Incorporating backend data into your digital marketing initiatives is a performance changer.
But what can you do when back-end conversion data is unavailable or unreliable?
How can marketers improve lead quality and increase profit margins without a clear vision about which keywords and audiences have the most value?
This article will walk you through some of the indirect ways you can improve the quality of your Google Ads leads, despite not having the perfect data recovery through your digital advertising platforms.
First, let’s review why this is important.
Why should bottom path or margin events be optimized?
Before we get into the strategies, let’s first agree on why this is important. What’s the harm in just optimizing towards a key event or transaction?
This visualization below is one of the things our agency uses when reporting the need to integrate background data to inform campaign strategy and decision making.
Note that although this example is for B2B, B2C advertisers generally will have a progression towards earnings as well.
For example, a B2C e-commerce could contain a Click > add to cart > Start logging out > Create an account > Complete the application flow.
As explained above, the path to earnings has several milestones, including clicks, leads, MQLs, opportunities, and closing/winner.
Most advertisers these days are savvy enough to realize that optimizing for the lowest website cost per click/visit will result in low quality, high tail keywords that don’t produce an impact in the bottom conversion funnel.
However, due to the technical hurdles required to blend back-end and front-end data, I often find advertisers stopping at leads when optimizing.
Isn’t it a big deal? Think again.
Here is an example that reinforces the impact that shifting your focus down the funnel can have:
On the surface, Campaign A has a much stronger performance when evaluating based on leads.
However, the gap in the funnel widens to the point where Campaign A’s cost of selling is more than 5 times that of Campaign B.
So, what do I do about it?
Must Not Wait until your ideal case solution is published before optimizing the quality of your leads.
Offline data can take time to be incorporated into Google Ads and other platforms.
However, you can still take meaningful steps to start moving the needle in the right direction as you work on this integral.
Before we get into these steps, let’s take a look at the ideal data case.
The ideal state for backend data
An ideal background data optimization scenario would include:
- Hidden fields are set up on all of your websites and native lead forms to pass the platform ID (GCLID, FBCLID, etc.) to your CRM record.
- Offline Conversion Tracking (Oct) Fully integrated with Google Ads and other supporting channels (Microsoft Ads, Facebook and LinkedIn).
- The values have been calculated and set for each transfer point.
- Value based bidding is enabled in the platform.
- Backend data is mixed across channels via a file Automated CRM export daily (Assuming not all ad platforms you’re running on support pass-through) Enable cross-channel and full-funnel reporting.
While this may seem obvious, it is my experience that it takes advertisers a long time to get to this point, due to the need to engage stakeholders from multiple departments.
Here are concrete steps you can take to improve your bottom track events While working on the ideal case.
Stage 1: Low hanging fruit
Perceived keyword intent
When optimizing for lead, the search terms that trigger said trigger will vary greatly in quality.
Assuming limited budgets and a desire to improve bottom funnel results, you should evaluate keywords (and allocate campaign budget) based on perceived intent, as well as occasional signals that determine quality, such as engagement signals relayed from Google Analytics.
If the SOV is less than ideal for high-performing, high-performance intent conditions, consider reducing exposures with low perceived intent conditions or weak incidental cues.
Don’t let the higher cost per bullet numbers scare you.
If you select keywords with a higher perceived intent, despite a higher lead cost, consider adding an “intent multiplier” for leads that are triggered from specific keywords and audiences.
Pro tip: Apply labels when making edits so you can easily filter for changes made at specific points in time.
This will enable you to quickly make updates to this data set in the future (for example, if your monthly budget increases and it makes sense to activate a segment of previously paused keywords).
Marketing 101 tells us that the higher the CTR, the more aligned your targeting and messaging will be.
However, one should not blindly improve efforts to maximize CTR.
Your ad copy is one of the easiest levers you have at your disposal when trying to improve the quality of your leads.
Think about the attributes that make up a high-quality lead, and then tailor your ads to speak to those people.
For example, if you are a B2B advertiser and attract IT leads in the retail sector, Mention things like “Enterprise IT Solution for Retail” in the title.
Personalization will reduce ad relevancy for some searchers.
However, it will save the budget for more compliant audiences.
By clearly defining who your product or service is for in the copy, you will weed out those for whom it is not a good fit, such as small and medium businesses and manufacturing companies.
Use audience layers
Google Ads has a wide range of close audience options, marketable, detailed demographic, and custom audiences for advertisers.
By applying audience layers to your campaigns, you can bid up or down (manual bidding), include or exclude across RLSA campaigns.
