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100+ Google Ads Custom Columns (with Formulas) to Improve Reporting

Google Ads provides an impressive amount of data, but unlocking its full potential often requires going beyond the default metrics. Similar to GA4 custom dimensions, custom columns give advertisers the flexibility to create tailored insights that can vastly improve reporting and campaign optimization.

Whether you’re looking to track specific conversion behaviors, analyze budget utilization, or compare your performance against competitors, custom columns allow you to see exactly what matters to your business.

In this comprehensive guide, we’ll walk you through 100+ custom columns, complete with formulas, that can elevate your reporting game and help you make smarter, data-driven decisions.

How to Set Up Custom Columns in Google Ads

Custom columns in Google Ads allow you to create metrics tailored to your specific needs, making reporting and campaign analysis more efficient and actionable. Setting up these columns can help you track data that matters most for your business goals. Here’s how you can set them up:

Step 1: Log into Google Ads

Begin by logging into your Google Ads account. Make sure you have the necessary permissions to create and edit custom columns, as some accounts may have restrictions depending on access level.

Step 2: Navigate to the Campaign or Ad Group Level

Custom columns can be applied at different levels in your account, including the Campaign, Ad Group, Ad, or Keyword levels. To start, choose the level where you’d like to create your custom column.

  1. Click on the desired tab (e.g., Campaigns, Ad groups, Ads, or Keywords) depending on the level where you’d like to track performance.
  2. Select the reporting table view to start customizing.

Step 3: Click on “Columns” and Select “Modify Columns”

In the performance table, click on the Columns button, which is usually located in the top-right section of the table.

  1. From the drop-down menu, select Modify columns.
  2. Scroll down and click on Custom columns.
step 3 click columns

Step 4: Create a New Custom Column

Once you’re in the Custom Columns section, you’ll see an option to create a new custom column. Click on + Custom Column to start defining the parameters for your new column.

 step 4 add custom column

Step 5: Define Your Custom Metric

In this step, you’ll need to define what metric you want to track and display in the custom column.

  1. Name your column: Give your custom column a descriptive name that reflects the data it’s going to display.
  2. Enter the formula: Use Google Ads predefined metrics (such as Conversions, Impressions, Clicks, Cost, etc.) to create a formula. You can add, subtract, multiply, or divide metrics to create tailored KPIs. For example, if you want to calculate “Cost per Conversion,” divide the Cost metric by Conversions.
  3. Apply conditions (optional): You can apply specific filters to your custom column, such as only showing data from a particular campaign type or network.
step 5 create a custom column

Step 6: Choose the Format

Choose how you want your custom metric to be displayed:

  1. Number: If you’re calculating totals or sums (e.g., total conversions, total cost), this is the default option.
  2. Percentage: Select this if you’re calculating a ratio or a percentage (e.g., conversion rate).
  3. Currency: Use this if you want to display cost or value metrics in your local currency (e.g., cost per click or revenue generated).

Step 7: Save and Apply the Custom Column

Once you’ve configured your custom column and reviewed your settings, click Save. The custom column will now appear in the table view along with the default columns.

Step 8: Apply Custom Columns to Multiple Views (Optional)

If you want to apply your custom column across multiple levels of your account (e.g., campaign and ad group levels), you can save it as part of a preset view. To do this:

  1. Click on the Columns dropdown again.
  2. Select Modify columns.
  3. Find the Custom columns section and apply your saved custom column to different reporting views by checking the relevant boxes.
step 8 save google ads column set

General E-commerce Custom Columns

These custom columns are designed to help you track e-commerce performance metrics at a granular level, focusing on impressions, conversions, cost, and revenue. Each column provides actionable insights for optimizing campaigns, improving smart bidding strategies, and managing ROAS and CPA.

1. Impressions per Conversion

Description: The number of impressions needed for a conversion.
Formula: Impr / All_conversions_by_conv_time
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how many impressions are typically needed to drive a conversion, which can help optimize ad visibility.

2. Conversions per Impression (CPI)

Description: Conversions per Impression rate (CPI).
Formula: All_conversions_by_conv_time / Impr
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how effective your impressions are in generating conversions, which helps in refining targeting strategies.

3. Revenue per Impression (RPI)

Description: Revenue per Impression (RPI).
Formula: All_conversion_value / Impr
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Tracking how much revenue is generated from each impression, helping to evaluate the quality of impressions.

