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.

eCommerce Personalization Strategies Using Google Analytics and Other Free Tools

Here we outline our method to personalize eCommerce sites using just Google Analytics and simple cookies. No elaborate third party tools required.

Enterprise personalization software is typically complicated, expensive, and possibly overkill for a majority of eCommerce companies. In our experience, this leads many to avoid or delay implementing personalized experiences on their sites, which likely leaves revenue — and a better conversion rate — on the table. 

So, to help more eCommerce brands implement personalized experiences that can increase conversions, we’ve begun developing a new process for personalizing eCommerce websites that solely uses Google Analytics and simple Javascript cookies. As a result, our method can work regardless of eCommerce platforms, marketing automation platforms, or in addition to any personalization technology already in place. 

This process gives eCommerce brands the flexibility to “do” personalization on their own terms, from the spectrum of light personalization (a few custom experiences in specific situations) to as much personalization as they want (many customizations for large portions of their audience), all without bloated, expensive personalization platforms with inscrutable artificial intelligence or machine learning algorithms. 

We’ve just begun developing this process at Inflow — we are actively applying it to client sites as we write this — but we’ve used these core concepts for a long time. Namely, our process is based on how we implement A/B tests for clients that aren’t using a 3rd party A/B testing tool.

In this article, we detail each step of our eCommerce site personalization process, using various eCommerce personalization examples throughout. 

Note: If you manage an eCommerce business and want to know how this process could help your website personalization efforts, you can learn more and talk to our CRO team here

Overview of Our eCommerce Personalization Process

Any eCommerce personalization process really just needs to do 2 things: 

  1. Bucket online shoppers into specific personas 
  2. Show custom (personalized) experiences to each persona. 

Ours is no different, but let’s use some examples to get a sense of how this works.

First, a clothing store may want to know if an anonymous user is a man or woman. The user could (a) indicate their persona through their site interactions which (b) helps the store display products that they would be interested in. 

Or, in a more subtle example, a yoga store would benefit from knowing whether a user is a beginner or an advanced yoga instructor. The bucketing of users (step a) in this case, is not as obvious as the man or a woman example above, but if they were able to do so, they could offer a personalized shopping experience (step b) for each group; showing beginner friendly items to one group and bulk discounts on commonly used items for instructors to the other group.

Our specific process for doing this breaks down into a 4 steps that we explain in turn below:

  1. Brainstorm and Bucket Personas
  2. Determine Characteristics and Site Behaviors
  3. Analyze Data
  4. Personalize the Website

Steps 1 – 3 are dedicated to the first goal: Bucket users into personas, which is the foundation of this process, while Step 4 is to show users a personalized experience depending on which bucket they are in (this is the easier, final step). 

Step 1: Brainstorm and Group Personas Together

The first step is to brainstorm who your users are and bucket them into personas. This step lays the foundation for the entire personalization process because it determines the types of potential customers we’re going to personalize for.

It’s important to note that we aren’t tracking anything here, we are just making a hypothesis about who our users are based on their actions. By the end of this step we want to have solid hypotheses of what user personas could benefit from a custom site experience.

To use a specific example, one client we have, Mountain House, sells freeze dried food. They’ve noticed over time that two different types of customers (personas) use their products: preppers and backpackers. 

A view of the landing page for Mountain House.

One of our clients, Mountainhouse.com, who sells freeze dried foods.

Preppers, or survivalists, are buying goods and food for potential emergency scenarios. Backpackers, of course, are buying goods and food for backpacking and camping trips. 

They use similar products but have vastly different needs and goals. But we may hypothesize that if we knew whether a given user was a prepper or a backpacker, we could increase the site’s conversion rate by showing a custom experience, and more relevant products, to each. For example, buying in bulk could be good for preppers while backpackers will want to buy individual items, perhaps in more variety. 

The details of your personas will depend on your particular store.

A photo showing the eCommerce personalization that Mountain House uses for their advertising.

Two types of promo graphics on Mountain House’s site at the time of writing. (Top) Imagery and copy clearly focused on preparedness. (Bottom) Images on the packaging of backpackers and campers.

