Update: The Google Analytics Blog discusses our Social Commerce Insights integration

ROI is the “white whale” for countless brands trying to measure (and justify) their social media efforts, and aligning measurement with preexisting goals is often easier said than done. Not so with social commerce, which is inherently measurable and performance-oriented. We’ve been releasing findings for years showing the impact of user-generated content on the metrics businesses care about, but our latest numbers are even better than we expected.

Analyzing a random sample of our many clients currently using our new Social Commerce Insights solution with Google Analytics, we’re able to easily quantify the impact of our social commerce platform on key metrics like conversion and revenue per visit.

On average, after viewing a product page, customers who interacted with Bazaarvoice solutions had more than a 50% higher conversion rate  and over a 70% increase in revenue per visit. These numbers, taken from over thirty-five million visits, show how important it is for customers to hear from others like them during the consideration process–before they have enough confidence to purchase the product in question.

The screenshot below shows just how easily brands can now monitor the influence of user-generated content in Google Analytics (click to enlarge).

Click to enlarge
Click to enlarge

For marketers, these findings provide yet more hard evidence that social media can be integrated with the online shopping experience in ways that move the needle on the critical metrics they already monitor.

Interested in the new solution behind the findings? Learn more from our press release or request a demo.

5 Responses to “Removing the guess work from social media ROI”

  1. Andy Wolfe

    Thanks for the question. A calculation like this might be used to approximate the increase in online sales for users who explicitly engage with Bazaarvoice content. Explicitly engaging means the user clicks a link; whereas, simply seeing an average rating, for example, doesn’t register an interaction – that eye contact can be approximated but becomes less accurate… To look at overall impact, i t’s also useful to analyze other metrics to see the relationship between interaction with user-generated content (UGC) and other online marketing and offline goals.

    As far as the numbers themselves, this chart is actually sample data of what the difference in conversion might be for users who do versus do not click on Bazaarvoice-hosted UGC. The sample number we’ve used for conversion of visits engaging with UGC is 6.78% (and 4.31% for visits not engaging – this difference is consistent with the findings from our case study); however, this graph doesn’t show the percentage of traffic marked as interacting with Bazaarvoice. Social Commerce Insights shows our individual clients which percentage of their users explicitly engage with UGC, but it’s difficult to generalize that across clients. That’s because these explicit interactions are very client and Bazaarvoice-implementation specific, depending on how strong the call to action is and where the content is located on the page.

    Great comment, and you’re right – we want to exclude visits that bounce from our calculations.

  2. Virusmaker

    I wonder what the net effect is, for that what’s needed is the percentage of all users (probably excluding the bounce rate) interacting with BV. From the graph it seems like this is slightly below 10%. Suppose that’s 7% of all traffic, then the net value-add would be 7%*70%(increase per visit) = ~5% total revenue increase (not bad at all). Is that right?

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