Identify the marketing touchpoints that influence a visitor's conversion with Factors.

View all the marketing touchpoints prior to conversion; the conversion event or value of the conversion can be attributed to the touchpoints using one of the following techniques -

Conversion Goal in Factors can be thought of as the final user action which a campaign is expected to drive. The success and ROI of the campaign will be measured based on the number of users who perform this action and the cost incurred for the same.

Typically conversion goals are high value actions such as:

Within the conversion goal drop down, all the events received by Factors would be listed down as shown in the image below. The user can simply choose from the list:

In case the required conversion goal that you’d like to track for your campaign isn’t listed in the dropdown, you can simply create a custom event and define the user action that you wish to analyse.

Before you start creating an attribution report on Factors, it’s important to determine the touchpoints that you’d like to have in your attribution report. For instance, a user in his journey with your organisation may be exposed to different types of marketing touchpoints such as:

Within Paid Marketing, given there is a hierarchy of levels (Source -> Campaign -> Adgroup -> Creative / Keyword) the user can select only one of the hierarchy elements for the attribution report.

For email marketing campaigns, one can also include offline touchpoints. Learn how to create Offline Touchpoints on Factors here.

After ensuring all the above mentioned requisites, you are all set to build your attribution report.

Custom Dimension: With Custom Dimensions you can create custom segments based on your campaign & ad group / set nomenclature and then analyse these data against these specific segments. For example, you can analyse performance based on Region, Campaign Type, Product Type or any other dimension you’d want to specify.

LP Content Groups: With Content Groups, you have the ability to group similar themed website pages into categories that enables a categorical view of website performance. For example, let's say if you find a landing page with a high bounce rate, that destination URL might not match the expectation set by your ad text, or it might not have engaging content with a clear navigation path.

Visualize The Impact of Content Groups on Leads & Revenue . This means that you can now place revenue and pipeline-centric KPIs at the center of your content marketing strategies and track the influence of your content groups on accounts as they move through the pipeline. For instance, you can track: Content pipeline influence (by MQL and SQL stages), Content revenue influence, etc.

You'll be able to find direct evidence of the content group's influence at each pipeline stage and on revenue via headline percentage of content-influenced leads/opportunities/deals and revenue.

Single Touch Attribution models assign 100% of the conversion credit to a single marketing touchpoints, primarily based on the position of the marketing interaction such as

Multi Touch Attribution models assign fractional credit to each touchpoint for every conversion and aggregates all such fractional credits at an overall level. Factors today supports the following multi touch attribution models:

Step 1: Once you login to the Factors website, click on the ‘Analyze’ icon and then click on the ‘Attribution’ icon as shown below:

Step 2: Choose whether you want to analyse the Users, HubSpot deals, Salesforce Opportunity from the dropdown menu.

Let’s take an example for building an attribution query for ‘Users’.

Step 3: Select the Conversion Goal

Within the conversion goal drop down, all the events received by Factors are listed down. Here, we will select ‘Contact Created’ as our conversion goal.

In addition to selecting the event, you may also choose to apply filters such as Industry, Country or any other event or user property to narrow down the scope of the report.

This section allows you to select the specific marketing touchpoints which you would like to include in the attribution report. Within Paid Marketing, given there is a hierarchy of levels (Source -> Campaign -> Adgroup -> Creative / Keyword) the user can select only one of the hierarchy elements for the attribution report.

Post selection of the Marketing Touchpoint, filters may be applied to include or exclude specific touchpoints. This capability becomes especially handy if you want to exclude a specific marketing tactic or set of tactics from the attribution report (for ex: excluding 'Branded' search campaigns).

In this case, we will select ‘Keyword’ in the property.

The attribution report can be run using a single attribution model or you can also select multiple attribution models for a side by side comparison. Here, we will be selecting the last touch model and will further compare it with the linear model.

Attribution Window can be set within a timeframe ranging between 7 to as long as 90 days. The attribution window determines the earliest time prior to the occurrence of a conversion event within which the marketing touchpoint should have happened for it to be considered in the attribution analysis.

For ex: If a conversion event occurs on 15th April and attribution window is set to 90 days, marketing touchpoints prior to 15th Jan will not be considered in attribution.

Attribution Timeline refers to two different widely used approaches for attribution, namely by Interaction Time or Conversion Time. The difference between the two models is caused by the fact that users might interact with campaigns in a certain month (say June), but the conversions may happen in another month (say July). In this case, in addition to attributing the user to the appropriate campaign (say Campaign ABC), we would need to determine whether the conversion should be attributed to the Campaign ABC's spend in June (interaction time) or July (conversion time). The two options can be described further as follows:

For these examples, assume the Attribution Analysis Time Frame (selected in the calendar) is 01 June to 30 June and attribution window is 30 days

Conversion Time : All conversions which happened during the timeframe of 01 to 30 June would be attributed to campaigns with a 30 day attribution window (implying the marketing touchpoint for a conversion on 01 June could have happened on 02 May to 01 June). However, the campaign spends would be computed for the same timeframe of 01 to 30 June, even if some of the touchpoints happened in May. This approach would also not credit marketing touchpoints which happen in June for future conversions that happen in July or August. The pros of using this approach are as follows:

Interaction Time : In this case, the model would consider all the marketing touchpoints which happened in 01 to 30 June and look forward up till 30th August (considering a 30 day Attribution Window) and attribute conversions. The pros of using this approach being that it would give an accurate picture of cost per conversions and conversions that result from marketing touchpoints (and hence spend) in a specific month. However the cons of using this approach are:

In general our recommendation is that for short conversion cycles (say less than 3 days), the conversion time analysis gives a sufficiently accurate mental model of attribution. However, in case of longer conversion cycles (in many weeks or months), it is better to use the interaction time to get a truer picture of the impact of the spend and cost per conversion

In this section, you can select downstream events which users are expected to do post the conversion event so that you can get an accurate picture of cost per downstream conversions.

An example would be using 'Lead Created' as the conversion event and adding Linked Events as 'Demo Completed' or 'Opportunity Created'. You can also apply filters for each of these conversion events as required.

Please note that the conversion events should happen within the Attribution Analysis Time Frame.

Attribution Analysis is the most crucial analytical module within Factors and hence takes time to run depending on the Analysis Timeframe. Here’s how your report will look like:

You can also add your report to the dashboard so that you do not have to wait for the report to run (which may take a few minutes). Once added to the dashboard, the attribution reports would be updated on a daily basis. Here’s how you can add it to the dashboard: