How Offline Conversion Tracking Led to 74% Increase in PPC Revenue: Case Study

We show you how using offline conversion tracking can reveal new PPC data that’s crucial to your optimization strategy.

Many modern eCommerce businesses don’t just rely on online channels to generate sales. More often than not, these brands employ additional channels — like brick-and-mortar locations, pop-ups, and call centers — to diversify and maximize their revenue streams.

But, if you’re not tracking these channels correctly, you’re probably not employing the best digital marketing strategy for your brand.

In today’s case study, we’ll tell you about one of our clients who recently found themselves in the same situation. With 20% of sales generated through their website and a whopping 80% generated through a call center, they needed to get accurate numbers (and fast) to successfully optimize their paid search advertising strategy.

So, Inflow stepped in to make it happen — ultimately resulting in a 74% increase in Google Ads revenue.

The Client: A Wholesaler Operating on Seasonal Trends

For this case study, the client in question is a wholesale retailer offering a variety of products across all niches and interests (think: school supplies, pet supplies, etc.). Therefore, their store performance is highly seasonal as customer behavior changes throughout the year.

This seasonal nature was already reflected in our team’s PPC strategy. We commonly pulled back or completely paused certain Google Ads campaigns and continually adjusted bidding strategy all in the name of one goal: maintain a 4x non-brand ROAS on all eCommerce purchases.

As mentioned above, this client sold products in two ways: through website purchases and through phone call orders. But, when we came aboard, there was no way to identify exactly which call conversions were stemming from our paid search campaigns. This was a huge piece of missing data.

Without knowing how their Google Ads campaigns were affecting call center orders, our client would never have the full paid search ROAS picture. Sure, we might assume that if we were driving 25% of online conversion revenue through Google Ads, it would be the same percentage for call center orders, too.

But our client didn’t want to fly blind, and neither did we.

So, we decided to implement offline conversion tracking for Google Ads.

Our Offline Conversion Tracking Strategy

To fully optimize our Google Ads approach, we needed to understand exactly how many call center purchases were driven by our paid search campaigns — and what the value of those purchases was.

The solution: Use Google Click ID (GCLID) tracking to associate users with our paid ads.

Our client had long ago implemented a login requirement for users to add items to cart and complete a purchase. By working with their development team, we were able to add a hidden field in the signup form submission process. This captured a customer’s GCLID (if they came to the site from a paid search ad click) and would store it in the client’s CRM to associate any future call center transactions to their account. 

Now, our PPC team not only sees the eCommerce conversion data from our Google Ads campaigns, but also that revenue created through call center orders, too.

Google Analytics campaign report, showing "call center transactions", "offline revenue," and "offline ROAS" for campaigns "New - School Supplies - Low Return" and "New - 05 - School Supply - Desktop - Tier 1" and "New - 05 - Shopping General - Desktop - Tier."

Using that Data in Our Google Ads Strategy

Now that we had understood which type of conversions were related to our ad campaigns, it was time to revisit our paid search strategy, campaign by campaign. 

Early in the school shopping season (and prior to implementing our Google offline conversion tracking), we had broken popular school supply products into high-return and low-return segments. Those that were high return (binders, markers, etc.) had historically high ROAS, but had previously been cannibalized by high-search-volume, low-return products (notebooks, folders). 

To maximize our budget and stay within our 4x goals, we ended up pushing more budget toward the high-return (4.82x ROAS) items, rather than the low-return (3.51x ROAS).

But, when we started tracking offline conversions through our call center, we revealed data we hadn’t seen before: While our low-return products were underperforming online, they were absolutely crushing sales in the call center. 

Because these low-return products were typically ordered in higher quantities, many customers were calling in to purchase them, even if they had originally arrived at the site through our Google Ads.

The offline sales picture for our school supplies was completely switched: Our high-return campaign was only generating 0.1x offline ROAS, while the low-return campaign was at 25.37x offline ROAS!

Google Analytics campaign report, highlighting "offline ROAS" for "call center transactions," "order placed," "registered," and "transactions." Campaigns are "New - School Supplies" and "New - School Supplies - Low Return."

Now that we had these metrics, we knew pulling back on our “low-return” campaigns was a mistake. Even if the ads weren’t generating online purchases, they were in the call center. Our optimization strategy needed to reflect that.

This opened the door for us to reflect on our goals with our client. If we were driving this type of return offline, and our impression share wasn’t currently at 100%, where did we have room to push harder on bids and budgets for next back-to-school season?

We also used the data to consider which categories to rework ad copy for in the next year, to highlight a “Call to Order” CTA, including the client’s phone number.

The Results

Knowing that our actual ROAS was much higher than it had been reporting before tracking offline conversion actions, we had leverage to expand our budgets — and could make appropriate adjustments to drive higher revenue, both in the online and offline worlds. 

