experiment #6: Treatment
How we addressed the issues:
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Experiment #6: Side by Side
Experiment #6: Results
5% Relative Increase in Conversion
The treatment significantly increased revenue per conversion by 11.6%
Design | KPI | % Rel. Change |
Control | 82.33% | - |
Treatment | 86.04% | 4.51% |
What You Need to Understand: While it might seem like a small increase, the changes in this treatment on this step of the funnel resulted in a projected $500,000+ increase in revenue per year. This underscores the potential impact of a properly identified research question.
Not This, But This…
Clarity
Protocol ID: TP1305
Experiment #7: 49% increase in conversions as well as significant increase in email capture for people-search software database company by changing the text and position of the call-to-action and adding an email capture field
Experiment ID: TP1000-13
Background: A company offering people-search software database for consumers
Goal: To increase the number of emails captured
Research Question: Which page will generate the highest email capture rate?
Test Design: A/B variable single factorial split test
Experiment #7: Control
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Experiment #7: Treatment
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Experiment #7: Side by Side
Experiment #7: Results
122% Relative Increase in Email Capture
The treatment path increased email captures by 121.80%
Design | KPI | % Rel. Change |
Control | 6.76% | - |
Treatment | 14.98% | 121.80% |
What You Need to Understand: By changing the position of the call-to-action and adding an email capture field, we were able to significantly increase emails and also increase orders by 49%.
Experiment #8: 29% increase in conversion for fitness company by removing the cart preview
Experiment ID: TP1620
Background: A fitness company that primarily sells fitness training content and gym equipment
Goal: To increase sales
Research Question: Which checkout process will result in a higher conversion rate?
Test Design: A/B multifactor split
Experiment #8: Control
Experiment #8: Treatment
Experiment #8: Results
29% Relative Increase in Conversion
The treatment path increased conversion by 28.60%
Design | KPI | % Rel. Change |
Control | 27.70% | - |
Treatment | 35.6% | 28.60% |
What You Need to Understand: By removing the unnecessary cart preview page, the treatment increased conversion by 28.60%.
Experiment #9: Orders increased 263% for online people-search company by adding the discount incentive
Experiment ID: TP1000-9
Background: An online people-search company that was losing many orders due to cart abandonment. We wanted to find a way to recover as many of these orders as possible with a minimum incremental marketing spend.
Goal: To recover partially completed but abandoned orders through a sequence of cart recovery emails
Primary Research Question: Which cart recovery sequence and offer will generate the most sales?
Approach: A/B split test (variable cluster)
Experiment #9: Control
Experiment #9: Treatment
Experiment #9: Results
263% Relative Increase in Order Rate
The treatment path increased conversion by 263.20%
Design | KPI | % Rel. Change |
Control | 19% | - |
Treatment | 69% | 263.20% |
What You Need to Understand: By adding the discount incentive, the treatment increased order rates by 263.20% and total revenue per email by 133%
Experiment #10: 25% increase in email open rate for organic meals home delivery service by including relevant information about the reduced minimum order
Experiment ID: CS771
Background: This company offers prepackaged organic meals delivered to your home. They believed that the order minimum was hurting repeat sales. They began a promotion that reduced the minimum order. An email was developed to inform previous customers of this new order option.
Goal: To get recipients to open the email
Primary Research Question: Which subject line will receive the higher open rate?
Approach: A/B single-factorial split test
Experiment #10: Version A/B
Experiment #10: Results
25% Relative Increase in Open Rate
Version B outperformed version A by a relative difference of 25.30%
Design | KPI | % Rel. Change |
Version A | 35.20% | - |
Version B | 44.10% | 25.30% |
What You Need to Understand: By including relevant information about the reduced minimum order, prospects opened the treatment email at a relative rate 25.30% higher than the control.
Experiment #11: 26% decrease in open rate, but 60% increase in conversion for large online florist by using offer-oriented subject line in Thank You email
Experiment ID: TP2033
Background: Large florist with a strong online presence seeking to increase the effectiveness of a “thank you” email campaign to previous customers
Goal: To increase the rate of return business from customers who made recent purchases
Research Question: Which email subject line will result in the greatest volume of return business?
Approach: A/B single-factorial split test of the subject line
Experiment #11: Control
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Experiment #11: Treatment
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Experiment #11: Side by Side
Experiment #11: Results
26% Decrease in Open Rate
The offer-oriented subject line decreased open rate by 25.7%.
