In the summer of 2010, ATG commissioned a survey to analyze consumers’ online shopping preferences and behaviors. The online survey polled 1,002 U.S. consumers aged 18 and older. Respondents were selected from a panel of more than 2.5 million individuals, who were profiled across more than 500 attributes, such as demographics, lifestyle, and behavioral characteristics.

The survey asked consumers a wide range of questions about:

• What online and offline channels are most likely to lead consumers to discover new products;
• How consumers use mobile devices to browse and research products, and make purchases, and how these behaviors vary by age segment;
• Whether and how often consumers use their social networks to make shopping decisions, and how these behaviors vary by age group;
• Which areas of web stores need to be improved the most;
• When consumers conduct most of their holiday shopping;
• Whether consumers are influenced by website recommendations; and
• The most common factors that lead to shopping cart abandonment.

I highlighted some of the most interesting charts above. Download the entire 26-page PDF report at ATG for lots more data and charts.

Download the free report at ATG »

Home improvement site, Build.com, which had online sales of more than $166 million in 2009, boosted conversion rates 23.1% and the average order value by 9% year over year, when they added personalized recommendations for similar and complementary products to its product pages.

Before adding the personalization application, they manually suggested additional items for purchase on product pages. The process was tedious and required constant updating.

Build.com added Omniture Recommendations to its site which uses algorithms to analyze visitor data to deliver relevant content to consumers based on what other consumers have viewed, searched and purchased.

The success of the program has led to extending its personalized recommendations to its category pages, home page, and marketing e-mails-which boosted conversions by triple digits.

Does your website offer personalized recommendations for similar and complementary products?

Full story at Internet Retailer »

Related: Retailers are sharpening their focus on recommendations: Survey of 100 companies found that every respondent who didn’t already have a product recommendation engine was planning to deploy one by 2011 »

Original

Test Ad #1

Test Ad #2

Test Ad #3

Test Ad #4

37Signals used Google Website Optimizer to randomly rotate five different headline and subhead combinations on the signup page.

They measured the number of clicks on any green “Sign Up” button. They ran the test for 4000 page views, because the numbers didn’t change much after about 3000 page views, so they stopped at 4000.

So which ad converted 30% better than the original?

The answer….

Test ad #1 performed 30% better than the original. Test ad #2 performed 27% better; test ad #3 performed #15% better; and test ad #4 performed 7% better than the original.

Are you split testing your sales letters? It is the quickest and cheapest way to increase sales and profits.

Full story at the 37Signals Signal vs. Noise blog »