How to Leverage Salesforce Lead Data for Account Optimization

Google rolled out the conversion import for Salesforce feature in 2016, and it is truly a game-changer. As any good digital marketer knows, not all leads are good leads, and we’re constantly looking for ways to help improve lead quality for our clients. The ability to evaluate lead quality at many different data layers of an account has been crucial to improving the quality of our campaigns.

Today I’ll review some of the ways we’ve found to effectively leverage this information to drive better campaign results.

Getting Started

If you’re on the fence about using this feature, this post offers a good breakdown for how the process works and why you should consider using it.

I won’t be covering the setup process in detail here, but if you’re using Salesforce and haven’t imported conversions to Google Ads yet, this post has a great step-by-step walkthrough as well as requirements that must be met first.

Once you’ve linked your Google Ads and Salesforce accounts, you’ll do the important work of selecting the milestones you want to import. Go to ‘Tools & Settings’ in the top navigation bar, then choose ‘Conversions’:

From there, choose ‘Salesforce’ on the left-hand side and choose the linked account. You’ll see your list of Milestones with the option to associate them with a conversion action:

A few important notes here about Milestones and Conversion Actions:

  • Once the accounts are linked, you’ll see a conversion every time a lead moves through your funnel to one of your milestones; however, if a lead moves backward to a previous milestone then a conversion isn’t recorded in Google Ads. So, you’ll want to ensure that the order of your milestones in Salesforce follows your sales funnel process.
  • Make sure that you’ve named your Conversion Actions similarly to your Milestones so you can easily match them up.
  • Conversions that are uploaded more than 90 days after the associated last click won’t be imported. This is a limitation for clients who have longer sales cycles.
  • On the Conversion Actions page, you can choose to include your Salesforce leads in the primary conversion column for reporting. If you choose to do so, you could leverage auto-bidding with these leads incorporated. Google recommends that if you go this route that you set your import schedule to daily so the algorithm has the most current data to work with. If you choose not to include them in your main conversion column you’ll still be able to see them by adding the All Conv. column.

Viewing & Understanding the Data

To see the imported lead status data, just go to the page with the data you want to evaluate (campaign, keywords, etc) and segment by Conversion Action:

If your Salesforce leads aren’t being included in your main Conversion column, make sure you’ve added the All Conv. column to see the lead status breakdowns (shown below in the next screenshot).

It’s important to note that the lead statuses will not be overwritten, meaning that a lead will start in New status but will eventually move into a Converted, Rejected, or other status; however, that lead will still always be counted in the New column. So, as you can see in the keyword example below, if you were to add up the numbers from all the lead status segments, it will not match the total conversions number.

Optimizing Your Account

Evaluating by Cost per Good Lead

If you’re not including your Salesforce leads in your main conversion column and aren’t leveraging automated bidding, one key way you can use the Salesforce lead data is for evaluating your high CPL segments.

For our account, we had standard CPL goals in place, but we needed to calculate another goal metric for just our high-quality leads, as their goal should be higher since their likelihood of turning into a customer is higher. We could identify these leads through the Nurture and Converted Salesforce lead statuses. To calculate our new cost-per-good-lead goal, we reviewed some longer-term data for the account and divided our spend by just our Good leads, and we used this average as our goal for optimizing the account.

Here’s an example for a high CPL keyword for the past 30 days:

CPL goal for this account is $150, and this keyword has a $294 CPL. I can see that one of those leads is in Converted status, so it’s a good lead. However, the cost per Good lead goal for this account is $400 and this keyword has spent $588. Since the CPL and CPGL are both above their goals, I would lower this keyword’s bid or potentially pause.

It’s important to note that if you have a longer sales cycle, it’s beneficial to re-evaluate keywords you have paused on a regular basis. For instance, a keyword might have been paused at some point, but after its leads had more time to mature, more leads might have advanced through the funnel to a higher value status (Converted, SQL, etc).

Evaluating Rejection Rates

At the end of the day, not all of your efforts are going to drive quality leads. It’s especially important to identify the biggest offenders that might appear to have good performance on the surface (good conversion rates, good CPLs, etc) but actually might have a high number of leads that are ultimately Rejected.

For our account, we run this analysis on a quarterly basis. For keywords with a high percentage of Rejected leads and no Good leads (Converted or Nurture Salesforce status) we pause the keyword and add a label for a later re-evaluation (mentioned above).

For keywords that did drive Good leads but have a high percentage of Rejected leads we reduce their bids and review their queries to see if additional negative keywords can be added to help drive higher quality traffic.

Other Optimization Layers

The Cost per Good Lead and Rejection Rate reviews aren’t just applicable to keywords. You can also run these analyses for the following:

  • Audiences
  • Demographics
  • Geographies
  • Devices
  • Ad Schedules
  • Ad copy
  • Campaigns
  • Landing page tests

For the first 5 categories, you can use these analyses to influence the kind of bid modifiers you add. They can be small adjustments or bigger ones based on longer-term performance. For instance, we recently had to scale back on a client’s campaign spend due to COVID-related issues. We found that lead quality was generally higher for Desktop users than Mobile users, so we scaled down Mobile traffic to help reduce spend while trying to maintain good lead quality.

For ad copy, different ad messaging can lead to differences in lead quality. For instance, if you use more qualifying language in one copy variant, such as a target company size for B2B ads, but your other variant doesn’t include company size, you might see a difference in lead quality. Your second variant might have better in-channel metrics, but if your company size copy is generating higher-quality leads efficiently you might choose a different ad copy winner.

Using these analyses for campaigns can help you determine where to distribute your budget, focusing your spend not just on lower CPL campaigns but also on those that drive the highest quality leads.

For landing page tests, a new test page might have a higher conversion rate and lower CPL, but is there a variance in lead quality? This can certainly be the case if you’re testing a much different form submission process or two very different landing pages.

More Effort Pays Off

Adding additional optimization points to your campaigns is never easy, but our goal should always be to drive more quality leads for our clients, and importing backend lead data is a key way to do so.

Have you been using Salesforce or other backend data to optimize your accounts? Let us know in the comments!

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