Tony is the Marketing Manager at Sales & Orders heading up our inbound marketing and advertising team. His latest adventure, though? Being a dad!
ROAS or Return on Ad Spend is the “buzz metric” of Shopping campaign optimization. Naturally, and as we’ve seen it time and time again, retailers always ask the same question:
“How do I maximize my return?”
With just about every ecommerce retailer we have helped succeed on channels like Google and Bing Shopping, we’ve found that there are 4 key most common denominators that (when working in concert) contribute to substantial ROAS gains over time.
Take our friend Ken Harrison over at Enjuku Racing Parts LLC.
After executing these optimizations in his Google Shopping campaigns alone, Ken’s campaigns saw a dramatic 333% overall increase in ROAS in just his first year working with our team.
So, how did we do it for Ken and so many other of our honored retailers? Well, I’m going to share those four key strategies you should never go without in either Google or Bing Shopping.
Structure Campaigns to Achieve Granularity
At Sales & Orders we have pioneered a unique way of building and structuring Shopping campaigns for both Google and Bing.
Different names get thrown around for it but, put simply, we have always built campaigns at the Product Level thus allowing us to achieve perfect granularity in the campaign structure.
What is a Product Level Shopping campaign?
Instead of grouping moderate to large numbers of products together in multiple ad groups and/or product groups, our team leverages our one-of-a-kind software to eliminate product grouping altogether. In our groundbreaking structure, products live as their own line items. This allows us to bid on and analyze products individually as opposed to only being able to do so in rolled up groups with aggregate performance stats.
When finished, a Product Level campaign looks something like this:
Achieving this level of granularity is a monumental first step in working towards increasing your Shopping campaign ROAS:
- Granular Control: In grouped structures, merchants and advertisers are forced to bid and analyze performance at the broadest levels, having to set the same bid for multiple products and never being able to dig deeper into top performing SKUs easily. In a Product Level format, you can set unique bids for each individual product, review each products’ performance in greater detail that is not rolled up to the group level, and more readily break out additional strategies such as isolating Top Performers and then building custom campaigns focused solely on your conversion drivers.
- Negate Wasteful Spending: The ultimate killer of Shopping campaign ROAS is wasting precious ad spend on ill-performing products. Once again though, without the Product Level structure, its virtually impossible to determine what those ROAS killers actually are. Once you have achieved granularity though you gain control over pulling the “right levers at the right time.” You can quickly filter in your ads account for specific performance trends like Zero Impression products or High Cost/Zero Conversion segments, and very easily make widespread bid adjustments or even exclude products that are consistently bringing down your overall stats.
- Avoid Impression Crowding: Impression Crowding (also known as Impression Eaters) is a phenomenon that commonly occurs in grouped Shopping campaign structures. Essentially, when you have too many products together in the same group, all set at the same Max CPC bid, the products basically fight with each other for impression share. Many times, this leads to potentially higher performing SKUs not getting the attention they need to generate sales. Products that simply “eat impressions” (and most likely are getting clicks too) wind up holding you back from achieving better returns overall.
Implement RLSA Immediately
RLSA or Remarketing Lists for Search/Shopping Ads is a unique, audience-based type of remarketing that is not only super easy to implement, it acts very differently compared to its cousin Dynamic Remarketing which is a form of Display ad type.
Unlike Display Remarketing, RLSA retargets previous visitors based on the audience segment you build and delivers Shopping ads when they search again on Google.
So, instead of being followed around the internet on other websites (Dynamic Remarketing), your Shopping ads literally just re-trigger in search.
The best part of RLSA is that is a beastly ROAS booster.
We performed a few different studies over the years specifically on RLSA audiences and the results were astounding:
- In 2016, based on a collaborative report with Google, we found that retailers who adopted RLSA saw an over 50% reduction in cost-per-acquisition on repeat/return customers while also seeing an average 10% uptick in conversions.
- In 2017, after analyzing over 20,000 separate RLSA audiences, our team discovered that the average ROAS for RLSA alone was over 200 times. Additionally, CTR on RLSA audiences was found to average around 10% while Conversion Rates sat around 45%!
For any retailer that we work with, our team applies best practices in the development of audiences and the bidding optimization. It all starts with the implementation of 5 strategic audiences which can all be built in Google Analytics.
- All Visitors: A standard for just about any Remarketing campaign, the All Visitors segment can be built using either Google Ads (probably the easiest way since it is automatic) or Analytics.
- High Bounce Rate:What is nice about Analytics audiences is that you can customize based on data which cannot be found in Google Ads. With that, the setup and delivery to visitors with higher than average bounce rates for e-commerce websites (over 80% and up to 95%) is a prime target.
- View Cart:Analytics allows for the use of logic in building audiences where you can combine ‘include and exclude’ parameters. A View Cart audience would be anyone that viewed the cart page but not the checkout page.