Phase 2: Leveraging first-party audience building data
Regardless of whether your CRM system is connected to your advertising platforms, it still keeps records of customers and prospects that are so valuable to you as a marketer that you can extract.
Here are three ways you can take full advantage of that data.
Nurturing with CRM data
You can improve the quality of your leads – particularly in sales funnels that extend beyond a few days – with lead nurturing initiatives across offer/program, YouTube, social, and search.
The marketer’s job does not stop at the lead stage.
The organization must remain front and center throughout the entire buyer journey.
Marketers must work with sales to evaluate (often through a master scoring system) which leads in their system are promising.
Then ensure that they and your organization’s buying committee (via ABM) are imbued with both brand and thought-leadership content to keep you on top and build more authority.
Marketers should also collaborate with sales to evaluate promising leads (using a master scoring system) and ensure that they, including the organization’s buying committee (via ABM), are nurtured with content marketing to maintain brand awareness and industry authority.
Although Google does not offer ABM solutions, you can target specific companies and jobs within said companies via Microsoft Audience Network, LinkedIn, and other service providers.
List building using CRM data
Major advertising platforms provide listing upload options (via phone, email or mobile app ID) for seeds Similar/similar audience.
By thinking about your list load segments, you can target people who have similar traits to your most valuable lists (eg top customers).
On the flip side, you can upload lists for groups of low-quality leads and customers, and then exclude them from targeting (all bid strategies) or lower your bid if you’re using a manual bid strategy.
You don’t have to use this list for explicit targeting. It can also gather insights about your customer base or as an initial list of is similar to or Create a similar audience (Read on!).
Targeted modeling with CRM data
In addition to explicit targeting and/or creating similar audiences using a list upload, Google Ads and LinkedIn both have audience insights tools that can help you identify additional audiences that match your best and worst customers.
In Google Ads, head to File Shared Library > Audience Manager > Your Data Insights.
Here, you’ll be able to define an audience (upload, pixel, YouTube-based), and then see how that audience is indexed against a control group (eg US population; bad customer list) across dimensions such as age, gender, parental status, location, device, and most importantly From that Google convergence f sectors in the market.
Here’s a look at that report, using the closed/win list:
Once you have some ideas, you can decide how best to apply the ideas across your campaigns. This could be through bid adjustments, value rules, inclusions (RLSA), or exclusions.
TL; DR: Use Customer Match Uploads To feed customer data into Google Ads (and beyond), and then use that data through inclusions, exclusions, and attribute modeling.
Pro tip: While you can manually upload listings to the platforms, consider tools like Zapier, Salesforce Advertising Studio, and Liveramp to better automate this update process and improve match rates.
Stage 3: Use conversion values to inform bids
The holy grail to strive for is OCT-based conversion points + value-based bidding. Even without OCT data, using value cues in bidding decisions can still be a net performance gain.
Here are three steps to maximizing your conversion value use.
Step 1: Set the values for each conversion point
Don’t worry about providing the system with optimal value when starting out. The goal is to identify values that will push the algorithms in the right direction.
In the future, these values should be based on the value multiplied by the conversion rate from that action to the transaction.
Step 2: Test value-based bids (maximum conversion value/ROAS target)
When first starting out, you should set your tROAS (Target Return on Ad Spend) equal to the CPA of your old bid strategy.
The goal here is to shift to value-based bidding without undue volatility, and then start improving efficiency and/or scale by adjusting the TROAS target.
Step 3: Use value rules
A new Google Ads feature in 2021, it allows you to add, subtract, and multiply any conversion value based on audience, device, or location.
For example, imagine I want to target enterprise IT decision makers but I don’t have OCT, so I lack insight into what drives performance beyond leadership.
Even without the background data, I know intuitively that I want the algorithms to:
- Bid higher if on Similar to the audience based on participation in the site.
- Bid higher if Google bundles it into a On the market: Enterprise software package.
- A higher bid for those who work in project companies.
- Bidding is higher for those in San Francisco, California.
- Bid less if they work for a small business.
Translating that into value rules looks something like this:
With value rules, you can use tools like Google Ads Data Insights combined with results from detailed LinkedIn demographics reports, first-party personas, and customer data to tell the algorithms to serve ads to these potential customers at a higher quality.
wrapping things up
Integrating first-party data to inform audience building and bidding should be at the top of your priority list.
Integration of backend transformation data via OCT can be challenging, but it is a worthwhile endeavor.
Keep these techniques in mind when improving lead quality without using OCT while laying the groundwork for direct data resubmission.
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Featured image: Brovko Serhii / Shutterstock