A Step-By-Step Guide to Increasing Revenue at Every Stage in Your Buyer Journey

Last year, ecommerce accounted for 10 percent of retail sales in the U.S., according to Statista. By 2021, it’s expected to rise to nearly 14 percent.  More and more, U.S. shoppers are turning to the internet to make their purchases. An optimized …

Last year, ecommerce accounted for 10 percent of retail sales in the U.S., according to Statista. By 2021, it’s expected to rise to nearly 14 percent.  More and more, U.S. shoppers are turning to the internet to make their purchases. An optimized ecommerce site is your opportunity to get as much of the market share […]

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Monetate vs Certona: A Comparison of Kibo’s eCommerce Personalization Platforms

See our breakdown of Kibo’s Monetate vs Certona to know the difference between each personalization platform.

In this post, we’ll compare the two highest-rated software providers in the personalization engine space: Monetate and Certona.

KIBO Monetate vs KIBO Certona

Monetate and Certona are respectively rated the #2 and #1 Personalization Providers according to the Internet Retailer Top 1000. In the process of writing this article Kibo Commerce (which owns Certona) actually acquired Monetate. Kibo will be keeping the two platforms separate for the foreseeable future, so the question of Monetate vs. Certona is still very relevant for eCommerce businesses.

What do these eCommerce personalization engines do? Before we get into the specifics of each leading personalization engine, let’s take a moment to review what the general capabilities of tools like Monetate and Certona are.

What is a Personalization Engine Good for?

Certona highlights 6 key capabilities in their guide on Understanding Personalization Capabilities, these include:

  1. Collaborative filtering: Also referred to as the “Wisdom of the Crowd”, collaborative filtering does not focus on the individual behavior of shoppers, but rather collects data on how groups of people react to specific assets on your site.
  2. Customer segmentation: Segmentation allows you to target subsets of groups based on the specific attributes of those shoppers (such as customer intent and purchase history).
  3. Rule-based personalization: Business rules allow you to define, test and execute different experiments while still meeting your specific business goals.
  4. Real-time profiling: Profiling is one of the most powerful aspects of personalization, this helps you create individual shopping profiles in real-time and customizes the experience for those customers accordingly.
  5. Predictive modeling: Predictive modeling uses many techniques from data mining, machine learning, and artificial intelligence (AI) to predict the future behavior of shoppers.
  6. Data integration: Data integration is the process of leveraging data from various sources to gain additional insights into each and every shopper.

In the experience of eCommerce businesses we’ve spoken to, there are three main use cases that both Monetate and Certona can handle well, these include:

  1. Product recommendations
  2. Content recommendations (and content personalization)
  3. Dynamic UI changes (i.e. changing the navigation to match a customer profile)

Now that you know the high-level functionality and use cases for personalization engines, the question then becomes:

Are Monetate and Certona functionally different in terms of their capabilities, or are they extremely comparable platforms with different branding? 

The short answer is: There are major differences in their capabilities as well as the users they are best for. To illustrate these differences, let’s discuss the use cases and unique features of each platform.

Note: Do you want to know more about getting started with personalization on your eCommerce store, or want to improve your personalization such as product recommendations?

Get in touch with our CRO team today to get started.

Monetate vs. Certona: Use Cases of Each Personalization Engine

Although these two software providers are similar, they do have several unique features that they each specialize in. If we had to break down the differences of each platform in a single sentence:

Monetate specializes in testing and optimization, while Certona specializes in AI-powered personalization throughout the customer journey.

Is one tool better-suited for your eCommerce store’s needs than the other? Do you even need either of them? Let’s zoom in to review the unique features and use cases of Monetate and Certona in a bit more detail.

Monetate: Use Cases & Unique Features

As mentioned, Monetate is best known for its testing and optimization capabilities. The platform lets you launch controlled experiments to test everything from creative, recommendations, messaging, and UI changes. There are a few different types of tests you can run with Monetate, including:

  • A/B testing: these are used to determine the better of two content, product, or UI variations.
  • Multivariate testing: these are used to test more than two components of a website.
  • Dynamic tests: these allow you to test multiple features, monitor results in real time, and then automatically allocate more traffic to the winners.

One of the unique aspects of the Monetate platform is that you can combine your own customer data with third-party data from their personalization exchange. The personalization exchange is meant to help solve the “cold start” problem faced by consumer retailers who don’t have existing customer data for the software to model off of.

By supplementing your customer profiles with third-party data from such as behavioral, attribute, and location, Monetate’s user data from external sales channels can help fill the gaps in your own data to enable the full use of the platform.

In addition to the data exchange, the platform also has an open architecture that allows for data integrations and APIs to feed data into the decision engine from your existing analytics systems.