Once we finish creating our personas, the next step will be to think about the site behaviors that can indicate to us which persona an anonymous user belongs to. This will allow us to eventually cookie each user into a persona so we can later show them the proper personalized experience.

Step 2: Determine Characteristics and Site Behaviors That Indicate Which Persona a User May Belong To

Once we have the buckets from Step 1 we need to figure out what actions or behaviors can help us determine which persona new, anonymous, users belong to. 

Some examples of these actions include:

  • Viewing a category
  • Purchasing a product
  • Entering information into the website (i.e. searching for something)
  • Clicking on the navigation menu
  • Engaging with a module that helps narrow products
  • Subscribing to an email list to receive relevant content

We’ll start by finding some obvious actions. Continuing on with our hypothetical clothing eCommerce store from above, viewing men’s jeans or bras for example could be a clear and obvious site behavior that indicates which persona (men or women) an anonymous user belongs to. 

In some situations, finding a difference between personas is more difficult. Consider the yoga store example from earlier where we’re trying to differentiate between beginners and instructors. If there aren’t products or categories that clearly differentiate between the personas (both may buy yoga mats and clothing for example), one option is to use personalized content to help us differentiate. 

Two variable eCommerce personalization blog examples on Yoga Outlet.

Two content pieces on Yogaoutlet.com’s blog. The left, could apply to any persona, however the right likely applies to beginners or non-instructors. In contrast, a blog post on managing or growing a yoga studio, for example, would clearly appeal to instructors.

If a new, anonymous user site visitor signs up to receive basic yoga instructions, for instance, we could safely assume they belong in the beginner bucket. Likewise, you might have, or be able to write, content targeted specifically at instructors or more experienced yogis that will help you identify and personalize those user experiences. 

We have even been able to bucket an anonymous user by promising future personalized content in an email opt-in form. The act of offering this content can often convince a user to indicate their persona by allowing them to choose to receive relevant content.

Step 3: Track and Analyze Data to Confirm Actions That Will Bucket Users Into Personas

In Step 3, we’ll track and analyze the customer data we’ve been gathering and use it to figure out what actions are strongly indicative of an anonymous user’s persona. We’ll use these to actually personalize our site customer experience later on. 

How to Setup Custom Dimensions to Track Site Actions

In Google Analytics (GA), we can track user actions using custom dimensions. A dimension in GA is a characteristic of a user, session, or even hit (page view or event). Typical dimensions in GA include Page, Source/Medium, Device, etc. and are sent to GA as part of any page view or event. 

Some common dimensions in Google Analytics.

Custom dimensions are similarly not sent on their own, but must be sent as a parameter of another event or page view. For instance, if you wanted to log that someone viewed Men’s products in a custom dimension, you would have to either add the dimension to the page view of men’s product pages, or add an event to any clicks leading to men’s pages that would include the custom dimension. 

For more information on how this works, check out the GA Help Article on Custom Dimensions here

Once the dimension is in GA, you are then able to view reports based on whether someone has the dimension set or not, with separate line items for each value in the dimension.

For example, the image below shows a custom dimension with various “Product Color” values for a particular client. If we hypothesized that product color choice was indicative of a certain persona, we could use this data to help us bucket users into personas. 

Google Analytics Product Color Values for a client

So for example, in our men/women’s apparel store, clicking on a women’s category might trigger us to set a custom dimension identifying this user as a woman in the customer journey. 

In our yoga example, someone visiting an article on how to do beginner yoga poses might trigger us to set a dimension identifying this user as a novice, while someone visiting an article on mastering acroyoga moves might be pegged as an advanced user. 

Compare Stats from Different Custom Dimensions to Finalize the Criteria for Bucketing Users Into Personas

So what actions should we track that will hopefully indicate whether an anonymous user belongs to a given persona? 

This is a critical part of the process, and here’s how we typically do it. 

First, we think of some “anchor actions” that almost definitely indicate the user is in a given persona. These are the ones you’re sure of. For example, in our hypothetical apparel online store, it’d be something like adding women’s jeans to their shopping cart indicates they are interested in women’s apparel, and adding men’s jeans indicates they’re interested in men’s apparel.