4. Profit per Impression (PPI)

Description: For Profitmetrics users: Profit per Impression (PPI).
Formula: All_conversion_value_by_conv_time.conversion_action(“Gross Profit – Conversion Booster”, “Gross Profit – Browser”) / Impr
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding how much profit is generated from each impression, useful for profit-focused campaigns.

5. Soft to Hard Conversion Rate

Description: The conversion rate from a soft conversion to a hard conversion within the same funnel.
Formula: All_conversions_by_conv_time / All_conversions_by_conv_time
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Tracking how many soft conversions (e.g., Add to Cart) turn into hard conversions (e.g., Completed Purchase).

6. ROAS by Time

Description: ROAS by time in percentage.
Formula: Conversion_value_by_conv_time / Cost
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring the return on ad spend over specific time frames.

7. ROAS (Last 7 Days)

Description: The most recent ROAS performance for the last 7 days.
Formula: All_conversion_value_by_conv_time.date_range(last_7_days) / Cost.date_range(last_7_days)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Providing a snapshot of recent performance, useful for short-term optimization.

8. ROAS (Last 14 Days)

Description: The most recent ROAS performance for the last 14 days.
Formula: All_conversion_value_by_conv_time.date_range(last_14_days) / Cost.date_range(last_14_days)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Monitoring mid-term ROAS trends to identify areas for optimization.

9. CPA (Last 7 Days)

Description: The most recent CPA performance for the last 7 days.
Formula: Cost.date_range(last_7_days) / All_conversions_by_conv_time.date_range(last_7_days)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding short-term customer acquisition cost trends for quick budget adjustments.

10. CPA (Last 14 Days)

Description: The most recent CPA performance for the last 14 days.
Formula: Cost.date_range(last_14_days) / All_conversions_by_conv_time.date_range(last_14_days)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Assessing mid-term trends in cost per acquisition to inform bid and budget strategies.

11. Recent ROAS Development

Description: Comparison of your recent ROAS performance and your manually selected timeframe-ROAS.
Formula: (All_conversion_value_by_conv_time.date_range(last_7_days) / Cost.date_range(last_7_days) – (All_conversion_value_by_conv_time / Cost)) / (All_conversion_value_by_conv_time / Cost)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Tracking how recent ROAS compares with a manually selected timeframe, allowing for quick assessments of changes in performance.

12. Recent CPA Development

Description: Comparison of your recent CPA performance and your manually selected timeframe-CPA.
Formula: (Cost.date_range(last_7_days) / All_conversions_by_conv_time.date_range(last_7_days) – (Cost / All_conversions_by_conv_time)) / (Cost / All_conversions_by_conv_time)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating short-term CPA trends compared to longer periods to gauge campaign efficiency.

13. Effective Search Terms (CPA)

Description: Identifies whether keywords perform within CPA targets and hit a conversion threshold.
Formula: if(and((Cost / All_conversions_by_conv_time) < 80, All_conversions_by_conv_time > 2), true, false)
Level: Search terms
Data Format: True/false
Useful for: Quickly identifying search terms that are meeting CPA targets, useful for keyword optimization.

14. Effective Search Terms (ROAS)

Description: Identifies whether keywords perform within ROAS targets and hit a conversion threshold.
Formula: if(and(Conversion_value_per_cost > 5, Conversions > 2), true, false)
Level: Search terms
Data Format: True/false
Useful for: Flagging keywords that are performing well against ROAS targets, helping to refine bidding strategies.

15. Conversion Increase

Description: Comparison of yesterday’s performance with the average number of daily conversions over the last 30 days.
Formula: if((Conversions.date_range(yesterday)) < (Conversions.date_range(last_30_days) / 30), true, false)
Level: All (Campaign, ad group, keyword)
Data Format: True/false
Useful for: Monitoring daily conversion spikes or declines, allowing for quick adjustments based on short-term trends.

16. True ROAS

Description: Shows ROAS as a percentage.
Formula: conversion_value / cost
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Providing a clear, percentage-based representation of return on ad spend.

17. Engaged Conversions Percentage

Description: Percentage of engaged conversions compared to total conversions.
Formula: Conversions.ad_event_type(engaged_view) / Conversions
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Understanding the proportion of conversions driven by user engagement, useful for optimizing engagement-driven campaigns.

18. Percentage Spend on Search Partners

Description: Shows spend on Search Partners as a percentage of total spend.
Formula: Cost.network(partners) / Cost
Level: Campaign/ad group
Data Format: Percentage (%)
Useful for: Monitoring the proportion of your ad spend allocated to search partners, helping to assess whether this traffic source is cost-effective.