Another one of the main use cases of Monetate is for personalized product recommendations (Certona also has this capability). You can either choose to manually curate product recommendations, or you can use their algorithmically driven recommendations if you have a larger product catalog.

Monetate makes product recommendations by factoring contextual attributes about the shopper. For example, in the screenshot below you can see several examples of customer attributes like the Lifetime Purchases and Most Frequently Bought Category:

In addition to customer attributes, recommendations can be made based on things like the weather, ratings, inventory status, audience segmentation, or almost any other attribute you deem appropriate.

If you want to read an example of a company using Monetate for product recommendations, check out this case study of Helly Hansen using their geotargeting capabilities to deliver customized experiences based on the local weather conditions.

Certona: Use Cases & Unique Features

Similarly to Monetate, Certona allows you to personalize product discovery by rearranging your catalog to feature the most relevant and complementary products at the top of the page.

One of the unique features of Certona in terms of product discovery is that you can engage customers with interactive content to help expose relevant products and build customer profiles (what Certona calls “exceptional content experiences”). 

For example, in the screenshot below you can see a popup designed to help with audience building. It prompts the user to answer a questionnaire to help them find the right product:

Another unique feature of Certona is its predictive search engine, which populates recommended products based on a customer’s search term and buyer intent. As you can see in the screenshot below, the search bar becomes a visual recommendation engine:

In addition to personalizing the customer experience of your website, Certona offers personalization capabilities that can be applied to the following use cases:

  • Brick-and-mortar shopping: allows you to connect online and offline customer data.
  • Contact centers: lets you automate manual merchandising processes to help your representatives recommend relevant upsells and cross-sells.
  • Email: allows you to send dynamic email campaigns that are tailored to each customer.

If you want to read an example of a company using Certona, check out this case study of PUMA, which used the platform for real-time behavioral profiling and personalized product recommendations for their large catalog without increasing labor costs.

Monetate vs. Certona: Pros & Cons of Each Personalization Engine

Since Monetate and Certona are the top two leaders in the personalization software market, they’ve also been extensively reviewed by consumers, so let’s look at a few of the commonly mentioned pros and cons of each platform.

Monetate: Pros and Cons

One of the main advantages of Monetate that many consumers highlight is its ease-of-use. Like any other software platform, there is a learning curve and more complicated tests do require a bit of web development, but many say that their WYSIWYG interface can easily be taught to entry-level marketers. 

One of the limitations of Monetate that several consumers mention is their lack of training videos, and the fact that the platform is not built for running more complex tests that require extensive web development.

Pros of Monetate:

  • More of a self-serve user interface: you can test virtually anything with relative ease including A/B tests, multivariate tests, and dynamic tests.
  • Ease-of-use for building and deploying experiments in your website or marketing campaigns with an intuitive WYSIWYG interface.

Cons of Monetate:

  • Several consumer reviews mention that the interface is relatively simple to use once you get the hang of it, but there is still a learning curve and a lack of training videos in the documentation to help you become a power user.
  • The platform is not built for running more complex tests that require extensive web development.
  • Pricing is not transparent.

Certona: Pros and Cons

Although users have reported in reviews that Certona is a bit harder of a platform to learn how to use, it excels in its scalability and integration capabilities compared to Monetate. As highlighted on the consumer review site TrustRadius, if your company offers a wide breadth of products and services and you want to personalize a large amount of the customer experience, Certona may be well-suited for you. 

Rather than a hands-on platform that someone on your team works on, Certona is all about their account management. They will work with your team to optimize your personalization efforts. So if you’re looking for more of a hands-off, managed solution, Certona might be right for you.

One of the limitations of Certona is that while you can run A/B and multivariate tests, their Smart Test & Analytics platform does require you to go in and identify the winning test that you want to promote.

This is contrasted to Monetate’s dynamic testing capabilities, which identifies and takes action on winners without the need for human intervention (even if it may just be a few clicks). While they have complementary features, given the enterprise-level pricing, many businesses will likely not opt for a combination of Certona and Monetate.

Pros of Certona

  • Well-suited for companies with a wide breadth of products and services that want the ability to run more complex tests.
  • As highlighted on TrustRadius, their visual search has a strong return and improves the discovery process for customers.
  • The strength of their personalization algorithms — they currently hold 13 patents for AI-driven algorithms.
  • Many consumers say the account management is very helpful if you’re looking for more of a managed solution.

Cons of Certona

  • As mentioned on Gartner, ease of deployment is a bit lower with Certona compared to Monetate (you will likely rely on Certona’s account management, while Monetate might allow you to have more of a hand in things).
  • As with Monetate, pricing is not apparent on the site and may likely be tailored to your store and use cases.