With that strict ROAS goal and budget, our campaigns had historically been losing out on impression share as much as 80% due to budget. But, with the new offline revenue data, we had the ad spend freedom to be there for more conversions — and, year over year, our impression share lost due to budget dropped by 78.23%!

Line chart showing search impression share from Nov. 1-30, 2020, and Nov. 1-30, 2021. Search impression share for 2021 averages around 75%, while search impression share for 2020 hovers between 30% and 10%.

With a better understanding of our offline conversion value, we approached our holiday season search campaigns with a different strategy and saw incredible results!

No longer strictly limited by our 4x goal, we scaled spend by 34.8% year-over-year, generating a 74% increase in Google Ads revenue.

Final Suggestions: Implementing Your Tracking Strategy

Moral of the story: If your paid search campaigns aren’t generating the eCommerce results you expect, don’t pull back or pause your campaigns without doing a little digging — especially if you have multiple channels through which shoppers can make their purchases.

If you’re looking to set up offline conversion tracking for your Google Ads accounts, we recommend you consider all your sources of revenue first. 

Remember the old phrase about assuming things? If you’re starting your offline conversion tracking from scratch, take all of your purchase channels into account. This means call centers, third-party sellers, brick-and-mortar locations, and more. The more attribution data you have, the more informed your strategy will be.

If you’re not sure how offline conversion tracking is affecting your Google Ads campaigns, our strategists are always here to help. We stand ready to audit your accounts, incorporate offline conversion data into your campaigns, and create a personalized strategy for your business goals and needs.

Get started by requesting a free proposal today.

How We Helped Skreened Achieve 360% ROAS on Their Google Shopping Campaigns

Find out how we helped eCommerce brand Skreened improve to 360% ROAS in one month on their PLA campaigns.

Editor’s note: This blog was originally published in 2017. It has been updated for accuracy and modern practices.

Many eCommerce retailers struggle to coax results out of their paid search campaigns — especially without an experienced marketer manning the helm. 

Skreened was no different.

As an eCommerce brand that sold trendy design-driven apparel and other products, Skreened was missing out big by not running Google Shopping campaigns. Due to previous lackluster performance, the company hadn’t run Shopping campaigns in two years when they finally came to Inflow.

“Paid search is a beast,” Todd Barrs, Skreened’s vice president of eCommerce and marketing told us. “It’s tough for any small business to compete in it without expert advice or someone managing it.

Fortunately, they’d come to the right place.

Skreened product detail screenshot for a T-shirt with the text: Last clean t-shirt.

With Inflow’s help, Skreened would see 360% return on ad spend (ROAS) in just one month, with Google Shopping revenue making up 10% of that month’s overall income.

In this case study, we’ll explain how we did it, with a few Google Shopping Ads strategies you can use for your online business today.

The Challenges of Google Shopping

Google Shopping campaigns don’t target keywords like most Search campaigns. Instead, Google Shopping’s complicated algorithm relies on the details of your product data feed (found in your Google Merchant Center account).

Optimizing your Shopping feed alone can make or break your campaigns. But it’s not the sole piece of the puzzle; Shopping campaigns require time to set up, careful thought in targeting and account structure, and a complicated strategy to drive big results.

Which is why Skreened came to us. As an eCommerce marketing agency, we’ve experimented with countless Google Shopping strategies and tactics to identify the winning one for online businesses. Using our advanced, tiered campaign strategy, we were ready to help Skreened target the highest-potential search queries and boost their Shopping performance.

Want similar results for your eCommerce store? Request a free proposal here.

How We Maximized Skreened’s Google Shopping ROAS

Using our three-tiered eCommerce PPC strategy as a starting point and customizing it for Skreened’s unique brand needs and goals, we implemented the following campaign structure:

Step 1: Identify highest-value search terms.

If you want your eCommerce store to improve ROAS on Google Shopping, you need to start with historical data. Unfortunately, if you haven’t run many campaigns, you’re starting at a disadvantage.

Skreened was in this exact boat. Because they had no metrics or data from previous campaigns, they couldn’t know which products or searches were likely to perform well. And, with so many SKUs on their site, identifying which searches would have the highest sales potential would be particularly challenging.

Some background:

Skreened sells creative designs that can be printed on apparel (such as T-shirts and sweatshirts) and other products (such as coffee mugs or dog beds). The site allows users to upload their designs, as well as set up marketing accounts to sell their designs to others on Skreened.com. 

Because of this, they have over 900,000 products for sale!

Skreened’s top sellers are designs centered around trending topics and memes. Because these phrases are included in the product titles and descriptions, they’re also naturally included in Google’s algorithm, which takes all the data from a product feed into consideration when deciding which search terms are most relevant to your product.

Here’s the catch: People searching solely for the trending topic or meme (e.g., “Come at me bro”) are less likely to be searching for a product to buy.

For that reason, we knew we’d find the highest conversion rates on searches involving the combination of trending topics and memes with product terms (such as “shirt” or “tank top”).