Design | Open Rate |
Control | 20.12% |
Treatment | 14.95% |
% Relative Change: | -25.7% |
Experiment #11: Results
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Experiment #11: Results
60% Increase in Conversion
The treatment significantly increased conversion by 60.34% and revenues by 56%
Design | KPI | % Rel. Change |
Control | 10.11% | - |
Treatment | 16.21% | 60.34% |
What You Need to Understand: Looking solely at the open rate, one might conclude that the treatment underperformed. However, when drilling deeper into the metrics, it’s clear that the treatment outperformed the control. This underscores the importance of understanding the role of metrics in experimentation.
Experiment #12: 58% increase in conversions for automotive repair company by reducing friction
Experiment ID: TP1429
Background: The company is a leading automotive head gasket repair solution.
Goal: To increase total orders on cart page
Research Question: Which landing page/cart will result in a higher conversion rate?
Approach: Radical redesign of cart page through a variable cluster A/B split test
Experiment #12: Control
Experiment #12: Treatment
Experiment #12: Side by Side
Experiment #12: Results
58% Relative Increase in Conversions
The treatment generated 58.1% more conversions than the control.
Design | KPI | % Rel. Change |
Control | 2.1% | - |
Treatment | 3.3% | 58.1% |
What You Need to Understand: The reduction of friction throughout the process coupled with the single call-to-action led to a 58.1% relative increase in conversion rate.
Experiment #13: 14% increase in cart completions for travel agency by optimizing cart page with call-in data
Experiment ID: TP1368
Background: B2C company offering package vacations. In this test, we focused on improving the checkout process.
Goal: To increase cart completions
Primary Research Question: Which cart page will generate the highest completion rate?
Approach: A/B split test (variable cluster)
Experiment #13: Control
Experiment #13: Control
Experiment #13: Treatment
Experiment #13: Treatment
Experiment #13: Side by Side
Experiment #13: Side by Side
Experiment #13: Phone Numbers
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Experiment #13: Results
14% Relative Increase in Conversions
Without call-in center data, the treatment generated 13.83% more conversions.
Design | KPI | % Rel. Change |
Control | 18.73% | - |
Treatment | 21.32% | 13.83% |
6% Relative Increase in Conversions
With call-in center data, the treatment generated 6.25% more conversions.
Design | KPI | % Rel. Change |
Control | 22.63% | - |
Treatment | 24.04% | 6.25% |
Experiment #14: 43% increase in online purchases for direct-to-consumer printing brand by changing path
Experiment ID: CS31053
Background: Direct-to-consumer printing brand offering custom-printed products
Goal: To increase online purchases
Experiment #14: Funnel Analysis
Experiment #14: Problem
Experiment #14: Solution
Experiment #14: Results
Experiment #15: 40% increase in clickthrough rate for medical provider by adding “Symptoms” to both header and description
Experiment ID: TP4068
Background: Medical provider specializing in treating chronic pain
Goal: To plan a content marketing strategy based on which approach generates more appeal in condition-based searchers
Primary Research Question: Which content approach will achieve a higher clickthrough rate?
Approach: A/B Multifactor Split Test
Experiment #15: Control
Based on what we learned from the previous content approach test, if we use a symptom content approach while matching the control's specificity to each ad group, we can achieve a higher click-through rate. |
Experiment #15: Treatment
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Experiment #15: Treatment
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Experiment #15: Treatment
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Experiment #15: Results
40% Relative Increase in Clickthrough
Adding "Symptoms" to BOTH headline and description produced a 40% increase
Version | KPI | % Rel. Change |
Specialty Pain Resources | .28% | |
Treatment Options | .26% | |
Causes and Solutions | .21% | - |
Symptoms | .39% | 40. |
What You Need to Understand: Applying insight from the previous tests and inserting "symptoms" into both the headline and description created more successful treatments across all ad groups.
Experiment #16: 40% increase in revenue per order for health drink seller by clarifying value proposition in the copy
Experiment ID: TP1798
Background: A single-product company that sells high quality, all-natural, powdered health drinks
Goal: To provide clarity of value in an effort to better match prospect motivation and increase the CR of the prospects reaching the AG homepage
Approach: A/B Multi-factorial Split Test
Experiment #16: Control
Experiment #16: Treatment
Experiment #16: Side by Side
Experiment #16: Results
40% Increase in Revenues Per Order
The treatment generated an overall 34% increase in the conversion rate.