Criteria for Choosing Between Monetate and Certona

Of course, we’re all going to have specific business needs for choosing a personalization platform, but we’ve broken down the process into 6 main criteria to think about when choosing between Monentate and Certona. These include:

  1. Platform Ease of Use 

Monetate may be right for you if you want a simple interface that you can teach less-technical marketers how to use. Certona may be right for you if ease of use is not your top priority and instead want to be able to build more complex experiences with web development.

  1. Self-Serve Platform vs. Managed Solution

Since Monetate has a more user-friendly UI, it can more of a self-serve platform where you can be involved in setting up and testing different experiences. Certona, on the other hand, is a bit harder of a platform to learn how to use, but they are known for having excellent account management if you’re looking for more of a hands-off, managed solution.

  1. Use Case: Personalization vs. Testing & Optimization

While Monetate is still a personalization engine, it’s best known for its testing and optimization capabilities. Certona is less of a testing platform and more of an end-to-end personalization platform.

  1. Size of Your Product Catalog 

Both Monetate and Certona can certainly handle large catalog sizes (for example, auto parts and accessories).

They are also helpful for handling updates to dynamic catalogs that merchandisers are often changing from season to season (for example: fashion), and the account managers on the Monetate or Certona team can take care of this big regular task that your internal team might not have the bandwidth for.

  1. Unique Platform Features 

Both platforms have similar features like product recommendations, but there are several unique features of each platform that may be of interest to you. Namely, Certona’s predictive visual search engine and Monetate’s third party data exchange. If you already have and store data prepared well for personalization, you can plug in to Certona much easier — with less of a technical headache. If you are missing that data, Monetate can step in with their data exchange to fill in the gaps.

  1. Price

Price is, of course, another consideration for all businesses and some users report that Certona is priced slightly higher since it is more of a managed solution. However, neither company is transparent on price and they likely adjust pricing to individual clients depending on the business and use cases of the tools.

Summary: Monetate vs. Certona

There’s no question that one of the most powerful technologies in eCommerce right now is personalization in the customer journey. Personalization is more than just product recommendations; rather, it should be thought of as a steady delivery of unique experiences starting from the very first touchpoint to the end of the buyer’s journey. 

Both Monetate and Certona can be complements as part of a larger commerce platform to enable personalization. That said, businesses will likely choose one platform over the other depending on the use case and how hands-on or hands-off they want to be rather than opting for both platforms.

Note: If you have a solid JavaScript developer, you will probably be able to do some of the personalization that these platforms offer yourself. If you just have a one-off use case, or a small product catalog that doesn’t require large updates to enable personalization, this might be the more cost-effective way to go.

That said, if you’re in a business that is constantly changing, (for example if you’re in an industry like fast fashion) you may feel like you need to hire someone full-time just to handle all the product recommendations. In that case, the price paid for AI assistants like the addition of Monetate or Certona might make sense to enhance revenue and customer lifetime value — especially compared to hiring a full-timer to handle that on your own team.

As Meyer Sheik, the former CEO of Certona said in a Q&A, one of the main challenges that retailers and brands face when it comes to personalization is that they lack the technology infrastructure and internal resources to stand something like this up on their own.

One of the key takeaways that we learned from speaking to eCommerce business owners about their experience with personalization engines is that whichever platform you go with, there is still going to be a good amount of technical training needed to get everything up and running. So make sure someone from your team gets a technical onboarding from the personalization platform’s team to be safe.

If you do decide to go with one of these personalization engines and want to get everything set up correctly, that’s where Inflow can help. We’ve helped leading eCommerce companies implement personalization into their businesses to help drive more purchases and revenue from their customers.

If you’re looking for a team to help you personalize your customer experience to help increase conversions, schedule a call with us here.

How to Use Personalization and Automation for Small Business Growth

New technologies are radically changing the way businesses interact with customers. As a result, customer expectations are constantly changing. Businesses should innovate and evolve in order to meet those expectations and build relationships that custo…

New technologies are radically changing the way businesses interact with customers. As a result, customer expectations are constantly changing. Businesses should innovate and evolve in order to meet those expectations and build relationships that customers value. To do this, businesses should rethink their approach to customer experiences and engagement. 84% of consumers consider the experiences […]

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Practical Advice for Keeping Your Holiday Marketing Campaigns Streamlined

Automation is the key to making sure that your business runs smoothly and that you can concentrate your time on meaningful (rather than mundane) tasks. As we approach the holiday season, automating customer outreach becomes that much more important to …

