Five top practices for using Google Ads to track offline conversions

 First time setting up offline conversions? Here's how to launch your PPC advertisements without experiencing volatility.

Any marketer's job involves taking risks. No plan can be relied upon to succeed.

I prefer to see myself as someone who takes measured risks. I get to the airport just an hour before my flight because I have TSA PreCheck and can check the status of my trip from home. I check out new eateries in the area, but I don't get in the car until I've read reviews and perused the menu.

I take a similar attitude to taking risks at business. I enjoy experimenting with the newest bidding techniques, but I take care to not interfere with performance.

A Google Ads account that has undergone significant adjustments will enter a learning phase and experience instability while it re-learns.

I can be impatient, like many marketers who want results right away. But maintaining a balance between future-focused plans and the possibility of upsetting KPIs is crucial for maintaining client satisfaction.

We are aware by this point that offline conversion tracking (OCT) is essential for every account.

It can be challenging to switch out web-based campaign optimization goals for CRM-based goals when first setting it up. Here are five top strategies for reducing the risk.

1. Give your conversions values

Giving each action a value is necessary to fully utilize OCT.

If your CRM doesn't provide actual and dynamic values, Google has a calculator that can be used to make estimates.

The algorithms can profit from this offered guidance even if the values are not exact.

Machine learning is informed by the assigned values of the value of each conversion. As a result, the system can use value-based bidding algorithms to bid appropriately.

Setting these variables from the beginning enables a simple launch when you're ready, even if you're not quite ready for target return on ad spend (tROAS) or maximize conversion value.

2. Make all funnel stages more optimized

Start optimizing campaigns for each stage of the marketing funnel once Google Ads has received data from all of them with their corresponding values.

This strategy will increase the amount of conversion data produced for your campaigns and hasten the process of learning.

A risk-taker might alter the account's optimization all at once. Rips the bandage off, please.

• If you can handle performance changes.
• if it's a brand-new account.
• or if the volume of conversions is already dreadful.

In order to reduce the volatility in the account, I like to put up an experiment for any significant bidding adjustments.

Before choosing a winner, experiments should run for at least two weeks, but if your resources are tight or the conversion lag is lengthy, it may take longer.

The main success metric for this experiment should be an increase in backend conversions.

3. Aim for the lowest conversion point possible when optimizing.

Once the full-funnel strategy is successful, you can start focusing on optimizing for individual conversion events. Adjust the campaigns that are about to travel down the funnel and treat each campaign differently.

Given Google's requirement of at least 15 conversions in the last 30 days, put up an experiment that optimizes to the lowest point in the funnel possible to reduce performance variations.

In the Google Ads interface, you can simply filter and visualize your data by creating custom columns. Analyze every campaign on its own.

In this instance, the top two campaigns had an adequate volume of MQLs to exclusively optimize for MQLs as opposed to the complete funnel.

Remember that not every keyword is created equal. Keywords at the top of the funnel will produce pipeline more slowly than high-intent non-brand or brand phrases.

The optimization objectives and bidding tactics for each campaign should be in line with the funnel stage and what is most effective.

OCT targets may only be specified as the conversion category as a whole through the UI, not as individual conversion events. As a result, when optimizing for a single point in the funnel, specific goals should be set.

Create a special goal for "sales," for instance, if that is your OCT conversion.

Using custom goals in campaigns "may make your bid strategy function less efficiently," according to Google, but if your account is established and has enough data, custom goals should be advantageous.

4. Continue to drive lower-funnel results

As time goes on and data collects, you can continue to push the limits and optimize for lower points in the funnel. 

Any bidding strategy can be tested alongside this tactic, but it’s critical that the experiment you create only changes one variable at a time. 

For example, the control campaign is on target cost-per-action (tCPA) and optimized for MQLs. The test campaign should remain on tCPA but optimize for the next stage in the funnel (Meeting Scheduled). After a winner is determined, test another variable by conducting a separate experiment.

Finding the ideal balance of optimization objectives and bidding tactics can take many months, depending on the size of the account. It can be concerning to observe little to no performance gain after the first two weeks, however it is advised to repeat studies for three complete cycles before selecting a winner.

This indicates that you should run the experiment for at least six weeks before giving up if it takes a MQL an average of two weeks to become a "Meeting Scheduled." To see how long each conversion takes, visit Google's journey metrics report.

5.Test value-based bidding in 

Increase your performance with Maximize conversion value or tROAS bidding techniques if you feel comfortable optimizing for lower-funnel conversion points.

When a user searches for the keywords you're bidding on, these intelligent bidding strategies alter bids automatically to anticipate the value of a prospective conversion.

Particularly if you're afraid of messing up the system, you should test these bidding tactics in an experiment.

Despite the dangers brought on by performance variations, the advantages ought to outweigh the volatility.

One of my clients achieved a 74% improvement in cost per MQL after using OCT to optimize for backend conversions with a little perseverance and deep breathing.

We shifted to optimizing for MQLs only when their brand campaign received more than 15 MQLs in a single month, which led to a 4x increase in conversion value for that campaign.

So venture forth and take calculated chances. When you're nervous about starting an experiment, be clever, brave, and eager.