Conversion Impact report

Bazaarvoice offers a detailed, interactive Conversion Impact report (CIR) that reveals key information about the impact of Bazaarvoice content on your online business. The CIR describes the differences in behavior between visitors who interacted with Bazaarvoice content and those who did not.

Why is it important?

At a glance, you can see and evaluate the business impact of Bazaarvoice content on your visitors, conversions, and percent lift. You can also use the information in the report to measure other aspects of your business.

The following examples describe ways in which the CIR might be helpful.

A company recently started using Bazaarvoice products, and the digital marketing lead for the company wants to know how much of a return on investment the products provide. She consults the CIR and sees that the conversion rate of customers who interacted with Bazaarvoice content shows a 35% lift over the conversion rate of customers who did not. She infers that Bazaarvoice products helped drive higher conversion rates.
A company maintains separate storefronts for different regions—an English site, a French site, and a German site. Each site uses Bazaarvoice Curations and displays consumer-generated content (CGC) in its native language. A marketing specialist looks at the CIR data for each site and sees that the French site has a much higher average order value lift than the English and German sites. He surmises that efforts to solicit French-language CGC are working exceptionally well and that the content is especially compelling. He directs his team to study the French-language marketing and content to see if any lessons can be learned and applied to the English and German sites.
A company recently implemented the BV Pixel and wants to independently verify that it is working as they expect. The analytics lead for the company compares CIR data to data from her own internal sales reports. She notices that the CIR lists significantly fewer sales than her own data and contacts Bazaarvoice to determine why. She learns that her company’s implementation of the BV Pixel has issues and corrects them.

Access the dashboard

Bazaarvoice offers two different versions of the CIR. The version you use depends on your reporting needs:

e-Commerce Conversion Impact report—Available to e-commerce clients and offers new audience segments, category filtering, mobile and non-mobile views, currency normalization, and support for all Bazaarvoice products. This report provides a three-day attribution window of data, which attributes any conversion action that takes place within three days of the visitor’s initial visit to a visitor segment.

To access this report:
1. Log in to your Bazaarvoice Workbench.
2. Select Reports » Dashboards.
3. Click e-Commerce under Conversion Impact in the Dashboards navigation menu.
Non-e-Commerce Conversion Impact report—Preferable for all non-e-commerce clients and some e-commerce clients who want a one-day attribution window and flexibility over reporting date ranges.

To access this report:
1. Log in to your Bazaarvoice Workbench.
2. Select Reports » Dashboards.
3. Click Non-e-Commerce under Conversion Impact in the Dashboards navigation menu.

e-Commerce Conversion Impact report

The e-Commerce Conversion Impact report (CIR) provides e-commerce reporting data only.

Note: If you have not implemented the BV Pixel, the Conversion Impact report does not display report data. However, the page includes information and a link to help you get started with BV Pixel setup.

The e-Commerce Impact tab shows how shopper purchasing behavior varies with the presence of and interaction with Bazaarvoice content. The Enagement Breakdown tab shows how purchasing behavior varies by shopper engagement level.

Filters

The CIR allows you to segment your visitor data through the use of filters at the top of the report.

Date Range—The month or single day for which you wish to segment your CIR data.
Bazaarvoice Solution—One or more Bazaarvoice solutions for which you want to view conversion data.
Display Code—Deployment zones created during your Bazaarvoice implementation. You can create unique display codes for each locale that you support, which enables you to filter your CIR data by those locales (display codes).
Device Type—The device category (mobile or desktop) that the visitor used to access your site. “Mobile Web” refers to browser traffic from mobile phones and tablets rather than a company’s native app. “Desktop” refers solely to desktop (non-mobile) traffic.
Root Category—The top-level category of your products based on your product catalog.
Sub Category—A category-level beneath the top-level category of your products based on your product catalog.

Definitions

This section provides definitions for the metrics and visitor segments found in the CIR.