Automation is the key to making sure that your business runs smoothly and that you can concentrate your time on meaningful (rather than mundane) tasks. As we approach the holiday season, automating customer outreach becomes that much more important to ensuring that no one falls through the cracks and that you’re hitting your customers with […]

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5 Last Minute Conversion Tips Before the Holiday Season

How to Quickly Boost Conversion Rates for Your Online Store If you’re an ecommerce owner, you’re probably looking forward to the upcoming holiday season.  You’re planning your marketing campaigns carefully, maybe hiring new people to help, and wai…

How to Quickly Boost Conversion Rates for Your Online Store If you’re an ecommerce owner, you’re probably looking forward to the upcoming holiday season.  You’re planning your marketing campaigns carefully, maybe hiring new people to help, and waiting for more traffic to come. But you may also think it’s too late to do anything with […]

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Our Winning PPC Strategy for eCommerce: How We Increased Google Ads ROAS by 76%

Increase your PPC ROAS and spend less on ads with the strategies in this eCommerce PPC case study.

In our conversations with hundreds of eCommerce business owners, many have told us that their Google ads (formerly Google Adwords) campaigns aren’t performing as well as they originally thought they would, and could be working more efficiently for a lesser cost.

When setting up their PPC advertising strategy, many of these eCommerce stores assume that setting up their feed and launching one Shopping campaign containing all of their products is all that it takes to create a profit.

They are disappointed and sometimes mystified that their ads don’t drive a good return and the work that went in setting them up was wasted.

That’s when I explain that if managed correctly and implemented by pros, Google Ads can actually be a great revenue driver that will grow your business… But it takes more than just keywords and ad creative.


This is exactly what one of our clients in the camera equipment niche came to us with. Unfortunately, the agency they had been working with prior to us hadn’t been doing a great job on their Google PPC.

After we took over their PPC efforts, between Feb 1st, 2019 – August 31st, 2019, we got them a 76% increase in ROAS, from 5.61x to 9.89x, compared to July 1, 2018 – Jan. 31, 2019 when they had been working with the other agency:

Google analytics: 76% increase in ROAS, from 5.61x to 9.89x.

Year-over-year, we got them a 56% increase in ROAS from 6.34x to 9.89x:

Google analytics: 56% increase in ROAS from 6.34x to 9.89x.

You can see a breakdown of the Google Ads strategies that we use for our clients in this linked article. 

In this case study, we’d like to demystify the actual work involved and the combination of eCommerce PPC marketing strategies that we used to get results for this online store.

You’ll see:

  • The Google Ads Strategies We Implemented for a 9.89x ROAS
  • Our Tiered Bidding Strategy: Implementation and Best Practices
  • Other Shopping and Search Ad Best Practices We Recommend to Reduce Spend

As eCommerce growth experts, our clients include not only 7 and 8-figure businesses, but 9-figure annual revenue eCommerce companies as well. Talk to us today to see if we can help you optimize your eCommerce brand’s paid search, SEO, and conversion rates.

1. The eCommerce PPC Strategies We Implemented for a 9.89x ROAS

While every client presents unique aspects of their business and different challenges, we’ve learned through working with hundreds of clients about how important it is to follow a system in order to create results, which is what we did.

Audit and Analysis

When we begin running PPC for eCommerce sites, the first thing we do is audit the client’s product feed, campaigns, and other performance indicators to see what is working and what is causing issues.

This site had high search volume and a very extensive product catalog of cameras, lenses, and other camera-related equipment. Due to the store’s scale, we discovered that there were problems like incomplete/missing information about products in their Google product data feed. Their current PPC campaigns were also too broad given the different product categories on the site, which created wasted spend.

The work we determined would increase ROAS for this client included:

  • Product data feed setup and optimization
  • A Google Shopping campaign restructure
  • A Google Search ad campaign restructure
  • Google Display ad optimizations
  • Implementing the campaigns that worked in Google to Bing Ads

By optimizing each of the above, we positioned our client’s products in a way that encapsulates the customer’s entire buying journey. This resulted in less spend per click and more sales.

Here’s How It Worked:

Product Feed Setup and Feed Optimization

The product feed contains your products and their related information including: product category, brands, quantities, sizes, colors, materials, etc.

Google Shopping Ads and Display Ads are based on information that Google pulls directly from your store’s Product Feed:

Google shopping ads and Google search ads (results for "washing machines")

(An example of Google Shopping Ads and Search Ads)

This is why optimizing the Google Product Feed is so important.

For this client in the camera equipment niche, that meant making sure that information like the camera brands, their lens sizes, and so on were all present, accurate, and easily found by Google.

The site had huge potential to be shown for many different specific product queries, but Google wasn’t able to match those search queries to the product in this store’s catalog.

