Offline conversion tracking: 7 best practices and testing strategies


Offline conversion tracking (OCT) is one advertising tool that can help you get more from your PPC spend. 

In brief, advertisers use offline conversion tracking when they integrate CRM data on customer lifetime value (LTV) / purchase history (ecommerce) or down-funnel lead activity (B2B) into Google, Meta and/or LinkedIn campaigns to get valuable insights or tell the algorithms more about their very best customers – and how to find more users like them.

If you’re even doing the basics of using OCT data in your ad campaigns, you’re ahead of the curve.

But to truly nail your competitive advantages, start using the following list of OCT best practices and testing techniques.

1. Assign values to your conversion events

Believe it or not, many B2B advertisers don’t know when a lead is worth to them. If you can’t calculate the value of a lead, demo request, booked meeting, etc., you won’t be able to use OCT with much precision, so let’s start by defining values.

To start calculating your values, work backward based on real sales data to calculate the average worth of events along the buying journey. That mindset alone will help you stop focusing on getting the most leads for your spend, which typically leads to spam.

Some ad platforms will allow you to optimize towards more than one conversion action at a time (which I’ll cover in a second). Numerical values tell the platforms which action is the higher priority while feeding more information to the platforms to dial in bidding like tROAS.

2. Test optimizing for one or multiple actions in Google

Google allows advertisers to optimize for one or multiple conversion actions at the campaign or account level. If you have enough volume, it’s always best practice to start by trying to optimize campaigns for your most valuable action (usually closed/won sales).

That said, it’s pretty common to lose enough data density as you move down the funnel to get out of the volume range.

If you don’t have enough volume at a certain conversion stage, you can test optimizing for multiple actions, including the highest-value stage and the next-most-valuable stage that gets you to your volume goal.

For example:

  • If you don’t have enough MQLs, combine leads and MQLs.
  • If you don’t have enough opportunities, combine SQLs and opportunities (and maybe bring MQLs into it if you need a volume push). 

3. Test different bidding strategies in Google

I’ve seen different bidding strategies work for different clients. I recommend testing a few to see what will work best for you. Use these guidelines:

  • If you have lower volume, testing Max Conversions with multiple conversions can be a great way to feed the system enough data to use automated bidding.
  • If you have enough volume to focus on one offline conversion, testing tCPA bidding is a good place to start.
  • If you’ve calculated values for each conversion action, you can test max conversion value with multiple conversions to help the algorithm understand which actions are more meaningful.
  • If you’re able to dynamically bring in values for offline actions like opportunities or closed won deals, tROAS bidding can be a great way to dial in your return.

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4. Test Google’s Performance Max if volume allows

I use healthy skepticism in my approach to Performance Max, especially in lead gen and B2B campaigns where we’re not (yet) forced to use it.

That said, as a goal-based campaign type that allows performance advertisers to access all of their Google Ads inventory from a single campaign, it is worth testing Performance Max with OCT-powered campaigns if:

  • Your search campaigns are fully funded (which is to say, you’re not borrowing budget from effective search campaigns to test Performance Max)
  • You have more than 30 offline conversions in the last 30 days.

If neither of those conditions is true, save Performance Max testing for another day.

5. Get granular with Custom Columns

Once you have defined your conversion events (which could also be categorizations, like MQL, SQL or opportunities), I highly recommend you set up Custom Columns.

On Google, you can create custom columns that segment specific conversion actions, which makes it easier to realize performance and analyze data.

Google Ads - Custom Columns

Use the All conversions metric, as shown above, and select a specific action to study the data related to it – which is especially useful when you set up additional columns to calculate cost/conversion and conversion rate.

Google’s Custom Columns lets you sort and visualize your data, whether you’re looking at keywords, search queries, demographic data, location data, or other reports inclusive of offline data. You’ll be able to spot the weak/inefficient stages of your purchase journey very quickly.

Custom Columns work a little differently on Facebook. To have easy visibility in each of your offline actions on Facebook, you’ll need to either associate each offline action with a unique standard offline event (recommended) or create a custom conversion to avoid aggregated reporting.

Facebook Ads - Custom Columns

Either of these methods will create a built-in column to track these actions separately, along with cost/conversion and value, although you’ll need to create custom columns for conversion rate,

Similar to Google, once you have these views created, you’ll be able to more easily filter, visualize and analyze data.

You’ll actually get more nuance with Facebook, which is now providing detailed reporting that shows which demographics, placements, devices and geos are producing conversions.

Facebook doesn’t (yet) let you optimize for offline conversions, so the main value in using OCT on the platform is the insights you’ll be able to glean from its reporting.

6. Weigh lead gen vs. conversion-focused events on LinkedIn

When incorporating offline conversions for LinkedIn, consider whether you’d like to use lead gen campaigns (on the LinkedIn platform), conversion-focused campaigns that drive traffic to your website, or both.

If you’re running lead gen campaigns, LinkedIn will still focus on the lead gen objective. Still, the platform allows you to measure the number of offline conversions coming from these campaigns, which makes in-platform optimization easier.

If you’re running conversion-focused campaigns, you can incorporate offline conversions and set campaigns to optimize around them.

Either way, setting up OCT may show you in short order which conversion event is providing to be more efficient in producing high-quality leads.

Dig deeper: 5 ways to improve PPC lead quality

7. Roll up your sleeves and get analytical

As with most discussions about analytics, I could go on forever with your options here.

Whether you are or aren’t optimizing for offline actions, analyzing offline data can help uncover interesting insights for your business on just about any platform.

Studying which keywords, ads, campaigns, or creative themes are driving offline conversions helps you uncover the following areas:

  • Where you may be wasting spend (i.e., if you’re driving many leads with no down-funnel movement).
  • Where you should invest more (i.e., in places where you’re driving a few leads of uniformly high quality).
  • Where you should reevaluate your strategy and consider dialing in ad copy to qualify the right users or landing page experience, among other levers.

The above conclusions are a great start, but Google and Facebook provide many other data points, like demographics, geos, and devices, to help you learn more about your advertising campaigns.

Get ahead in PPC with these OCT best practices

There’s a lot to keep track of here, especially if you’re new to the practice of OCT. 

But remember its main benefit: you’re helping the algorithms use your advertising spend to find more valuable customers. 

In a landscape where advertisers have fewer manual controls than before, finding ways to get more out of your money (or your clients’ money) is worth some extra elbow grease.

Dig deeper: 5 best practices for tracking offline conversions in Google Ads

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.



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