E-commerce Cart and Checkout

This list provides metrics to track and optimize Add to Cart and Begin Checkout actions, helping advertisers understand how well their ads are driving users through the eCommerce funnel and where potential drop-offs might occur.

19. Cost per Begin Checkout

Description: Costs per begin checkout. You need to change the name of the conversion action.
Formula: Cost / All_conversions.conversion_action(“begin_checkout”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Identifying the cost efficiency of getting users to begin the checkout process.

20. Cost per Add to Cart

Description: Costs per add to cart. You need to change the name of the conversion action.
Formula: Cost / All_conversions.conversion_action(“add_to_cart”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Measuring how much you are spending to get users to add products to their cart.

21. Begin Checkout Conversion Rate

Description: Conversion rate from clicks to users beginning the checkout process.
Formula: All_conversions.conversion_action(“begin_checkout”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Analyzing how well your ads are driving users to start the checkout process after clicking the ad.

22. Add to Cart Conversion Rate

Description: Conversion rate from clicks to users adding items to their cart.
Formula: All_conversions.conversion_action(“add_to_cart”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how effectively your ads lead to users adding products to their cart after clicking the ad.

23. Cost per Begin Checkout Conversion

Description: Average cost per user beginning checkout, based on conversion tracking.
Formula: Cost / All_conversions.conversion_action(“begin_checkout”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Determining how much each ad spend unit is costing you for a user to begin the checkout process.

24. Cost per Add to Cart Conversion

Description: Average cost per user adding a product to their cart, based on conversion tracking.
Formula: Cost / All_conversions.conversion_action(“add_to_cart”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Analyzing the cost of getting users to add products to their cart and optimizing spending on these actions.

25. Begin Checkout Rate by Impressions

Description: Percentage of impressions that lead to users starting the checkout process.
Formula: All_conversions.conversion_action(“begin_checkout”) / Impressions * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Understanding how often your ads lead to the checkout process relative to total impressions, aiding in ad creative and targeting improvements.

26. Add to Cart Rate by Impressions

Description: Percentage of impressions that result in an “Add to Cart” action.
Formula: All_conversions.conversion_action(“add_to_cart”) / Impressions * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how many impressions result in users adding items to their carts, helping to fine-tune ad copy and product presentation.

27. Begin Checkout vs Add to Cart Ratio

Description: Ratio of users beginning checkout to those adding products to their cart.
Formula: All_conversions.conversion_action(“begin_checkout”) / All_conversions.conversion_action(“add_to_cart”)
Level: All (Campaign, ad group, keyword)
Data Format: Ratio
Useful for: Comparing the efficiency of moving users from “Add to Cart” to beginning the checkout process, which helps identify bottlenecks in your eCommerce funnel.

28. Total Add to Cart Conversions

Description: Total number of times users added products to their cart.
Formula: All_conversions.conversion_action(“add_to_cart”)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Tracking the total volume of add-to-cart actions to gauge the level of purchase intent generated by your ads.

29. Total Begin Checkout Conversions

Description: Total number of times users began the checkout process.
Formula: All_conversions.conversion_action(“begin_checkout”)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Measuring how many users progressed to the checkout stage, which is a key indicator of purchase readiness.

30. Add to Cart to Checkout Conversion Rate

Description: Percentage of users who added items to their cart and then started the checkout process.
Formula: All_conversions.conversion_action(“begin_checkout”) / All_conversions.conversion_action(“add_to_cart”) * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating how efficiently users transition from adding products to their cart to beginning the checkout process, helping identify potential drop-off points.

31. Add to Cart Value

Description: The total value of items added to the cart by users.
Formula: All_conversion_value_by_conv_time.conversion_action(“add_to_cart”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Tracking the total monetary value of products added to carts, which helps in evaluating the impact of ad campaigns on potential revenue.

32. Begin Checkout Value

Description: The total value of purchases in checkout initiated by users.
Formula: All_conversion_value_by_conv_time.conversion_action(“begin_checkout”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Monitoring the total monetary value of items in checkout, offering a clear view of how much potential revenue your ads are driving.

33. Revenue Lost from Abandoned Carts

Description: Estimated potential revenue lost due to users abandoning their carts after adding products but not checking out.
Formula: All_conversion_value_by_conv_time.conversion_action(“add_to_cart”) – All_conversion_value_by_conv_time.conversion_action(“begin_checkout”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Highlighting the difference between the value of products added to the cart and those that proceed to checkout, helping to address cart abandonment issues.