Fixing this meant that now when somebody searched Google for a product in our client’s catalog, such as a specific camera lens model, our client’s product was more likely to appear right there as a Shopping ad. (We optimized the product feed in a tool called Feedonomics).

Shopping Campaign and Search Ad Campaign Restructures

A mixture of Google Shopping ads, Google Search ads, and Google Display ads is beneficial to most big online retailers.

Implementing all three often leads to enhanced product visibility across the buyer’s entire journey, from research through to purchase.

With the product feed optimized, we began restructuring the client’s search and shopping structures.

This particular industry has high search volume which makes it easier to gain traffic, but also harder to figure out the specific combination of search queries that drive the highest return.

So because of this, we created separate multiple tiered campaigns segmented by product type—creating different tiers for different product categories. In this case, a lens tier, digital camera tier, video camera tier, film camera tier, etc.

Display Ad Optimizations

Products ads that follow customers around the web might seem annoying on first glance, but in fact, retargeting ads do convert very well and have a great ROI. Why? Because they get customers at the end of the buying cycle (once they’ve already visited the store and looked at products).

People were visiting our client’s store, but they weren’t being remarketed to. The dynamic remarketing feature from Google Shopping enabled us to automatically show ads to people who came to the client’s site without completing a purchase.

Dynamic remarketing makes use of your product feed to determine what products Google displays on its ad network. It can intelligently group different products together based on what’s likely to convert best.

An example of a dynamic retargeting ad:

A dynamic retargeting ad

Using dynamic remarketing is a fairly straightforward strategy to skyrocket eCommerce performance, and we believe it’s a must for any online retailer.

Bing Account Changes

Once we saw what was working in Google, we began transferring the Google Ads changes to attempt replicating their success in Bing Ads.

While Bing has a far lower search engine market share (2.63% as of this article’s writing), we’ve found that what works well in Google Ads can often work in Bing Ads (now called Microsoft Advertising). Why not duplicate the strategies that work in Google to capture shoppers from another search engine?

2. Our Tiered Bidding Strategy: Implementation and Best Practices

When it comes to any PPC campaign, patience and being willing to adjust along the way are important. You’ll determine the highest return queries and adjust your bids to prioritize them as an ongoing process.

In this case, we identified the highest return search queries based on this store’s different product categories, and created a tiered campaign for each category.

Here’s a visual representation of that tiered strategy. The search queries each tier drives are based on negative keywords, and we created multiple tiered campaigns for each product category:

Tier 1: High priority, low bid, catch all; Tier 2: Medium priority, medium bid, higher ROAS; Tier 3: Low priority, highest bid, highest ROAS.

The Basic Steps to Establish Your Tiers

  1. Run Search Query Reports: Look at historical performance in Google Analytics by running search query reports, going back 6 months (or longer). Identify the queries or query combinations that have driven the highest revenue or ROAS in the past.
  2. Filter those queries in Google Analytics to see if they have a high churn or not. Decide which high return queries you want to filter into Tier 2 or 3.
  3. Mark any interesting patterns. For example, we saw a pattern of queries containing certain modifiers that tended to convert well, and we made sure to figure out the revenue and ROAS for those terms.
  4. Keep building it out on a spreadsheet to organize what you find. Organize those patterns to create the list containing the search query, revenue, and ROAS numbers.
  5. Segment the tiers according to the revenue and ROAS numbers: We optimized Google Shopping campaigns through the use of priority settings, bid stacking and negative keywords.

    The basic premise is to apply low, medium, and high bids on search terms with low, medium, and high returns. Thus optimizing the cost-per-click (CPC).

Conversely, we apply high, medium, and low priority levels to low, medium, and high bids/returns. For context, the priority setting determines the order in which Google will cycle through the campaigns. High priority literally means Google takes this campaign into account first because it will be Google’s highest priority.

To Illustrate:

Tier 1: We placed low bids on our catch-all campaign that drives all general queries. We added negative terms to avoid targeting queries that we wanted to bid higher on in the other tiers. Set to a high priority setting.

Tier 2: We placed medium bids on search queries we found to have a higher return than those in tier 1, but lower return than the queries we want to filter to tier 3.

As in tier 1, we added negative keywords for the queries we wanted to filter to tier 3. This tier was set to a medium priority setting.

Tier 3: Knowing what the most profitable search queries are, we place the highest bids on them. This tier was set to a low priority setting.

The tiered system works because in recognizing the performance of a store’s different relevant search queries, you can have much more control over how much ad spend is allocated to each query.

3. Other Shopping and Search Ad Best Practices to Reduce Spend

  • Always send the best performing / highest return queries to tier 3. By identifying the highest return queries, we are able to ensure less wasted spend by spending the least amount of money on low return queries and allocating the largest percentage of money to terms we are positive will actually drive a high return.