See our example below, where adding “T-shirt” to the search phrase changes the search intent to show Shopping listings.

Two Google search results. Search on left for "come at me bro." All the results are memes. Search on the right for "come at me bro" t shirt. The first results are a row of shopping ads for t-shirts followed by an amazon text ad for a t-shirt.

Because of this, product-related terms would be Skreened’s highest-value keywords.

But here’s where these campaigns get tricky. Unlike other Google Ads (formerly Adwords) campaigns, Google Shopping campaigns do not allow you to target specific keywords. So, we can’t simply bid the highest on search queries that include the product terms most likely to turn into sales.

If we want to ensure our campaign dollars go to these top-converting queries, we need to think outside the box. And that’s where our tiered bid strategy comes into play.

Step 2: Split PLAs into three campaigns.

While Google doesn’t allow for targeted keywords in Shopping campaigns, you are allowed to add negative keywords that filter out search queries not directly related to your products. 

So, instead of telling Google what queries we did want to be included on, we filtered searches out until only the ideal queries were left.

To use this to Skreened’s advantage, we set up three separate campaign types that allowed us to corral the most useful searches into our most aggressive bid strategy.

Three tiered inverted pyramid, with Google Ads Crawl Direction set as downward direction. Tier 1 - $, high priority, low bid, catch all search queries. Tier 2 - $$, medium priority, medium bid, higher ROAS search queries. Tier 3 - $$$, low priority, highest bid, highest ROAS search queries.

Tier 1: Highest campaign priority, lowest bid

We set our first campaign up with the highest campaign priority, so that Google’s algorithm would always hit this tier with search queries before anything else. Since we expected these searches to have the lowest conversion value, we bid the lowest on this campaign.

For this tier, we wanted to capture traffic that was searching for trending themes and memes — but not including specific search queries such as “shirt” or “racerback.” This way, we could capture lowest-converting search terms without spending much money.

Because Skreened’s product data feed included the titles and descriptions of products related to trending topics, this campaign captured searches related to those topics. It also naturally captured searches that included the phrase printed on the product.

For that reason, we added negative keywords to filter queries that included the actual words describing the type of product — such as “sweatshirt,” “sweater,” “T-shirt,” “tanks,” or “tank tops.” Those queries would pass through to the second tier, where we bid more aggressively.

Finally, to exclude any high-converting brand traffic, we also added “Skreened” as a negative keyword in this tier and the next (saving that traffic for our most aggressive bids further on).

Note: The focus here isn’t just conversions. This first tier can be great for mining new keywords or product groups at a cheap cost. 

Tier 2: Medium campaign priority, medium bid

Any higher-potential search queries that contain our designated negative terms now bypass the first tier and are filtered into the second tier (except, of course, for “Skreened” brand terms). 

As a result, these search queries could include both terms describing trending topics and product terms, such as “unicorn racerback” or “I can’t adult today sweatshirt.”

To further filter out this tier, we added negative keywords for style and model terms (ie. “boss”). Because these specific searches are extremely high-intent, we save them for our final tier (more on that below).

Because this second tier gathers higher-intent search queries than our first, we intentionally configured this tier to bid more aggressively.

Two product photographs. On the left, a sweatshirt with the text: Please don't make me adult today. On the right, a racerback with the text: Be the unicorn you wish to see in the world.

Tier 3: Low campaign priority, highest bid

Our final campaign exists to catch any remaining search terms negated from the previous tiers — which tend to be the highest-converting brand traffic and specific style/model search terms (“i can’t today adult sweatshirt skreened medium”). 

Because of the specificity of these terms, we bid the most aggressively here out of all of our tiers. The high conversion value requires us to pay the highest to get the purchase. But, thanks to all the work we’ve done in the first two tiers, it’s well worth the cost.

The Results

In the first month since launching this three-tier campaign strategy, Skreened’s campaigns saw 360% ROAS — and made up 10% of total site revenue for that month.

Over time, we’ll expect even better results as we continue our optimization of negative keywords, eliminating patterns of search terms that don’t perform well and waste our ad spend.

It’s also important to continually optimize product groups in our product data feed. That way, Skreened can further integrate its brand and Shopping campaigns to highlight top-selling products. 

The bottom line?

Unstructured paid search campaigns waste money — because they make you pay for ads that almost always have lower conversion rates. 

Our tiered Shopping structure enables you to get the results you want, while spending less in the process.

It’s for good reason that we recommend Shopping campaigns to all of our eCommerce business clients. After branded search campaigns, these kinds of campaigns generate the highest average ROAS of all digital marketing campaigns. 

If your Shopping ads have been falling short of expectations, our team of PPC experts is always happy to take a look. Contact us today for a free campaign analysis and custom proposal for your online business’s target ROAS goals. 

In the meantime, check out more Google Shopping strategies below: