Action: When a user does actions like signup, product purchase, form filing etc

CPA means cost per Acquistion or Action

– It helps interested users or people who are active and ready and likely to convert
– Reach as many high-value consumers as possible by targeting your remarketing lists

By Optimizing this campaign you can win customers at the lowest cost

Optimizations that help to bring the Campaign’s best performance improvements when its goal is to drive consumer action are Budget, CPA, and Recency Targeting

The main focus of this Action campaign is to help interested consumers who are active and already interested in your product or services which are likely to convert

Main Focus:

the main focus of the Buyer or Advertiser is to convert the consumers at low cost as possible so that they can achieve more conversions for their planned budget

Purchase Goal:

Make the consumers finish the next stage of the purchase funnel

After crossing the awareness, and consideration stages, or when they show interest or are ready to convert

Pre-Launch things to remember

First of all, we should check the pacing and budget to ensure it is delivering well with the current pacing settings for the IO and line item

If we are targeting Remarketing list, you understand that users are less available in the list

So, please follow the below settings in the campaign setup

IO level pacing setting – Pacing Flight ASAP

Line item level Pacing Setting – Unlimited

1) Optimize Budget and Pacing :

a) Pacing of line

  • Budget and Pacing settings affect the delivery
  • So go through the line and check the Budget and pacing settings
  • First Party Audience list limits the number of users you can reach
  • Therefore, set the IO level of the line which controls the whole budget pacing to ASAP, and the respective line’s budget to Unlimited
  • Make certain the line budget is greater than the IO level hierarchy than a line budget to ensure the item budget does not limit ad buys while the budget remains available at the Campaign level
  • Set a line’s budget to Unlimited, and add a pacing mechanism to ensure you speed up optimizations and prioritize these lines

b) Underspending

  • If the IO is underspending, it means that your budget is limiting your remarketing serves
  • Use the line item pacing view to see if this is an issue with your budget today or if your budget is set correctly

b) Impression share loss

  • Check the impression share loss by looking at line item pacing to see how much the budget might have played a role in impressions you didn’t win.
  • This data helps to increase the bid and budget.
  • Frequency caps are limiting impressions in this example, as well
  • However, we don’t adjust them since there is a recency targeting setting that is frequency capped to avoid over-delivery

2) Optimize CPA

Optimize your CPA by making each line item represent a specific action you want to drive

Create Line items w.r.t action what advertisers want users to take

Then bid more for more valuable actions and less for less valuable ones

Lower bid – They searched for something you offer or products you are offering

Low bid – They viewed your home page of the product website

High bid – They went to your product page

Higher bid – They added your product to their cart

This means that you can create different audience lists targeting the lines under the IO for different steps in the conversion stage

Steps to bring low CPA :

  • Make sure your conversion counting is set so your CPA is calculated correctly for what you’re trying to achieve
    • Example: If you have $1000 Budget and want 100 conversions, then keep $1000/100 = $10 as CPA


  • Make sure your Floodlight pixel is assigned to the line so it can track visitors to the pixel’s page and double Cross-check it.


  • For the Home page remarketing strategy, you can exclude the pixels related to the users who visited the shopping cart


  • As a Buyer, Make sure the post-view counting choice serves your key performance indicator
    • Post-View Conversions:
      • The number of times a person has landed on a success page, after viewing an ad
      • Post-view conversions can also be thought of as “post-impression” conversions.

Note: Display & Video 360 only records conversions if your line item is associated with a pixel for conversion counting

  • If not, enter the correct percentage
  • On the DV360 table, Customize your view of the line’s metrics so it’s easier to evaluate performance with conversions, revenue, budget, and spend


  • Evaluate line performance by pulling the data and check which are performing well and exceed CPA Goals
  • This can help to find out line items to adjust budget, bid, or frequency
  • In this scenario, you can check if all the lines under the IO are meeting within CPA goal set for the given targeting set
  • The closer the customer gets to the “Thank you” page the more likely they are to complete the purchase — it means a lower CPA
  • That’s CPA optimization in action


  • Find out by expanding each line item to adjust bids, budgets, or frequency
  • Here you can see if you’re meeting your CPA goals for each of the audience-targeted line
  • Reviewing impression loss data can help you optimize by ensuring you’re not losing out on desired inventory due to inefficient settings
  • Review impression loss charts for lines for losses due to bids, budget, or frequency
  • Adjust for these if necessary
  • Shift budget to higher-performing line


  • In case if the Advertiser wants to run the lines with new ad messages, Duplicate high-performing lines and add new messaging with frequency caps to keep creatives fresh


  • When you add audience targeting, you can get the forecast data to see how much reach you can get from this targeting
  • If you notice less scale, you can add a similar audience to extend the reach
  • Ensure the forecasted impressions have an adequate scale of over 5,000 users
  • If not, add similar audiences to extend your reach
  • You can also bid higher on smaller segments which are worth enough for the campaign


  • Have line items that exclude pixels on pages that are further along in the purchase journey


  • If there aren’t enough actions on the “Thank you” page, try optimizing for line items that get the most people to click. In this case you are optimizing towards clicks and monitor the performance

One to make sure that budget and pacing settings don’t prevent from reaching high-value audiences and bidding efficiently for audiences who visit suggest they are ready to convert

Bid Strategy

  • When you are ready to spend the budget in full, you can set the Bid strategy as
    • “Minimize CPA”
  • You have to make sure, the correct conversion method for each line item
  • First-party targeting must be set alone.
  • Make sure you do not add any additional layers

Bidding and Frequency caps:

Buyers can use reasonable bids and frequency depending on consumers at which funnel position

For example, Whether the user had seen the ad an hour ago or two days ago

In this case, buyers can take advantage of recency targeting and target as per the list.

Recency defines how long ago a user had lastly visited a page on a website

Example: Create one list with users who have seen one hour below and others with one hour above.

More the recency, more the value of users to target

That means you can use higher recency for consumers who are lower in the funnel and lower recency for those higher in the funnel

Optimize lines using bid changes and frequency as per the position of consumers in the purchase funnel

You can also increase bids and increase frequency for the consumers who are at the lower stage of the purchase funnel

Best Practices:

Create different 1st party audiences list for different steps in the conversion stage like visiting the home to purchasing the product

You can exclude consumers who are converted from targeting

More the recency, more the value of users to target

Optimize for loyalty

  • Target the “Thank you” page and assign creatives to upsell or bring customers back for a new experience
  • Target similar audiences to the one that’s been to the conversion page

Purchase funnel:

  • Optimize Bid value by increasing it from Upper level of funnel to lower level of Purcahse funnel

Dimensions and Metrics


Conversion performance

% Clicks Leading to Conversions = Conversions / Clicks

% Impressions Leading to Conversions = The rate at which impressions led to conversions, calculated as the product of Conversions / Impressions × 100

Conversion rate = Number of conversions and divide it by the number of total clicks or visits

For example, if your latest marketing email had 1,000 clicks and 30 sales, your conversion rate would be 3%.

Conversion rate formula
Conversion rate = (conversions / total clicks or visits) * 100

Conversion rates are calculated by simply taking the number of conversions and dividing that by the number of total ad interactions that can be tracked to a conversion during the same time period


Post-Click Conversions =

The number of times a person has landed on a success page, after clicking on an ad

Post-View Conversions

The number of times a person has landed on a success page, after viewing an ad.

Post-view conversions can also be thought of as “post-impression” conversions.


Revenue eCPA (PC), Post Click

Revenue eCPA (PV), Post Views


Total Conversions  = The aggregate total of all Post-View Conversions and Post-Click Conversions


Floodlight Impressions : The number of times a Floodlight activity tag has been served to and loaded by browsers

Total Paths : The total number of times a path occurred for unique cookies with a given path pattern

Converting Paths: The total number of unique cookies with one or more last interaction conversions

Path Conversion Rate: Converting paths / total paths for the entity

Total Exposures : Total impressions + clicks for the entity


they give all the credit for a conversion to the last-clicked ad and corresponding keyword

marketing attribution is the analytical science of determining which marketing tactics are contributing to sales or conversions

Attribution modeling

Assign credit for sales and conversion to touch points in conversion paths

Determines how credit for sales and conversions is assigned to touchpoints (impressions and clicks) in conversion paths.

For example, the Last Interaction model assigns 100% credit to the final touchpoints that immediately precede sales or conversions.

In contrast, the First Interaction model assigns 100% credit to touchpoints that initiate conversion paths

Default attribution models

Floodlight model attributes 100% of the conversion value to the last click made by the user before buying or converting

The last Interaction model attributes 100% of the conversion to the last channel with which the customer interacted before buying or converting

  • Role of a channel in closing sales or conversions
  • It’s relevant for campaigns that are designed to attract people at the moment of purchase or conversion
  • It’s also useful if your business is mainly transactional, with a sales cycle that doesn’t involve a long consideration phase

The first Interaction model attributes 100% of the conversion value to the first channel with which the customer interacted

  • If you’re running campaigns to create awareness
  • For example, if you’re marketing a brand that’s not well known, you might put a premium on keywords or channels that first expose customers to the brand
  • Use this model to emphasize the role of display advertising in initiating conversion funnels

The Linear model gives equal credit to each channel interaction on the way to a conversion

  • Use case: For campaigns that are designed to maintain customer contact and awareness throughout the sales cycle.
  • In this model, each touch point is equally important during the consideration process

The Time Decay model is appropriate for a sales cycle that involves only a brief consideration phase.