  • Use negative targeting. Negative keyword segmentation in a tiered system allows us to pay less ad spend for lower returning queries.

  • Optimize by device. After the tiers had run for enough time and gathered significant data, we analyzed performance by device to ensure no wasted spend.

  • Cut wasted spend on the least performing hours / days of the week. After gathering significant data, we ran a time of day analysis to ensure we were optimizing for our best performing days and hours.

  • Launch Search Competitor campaigns alongside your own search ads to target the competition (rest assured, they are likely doing this too).

  • Optimize by demographics We ran demographic based analyses for age, gender & household incomes then implemented bid adjustments accordingly.

  • Optimize your display ads to capture who they retarget. In addition to optimizing their bids and budget, it’s important to update the ad copy to better target users at different stages in the buying funnel. For example, newer users require more brand focused CTAs, while previous purchasers do not. We also started testing new ad features from Google such as Smart Display ads. We often test Google’s new features for our clients because we’ve seen that being one of the first to use new ad features is a competitive advantage (because competitors may be slow to adopt new features).


PPC is a dynamic advertising practice—meaning that management is ongoing—it’s not a “set it and forget it” platform.


Adjusting our PPC strategy allowed us to achieve a year-over-year 56% increase in ROAS from 6.34x to 9.89x.

PPC Strategy for eCommerce: Within Google analytics, you can see their increase in ROAS from 6.34x to 9.89x.

When Inflow took over, their PPC strategy greatly increased, causing a major ROAS!

I hope this case study helped paint a picture of how a Google Ads strategy based on a systematic review and restructuring can quickly yield a higher ROAS.

eCommerce brands who work with us receive a tailored set of strategies like these to maximize their Google ads campaign budgets.

If you would like us to evaluate and improve your online store’s PPC campaigns or identify additional growth opportunities, please get in touch with us today to see if we can help.

Google Ads Automation for eCommerce: 4 Winning Strategies for Your Online Store

Google’s automated ad types are becoming practically required for eCommerce brands to retain their competitive edge in PPC. Google is moving toward automation for a few reasons: As more people use Google’s search engine for shopping, Google wants to find the relevant ad type to show depending on how somebody is searching. To accomplish this,

Google’s automated ad types are becoming practically required for eCommerce brands to retain their competitive edge in PPC. Google is moving toward automation for a few reasons:

  1. As more people use Google’s search engine for shopping, Google wants to find the relevant ad type to show depending on how somebody is searching.
  2. To accomplish this, they are using their machine learning AI to figure out which ad type is “relevant” to a given search.
  3. As a result, advertisers who use Google Ads (formerly AdWords) automations tend to get their products in front of a broader audience who they may not have necessarily targeted manually.

We often encourage our clients to adopt these newer Google Ads types to help prevent being left behind as the competition starts to use them. We’ve already used automated campaigns to expand traffic, boost awareness of our clients’ brands, and improve efficiency.

This graph shows the growth in both traffic and transactions that we have accomplished using Google Ads automations. There is a spend increase of 115% due to the success, and Transactions are up 323%, Revenue is up 182% and ROAS is up 31%:

A graphic showing Google Analytics: Transactions are up 323%, Revenue is up 182% and ROAS is up 31%.

What can Google automate in terms of PPC? 

Quite a lot, and more is likely on the horizon. The Google Ads automation features we have seen some of the most client success thus far are:

  1. Automated bidding
  2. Smart Shopping
  3. Smart Display Ads
  4. Dynamic Search Ads

Below, we’ll illustrate how these Google automation capabilities play a big role in how we manage our client accounts and some crucial things to keep in mind when using them.

Want us to automate and optimize your eCommerce store’s paid search and PPC campaigns? Get in touch to see if we can help.

1. Google Ads Automated Bidding Campaigns

For larger accounts such as enterprise eCommerce stores, there usually isn’t enough time in the day for manual bid management to adjust the max CPC of individual keywords (and in doing so, optimize the campaigns).

Automated bidding takes care of optimizing the max CPC of keywords for specific goals, using strategies that Google has built into their AI.

Google’s automated bidding strategies and their goals are:

Goal and Bid Strategy

Note: Target CPA, Target ROAS, and Maximize Conversions are part of a subset of automated bidding strategies called Smart Bidding.

Which automated bid strategy should you use, and when? 

It depends on your business objectives

What KPIs are you focusing on?

