Path Analytics FAQ

Path Analytics provides a unified view of the role of content in the buyer’s journey and the impact it is having on your business across the three key dimensions of visitors, accounts, and content.

Whereas the Target, Recommend and Explore track analytics provide a great deal of descriptive detail on what has happened with specific visitor journeys at the track level, Path Analytics seeks to provide a new level of insight across all of your marketing that helps you identify what is and is not working.

By highlighting things like trending topics, performant channels, underperforming assets, account penetration, when and where conversions are happening, and showing your content’s influence on pipeline and revenue, Path Analytics arms you with the data you need to make informed investment decisions on content, tactics, and campaigns.

In addition to standard content engagement data that we capture across key dimensions like visitor, account, and content, there are some calculated metrics unique to Path Analytics that are presented to marketers in to order to provide them with new insights, highlight areas of interest, and provide a data-driven view of what is and is not moving the needle with your marketing. Some examples of these include our Engaged Intent score, Cost per Minute of Engagement, Content ROI, and Content Influence on pipeline and revenue.

Engaged Intent is the cumulative engagement score for a visitor or account, based on the engagement time thresholds you set for a content asset in the Content Library. A higher Engaged Intent score in a period for a visitor or account shows their real depth of engagement as measured in significant time spent with your content. Much like a lead score is used as a proxy for the qualification of a lead across many criteria, Engaged Intent is a proxy for depth of interest in your content and its related topics.

Typically when you are looking at any bubble chart and hover over a bubble, you will see at least three main figures related to that specific bubble. Two of those figures are the x-axis and y-axis and the third one is the Bubble size criteria.

Previously existing Target, Recommend, and Explore track analytics remain the same. Path Analytics aggregates data over all of the content engagement tracked by PathFactory and provides visitor, account, and content specific views of it.

The data shown in Path Analytics is derived from the same detailed visitor session data that we capture when your prospects and customers interact with your content. There is no impact on the rich dataset that we can set to the MAP today, but we are currently not sending any aggregated or calculated metrics in Path Analytics such as Content ROI or Top Topics at an account to the MAP.

Yes, any visitor who is excluded from analytics due to the exclusion rules that have been set won’t show on Path Analytics.

As of April 16th, 2020, all Account Identification within PathFactory is provided by 6sense by default, so the accuracy of a match from a visitor to an account is dependent on upon what they provide back to us. An accurate match rate can vary based on geography, the size of the account, and whether a visitor happens to be on a different company’s network. Occasionally 6sense may mis-attribute a company name.

We also support integrations with Demandbase for customers with eligible Demandbase licensing. Contact your CSM to learn more.

In some visitors pages in Path Analytics, you may see sessions with a Total Time of “Bounce”. This can happen when a visitor starts viewing your content online (starts a session), spends some time on it, and then leaves the web page in their browser without closing the tab. While PathFactory will recognize the idle time and stop tracking that session, if the visitor then quickly passes through the tab again or clicks on the tab in order to close it we record that brief interaction as a ‘bounce’ since there is no true engagement except for a strong signal that the visitor has left the site altogether.
We believe this information may be useful in the future to understand engagement patterns so we have chosen to retain it. You may filter the bounces out of your view in order to focus on sessions with real engagement.

In Path Analytics we are using aggregate data from the latest day. As a result, there is a filter to show you the last 7, 30, 60, and 365 days of aggregate data in most of the Path Analytics reports. Simply click on dropdown on the top right of the page and change the filter to see a different timeframe. By default, we are showing the last 30 days data. More flexibility around time ranges is planned for future releases.

Opportunity Influence gives you insight into the relative performance of your content assets, based on their impact on revenue and pipeline. This is a measure of how content was involved in, and influential to, engagement across target accounts—​not to be confused with attribution.

It is calculated as the sum total of all opportunities tied to accounts which have engaged with your content.

There are two places in Path Analytics where you’ll find Opportunity Influence:

It is important to note that these are Influence models, not Attribution models.

Content Opportunity Influence reflects all open or closed-won opportunities which the content influenced, not which the content was directly responsible for.

In PathFactory, a known visitor’s linked account is determined based on the visitor’s email domain first. PathFactory passes this domain to our IP address intelligence provider to see if it can identify the visitor based on the email domain. If the provider can’t identify it as a non-internet service provider account, the account name associated with the IP address is used to determine the visitors linked account name. As a result, you may see Google as a top account if the domain is associated with Google.

This can be caused by a few reasons:

If you see the same visitor appear in multiple accounts at the account level, this is because at the time of the visit it was determined they were linked to that account. However, at the visitor level, the account that is shown will always be the latest account that we have seen for them.

Addressing Bot Traffic in your PathFactory Data 

Bot traffic is an issue in market-leading analytics tools (such as Google Analytics) most of which implement algorithms to detect and exclude bot traffic. PathFactory uses similar logic to detect and exclude visits from known bots and spiders on the web. However, this is not foolproof, as bots proliferate in ways that make them more elusive and hard to detect in some cases.

PathFactory will continue to update our session processing, to mitigate inflated traffic from bots and browser anomalies.

Reducing bot traffic appearing in session data

An exclusion is added to all PathFactory environments, filtering any session with “utm_TrafficCategory=Server” in the URL. Terminus uses this in it’s advertising platform to identify crawling bots. All data, reporting and analytics filter this traffic out.

PathFactory only records visits when, at a minimum, the PathFactory asset has loaded including our scripts

• In order for PathFactory to record a pageview, the asset link needs to load in a web browser and our script needs to run
• Not all bots need to load assets in a web browser when they conduct their activities. Bots are software applications that come with different behaviors: some may just look at the source code of the page, and some might crawl the email link in a way that triggers a click/open but not a pageview
• PathFactory maintains a list of bots using IPs and browser agents that have been identified and shown to either be benign or malicious. However, many bots do not identify themselves as such and the technology behind them keeps evolving.

PathFactory is confident in the accuracy of the pageviews counted in reports, however, we are happy to work with your team to create a testing plan to confirm that a view is getting recorded in our analytics when legitimate visitors launch a PathFactory track. 

How to tell if it’s bot traffic

• Engagement times that are excessively high.
• Engagement times that are extremely low with an excessive amount of clicks within seconds
• Large volume of traffic from a company/account that could be masking as a network/internet service provider, eg Microsoft.

Reducing bot traffic within a Marketing Automation System

Bot traffic inflating clicks and opens is on the rise for Marketing Automation systems across the board. 

• Marketo offers a filtering mechanism that removes bot activity based on bot lists, UA/IPs, and proximity patterns
• Hubspot offers a bot detector that takes a behavioral approach to assess bot patterns
• Pardot automatically filters bot traffic based on certain IP ranges 
• Eloqua removes bot traffic from performance reporting by working with their clients to identify click-bot suspicions 

You can also limit the amount of bot data driving to your system by specifying a minimum session time that must be met for data to pass to your marketing automation platform. You can set this minimum session time for activity and session webhooks by navigating to Gear > Webhooks. Select an existing webhook; in the right sidebar, select Minimum Session Time and enter your desired time.

If you are a Marketo user, you can also set a minimum session time requirement for both your form submission and custom object exports. Navigate to Organization Settings and select the Marketo Account tab. Within the form submission or custom object export you want to update, select Edit and the minimum session time will be available to set in the edit modal.