Active—Visitors who actively interacted with Bazaarvoice content by taking an action such as sorting, filtering, paginating, clicking, hovering, or highlighting within the Bazaarvoice container.
Passive—Visitors who saw Bazaarvoice content on screen, but did not actively interact with any functionality.
Note: On-screen content is detected by InView and ViewedUGC events.
Did Not Engage—Visitors who reached a page where content was present, but did not passively or actively engage the content.
No Content—Visitors loaded a page with Bazaarvoice code that had no content, such as a product page that does not have reviews yet.
Visitors—Unique visitors detected across tracked pages during the specified date range. Tracked pages include any page that loaded Bazaarvoice analytics tagging, whether through the Bazaarvoice-hosted display or through the Analytics for API solution.
Note: The monthly report calculates and displays monthly unique visitors. Selecting multiple months at a time will have the report display a summary of the visitors across each monthly report selected. The daily report calculates and displays daily unique visitors.
Orders—The total number of orders placed, where each unique orderId sent by the BV Pixel transaction event counts as one order.
Revenue—Total revenue from orders, defined by the total from each order sent by the BV Pixel transaction event. All revenue is converted to USD using the closing currency conversion rate for that day.
Conversion Rate—Orders divide by visitors.
Average Order Value—Revenue divided by orders.
Revenue Per Visitor—Revenue divided by visitors.

Attribution window

When a visitor meets the criteria of one of the segments (No Content, Did Not Engage, Passive, or Active), the CIR associates conversions that occur within three days of meeting that criteria. The three days are known as the attribution window.

For example, a customer might look at reviews for a product one day but not purchase the product until the following day. This purchase falls within the window of time when Bazaarvoice attributes the purchase to the reviews that were read by the customer.

Since 90% of transactions in the Bazaarvoice network occur within three days of viewing a product, the default conversion attribution window is set to three days. The attribution window cannot be customized at this time.

Report availability

The e-Commerce CIR cannot generate a report for a given month or day until the three-day attribution window has passed. Then, it takes two full days to transform the raw data into the final report.

For a monthly report, you can view the report at the end of the sixth day of the following month. For example, for April’s monthly report, the attribution window accounts for May 1-3, May 4-5 are required for calculations to create the final report, and the report becomes available May 6. Report processing begins 12:00 AM Pacific Time on May 4, so the report is typically available at the 11:59 PM of May 6.
For a daily report, you can view the report six full days after a given date. For example, to view a daily report for April 15, the attribution window is April 16-18, April 19-20 are required for calculations to create the final report, and the report becomes available April 21. The report will typically be available at 11:59 PM Pacific Time on April 20.

Note: The e-Commerce CIR contains data from July 1, 2016 to present, assuming you passed the required BV Pixel events during that period of time.

The following image is an example of the period of time captured in a monthly report.

The following image is an example of the period of time captured in a daily report.

Visitor segmentation

The Conversion Impact Report assigns visitors, orders, and revenue to the segment of highest engagement that the visitor met the criteria for during the selected reporting window for each product category and sub-category. These segments are Active, Passive, Did Not Engage, and No Content, and are defined in the Definitions section. The reports are further separated by product categories to better understand how products in each category compare with one another.

If, for example, a visitor named Skye browses multiple tracked pages in the same reporting window, but engages at a different level on each, the report will count her as only one visitor and assign her to the segment of highest engagement. So, if Skye passively engaged with Bazaarvoice content on March 15, and then actively engaged on March 19 (on a product in the same category), the monthly report for March would count her as one visitor in the Active segment.

Example scenarios

Jane

Day 1 (March 18, 12:08p): An online visitor, Jane, arrives at your site and browses the product page for the “SUPER Speed Running Shoes.” These shoes have Ratings & Reviews content. She scrolls down to read the content, but does not actively click on it (for example, she does not sort or filter the Ratings & Reviews). She decides to wait before making her purchase because she wants to do more research, so she does not place an order.

Jane is considered a Passive visitor in the Shoes category because she did not actively interact with Bazaarvoice content.