  • If conversions are your primary goal, then you may use the Maximize Conversions bid strategy in order to focus on maximizing conversion volume.
  • If you want to get more conversion value out of your budget: Maximize Conversion Value.
  • If it’s traffic, then Maximize Clicks and Target Impression Share may be the best bid strategies. We have also used Target Impression Share to ensure we are maximizing impression share on brand. And we have leveraged this bid strategy to target and outrank specific competitors.
  • Often, our clients have a target ROAS and conversion rate in mind. We’ve found that Target ROAS and Target CPA are useful in reaching their goal numbers because these 2 KPIs tend to be more directly correlated to profitability.

Keep in mind, there are some other things to note about using Target ROAS and Target CPA:

Target ROAS

Target ROAS is useful if your goal is to increase the return on investment (ROI) and/or ROAS from PPC.

For example, one of our clients was struggling to hit their strict ROAS goal. We had refined a tiered Shopping campaign strategy to segment search queries and prioritize bids based on different performance buckets for those search queries. This was very successful in directing search queries to these different tiers, but we were struggling to hit their strict ROAS goal.

We tested adding a Target ROAS bidding strategy and saw a gradual, but steady lift in performance. With the ROAS goal set at a higher number than what we typically see, we assumed this would limit our targeting. However, automated bidding was able to find efficiency without decreasing our traffic.

For Target ROAS to work: It’s important to adjust the Target ROAS up toward the goal in increments. You want to “massage” the campaign by gradually increasing the Target ROAS. In our experience, Google’s machine learning algorithm will better adjust to this as opposed to a large jump.

Additionally, Target ROAS requires existing conversion data (such as 30-50 conversions within a 30-day window) in order to work well. We have seen that this is also true when using Target CPA.

Target CPA

If a client wants a specific return, or if they are concerned about specific margins and don’t want to invest too much, Target CPA may be the right approach.

Margins become a concern when selling higher-priced products because marketing them via PPC can sometimes (but not always) be more expensive from a keyword perspective. Higher priced items have longer conversion and lead times, so CPA can be more efficient.

For example: A home heater priced at $2400 may very well have a margin of $150. Anything over that is a straight loss, and if the sales cost $150 in ad spend that break-even amount simply went to pay for a conversion. For a successful campaign, ROAS in this case would be 16x or 1600%. In most campaigns, that ROAS would be incredible! But that’s why margins are so important to consider in any strategy.

We’ll usually work with clients to determine what the Target CPA and Target ROAS will be. Target CPA ads have also been good for generating leads at a cost that makes sense for our clients to acquire them.

For Target CPA to work: Like Target ROAS, Target CPA bid strategies require existing conversion data so that Google’s artificial intelligence has a model from which to spend your ad budget.

Note: Target CPA and Target ROAS can work especially well If you have a competitor with a manual CPC and yours is automatic. In our experience, Google seems to be more incentivized to hit target CPA or ROAS for the automatic campaign when one competitor is not using it.

Is there still room for manual bidding?

Automated bidding may be the future of PPC marketing overall, with algorithms that will rely on conversion data more than ever for its improved efficiency, better budget spend, and opportunities to pursue more fresh and broad targeting opportunities.

That said, it may not work across all campaigns. Depending on the competitor landscape, manual bidding will still be useful when the AI doesn’t work.

Strategically, manual bidding makes sense in certain cases. Such as campaigns that do a “scorched earth approach” of Maximizing Impression Share to dominate a search query or category. Or, to run a manual campaign that gathers the minimum conversion volume needed to run an effective automated campaign.

Smart Shopping Campaigns

Smart Shopping automates bidding and ad placement in a combination of Standard Shopping and remarketing Display Ad campaigns.

Google Search Results for "Red New Balance Sneakers"

An example of a Shopping Ad (which could be either a Smart or a regular Shopping Ad)

We like to use Smart Shopping campaigns to fill in the gaps our Standard Shopping campaigns leave open.

For example: One of our clients had a very efficient Standard Shopping campaign that was performing well, but wasn’t bringing in the transaction and revenue volume they wanted. Although this campaign was converting well, we were struggling to find growth for it.

When we introduced a Smart Shopping campaign, we immediately saw a boost in transaction volume without sacrificing our efficiency. The Smart Shopping campaigns allowed us to increase spend and discover new pockets of relevant traffic. This also increased our year-over-year revenue by 200% while maintaining the account’s ROAS.

As another example: We started using Smart Shopping in another account last Fall. This was one of the first accounts we had tested this campaign type on and we were unsure if this would boost performance. However, we began to see results almost instantly.

Within a month, shopping ROAS had doubled. By the third month, we broke our ROAS record at 1500%. Revenue has also consistently been up 200-300% year over year. 