Budget/Ad Spend Custom Columns

34. Exp. Month Spend

Description: Expected total spend for the current month.
Formula: Cost.between_dates(month_start, yesterday) + (Cost.date_range(last_7_days) / 7) * (day(offset_days(offset_months(month_start(), 1), -1)) – day(today()))
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Predicting total monthly spend based on historical data and recent trends.

35. Daily Budget Spend

Description: The percentage of the daily available budget that has been spent.
Formula: (Cost.between_dates(report_range_start, report_range_end) / report_days_count() / Daily_Budget)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Monitoring daily spend relative to your set daily budget, ensuring budget efficiency.

36. Avg. Daily Spend this Month

Description: The average month-to-date daily spend (until yesterday).
Formula: Cost.between_dates(month_start, yesterday) / (day(today()) – 1)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding daily spend patterns over the month to identify over- or underspending.

37. Avg. Daily Spend this Period

Description: The average daily spend over a selected period.
Formula: Cost.between_dates(report_range_start, report_range_end) / report_days_count()
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Reviewing how daily spend averages across custom date ranges.

38. New Daily Budget

Description: Recommended daily average spend for the rest of the month. Adjust for actual monthly budget.
Formula: (budget – Cost.between_dates(month_start, yesterday)) / (day(offset_days(offset_months(month_start(), 1), -1)) – (day(today()) – 1))
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Adjusting your remaining daily budget based on current spend and remaining days in the month.

39. Actual Day Spend

Description: The actual average spend per day for the selected time frame.
Formula: Cost.between_dates(report_range_start, report_range_end) / report_days_count()
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding your daily spend pattern over a selected time frame for better budget planning.

40. Overspend/Underspend

Description: Shows whether you have overspent or underspent based on the current run rate.
Formula: ((Cost / report_days_count()) – ((budget – Cost.between_dates(month_start, yesterday)) / (day(offset_days(offset_months(month_start(), 1), -1)) – (day(today()) – 1)))
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Identifying how much you are over- or underspending relative to your planned budget.

41. Budget Runrate [Campaign X]

Description: Compares actual spend for the month with the budgeted amount that should have been spent so far. Percentages below 100% indicate potential room to scale.
Formula: (Cost.between_dates(month_start, yesterday)) / ((budget / day(offset_days(offset_months(month_start(), 1), -1))) * (day(today()) – 1))
Level: Campaign
Data Format: Percentage (%)
Useful for: Tracking actual spending compared to budget allocation, helping to optimize campaign pacing.

42. Adjusted Expected Spend this Month

Description: Combines actual spend with extrapolated future spend based on recent changes, providing an adjusted expected spend.
Formula: (Cost.between_dates(month_start, yesterday)) + (Cost / report_days_count()) * ((day(offset_days(offset_months(month_start(), 1), -1))) – (day(today()) – 1))
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Forecasting end-of-month spending based on current and recent spend rates.

43. Budget Utilization Rate (30 Days)

Description: Measures how much of your budget has been spent or committed over the last 30 days.
Formula: Cost.date_range(last_30_days) / 30 / Daily_Budget
Level: Campaign
Data Format: Percentage (%)
Useful for: Monitoring how well your budget is being utilized, ensuring you stay within monthly spend limits.

44. Spend Last Month

Description: Static view of last month’s total cost. Useful for comparison purposes.
Formula: Cost.date_range(last_month)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Comparing past month’s performance with current spend to understand budget trends.

45. Budget to Spend Gap

Description: The gap between your actual and expected spend for the month.
Formula: budget – Cost.between_dates(month_start, yesterday)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Knowing how much of the monthly budget remains unspent, helping with reallocation.

46. Max Daily Budget Utilization

Description: The maximum percentage of the daily budget that has been used across all days in a specific period.
Formula: MAX(Cost.date_range(last_7_days) / Daily_Budget)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Identifying the peak budget usage day to understand when you’re spending the most.

General Columns

These general custom columns will help you monitor lost opportunities in terms of impressions, clicks, conversions, and revenue due to budget and ad rank limitations, while also providing insight into your overall performance. This helps inform decisions on bid adjustments, budget increases, and overall campaign optimization strategies.

47. Available CPC Headroom

Description: The available space between your max CPC and average CPC.
Formula: (Max_CPC – Avg_CPC) / Avg_CPC
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Identifying opportunities to optimize bids and potentially reduce costs by lowering your Max CPC if the gap between Avg CPC and Max CPC is large.

48. Total Eligible Impressions

Description: Total eligible impressions you can get based on your impression share.
Formula: Impr / Search_impr_share
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding the total potential reach of your ads and identifying how many more impressions you could capture with better ad rank or increased budget.

49. Impression Lost (Budget)

Description: Indicates the number of lost impressions due to budget limitations.
Formula: Impr / Search_impr_share * Search_Lost_IS_budget
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how many impressions you missed because of budget constraints, helping you identify potential budget adjustments.

50. Click Lost (Budget)

Description: Measures the number of lost clicks due to budget constraints.
Formula: (Impr / Search_impr_share * Search_Lost_IS_budget) * CTR
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Quantifying the number of clicks lost because of budget limits, important for optimizing click volume.

51. Conversion Lost (Budget)

Description: Quantifies the lost conversions due to budget constraints.
Formula: ((Impr / Search_impr_share * Search_Lost_IS_budget) * CTR) * (Conversions / Clicks)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how many potential conversions were lost due to limited budget, helping you prioritize budget increases.

52. Revenue Lost (Budget)

Description: Estimates the revenue loss resulting from budget restrictions.
Formula: (((Impr / Search_impr_share * Search_Lost_IS_budget) * CTR) * (Conversions / Clicks)) * (Conversion_value / Conversions)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Estimating the amount of revenue you’re missing due to budget limitations, offering insights into potential gains from increased budget.

54. Investment Opportunity (Budget)

Description: Provides a potential investment opportunity due to budget constraints.
Formula: ((Impr / Search_impr_share * Search_Lost_IS_budget) * CTR) * Avg_CPC
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Highlighting how much additional investment might be required to capture lost clicks due to budget constraints.

55. Impression Lost (Ad Rank)

Description: Measures the number of lost impressions due to ad rank factors.
Formula: Impr / Search_impr_share * Search_Lost_IS_rank
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how many impressions you missed due to low ad rank, helping you improve quality score or bidding.

56. Clicks Lost (Ad Rank)

Description: Quantifies the lost clicks due to ad rank factors.
Formula: (Impr / Search_impr_share * Search_Lost_IS_rank) * CTR
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Measuring how many clicks you’re losing due to poor ad rank, allowing you to optimize ad rank and visibility.

57. Conversion Lost (Ad Rank)

Description: Calculates the lost conversions due to ad rank factors.
Formula: ((Impr / Search_impr_share * Search_Lost_IS_rank) * CTR) * (Conversions / Clicks)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Estimating how many conversions are being lost because of your ad rank, helping you prioritize optimization.

58. Revenue Lost (Ad Rank)

Description: Estimates revenue loss resulting from bid adjustments due to poor ad rank.
Formula: (((Impr / Search_impr_share * Search_Lost_IS_rank) * CTR) * (Conversions / Clicks)) * (Conversion_value / Conversions)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding how much revenue is lost because of ad rank issues, which can guide bid increases or quality improvements.

59. Investment Opportunity (Ad Rank)

Description: Provides a potential investment opportunity based on bid and ad rank considerations.
Formula: ((Impr / Search_impr_share * Search_Lost_IS_rank) * CTR) * (Avg_CPC * (1 + Search_Lost_IS_rank))
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Assessing the financial opportunity of improving ad rank, showing the investment required to gain back lost impressions and clicks.

Lead Generation Custom Columns

With these custom columns, you can now directly track specific Google Ads conversion actions such as “submit_form” for leads, “qualified_lead” for qualified leads, and “closed_lead” for closed deals, enabling detailed performance analysis at each stage of the sales funnel.

60. Lead to Qualified Lead Percentage

Description: Percentage of leads (submit form actions) that become qualified leads.
Formula: All_conversions.conversion_action(“qualified_lead”) / All_conversions.conversion_action(“submit_form”) * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring the efficiency of turning form submissions into qualified leads, a key metric in lead quality assessment.

61. Qualified Lead to Sale Percentage

Description: Percentage of qualified leads that convert into closed leads (closed deals).
Formula: All_conversions.conversion_action(“closed_lead”) / All_conversions.conversion_action(“qualified_lead”) * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Tracking the effectiveness of sales processes in converting qualified leads into closed leads.

62. Lead to Sale Percentage

Description: Percentage of total leads (form submissions) that convert into closed leads (closed deals).
Formula: All_conversions.conversion_action(“closed_lead”) / All_conversions.conversion_action(“submit_form”) * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating the overall lead-to-sale conversion rate, a critical indicator of campaign success.

63. Cost per Qualified Lead

Description: The cost of acquiring a qualified lead.
Formula: Cost / All_conversions.conversion_action(“qualified_lead”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding the cost efficiency of generating qualified leads, helping to optimize budget allocation.

64. Cost per Closed Deal (Customer Acquisition Cost – CAC)

Description: The cost of acquiring a closed lead (closed deal).
Formula: Cost / All_conversions.conversion_action(“closed_lead”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Tracking customer acquisition cost (CAC), a key metric for determining profitability and marketing effectiveness.

65. Qualified Leads Conversion Rate (CVR)

Description: Conversion rate from clicks to qualified leads.
Formula: All_conversions.conversion_action(“qualified_lead”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating how well your campaigns convert ad clicks into qualified leads, a crucial step in the lead generation funnel.

66. Closed Deal Conversion Rate (CVR)

Description: Conversion rate from clicks to closed leads (closed deals).
Formula: All_conversions.conversion_action(“closed_lead”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Assessing how efficiently ad clicks are being converted into closed leads, a direct measure of campaign ROI.

67. Impressions to Form Submit Ratio

Description: The ratio of impressions that result in form submissions.
Formula: All_conversions.conversion_action(“submit_form”) / Impressions * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how effectively impressions are turning into leads (form submissions), helping to optimize ad visibility and relevance.

68. Click to Form Submit Ratio

Description: The ratio of clicks that result in form submissions.
Formula: All_conversions.conversion_action(“submit_form”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating how many clicks convert into form submissions, crucial for understanding landing page effectiveness.

69. Impressions to Qualified Lead Ratio

Description: The ratio of impressions that result in qualified leads.
Formula: All_conversions.conversion_action(“qualified_lead”) / Impressions * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Understanding the overall effectiveness of ad impressions in generating qualified leads, providing insights into ad relevance.

70. Click to Qualified Lead Ratio

Description: The percentage of clicks that result in qualified leads.
Formula: All_conversions.conversion_action(“qualified_lead”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Analyzing how well your clicks are converting into qualified leads, allowing for optimization of targeting and ad copy.

71. Cost per Form Submit

Description: The average cost of generating a form submission (lead).
Formula: Cost / All_conversions.conversion_action(“submit_form”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding the cost-efficiency of generating leads through form submissions, aiding in budget optimization.

72. Form Submit Conversion Rate

Description: Conversion rate from clicks to form submissions.
Formula: All_conversions.conversion_action(“submit_form”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how many clicks convert into form submissions, crucial for understanding the effectiveness of your landing page or ad copy.

73. Cost per Form Submit Conversion

Description: The average cost per form submit (lead conversion).
Formula: Cost / All_conversions.conversion_action(“submit_form”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Evaluating the cost-efficiency of form submissions, helping to optimize budget for lead generation.

74. Impressions to Closed Deal Ratio

Description: The ratio of impressions that result in closed deals.
Formula: All_conversions.conversion_action(“closed_lead”) / Impressions * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how effective your overall ad impressions are at driving sales (closed deals), a key metric in evaluating ad quality and targeting.

75. Click to Closed Deal Ratio

Description: The ratio of clicks that result in closed deals.
Formula: All_conversions.conversion_action(“closed_lead”) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Assessing how well clicks are converting into sales (closed leads), a direct measure of ad effectiveness.

76. Cost per Impression to Form Submit

Description: The cost of each impression that leads to a form submission.
Formula: Cost / All_conversions.conversion_action(“submit_form”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding the cost of each form submit relative to impressions, useful for optimizing bid strategy.

77. Cost per Click to Form Submit

Description: The cost of each click that results in a form submission.
Formula: Cost / All_conversions.conversion_action(“submit_form”)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Measuring the cost efficiency of converting clicks into form submissions, providing insights for campaign optimization.

Device-Based Custom Columns

These custom columns allow you to break down your performance data by device (mobile vs desktop), offering detailed insights into how traffic sources contribute to your key metrics.

78. Mobile Clicks

Description: Number of clicks coming from mobile traffic.
Formula: Clicks.device(mobile)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Tracking mobile-specific traffic to evaluate the performance of mobile campaigns or ad targeting.

79. Mobile Click Share

Description: Percentage of total clicks that come from mobile traffic.
Formula: Clicks.device(mobile) / Clicks
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Monitoring the proportion of mobile traffic to overall clicks, which can inform device-specific bid adjustments.

80. Mobile Conversions

Description: Number of conversions coming from mobile traffic.
Formula: Conversions_by_conv_time.device(mobile)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how mobile traffic contributes to your overall conversion volume.

81. Desktop Conversions

Description: Number of conversions coming from desktop traffic.
Formula: Conversions_by_conv_time.device(desktop)
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Understanding how desktop traffic contributes to your overall conversion volume.

82. Mobile Revenue Share

Description: Percentage of total revenue generated by mobile traffic.
Formula: Conversion_value_by_conv_time.device(mobile) / Conversion_value_by_conv_time
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Assessing how much revenue is driven by mobile users, important for evaluating device-specific performance.

83. Mobile Conversion Share

Description: Percentage of total conversions coming from mobile traffic.
Formula: Conversions_by_conv_time.device(mobile) / Conversions_by_conv_time
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring the significance of mobile conversions in your overall performance.

84. Desktop Conversion Share

Description: Percentage of total conversions coming from desktop traffic.
Formula: Conversions_by_conv_time.device(desktop) / Conversions_by_conv_time
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Monitoring how desktop traffic contributes to your conversion goals.

85. Mobile Conversion Rate (CVR)

Description: Conversion rate for mobile traffic.
Formula: Conversions_by_conv_time.device(mobile) / Clicks.device(mobile)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Evaluating the effectiveness of mobile traffic in driving conversions.

86. Desktop Conversion Rate (CVR)

Description: Conversion rate for desktop traffic.
Formula: Conversions_by_conv_time.device(desktop) / Clicks.device(desktop)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring how effective desktop traffic is at converting.

87. Mobile vs Desktop CVR

Description: Compare mobile conversion rate with desktop conversion rate.
Formula: ((Conversions_by_conv_time.device(mobile) / Clicks.device(mobile)) – (Conversions_by_conv_time.device(desktop) / Clicks.device(desktop))) / (Conversions_by_conv_time.device(desktop) / Clicks.device(desktop))
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Understanding the performance difference between mobile and desktop traffic in terms of conversion rates.

88. Mobile Performance (CPA)

Description: Cost per acquisition for mobile traffic.
Formula: Cost.device(mobile) / Conversions_by_conv_time.device(mobile)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Evaluating the cost efficiency of mobile traffic in driving conversions.

89. Desktop Performance (CPA)

Description: Cost per acquisition for desktop traffic.
Formula: Cost.device(desktop) / Conversions_by_conv_time.device(desktop)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding how cost-effective desktop traffic is at acquiring conversions.

90. Mobile Performance (ROAS)

Description: Return on ad spend for mobile traffic.
Formula: Conversion_value_by_conv_time.device(mobile) / Cost.device(mobile)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Assessing how well mobile traffic is driving revenue in relation to ad spend.

91. Desktop Performance (ROAS)

Description: Return on ad spend for desktop traffic.
Formula: Conversion_value_by_conv_time.device(desktop) / Cost.device(desktop)
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Analyzing how desktop traffic performs in terms of revenue generation compared to ad spend.

92. Mobile vs Desktop (CPA)

Description: Compare mobile cost per acquisition (CPA) with desktop CPA.
Formula: ((Cost.device(mobile) / Conversions_by_conv_time.device(mobile)) – (Cost.device(desktop) / Conversions_by_conv_time.device(desktop))) / (Cost.device(desktop) / Conversions_by_conv_time.device(desktop))
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Understanding the difference in cost-per-acquisition between mobile and desktop users, enabling device-level budget allocation optimization.

93. Mobile vs Desktop (ROAS)

Description: Compare mobile return on ad spend (ROAS) with desktop ROAS.
Formula: ((Conversion_value_by_conv_time.device(mobile) / Cost.device(mobile)) – (Conversion_value_by_conv_time.device(desktop) / Cost.device(desktop))) / (Conversion_value_by_conv_time.device(desktop) / Cost.device(desktop))
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Assessing the relative performance of mobile vs desktop in terms of revenue return on ad spend, guiding strategic budget shifts.