But (and this is key) just having a few anchor actions is not enough because it’s very likely that a large fraction of your site traffic will never take that action. If you only have a small number of dimensions that lead to a user being bucketed into a persona but, say, 50% of your traffic never takes those actions, then your personalization effort just won’t apply to a large percentage of your traffic, which means all your effort in personalization may not be as impactful as it could be. 

So, second, you’ll want to liberally think of many other user actions that could also indicate a user should be bucketed into a given persona. Let’s call these “candidate actions”. These can be any of the action types we’ve been discussing so far: clicks on certain pages, adds items to cart, downloads a PDF, whatever you think could indicate a user belongs to a certain persona. Create custom dimensions for them in GA, as well. 

Third, let some time pass, ideally a few weeks to collect data in GA. 

Fourth, now compare how well the data from your candidate actions line up with your anchor actions. Basically you’ll assume the anchor actions are the source of truth for whether a user is in a specific persona. So each candidate action can be compared to the anchor actions to see, whether there’s overlap between users. 

Candidate Action + Anchor Action: Good Overlap vs Poor Overlap.

For example, let’s say you think downloads of certain content indicates a user is interested in women’s products. You’d compare and see, of the users who took this downloading action, what percentage also took the women’s anchor action vs. the men’s at various touchpoints with your site. If a decent fraction also took the men’s anchor action, your hypothesis that downloading this content indicated they were interested in women’s products is not likely to be true, so we’d discard this candidate action as not very telling of which persona a user belongs to. 

From a high level, our goal here is to pick a handful (3-5) of the most indicative and consistent criteria for accurate personalization without going into too much detail. Too many details can lead to conflicting signals and make personalization too complicated. At some point if we keep adding behaviors, we’ll either have to use an algorithm or manually choose a prioritization to follow. 

It’s important to note again that we still haven’t personalized anything on the site yet. Step 1, 2, and 3 are all about figuring out exactly who our personas are, how to bucket them, and what types of actions we can use to personalize our site and product recommendations.

Step 4: Personalize the Website

At this point we have clear buckets for our personas and we know what behaviors we can use to bucket a new user into each of them. Now we’re going to leverage the data we’ve gathered and finally set up the personalization for our site. 

This is the easy part! If you’ve done the first 3 steps well, a good marketer can easily identify tests/personalized recommendations that are likely to move the needle.

To do this, we’ll start building a list of hypothesis of custom experiences that we could show to the different personas that we think could increase their chances of converting.

  • Change homepage tiles to show products that appeal to one or the other
  • Prioritize navigation to show the categories most likely to convert or have a high AOV to one persona or the other
  • Change messaging and value proposition language in real-time on product pages around certain products (e.g. in our prepper vs. backpacker example, the same food could be positioned as “long lasting” (prepper) vs “light and delicious” (backpacker)
  • Show messaging around abandoned cart items on the homepage, in pop-ups or somewhere else on the site
  • Segment to a separate email newsletter to deliver more relevant email marketing campaigns to certain personas
  • Show a specific upsell on checkout, or somewhere else onsite so the right visitors see better related products (to increase average order value)

To actually execute on this, we’ll code simple Javascript cookies, which we deploy through Google Tag Manager, that essentially say: if a user takes one of the actions indicative of persona A, show them the personalized experience(s) we’ve come up with for that persona. 

Pro Tip: We recommend setting up these cookies as you do the research in Step 3 so that you already start building your cookied user list. That lets you start putting out personalized content much faster after you finalize your criteria. 

What If a User Takes Conflicting Actions

We should emphasize that it’s important to keep your final custom dimension list small to minimize the risk that users take conflicting actions (one action indicates they’re in Persona A, another indicates they are in Persona B). But if that happens, you can simply choose certain actions as “trump cards” that outweigh others. Alternatively you could also just not personalize the site for users who take conflicting actions. As long as you keep the action set small, this should only apply to a small percentage of your total traffic. 