Best Practices for Smart Shopping Campaigns

An optimized product feed is important for both automated and manual shopping campaigns. For SMART shopping in particular, you really need a highly optimized shopping feed to give Google the signals it needs to find your product relevant to a search.

For example, we especially look at titles, descriptions, and keywords, making it relevant to the product. If it’s a yellow T-shirt then we need the size, color, and material of it in the product feed.

Because of the nature of smart shopping campaigns, you don’t have any visibility into which search terms are triggering products to display. Optimizing the data feed will help ensure that search terms remain relevant and accurate to the product they trigger.

With that said, certain businesses need a lot of control over the search terms and audience that they’re targeting.

For example, large name brands may decide not to go in the automated direction because they need to know how their brand terms are being used or associated. They also need to have control over what they are targeting and what audiences based on specific brand guidelines and user demographics. Certain campaigns like Smart Shopping take away that control and insight.

Smart Display Ads

Smart Display is another automation type we have begun incorporating into our overall account strategies. Smart Display campaigns use automated bidding, automated targeting, and automated ad creation based on information about your products and their performance. Google displays the ads across the Google Display Network to reach customers outside of your manually targeted campaigns.

Smart Shopping Campaigns: Search, Display, YouTube and Gmail.

Smart Shopping Ads are also shown as Smart Display Ads in the Display Network.

We have used Smart Display campaigns primarily as a branding play to increase awareness and attract users to our client’s sites whom we might not typically target. It has been a powerful traffic driver, and we have capitalized on this increased volume by utilizing remarketing lists to continue re-engaging people who have visited a client’s website. This has enabled us to nurture these top of funnel, less targeted users into potential conversions by reaching that at multiple points in the buying cycle.

Smart Display campaigns are based on a Target CPA strategy that continually optimizes for conversions (and it’s another case where your store’s performance data is integral). So make sure to set the Target CPA at a rate that would get a viable return.

Dynamic Search Ads

Dynamic search ads have been helpful in our accounts. It seems that Google has larger eCommerce stores with a wide inventory in mind for this ad type.

What’s interesting about how they work is that Google uses a landing page from your website to create the copy for the ad when someone searches for a keyword that is relevant to that landing page. It’s “dynamic” in that it pulls information from your website to create the text ads within search results in real time. These ads are also dynamic in the keywords they match and target.

For example, if someone searches Google for “rain jacket women” and you have a landing page for women’s jackets, they will see your Dynamic Search ad with the headline “rain jacket women” if Google’s algorithm finds it relevant to the search and decides to display it:

Dynamically created headline based on the Google search: "rain jacket women"

An example of a dynamic search ad.

We frequently use this campaign type when launching new accounts to ensure we have coverage on all relevant keywords. We also use it to identify new pockets of traffic in existing accounts that we are trying to expand. Not only is this a good keyword mining tool, but we also find that it may foster strong performance when paired with a target ROAS or target CPA bidding strategy.

To make Dynamic Search ads work: First, think of them as a very basic ad type. We like to look at them as research tools because these ads frequently look at areas you aren’t necessarily targeting.

Second, understand that they revolve and change. These ads will continue to target new keywords and new ad copy and thus they fill in temporary gaps, but they will not necessarily continue targeting any one keyword.

Above all, Dynamic Search ads are an ongoing strategy. As Google creates these ads and you see what resulted in conversions, you can use that information to expand your thinking for other campaigns.


We hope this has given you some insight into several main automated strategies that Google provides. In our view, it can’t be overstated that using these strategies are a requirement to stay competitive in the eCommerce PPC landscape.

If you don’t use these automated strategies, chances are that your competitors will…and their stores may benefit from the increasing opportunities these strategies open up instead of yours.

To recap:

  • We have used Google’s automated ads to both expand traffic as well as increase efficiency for our eCommerce clients. The ad types we’ve seen the most success with are:
    • Automated bidding
    • Smart Shopping
    • Smart Display Ads
    • Dynamic Search Ads
  • We have also used these campaigns to boost brand awareness and build a wider funnel for a more holistic marketing approach that takes a broader consideration in what and who to target (thanks to Google doing that targeting for us).
  • Maybe most importantly, these automated bidding strategies have helped us to improve our PPC metrics and divert time toward higher-level strategic initiatives that may normally be spent on granular adjustments to the campaigns.

Your turn: The first step and key for any eCommerce business to begin using automated strategies effectively is to gather their conversion data. With that, Google’s AI can effectively target a broader audience than manual ads will allow.

Wondering what you could be automating in terms of PPC? If you’re interested in getting started with these automated strategies, please get in touch to see how we can help you with them as a marketing agency. Or, take advantage of our other growth-focused eCommerce SEO, SEM, PPC, and CRO services.