Examine Campaign Statistics
Learning Objectives
After completing this unit, you’ll be able to:
- Recall essential Marketing Cloud Personalization (MCP) terminology and metrics.
- Explain how attribution and goal setting work in MCP.
- Access and interpret MCP campaign statistics.
Campaign Statistics Key Terms
Before you pore over MCP campaign data, it’s important to get to know some key terms around campaign statistics, which are segmented by topic. Start with statistical significance—the measure of how certain you can be with a reported lift. (Note: Lift is a statistically significant improvement in a measured business goal.) A metric is determined to be statistically significant based on a number of factors built into Marketing Cloud Personalization’s algorithms attribution window. Marketing Cloud Personalization attributes visitor purchases, clicks, and goal achievements based on their interaction and level of interaction with an MCP campaign.
For the event to be attributed, both the visit impression and the goal event (for example, a purchase, a click, or other goal achievement) need to happen within the timeframe selected, known as the attribution window. The attribution window you select depends on the type of campaign you’re running. For example, for a campaign that needs an immediate response, like a popup, you typically look at an attribution window of 30 minutes.
Here are some terms associated with visitors that you see in campaign statistics.
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Unique visitors: This is the number of tracked individuals who saw the campaign.
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Impressions: This is how many times the campaign was seen. It may be greater than the number of unique visitors, since they may see a campaign more than once.
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Clickthroughs: This is the number of click actions that happened during the campaign. Be aware that you only see click-through data if there’s something to click on the campaign, like a button or a link.
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Click-through rate: This is the number of clicks divided by the number of impressions. Keep in mind that if clickthroughs are zero, the click-through rate is also zero.
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Dismissals: This is the number of times the message was closed using the close icon.
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Dismissal rate: This is the number of dismissals divided by the number of impressions.
Here are revenue-related terms you see in campaign statistics.
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Revenue: This is the amount of revenue generated from the people who saw the campaign and then made a purchase or a download during the selected attribution window.
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Revenue per user: This is the total revenue generated divided by the number of visitors who saw the campaign experience and then made purchases or downloads during the selected attribution window.
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Average order value (AOV): This is the total revenue collected divided by the number of orders. This gives the average basket size for the visitors who saw the campaign and made a purchase during the attribution window.
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Orders: This is the number of orders placed by visitors who saw a campaign experience during the attribution window. These are not only product orders, but are considered by Marketing Cloud Personalization as a goal completion on your site. This includes things like product purchases, content download registrations, form submissions, and newsletter signups.
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Conversion rate: This is the number of orders collected divided by the number of unique visitors who saw the campaign.
Global and Campaign Goals
There are two types of goals in Marketing Cloud Personalization—global and campaign level. Both types of goals use segments you create that define the goals you want visitors to complete. Global goals are the primary actions you want visitors or users to complete on your website or mobile app. For example, global goals can include completes a purchase, adds to cart, downloads or views content, or completes a form. An admin configures them in settings and they can be used for reports and campaign statistics.
Once a global goal is created, you can view how any campaign is performing against the goal. Applying global goals to a campaign gives you a broader view of the effects of a campaign beyond the immediate metrics. Campaign-level goals are set for a campaign only and are usually tied to very specific narrow actions because when you set a campaign-level goal, any visitor who reaches the goal doesn’t see the campaign again. One example of a good campaign goal is moving people through different audience segments. For example, once a visitor watches a getting started video, they complete the campaign goal and don’t see the message again.
How to Access Campaign Statistics
Here are the steps to follow to see your campaign stats in Marketing Cloud Personalization.
- Hover over the channel and then select Campaigns.
- Click Web and Web Campaigns.
- Click Campaign.
- Select Statistics.
Here’s what you find when you view MCP statistics.
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The activity timeline shows activity for your campaign since its creation. The range selected for viewing reports is highlighted in blue. A marker indicates changes.
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The green bar begins on the date the campaign went live. Date and time range can be adjusted to show dates and times during which the campaign existed. Click the header to jump to months and then click again to jump to years. Dates and times are shown in local time.
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The comparison baseline is what you compare the campaign metrics against. You can compare each experience to the other to see which one performed better. If experience A is the baseline, you can see if the revenue or conversion rate was higher for experience B as compared to experience A activity.
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The chart directly below the graph gives the aggregate data for the selected time window. Depending on the selected comparison baseline, you see different information in the section.
There are also other options and filters that you can apply. For each detail graph, you can get insight into which experience was most successful. You can also hover over the graph to see details about the data points. For example, with the attribution window set at 30 minutes, revenue per user shows that recommendation A is several percentage points above B. You can add and remove the experiences on the graph by selecting them. Goals and filters add a layer of detail to campaigns. Using them gives you the most helpful analytical data. The campaign statistics graphs and charts give you insight into the effectiveness of your campaign.
So what’s the bottom line? Effective use of templates and campaigns (including campaign statistics) in MCP ensures you get the right messaging to the right audience as efficiently as possible. Use campaign statistics as a guide to continually adjust to improve results.