Conclusion

We’re excited that this method of creating personalized eCommerce experiences involves no 3rd party software (besides GA, which so many online retailers use already) and offers lots of customizability. 

If you see how this could apply to your eCommerce brand, you can reach out to our CRO team here or leave a comment below. 

Why Content Quality Matters for Your eCommerce Website

Do you want to keep the traffic from search engines coming to your eCommerce website? Competing search results along with Google’s periodic updates can cause organic traffic and corresponding sales to go down: The image above shows the year-to-year difference in clicks for search queries on a “money page” that was getting traffic and driving

Do you want to keep the traffic from search engines coming to your eCommerce website?

Competing search results along with Google’s periodic updates can cause organic traffic and corresponding sales to go down:

Organic traffic took a big dip from August of 2018 to August of 2019.

The image above shows the year-to-year difference in clicks for search queries on a “money page” that was getting traffic and driving sales for one of our eCommerce clients.

Overall, this page took a 38% hit to the traffic it was getting from these queries in August 2019 compared to August 2018. Revenue from the products it linked to followed suit.

That’s why the questions we’re answering today are:

  • How do you keep valuable content assets driving traffic from search engines?
  • How do you recover if your content loses its search engine rankings?

In past posts, we’ve outlined:

In this post, we’ll outline how to help the best content on your eCommerce site continue to “sell while you sleep”… and what to do if things drop off.

Note: We specialize in helping eCommerce businesses to automate more of their sales through SEO, PPC, and CRO. If you want us to drive more traffic and sales to your store, get in touch.

Why Organic eCommerce Sales Drop When Traffic Drops

When your best content loses its search engine equity, so do the product pages that the content links to.

Those specific products, in turn, don’t pass on as much link equity to the additional products that they link to.

Search engine optimization (SEO) can often be a “survival of the fittest” of competing websites vying to rank at the top of Google for potentially valuable search queries.

At the same time, Google is always experimenting with new ways to feature the pages that they think are most relevant for a given search. We see them do this all the time.

To illustrate, Google used to look like this, with purely organic results:

Old Google search results for "how to make a volcano science experiment".

Today, here is what the top of the search engine results page for this query actually looks like with Google’s “rich snippets”:

Old Google search results for "how to make a volcano science experiment" (rich snippets are now included).

The organic results shown above are actually down on the page. This is because there is a larger variety of result-types Google is using in addition to the old-fashioned organic rankings. 

Including:

  • Featured Snippets (like recipes and step-by-step lists)
  • Knowledge panel
  • Local pack results
  • “People Also Ask” questions
  • Paid ads
  • Images
  • And Video content

One of our clients saw traffic drop several times due to Google’s updates like these.

Even though their strategic content maintained its organic rank at position 0 AND position 1 (the “top” of Google’s organic results), the traffic to their money page went down between August 2018 – August 2019.

Organic traffic took a big dip from August of 2018 to August of 2019.

Queries hidden.

Searching Query 1 in Google, we saw several things pushing their top-ranking strategic content further down:

  • A Google Ad for a product
  • A “People Also Ask” section
  • A video carousel section

These rich snippets dramatically reduced the number of people going to the client’s ranking content. This was correlated with lower revenue from the products that page links to.

While we have a general traffic drop checklist, how do we fix this specific situation of a traffic drop on quality content, and get more sales flowing back?

How to Help Your Best eCommerce Content Recover

There are three SEO remedies we recommend to reclaim valuable traffic that was lost due to a rankings drop like this:

#1: Reclaim Real Estate for the Page in the Search Engine Results Page (SERP)

To do this, improving the on-page SEO and technical SEO for the content and overall website can help Google rediscover their relevance. Sometimes, doing this can even land your content in place of the rich snippets that knocked yours down the page in the first place.

To help your content reclaim real estate in the SERPs and help the likelihood of it appearing as a rich result:

  1. Add schema markup to create structured data where possible, as it makes your existing search listings visually stand out more. This could include the following types of markup:
  • Local business
  • Site navigation
  • Logo
  • Q&A
  • How-to
  • Product
  • Rating & Review
  • Article
  • Author

…the list goes on!