Day 1 (March 18, 2:23p): Later that day, Jane decides to browse a different product: “Formula Fresh Laundry Detergent.” This product also has Ratings & Reviews content. She notes the Rating Summary at the top of the page indicates the product has 721 reviews with a 4.5 average star rating. This information gives her the confidence to place an order without scrolling down to read or click on Ratings & Reviews.

Jane is considered a visitor in the Did Not Engage segment in the Laundry category because there was content on the page, but she did not engage with it passively or actively.

Day 1 (March 18, 6:39p): Later that evening, Jane decides to browse a third product, which also happens to be in the Laundry category: “Amazing Scent Fabric Softener.” This product does not yet have Ratings & Reviews content, but she decides to place an order for this product anyway, given the product requires a fairly low level of consideration.

This action alone would put Jane in the No Content segment in the Laundry category.

Day 4 (March 21, 9:32p): Three days later, Jane comes back to research the “SUPER Speed Running Shoes” again. She scrolls down to the Ratings & Reviews content and, unlike her previous visit to the page, actively filters for only the 4-star reviews. She now decides she has enough information to make her purchase decision and places an order for the shoes.

Jane is now considered an Active visitor in the Shoes category.

Michael

Day 7 (March 24, 7:28a): A second online visitor, Michael, reaches the site and browses the “XTREME Speed Running Shoes.” These shoes have Ratings & Reviews content. He scrolls down to read the Ratings & Reviews, but does not actively click or place an order.

Michael is considered a Passive visitor in the Shoes category.

Day 12 (March 29, 10:43a): Michael returns to the “XTREME Speed Running Shoes” page again. This time, he clicks to sort the reviews by Lowest Rated to Highest Rated, and then places the order.

Michael is now considered an Active visitor in the Shoes category.

Results and interpretation

The resulting data displayed in the report depends on which report was accessed (monthly or daily).

Daily report example

Report accessed on: March 24
Report selected: Daily for March 18

If you filter for the Shoes category: one visitor and one order added to the Passive segment; zero visitors and zero orders added to Active, Did Not Engage, and No Content.

Note: Because Jane’s order on March 21 falls within the three-day attribution window for March 18 (when she passively engaged), the order is attributed to the Passive segment.

If you filter for the Laundry category: one visitor and two orders are added to the Did Not Engage segment; zero visitors and zero orders are added to Active, Passive, and No Content.

Note: Because Jane browsed and purchased a product without content—the "Amazing Scent Fabric Softener"—you might have expected her to fall under the No Content segment. However, she remains in the Did Not Engage segment because she previously browsed and purchased a product with content that is also in the Laundry category—"Formula Fresh Laundry Detergent." While she may have been influenced by the Rating Summary, she did not meet the criteria of the Passive segment, which requires visitors to have the primary Ratings & Reviews content container on screen.

Monthly report example

Report accessed on: April 14
Report selected: Monthly for March 2017

If you filter for the Shoes category: two visitors and two orders are added to the Active segment; zero visitors and zero orders added to Passive, Did Not Engage, and No Content.

More detail: This is because the Conversion Impact Report gives credit to the action (segment) of highest engagement during that time frame. Even though Michael passively engaged on March 24, he then actively engaged on March 29 before he made his purchase.

e-Commerce Impact

This section compares the conversion rate of No Content, Passive, and Active visitor segments against the Did Not Engage segment, and it highlights the difference between each. The +/- percentage reported for each visitor segment shows the lift when comparing that visitor segment against the Did Not Engage segment. A green + indicates a positive lift, and a red - indicates a negative lift.

The following formula is used to calculate the conversion rate lift:

Engagement Trend

This section in the Engagement Breakdown tab shows the conversion rate for each visitor segment over the course of the selected time frame. You can use this section to quickly spot anomalies that you want to investigate further using the Daily Report tab or your own web analytics.

Note: This section of the report is unaffected by the filters.