Even More Custom Columns

94. Conv + VTC

Description: Video of Display conversions: Total Conversions + View-Through Conversions.
Formula: All_conversions_by_conv_time + View_through_conversions
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Tracking the combined impact of direct conversions and view-through conversions from video campaigns, giving a clearer picture of video ad effectiveness.

95. Conv + VTC CVR

Description: Video conversion rate: Conversions + View-Through Conversions as a percentage of clicks.
Formula: (All_conversions_by_conv_time + View_through_conversions) / Clicks * 100
Level: All (Campaign, ad group, keyword)
Data Format: Percentage (%)
Useful for: Measuring the overall conversion rate from both direct conversions and view-through conversions, providing insight into the total effectiveness of video campaigns.

96. Conv + VTC (CPA)

Description: Cost per Conversion for video and display campaigns, including View-Through Conversions.
Formula: Cost / (All_conversions_by_conv_time + View_through_conversions)
Level: All (Campaign, ad group, keyword)
Data Format: Money
Useful for: Understanding the cost per conversion when including both direct and view-through conversions in video campaigns.

97. Exp. Month Clicks

Description: Expected number of clicks for the current month, combining actual clicks and an extrapolation based on the last 7 days of data.
Formula: Clicks.between_dates(month_start, yesterday) + (Clicks.date_range(last_7_days) / 7) * (day(offset_days(offset_months(month_start(), 1), -1)) – day(today()))
Level: All (Campaign, ad group, keyword)
Data Format: Number
Useful for: Estimating total monthly clicks based on recent performance, which can help in forecasting and budget allocation.

98. Increased Competition

Description: Identifies whether competition has increased based on changes in Search Impression Share and Average CPC.
Formula: if(and((Search_impr_share.between_dates(report_range_start, report_range_start) – Search_impr_share.between_dates(report_range_end, report_range_end)) > 0.02, ((Avg_CPC.between_dates(report_range_end, report_range_end) – Avg_CPC.between_dates(report_range_start, report_range_start)) / Avg_CPC.between_dates(report_range_start, report_range_start)) < 0.01), “Increased”, “-”)
Level: Campaign / Ad Group / Keyword
Data Format: Text (ABC)
Useful for: Quickly identifying when competition has increased, allowing you to adjust bidding strategies accordingly.

99. Identifying New Keywords

Description: Flags keywords that have more than two conversions but fewer than 100 clicks, which might indicate potential for optimization.
Formula: if(and(Conversions > 2, Clicks < 100), “yes”, “-”)
Level: Keyword
Data Format: Text (ABC)
Useful for: Helping you spot new, underutilized keywords with strong conversion potential that may need more focus or budget.

99. Increased Competition V2

Description: Detects increased competition based on changes in Search Impression Share and Average CPC. It flags when either Impression Share has decreased and Average CPC has increased or stayed the same, or Impression Share has stayed level while Average CPC has significantly increased.
Formula: if(or(and((Search_impr_share.between_dates(report_range_start, report_range_start) – Search_impr_share.between_dates(report_range_end, report_range_end)) > 0.02, ((Avg_CPC.between_dates(report_range_end, report_range_end) – Avg_CPC.between_dates(report_range_start, report_range_start)) / Avg_CPC.between_dates(report_range_start, report_range_start)) > -0.1), and((Search_impr_share.between_dates(report_range_end, report_range_end) – Search_impr_share.between_dates(report_range_start, report_range_start)) < 0.005, ((Avg_CPC.between_dates(report_range_end, report_range_end) – Avg_CPC.between_dates(report_range_start, report_range_start)) / Avg_CPC.between_dates(report_range_start, report_range_start)) > 0.2)), “Increased”, “-”)
Level: Campaign / Ad Group / Keyword
Data Format: Text (ABC)
Useful for: Advanced detection of competition spikes, enabling advertisers to respond quickly when competitors raise bids or maintain position while increasing costs. This allows you to adjust your strategy to stay competitive in auctions.

100. Campaign & Group Labelling

Description: Returns a label based on whether the campaign or ad group name contains “Brand.” It returns “Brand” if the campaign name includes the word “Brand,” otherwise, it returns “Generic.” This is useful for filtering or ordering campaigns and ad groups for better organization.
Formula: if(contains(“Brand”, Campaign_name), “Brand”, “Generic”)
Level: Campaign / Ad Group / Keyword
Data Format: Text (ABC)
Useful for: Easily distinguishing between brand and generic campaigns or ad groups, helping streamline reporting and filtering for more targeted analysis.

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