Lift shows us the effect of attributable web visits during the campaign period. Lift is calculated by dividing the Ad Visits by Non-Ad Visits. Hover over the ‘i’ icon on the Lift top line metric to view the equation with your unique campaign data!

Visits will detail the total number of site visits which occurred on your client’s website during the time frame selected. Next to that number, we will also see a metric here for the total visits on days when our ads were on air. So of the total visits this Advertiser website experienced during the selected date range, a certain subset of them are from days when ads were running.

Ad Visits represent sessions as defined by Google Analytics. This refers to visits to the advertiser website that occur within the 10-minute attribution window. This is also synonymous with the term “Attributable Sessions.”

New Ad Users shows us the number of first time visitors to a client’s website during Attributable Sessions. This is a different metric than Sessions or Visits, showing the power of broadcast to drive new people to a website. It is determined by the web user’s IP address.

Total Ads is the number of commercials that ran during your campaign, including any tracked spots or unlogged lives. We track this by how you’ve set up your searches in Step 3: Find Ads during campaign creation.

Average Ad Cost represents the average cost of commercials for the metric you are viewing. Example, the Ad Cost for Morning Drive is the cost of all commercials in that daypart divided by the number of spots. Keep in mind that any low charge or no charge commercials will lower your average rate. This data is needed to help your client understand the efficiency of dayparts, ads, days of week, etc. when compared with Ad Visits per spot. This metric will only appear in your dashboard if you are sharing that information with Veritone in your traffic logs.

You can further drill down to your Campaign Dashboard by clicking into the various reporting tabs.

On the WEB TAB, you can view your client’s top line web traffic trends according to their Google Analytics reported activity, during, before or after a campaign. Toggle on the Compare Date Range setting on the first Web graph to compare on air periods to off air periods, essentially establishing a baseline of web activity to demonstrate your campaign’s effect on web traffic trends. In order to accurately compare data trends, you should also keep the time period duration being compared 1:1. In other words, if you are looking at a 2 week span during the on air Campaign period, you should update the comparable, inactive (or off air) period to a 2 week span as well. You can customize the dates being compared to determine the best and most accurate depiction of lift.

While this will default to show 30 days prior to your campaign start date, we recommend you adjust this date to select a time period that can reasonably reflect when your client was not actually running ads at all; the idea is to establish a baseline comparison.

Web data visualized in the graph is broken out in more granular detail in the associated table below.

Please note: You can view this data through different data cuts by selecting the drop downs shown, by Total Visits or by Ad Visits. Keep in mind when viewing the graph through the Ad Visits data cut, you should not be using the Compare Dates feature.

The two smaller visualizations on this page further break down the web data comparisons available. First, the Time of Day graph displays a heat map of when an on air Ad performed the best via Ad Visits. Second, the Total Change graph shows us the daily average web visits on days when ads are running (Daily avg. visits with ads), compared against the daily average visits on days without ads running (Daily avg. visits without ads). We get the final percentage number by dividing the total change divided by Daily avg. visits without ads. The total change is calculated by subtracting the Daily avg. visits with ads and Daily avg. visits without ads.

Moving to the DAYPART TAB, we will see how our ads map against our client’s attributable and non-attributable website traffic. Optimize your current or future campaigns by viewing Ad Visits by Daypart, Hour, Day of the Week or Date and determine where ads performed the best. Optimized campaigns will show a strong correlation - represented by the pink overlay representing ads shown here - between when ads ran and when visits occurred. Utilize the associated drop-down menus to switch between different data cuts, including Ad Visits versus New Ad Users, and/or the various reporting views (by daypart, by hour, by day of week, or by date). You can also adjust the visit and ad data included by selection or de-selecting Non-Ad Visits, Ad Visits, and/or Ads to build the most effective story for your reporting.

This data visualized in the graph is broken out in more granular detail in the associated table. The table will dynamically update based on the data cuts selected in the graph.

Surface top performing ad types for mid or post-campaign optimizations in the PLACEMENT TAB. In this tab you will be able to view how all the elements of your Campaign, including Pre-Recorded spots and non-logged or unplanned Lives, stack up to drive traffic during the Campaign period. Please note you will only see native live mentions broken out on this tab if your Campaign includes this type of placement and the Live Reads search was set up during Campaign creation.

You will also gain better visibility into the relationship between all ads and mentions on a station by station level. Analyze performance by referencing Ad Visits per Ads in the data table to identify underperforming stations and optimize accordingly.

The CREATIVE TAB is where you can see a break out of all creative running during a Campaign. Like on the other tabs we reviewed so far, you can view this data through different data cuts - such as by Creative or by Duration as shown in the drop down here. Evaluate creative performance based on type, duration, the number of ads run, and creative messaging.

Tip: Use the Ad Visits per Ad metric in the associated data table to optimize your Campaign by identifying the Creative that drives the best attributable web traffic.

On the LOCATIONS TAB, we will see how campaigns running nationally, in multiple markets or a single market are performing. You can use this tab to understand how different markets performed by referencing the Visits per Ad metric in the table. Note that the map will update as you click the displayed location, continuing to drill-down into more granular geographic areas.

Use the CHANNELS TAB to view various traffic sources and their contribution to attributable web activity. This indicates how a web user got to the associated website URL we are tracking. These values and definitions are specified by Google Analytics. Please see below for a description of each Channel:

  • Organic Search - This traffic found the site via a search engine such as Google or Bing.

  • Display - This traffic found the site by clicking on an ad which ran on another website. Banner ads on blogs and image ads on news sites are some common generators of display traffic.

  • Direct - This traffic came to the site by entering the URL directly into the address bar of browsers. This requires audiences to remember and type out the web address.

  • Referral - This traffic follows a backlink from another website to the one Google Analytics (and Attribute) is tracking, and you'll see this traffic if it doesn't fall under one of the other buckets.

  • Paid Search - This traffic comes from paid search ads which appear at the top of the search results of Bing, Google, or other search network players like AOL and

  • Social - This traffic will be counted from people who find the webpage through an associated social media account.

  • Email - This traffic clicked on links from email campaigns, follow up emails, and even email signatures.

  • Other - If Google Analytics cannot determine how a user landed at the website, it is defined in this Channel.

Finally, on the REPORTS TAB, you will be able to pull a report of this data to share internally or with your clients. You can customize your report by leveraging the side panel to enter personal details. To export your report, click on the blue Download button at the bottom of the page and select a format to export locally to your computer.

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