Conversions

Goals

Use goals to measure how often users complete specific actions.

Goals measure how well your site or app fulfills your target objectives. A goal represents a completed activity, called a conversion, that contributes to the success of your business. Examples of goals include making a purchase (for an ecommerce site), completing a game level (for a mobile gaming app), or submitting a contact information form (for a marketing or lead generation site).

Defining goals is a fundamental component of any digital analytics measurement plan. Having properly configured goals allows Analytics to provide you with critical information, such as the number of conversions and the conversion rate for your site or app. Without this information, it's almost impossible to evaluate the effectiveness of your online business and marketing campaigns.

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Funnels for Destination goals

With a Destination goal, you can specify the path you expect traffic to take. This path is called a funnel. When you specify steps in a funnel, Analytics can record where users enter and exit the path on the way towards your goal. This data appears in the Goal Flow and Funnel reports. You may see, for example, a page or screen in a funnel from which a lot of traffic exits before completing the goal, indicating a problem with that step. You might also see a lot of traffic skipping steps, indicating the path to conversion is too long or contains extraneous steps

Use the destination goal type if you want to track pageviews or screenview as a goal. This goal type is ideal for tracking those conversions where a user sees a 'thank you' page or 'order confirmation' page after completing a conversion.

Add a new Goal

  • Click + NEW GOAL to create a new goal, or click an existing goal to edit its configuration.
  • Add Step: Use destination goals to treat a pageview or screenview as a conversion. Enter the screen name or page URL in the Destination field.
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Attribution Model

What are marketing attribution models?

Attribution modelling is a framework for analysing which touchpoints, or marketing channels, receive credit for a conversion. Each attribution model distributes the value of a conversion across each touchpoint differently.

There isn't necessarily a "best" attribution model. You may choose one as your primary attribution model for reporting and analysis. Different factors, like business goals or buying cycles, can make one model better than another.

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Types of Attribution Model

Plumb5's model comparison tool allows you to analyse how each model distributes the value of a conversion. There are five baseline attribution models that is available in plumb5. They are:

First Interaction Attribution

First Interaction is similar to Last Interaction, in that it gives 100% of the credit to one single click/interaction. First Interaction (also called "First-Click") gives all of the credit for a conversion to your business' first interaction with the customer. For instance, if a customer first finds your business on Facebook, then Facebook gets all of the credit for any sale that happens after that interaction. It doesn't matter if the customer found you on Facebook, then clicked a display ad a week later, and then went to your site directly. Facebook, in this example, gets the full credit.

Pros & Cons

As mentioned above, eliminating direct clicks makes this a more insightful model than last interaction. However, it still assigns 100% of the value to one interaction. If your customer had 4 touchpoints prior to that last non-direct click, it's completely ignored.

Last Interaction Attribution

Last Interaction Attribution is also referred to as "last-click" or "last-touch." As the name implies, this model gives 100% of the credit to the last interaction your business had with a lead before they convert. For example, a visitor finds your website through organic search. A week later they see a Facebook Ad and click the ad. Later that day, they go to your website directly and make a purchase.

Pros & Cons

Last Interaction attribution is the simplest to implement and evaluate. It is also often the most accurate. Digital marketing today is scattered. People may access from multiple devices, clear cookies, or use multiple browsers. This makes it difficult to track their entire journey.

Linear Attribution

With a Linear attribution model, you split credit for a conversion equally between all the interactions the customer had with your business. For instance, a customer finds you on Facebook, signs up for your email list and later clicks an email link. The next week they go to your site directly and make a $120 purchase. There are 3 touchpoints in this situation. Each touchpoint gets equal credit of 33%, or a $40 conversion value attributed to the channel when the purchase was made.

Pros & Cons

Linear attribution gives you a more balanced look at your whole marketing strategy than a single-event attribution model does. However, this means it also assigns equal importance to everything. Some marketing strategies are more effective than others, and this model will not highlight the most effective strategies.

Position Based Attribution

The Position-based attribution model (also called U-shaped attribution) splits the credit for a sale between a prospect's first interaction with your brand and the moment they convert to a lead. 40% of the credit is given to each of these points, with the remaining 20% spread out between any other interactions that happened in the middle. For example, if a prospect first makes contact with your business through a Google search, looks at your Facebook page, and later signs up for your email newsletter, the first and third touches each receive 40% of the credit, and the Facebook visit receives the remaining 20%.

Pros & Cons

Position-based attribution is a strong model for many business types that have multiple touchpoints prior to a conversion. It gives at least some credit to every interaction. But, it gives a stronger weight to your two most important interactions: the first time a customer found you and the interaction that prompted a conversion.