Design | KPI | % Rel. Change |
Control | 3.3% | - |
Treatment | 4.4% | 33.37% |
What You Need to Understand: By better expressing the value proposition through the copy and limiting imagery distractions, the treatment homepage not only increased conversion by 33.77% but also increased overall revenue per order by 39.95% at a 97% level of statistical confidence.
Experiment #17: 56% increase in revenue per order for precious metals exchange business by adding security seals and testimonials and removing unnecessary form fields
Experiment ID: TP1257
Background: This research partner offers investors a place where they can purchase gold, silver, platinum and palladium for their portfolios.
Goal: Goal of the experiment was to increase registration rate and revenue per visitor
Primary Research Question: Which of the following pages will produce the highest registration rate?
Approach: A/B Split
Experiment #17: Control
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Experiment #17: Treatment
Experiment #17: Side by Side
Experiment #17: Results
56% Increase in Revenues per Order
The treatment generated 56.16% higher revenue per order than the Control.
Design | KPI | % Rel. Change |
Control | $10,716.55* | - |
Treatment | $16,734.96 | 56.16% |
What You Need to Understand: Adding security seals and testimonials reduced anxiety and removing unnecessary form fields reduced friction to increase the money each customer was willing to spend.
Experiment #18: 18% increase in rate of conversion for ecommerce textbook site by sequencing the cart and justifying each action the customer is required to take
Experiment ID: TP1434
Background: An ecommerce site selling textbooks to professors in academic institutions
Goal: To increase textbook purchases
Primary Research Question: Which treatment will generate the highest conversion rate for new and existing users?
Approach: A/B/C Split Test
Experiment #18: Control
Experiment #18: Control
Experiment #18: Control
Experiment #18: Treatment
Notice the copy:
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Experiment #18: Treatment
Notice the copy:
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Experiment #18: Treatment
Notice the copy:
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Experiment #18: Treatment
Notice the copy:
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Experiment #18: Results
19% Relative Increase in Conversion
The treatment cart flow increased generated an 18.6% increase in conversion.
Design | KPI | % Rel. Change |
Control | 33.74% | - |
Treatment | 40.02% | 18.6% |
What You Need to Understand: By sequencing the cart and justifying each action the customer is required to take, the treatment cart process increased the rate of conversion by 18.6%.
Experiment #19: 3x the projected revenue by increasing email frequency
Experiment #19: Background
Projected monthly revenue rose consistently with increasing send frequency and the number of sends did not have a significant impact on the overall rate of transaction.
Experiment #19: Background
Though projected unsubscribes rise with more sends …
Experiment #19: Background
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Experiment #19: Background
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Experiment #19: Results
3x Increase in Projected Monthly Revenue
Increasing email frequency yields three times the projected revenue
What You Need to Understand: This company is losing three times its revenue by sending email only once a week instead of every other day. More frequent email sends won’t increase unsubscribes or decrease open rates.
Experiment #20: 20% relative increase in order rate for fitness company
Experiment ID: TP1665
Background: A company offering training tools for professional-grade strength and conditioning
Goal: To increase orders from website
Primary Research Question: Which category page will generate the highest order rate?
Approach: A/B variable cluster test
Experiment #20: Category Page A
Experiment #20: Category Page B
Experiment #20: Side by Side
Experiment #20: Results
20% Relative Increase in Order Rate
Category template A increased visit order rate by 19.9%.
Design | KPI | % Rel. Change |
Version A | 1.67% | 19.9% |
Version B | 1.37% | - |
What You Need to Understand: Removing the copy and moving the customer straight into course selection better matched motivation and increased orders by 19%.
Experiment #21: 13% relative increase in clickthrough rate for fitness company by changing call-to-action, and 61% increase in purchases by changing elements on category page
Experiment ID: TP1631
Background: A company offering training tools for professional-grade strength and conditioning
Goal: To increase orders from the website
Primary Research Question: Which category page will generate the highest order rate?
Approach: A/B variable cluster test
Experiment #21: Category Page A
Experiment #21: Category Page B
Experiment #21: Side by Side
Experiment #21: Results
13% Relative Increase in Clickthrough
The “view details” call-to-action increased email clickthrough rate by 13.04% when compared to the “shop now” call-to-action.
Design | Conversion Rate | % Rel. Change |
Version A | 2.3% | - |
Version B | 2.6% | 13% |
61% Relative Increase in Purchase
The new category template B increased visit order rate by 61.2%.
Design | Conversion Rate | % Rel. Change |
Version A | 2.78% | - |
Version B | 4.47% | 61.2% |
What You Need to Understand: Adding value copy to help the customer understand what a Kettlebell is and how it can benefit them increased the value exchange and increased purchases by 61%.
Experiment #22: 36% relative increase in sales for auto repair parts company by building the problem on the landing page
Experiment ID: TP1700
Background: An organization that offers car repair products
Goal: To increase overall product sales
Primary Research Question: Which page copy will generate the highest sales conversion rate?
Approach: A/B multifactorial test
Experiment #22: Background
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Experiment #22: Treatment
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Experiment #22: Treatment
Experiment #22: Results
36% Relative Increase in Sales
The new page copy increased product sales by 36.1%
Design | KPI | % Rel. Change |
Version A | 1.33% | - |
Version B | 1.81% | 36.1% |
What You Need to Understand: Adding copy to the top of the page that immediately identified the customer’s problem and how the product would fix it increased the value exchange and increased sales by 36%.
Experiment #23: $3,000,000+ projected increase in revenue per year for storage space company by making simple changes in the sales funnel
Experiment ID: TP1758
Background: A company offering competitively priced, easily accessible storage space for residential and commercial customers
Goal: To increase the number of visitors that complete a storage reservation through the website
Research Question: Which checkout page will result in the highest reservation rate?
Approach: A/B Variable Cluster Split Test
Experiment #23: Version A
Experiment #23: Version B
Experiment #23: Side by Side
Experiment #23: Results
9% Relative Increase in Conversion
The treatment increased conversion rate by 9.10%
Design | KPI | % Rel. Change |
Version A | 17.68% | - |
Version B | 19.50% | 9.10% |
What You Need to Understand: While it might seem like a small increase, the addition of a progress bar in the checkout resulted in a projected $3,000,000+ increase in revenue per year.
Experiment #24: 36% more total conversions for one-stop vacation planning provider by clarifying the sequence in the checkout process
Experiment ID: TP1621
Background: The research partner is a one-stop vacation planning solution that allows users to book vacation rentals, car rentals, and activities.
Goal: To increase final vacation bookings
Research Question: Which page will yield the highest conversion rate from billing information to confirmation?
Approach: A/B variable cluster split test
Experiment #26: Control
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Experiment #24: Treatment
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Experiment #24: Side by Side
Experiment #24: Results
36% Relative Increase in Conversion
The treatment increased conversion rate by 36.10%
Design | KPI | % Rel. Change |
Control | 27.40% | - |
Treatment | 37.20% | 36.10% |
What You Need to Understand: By clarifying the sequence in the checkout process, the treatment generated 36.1% more total conversions than the control.
Experiment #24: Not This, But This
Experiment #25: 45% more Twitter followers and 31% more Facebook fans for ecommerce clothing site by hosting giveaway contests via social media channels
Experiment ID: CS31543
Background: B2C ecommerce site offering men’s and women’s clothing
Goal: To increase engagement and brand awareness among key social media channels
Research Question: What will help grow engagement with our social media channels? How can social media impact sales?
Approach: Giveaway contests via social media channels
Experiment #25: Social Media Campaign
“20 Days of Decent Giveaways”
Experiment #25: Example Messages
Example Facebook Message: "First Giveaway: We’re giving away 5 pairs of ... Renton and Latika fleece jackets. Reply to this post to enter. We'll pick 5 random winners in 30 minutes. Good luck. LTM Lola“ Example Twitter Message: "We’re giving away 5 pairs of … Renton & Latika Fleece Jackets. Retweet #WINMJFLEECE to enter to win. We’ll pick 5 randoms at 2:30 EST" |
Experiment #25: Results
15% Increase in Sales
The campaign increased sales for products the team used as prizes by 10% to 15%
What you need to understand: Overall, the team captured 45% more Twitter followers during the effort, bringing their total to more than 5,600. They also captured 31% more Facebook fans, bringing their total to more than 20,000. |
“Instead of just a customer re-tweeting a single tweet or replying something random [in Facebook], they really got into it and talked about why they liked the product, why it’s a good product, why they love the brand and why they love [our brand].”
- Gary Wohlfeill, Creative Director
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