  • This model is based on the concept of exponential decay
  • It gives the most credit to the touch points that are nearest to the time of conversion or sale
  • The Time Decay model has a half-life of 7 days, meaning that a touch point 7 days before conversion will get half the credit of a touch point on the same day as the conversion or sale.
  • Similarly, a touch point 14 days before the conversion will get 1/4 the credit of a day-of-conversion touch point.
  • The exponential decay continues to the end of your lookback window.

Use case: For short-lived promotional campaigns. If you run one-day or two-day promotions, you might want to give more credit to interactions during those promotions.

Touchpoints further back in time have less value compared to those that occurred right before the conversion.


The calculation we use for this is:

y = 2-x/7

where x is the number of days the referral happened prior to the conversion.

The 7 in the equation is the half-life.

A touchpoint 7 days before a different touchpoint, will receive half the credit.


For example, a user visits your site from a Google display ad, a remarketing ad and then finally a social channel, with the following timeline:

Display – 8 days out

Remarketing – 4 days out

Social – 1days out

Based on the equation above, we would split the credit up for each channel accordingly:

2-8/7 2-4/7 2-1/7
.453 .673 .906
22.29% 33.13% 44.58%


What Should I Use?

The truth of the matter is, there’s no silver bullet for modeling attribution. Our team has found the best way to get an accurate understanding, is to compare our numbers for each of the model. This is easy to do using the model selector in Attribution


What you already know:

Every traffic source gets a score, none of them is ignored as long as it is relevant.
It uses a simple algorithm that allocates points to each traffic source according to how close it is to the moment of conversion.
The traffic sources closest to the decision moment get the highest scores. It’s just fair, isn’t it? If one of the first traffic sources had been so efficient, why didn’t the user convert faster?

What are the issues and what can you do about them?

For one, not every session of a user is to be included in the calculation. Some of them are irrelevant and, if taken into account, could only lead to inaccurate results.

For instance, if a user clicks on your site by mistake, and leaves it just as quickly, that source should be ignored. And so should a session that was opened and left untouched for a very long time.

Say a user reached your site, and decided to explore it later on, but forgot to do so for a few days. There is no activity on his part, but every time he turns on his computer, another session is registered. Will you count every session, or ignore that traffic source until you register some activity?


The Position Based model is a hybrid of the Last Interaction and First Interaction models. Instead of giving all the credit to either the first or the last interaction, you can split the credit between them. A common scenario is to assign 40% credit each to the first and last interaction, and assign the remaining 20% to the remaining interactions.

Use case: When you value the touch points that introduce customers to your brand or promotion, as well as the touch points that result in sales or conversions.

The Social model is based on the linear model but impressions are weighted to account for social interactions. The default weightings are:
Impressions without social engagements = x0.5
Impressions with any low-value social engagements (and no high-value) = x0.75
Impressions with any high-value social engagements = x1.5
High-value social engagements extend reach to other users.

Examples include shares, and retweets. Low value social engagements show interaction, but don’t extend reach to other users. Examples include expands, and profile views.

Use case: When measuring campaigns run on social networks like Twitter.

Path to Conversion reports

how users were exposed to your advertising in the lead-up to a conversion.

which of your ads, and which types of media, are best at driving conversions

events you’d like to track, such as conversions on your website or adding users to audience lists


Floodlight conversion counting methods


Counting methods

Counter activities count the number of conversions associated with an event

  • Standard: Counts every conversion
  • Unique: Counts the first conversion for each unique user during each 24-hour day
  • Per session: Counts one conversion per user per session. You can define the length of a session for your site

Sales activities track the number of sales made or the number of items purchased. You can also capture the total value of each sale. There are two ways to define a conversion for sales activities:

  • Transactions: Counts all conversions, plus the total number of sales that take place and the total associated revenue.
  • Items sold: Counts each conversion, plus the total number of items sold and the total associated revenue

A conversion can be recorded on the basis of a click, an impression, or a Rich Media event.

A conversion is counted whenever a Floodlight impression is triggered by a user who falls within the specified lookback window

Conversion metrics count conversions, while transaction metrics count events.

A lookback window is a period of days for which an impression or click is considered relevant for Floodlight reporting

Terms to know

Multi-channel attribution modeling


Learn & Apply

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