- Abandoned Cart:A slight variation to ‘View Cart,’ Abandoned Cart audiences refer to shoppers you visited the checkout page but don’t finalize a purchase.
- All Converters:One that can work in both Google Ads and Analytics, targeting anyone who has already purchased is never a bad idea. Often you can increase return sales at a lower cost to convert than the base cost-per-acquisition from a Shopping or Search campaign.
Per each audience, a unique bid modification strategy needs to be implemented, and this is generally handled through Bid Modifiers in Google Ads.
Leverage Device Bid Modifiers
If you have historical data to back up your decision-making, a great way to optimize your Shopping campaigns for ROAS would be through Bid Modification. If you were going to start somewhere definitely then consider your Device Bid Modifiers.
Note that for optimal effect, we recommend using at least 30 if not 90 days of past performance data if you have it. If you have more, great, use more.
- Example in Google Ads
- From the menu select Devices
Note that you can set ad group level segmentation if you'd like. For beginners however, you are best off at the campaign level to begin with.
Once you have segmented, data will populate for your selected columns for the device types.
Now, the purpose of this is to measure certain KPIs to determine which devices you want to considering bidding up or down on. You want to add certain headers such as Clicks, Impressions, Average CPC, CTR, Conversions, Conversion Rate, Total Conversion Value, and Conversion Value/Cost (ROAS).
- Impression Sharecan come in as a big player here. Adding Impression Share and then Share Loss metrics can help you choose between bid increase or decrease modifiers.
- Lower Conversion Rates on mobile devices could be telling you that your site is not optimized for the mobile experience or that checkout is too complicated versus on a computer.
- ROAS, which is Conversion Value/Cost, can impact your decisions on how much to bid up or down on. Higher return devices with a tendency leaning towards lower spend (Mobile for example) may be worth an increase percent modifier.
- Conversely, you can decrease your bids on devices that see a lower ROAS to balance out costs. This can help cut back on wasted ad spend on devices where you see less of a return or a return that is not congruent with another device segment.
Build a Top Performers Campaign
One of easiest ways to optimize your Shopping campaigns to boost ROAS is by building out a Top Performers campaign.
Doing so provides a number of benefits as you’ll be isolating products that drive the majority of conversions and revenue while focusing on them with a dedicated budget.
Top Performers campaigns are also quite easy to manage and analyze when you implement a product level buildout as they tend to consist of only a small number of products in comparison to the rest of your inventory.
First, you’ll have to find your top performing products. This is where that product level structure really comes in handy.
For example, in Google Ads, you can drill down to the product groups and then simply sort by conversions highest to lowest from the top:
Here I have set an all-time date range as this is a campaign that had very deep conversion history. In general, you want to have as much of a conversion history as possible to help determine your true top performers. A good date range to start with would be between 60-90 days if you don’t already have years or more worth of data.
Pro Tip: A nifty trick for determining your top performers by profitability is to factor in your margin (average or actual) and match this to how high your ROAS needs to be to remain profitable. With this you can further weed out products with lower ROAS since even if they did convert, they did not convert profitably. A low, positive ROAS is not necessarily and indicator of true performance.
At this point, you will need to scan down the list of product IDs (using the conversion column as a guide) and find where conversions begin to taper off. I often call this the Conversion Sweet Spot.
That spot is going to be different for every retailer, but its important to note that your selected date range has a substantial impact on your decision. A product with 2 conversions in the last 90 days may not be necessarily valued as a “Top Performer” versus another product that generated 12 in the same time-frame.
Generally speaking, any product with fewer than 3 conversions in the last 90 days may not be worth putting into a separate campaign. With that in mind, however, you can quickly implement a filter for conversions greater than X (with X being the “Sweet Spot”) and use the download or export function to get the product IDs into a separate file:
With your product IDs handy, you can set up your new Top Performers campaign. Be sure to set this to Accelerated Delivery. Also ensure you set it to High Priority as it will prevent these products from competing with one another in separate campaigns.
For extra measure you can also consider excluding the products in the original campaign that you plan on putting into your Top Performers to ensure they never compete.
When building a Top Performers campaign such as when done in Google Ads, be sure to start out building it as an All Products campaign with no initial subdivision.
To achieve that product level granularity I highly recommend:
- Take your new all products Top Performers campaign and then subdivide by Item ID
- Using the export from earlier of your “top performing products by conversions”, paste your product IDs into the field provided by your ads platform
- Save this configuration
- Once complete, immediately locate the “Everything else” product group that is created automatically and exclude it
That’s it! You should now have a fully prepared Top Performers campaign. Be sure to apply a proper budget for these products as you want them to get as much attention as possible to build up the performance history.
Over time you can optimize bids and other campaign assets such as bid modifiers, custom ad schedules, location targeting, and RLSA to help improve performance and drive higher ROAS for this unique segment.