Google is more likely to pick up on structured data and use it as a rich result. You can test a webpage for missing markup with Google Search Console’s Rich Results Test.

  1. Outside of using markup, claim space in the other new organic sections by optimizing your page’s content toward them.

To do this: Structure your content in a featured snippet or people also ask-“friendly” way.

This usually means being clear in your formatting by making the page structured with headers, bullet points, numbered lists, and clean/concise questions/answers.

Tip: To see what Google “likes” to feature:

  • Search Google for the keyword you are targeting with your content
  • Look at the rich results that come up and any questions in the “People Also Ask” box
  • Incorporate similar content to the page, such as a similar definition or a recipe that showed up as the rich result, and add a Q&A section comprised of the questions in the “People Also Ask” box. (Similar in terms of topic and length: not identical to the competitor’s content, as this opens up the possibility of a penalty.)

Improving your website’s quality through on-page and technical SEO can help maintain it against SEO traffic drops. We have several other guides to help with optimizing your eCommerce website’s content:

  1. Finally, if you can’t beat the organic content to reclaim your real estate organically: pay to beat the competition using Paid Ads.

PPC can help your website to reclaim real estate in the SERPs with more certainty than the above strategies.

However, this strategy depends on several variables (your business, the ad targets, and the competitive landscape) and it might not be viable if the competition can outspend you.

If the ROI is possible from Google Ads, then paying to reclaim the lost real estate is a viable option. Often, though, it’s hard to compete when other eCommerce brands can outspend yours for a term.

#2: Do a Better Job Linking to Products from Existing Content

In our experience, interlinking across your own site (or across multiple owned sites) is one of the most overlooked SEO activities.

Chances are, there are other pages on your site getting traffic.

Can you link to relevant products in your store from that other existing content that drives visitors?

#3: Create More Content That Links to More Products

Should your store start publishing strategic content? Yes.

We highly recommend consistent content creation to:

  1. Create additional assets that can engage potential customers in organic and paid audiences
  2. Help improve the domain authority (the overall quality in terms of SEO) of your website through additional links.

We often recommend adding copy to product descriptions on product pages as well as to category pages to help with their overall quality. That said, we also see their revenue suffer when the quality content that links to them does.

We’ve found that applying inbound marketing tactics for eCommerce companies including the creation of high-quality content at scale can drive revenue without direct sales from product and category pages.

Why eCommerce Stores Can Benefit from Creating More Quality Content

What is quality content?

In general, quality content means pages that meet their stated purpose and satisfy someone who finds them in a search engine.

When it comes to product and category pages, “quality” usually means adding more comprehensive, helpful detail to them. The best content for eCommerce websites in terms of quality typically aren’t your product and category pages because online stores tend to leave these pages undetailed.

We recommend starting with adding content to product and category pages such as additional copy, pictures, and videos) to make them really high quality.

After product and category pages are optimized, layer in quality “strategic content” (e.g. articles). When people in the SEO industry talk about “strategic content,” they really mean successful or effective content that achieves a goal. For example:

  • It drives traffic, links and engagement
  • Ranks in Google’s search engine
  • Creates desire for your product or services
  • And/or it leads people to key conversion pages (like a lead gen form or product/category page)

Internally, we refer to quality content as “strategic content” because it strategically meets one or more of these goals. There is also “big content” like comprehensive guides that we refer to as “cornerstone content” and “keystone content” because they are longer than an average article. 

We recommend creating both types as “big content” can be supported by smaller pieces of strategic content (for example: strategic content that drives people to the big content where they convert).

Quality content gets inbound links naturally in ways that products do not. Links are a huge data source for Google about what different websites and pages are about, and to what degree they are relevant to someone’s search query.

In our experience, one type of content that gets a lot of inbound links is “How-To” content.

Why “How-To” Content = Quality Content for eCommerce Websites

“How-To” content (usually an instructional guide, infographic, or video) teaches your target audience something they didn’t know related to your industry.

It’s best to create content that is directly related to your eCommerce business.

An online cookware store might post a video and/or recipe using ingredients or cookware that you sell. An auto parts website may have installation and use guides for specific parts.

This type of content provides the perfect opportunity to add internal links to your product and category pages: driving relevant traffic from that quality content to your product pages where they can convert.

Plus, by teaching your audience and helping to solve their problems (i.e. the questions they are searching in Google), you position your store as an authority on the topic and build lasting trust with your customers.

Conclusion

While many of the eCommerce brands we help tend to focus on paid marketing, the most profitable stores we see often grow with the complementary combination of paid media and search engine optimization.

SEO doesn’t just help to drive more traffic to your products through internal linking. Google evaluates content quality for their ads. Adding and optimizing targeted content on eCommerce websites can help the conversion rate and efficiency of PPC like Google Ads.

We know that eCommerce content marketing can be a large task. We would welcome the opportunity to apply our eCommerce marketing expertise toward growth-focused content creation, copywriting, and SEO for your online store.

If you want to direct more people to your products or services, and help preserve your website’s discoverability against competitors and Google updates, please get in touch.

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.

Background:

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).

Takeaways

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

Results

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.

Conclusion

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.

SEO Mistakes: 6 Weird Errors That Can Hurt eCommerce Store Rankings and Traffic

Even our experts were confounded by these 6 eCommerce SEO errors. Avoid these mistakes for your online store.

eCommerce marketers know that when search engine optimization (SEO) errors occur, search volume goes down. This means that fewer visitors will arrive to your online store and enter your sales funnel.

If an error goes unresolved for too long, this opens up the possibility of it then causing additional errors that lead Google to bury the site’s webpages under many other search results in the search engine results pages (SERPs).

Most content about SEO mistakes references the same commonly made errors:

Common SEO Mistakes

  • Keyword stuffing
  • Over-optimized anchor text
  • Low-quality content
  • Link building too fast
  • Too many low quality backlinks rather than high-quality
  • Duplicate content
  • Unoptimized page titles and meta descriptions
  • Broken Links
  • Slow site speed
  • Site is not optimized for mobile devices

The list goes on, and these are HUGELY common problems that large enterprise sites deal with. Most of the time, you can monitor for these errors without an external SEO expert consulting.

Sometimes, though, a strange technical error can occur that results in one of these other errors, but you won’t know that it’s happening. Why? Because the original error can be hard to detect. For example, we often see problems created by website redesign mistakes that destroy SEO.

After years in auditing hundreds of online stores, we’ve seen that these common SEO errors tend to repeat themselves. Sometimes, though, we only find the uncommon “oddball” errors after running a technical SEO audit.

In our experience, it’s vital to follow a technical QA process to periodically audit eCommerce websites (which tend to have a large volume of pages compared to other sites). 

Adding a QA process to your SEO strategy will help you to avoid both common and uncommon SEO errors that could have an impact on your search rankings, traffic, and thus your bottom line. A technical audit is especially important after doing a redesign or eCommerce platform migration.

Below we’ll show you 6 uncommon SEO errors we’ve encountered that not many people know or think about. They’re lesser-known, but they could potentially happen to any enterprise retail site.

If you have seen SEO performance lag on your own site recently and aren’t sure why, running a technical audit can help catch weird errors like these and prevent one error leading to more.

Note: We audit sites all the time and it’s how we catch any errors that could make a big negative impact. Get in touch to see how we can make sure your eCommerce website’s SEO is completely optimized for maximum growth.

SEO mistakes: a photo of a magnifying glass and a Google search bar.

SEO Error #1: A Corruptive App or Plugin Added to the Site Has Unintended Consequences

The Problem: One of our clients, a pool supply store, added an app (added as a plugin) to their site. This app was intended to make the site mobile optimized and responsive. To do this, the app added a meta robots tag to the mobile templates which unintentionally blocked Google from indexing them. 

This was somewhat odd in that the eCommerce platform the client used was already mobile responsive. The client had added it for aesthetic reasons, and they used the plugin to style mobile pages to their liking.

Meanwhile, the plugin didn’t add that meta robots tag to the desktop pages, so those were indexed. 

Google Search Console alerted us as to the issue, but not the cause. We were scratching our heads at the beginning. We didn’t know it was this app that was causing it. (Imagine not knowing the reason why all of your site’s pages aren’t getting indexed all of a sudden!)

Normal crawls (using default, desktop settings) looked fine across multiple tools, but Google Search Console didn’t consider the issue resolved, and neither did the Structured Markup Testing Tool (which we use to view Googlebot rendered code.)

Given the world of mobile-first SEO, all pages (mobile and desktop) were deindexed until the source of the issue was discovered in the mobile template and our client took our recommendation to remove the app.

To solve: From this issue, we found that changing the user agent of the standard crawl to a mobile crawler instead of the desktop one was how you could find this issue if it occurred again. We recommend crawling the site in both modes to identify discrepancies.

There are other ways apps can break SEO. These issues might include:

  • Security concerns
  • Page load issues
  • Deindexing images
  • Inflating crawlable URL count
  • Automated dynamic parameters (such as automatic URL changes)

Takeaway: Plugins gone wrong can be BAD in many different ways. When adding new software to your website, do multiple crawls afterward, including a crawl where the user agent is a mobile bot in order to check for any issues on mobile pages. Since not all bugs are found via a crawl, an SEO QA process will also help you to discover them.

SEO Error #2: A Server is Delivering the Staging Environment Instead of the Live Site

On a major craft supplies ecommerce store, Googlebot was blocked from the site via the robots.txt file, according to Google Search Console. 

A visual view of the robots.txt rendered a normal .txt, though the robots.txt testing tool in GSC displayed the text of the file as a rule instructing Google to block all crawlers but AdsBot crawlers:

User-Agent: *

Disallow: /

As a large online retailer, this client used 8 load balancing servers for their website. One out of those 8 servers was delivering the stage environment version of the robots.txt file. This stage environment was blocking everything that was on the live production environment. Google just happened to access the site on the wrong server one day.

To solve: The Robots.txt was fixed, and we recommended rules to put in place to ensure it was crawlable and the error couldn’t happen again.

Takeaway: Google can access a site through any server they aren’t blocked on, so all servers need to be consistently the same. Keep track of any discrepancies that might exist between multiple servers that you are using, and any SEO errors Google reports to you. When your website uses multiple servers, Google may crawl one as a point of reference rather than observe all of them. If that one server has an error, it doesn’t matter if the rest are correct.

SEO Error #3: Your Site is Triggering Dynamic URL Changes 

In January 2019, we noticed that most of the URLs in the main navigation menu of a client’s site in the home renovation / building materials niche was redirecting. The category page URLs (like from /category-66/ to /category-70/) kept changing with a new number every day.

We looked at Google Search Console and found there were many variations like this that all redirected to the newest version. We asked them if they knew what was happening and they told us that their site has been changing URLs every day.

The website did this for about 90 days before the client finally fixed it. Unfortunately, this was a bit too long for the error to go on. As a result, the site took a big hit in traffic because of it.

This story doesn’t end tragically, though. Their site recovered once we found the problem and gave a recommendation on how to fix it.

To solve: To fix the issue, their dev team stopped pages from being created every day and 301 redirected all variations to the correct page without the number in the URL /category.

Takeaway: Watch out for dynamic URL changes on your website. If a certain platform or setting is causing them to change, it can be very detrimental to your traffic.

SEO Error #4: You’re on a Bad eCommerce Platform

Picking the right eCommerce platform for your store is vital. Some platforms are better for SEO than others. On a client site in the grocery/foods niche, we’ve seen that the platform they use repeatedly causes all sorts of technical errors without the client’s knowledge.

The platform made seemingly random updates that consistently messed things up. For example:

  1. There have been several occasions where the platform accidentally made a site they were using to test updates indexable, even after we asked them to make it non-indexable. The problem with this is that it creates a duplicate content error and can lead customers to pages that don’t have working checkouts before launching them on the main website.

  2. The platform made the canonical tag on every page of the client’s blog point to a non-existent page, which caused a 404 error. We have no idea how this happened. We just happened to notice it the day after it happened, and thankfully, caught it quickly.

To solve: If errors like this pop up frequently, it may be best to consider migrating to a better eCommerce platform that doesn’t undermine your control over certain settings.

Takeaway: Make sure that your SEO team is monitoring for these sorts of things regularly. We use a technical audit as part of our QA process (which is how we catch these things).

SEO Error #5: Part of Your Site is on a Separate (Unsecured) Platform

This same client in the grocery / foods niche who had problems with their eCommerce platform also had big problems with their blog platform.

Some sites choose to host their store on an eCommerce platform like BigCommerce or Magento, and their blog on a CMS like WordPress.

This method sounds good, in theory, by having the best of both worlds: a specialized eCommerce platform to host the store and a specialized blog platform to host the blog. However, in this case, the store and blog platforms were hosted on the same server, and the WordPress blog was not secure.

Unfortunately, a major hack occurred. As a result of hosting the blog on the same server as the eCommerce platform, the server the store was hosted on got accessed by the hacker.

To solve: The recommendation to solve this would be to use only one platform, and only the blog that comes with that platform (if it has a blog feature—in this client’s case, the platform doesn’t, so that’s why they used WordPress). If you need a separate platform, keep the blog on a totally different server to keep your main one protected. This client had to move the blog to a subdomain—blog.client.com.

Takeaway: Need we say it? Make sure every part of your website is secure to ensure hackers stay out. This means if you are hosting different parts of your site on different platforms, all of those areas of the site need to be secured. If you use WordPress, make sure the installation is secure, up to date, and that you are using other security plugins.

Additionally, Google weighs whether a site is secure or not as a ranking factor. They don’t want to send people to an unsafe site (an unsafe URL beginning with HTTP vs a secure site’s URL beginning with HTTPS).

SEO Error #6: Not Fixing SEO Mistakes Quickly Enough

Remember our client in the home renovation / building materials niche that had URLs changing to a different number every day? This large online retailer had some additional problems.

The initial problem now was a common one: thin, low-quality content. Their internal search result URLs were getting indexed by Google (thin pages that only showed search results and no content, etc.) and we were trying to clean it up.

To solve the thin content error: we recommended adding a canonical tag to the internal search result URLs that pointed back to a main search result page.

This created a new problem due to another error that was present: The main search page canonicalized all of those internal search URLs to have a noindex tag.

To solve this additional problem, we asked them to remove the noindex tag right away, but it took a long time for that to happen on their end (remember: we recommend fixing SEO errors as soon as possible to avoid them being noticed by Google).

The longer all of these URLs canonicalized to a page with a noindex tag on it, the more their indexation numbers climbed. Google started ignoring canonical tags and indexing a ton of low-quality URLs (the original problem we had been trying to solve).

As a result of waiting so long to fix it, another new problem was created:

Once the noindex tag was removed from the main search page to fix the low quality URLs being indexed, there was an even larger number of them indexed.

To solve THIS, we had them change the internal search URLs from having a canonical tag to instead having a noindex tag. This was to simply stop their being indexed by Google and hopefully fix the situation more quickly.

Finally, those low quality URLs started to come out of the index fairly quickly.

The bottom line here is: When you find an SEO error, whether uncommon or not, take care of it quickly, or you’ll find new ones popping up!

Conclusion

These examples illustrate that SEO errors can come from a variety of sources.

Make sure to use a technical QA checklist that can catch these things as they happen in any number of ways as part of your search marketing strategy. (Here are some of our main technical SEO checks).

We know that technical SEO can be intimidating. As experts in eCommerce SEO, we’ve dealt with the unique SEO situations that come from different eCommerce platforms.

Clients who work with us not only get any errors present on their site removed by our expert eCommerce SEO consultants, we also optimize the site further to drive more organic sales from search engines.

Does it seem like your site’s SEO could be doing better? We run SEO for hundreds of eCommerce Sites and we’re ready to get to work on yours. Get started now.