Shopify Plus vs Magento 2 Commerce (Magento Enterprise): Which Platform is Best for Your eCommerce Business?

This in-depth comparison between Shopify Plus and Magento 2 Commerce will clarify when to use each platform.

Shopify Plus and Magento 2 Commerce are two of the most popular eCommerce platforms for mid-market and enterprise-level online retailers. This post outlines their differences to make it easy to see what each platform offers for large and fast-growing stores.

While there are other great comparisons of Shopify Plus and Magento Commerce written, many of the ones we found were written by partners or affiliates of the platforms, and may be biased. 

(Full disclosure: At Inflow, we are a Shopify Partner, but this does not extend to Shopify Plus, which is a separate platform and a separate partnership.)

In writing this comparison, we sent a query out asking eCommerce business owners and consultants when they would choose one platform or the other.

Their answers revealed that, rather than one being “better” than the other, Shopify Plus and Magento 2 Commerce both have specific advantages.

According to nearly everyone we spoke to, how complex your store’s requirements are is what should drive the decision. If the initial answer is “simple,” Shopify Plus may be better. If your store’s needs are complex: Magento 2 Commerce is likely the way to go.

A significant number of the eCommerce brands we work with choose to host their stores on Magento 2 Commerce and Shopify Plus. We’ve also assisted clients in performing site migrations to one platform or the other.

Below, we’ll first break down the basic differences between Shopify Plus and Magento 2 Commerce. Then, we’ll zoom in a bit further on their most important aspects for retailers to see if they match your store’s requirements.

Let’s get started.

Note: Are you looking to move to an enterprise eCommerce platform? Schedule a talk with us today to get our recommendations on the right platform for your brand, help migrating to it, and/or optimizing for growth.

Shopify Plus vs Magento Commerce: Overview

To start, here is a summary of useful information about each platform:

Comparison table of Shopify Plus and Magento 2

Shopify Plus Overview

While it’s inarguably an enterprise platform, in many ways, Shopify Plus is geared toward existing Shopify stores that are ready to scale further.

Shopify’s own brand began by servicing smaller retailers. They have since grown quite a bit —  and so have the growth stages they service.

As a result, Shopify Plus is the iteration of Shopify geared toward mid-level and enterprise-level companies. Compared to Shopify, the “Plus” adds:

  • More apps, advanced features, and customization including a customized, responsive checkout.
  • More customer support from Dedicated Shopify Plus Account Managers and Launch Managers.
  • Flat pricing of $2,000 per month for retailers with less than $9.6m in yearly sales.

Shopify Plus’ offering differs from Magento’s because:

  • Shopify Plus is available as fully-hosted only while Magento has both hosted and non-hosted options.
  • Offers 24/7 managed account support that includes minor front-end development.
  • It requires far less backend development compared to Magento.

Overall: Shopify Plus is the more user-friendly version of an enterprise-level eCommerce platform. Smaller eCommerce teams whose needs require them to focus on product and marketing over pouring resources into development will likely prefer Shopify Plus.

Magento Commerce (Formerly Magento Enterprise)

Magento is its own software and service ecosystem that was acquired by Adobe in 2018. It comes in a few different flavors to cover businesses of all sizes and needs:

  • Magento Open Source (formerly Community Edition or “CE”)

There is a large community of Magento developers out there as a result of Magento’s continual free download of their core software. This is for businesses with advanced development capabilities on their end who don’t require support or hosting from Magento.

  • Magento Commerce (formerly Magento Enterprise/Enterprise Edition or “EE”)

In this article, we will be referring to Magento Commerce throughout. Unlike Magento Open Source, Magento Commerce comes with a license fee as well as support and other resources from Magento. There is also a hosted version branded as Magento Commerce Cloud that is folded into the Adobe Experience Cloud.

Compared to Shopify Plus, Magento Commerce’s offering is different because:

  • You can use Magento Commerce as a fully-hosted or externally-hosted platform
  • Magento Commerce is much more customizable than Shopify Plus
  • Magento Commerce is more apt for large product catalogs, product variations and attributes, and multi-store management.

Overall: Magento is geared toward businesses that can devote more time and resources toward the development and maintenance of their store. The tradeoff here is a wider range of capabilities with more work, cost, and often a longer development timeline.

Shopify Plus vs Magento Pricing Comparison

Right off the bat, we can see that each platform is better-suited toward different growth stages, applications, and product catalog sizes. As a result, their pricing varies considerably.

According to Kathryn Valentine, a business consultant to apparel companies, “Shopify is the Honda; Magento is the Ferrari.”

Valentine told us that smaller companies (under $25M, even $50M) will find the maintenance of a Magento site more time-consuming and expensive than their organization and budget are built for. That makes Shopify Plus the best option for start-ups and high growth businesses under ~$25M, and Magento the winner over $100M.

Companies in between these sizes will need to assess how important their DTC business is and if they are ready to make the investment in site maintenance.

Shopify Plus Costs

In general, Shopify’s pricing tends to be less expensive and thus better-suited to mid-stage growth periods.

  • License Fee: The monthly license cost is $2k plus .25% of average revenue after your store reaches $800K in revenue. The maximum monthly fee is capped at $40k.
  • Transaction Fees: Shopify Plus is not transparent on their pricing, but we have seen transaction fees reported of 1.6% + 0.35 and 2.15% + $0.30 per transaction (as of December 2019). Shopify Payments is the default processor, but if you use a third-party payment provider, there’s an additional 0.15% transaction fee on top.
  • Hosting: Hosting is included under Shopify Plus’ $2000/mo license fee as an optimized package. It also includes upgrades and maintenance, security and SSL certificates, payment card industry (PCI) compliance, and technical support.
  • Migration and Build Costs: These will vary, but they will generally cost less than a Magento migration or website build. Typically, a Shopify Plus site build will be a mid-five-figure cost and typically stays under $100k.

Magento Commerce Costs

The total cost of a website built with Magento will likely be more expensive because more development is usually needed. This means it’s well-suited to companies who want a lot of backend functionality.

  • License Fee: Unlike Shopify’s monthly + transaction and revenue fees pricing model, Magento’s license is an annual up-front fee based on merchants’ Gross Merchandise Value (GMV) and company size. As a result, the pricing for Magento varies a lot. Licensing starts at about $22k per year.
  • Transaction Fees: In contrast to Shopify Plus, Magento’s model is based on giving retailers ownership of all their own operations. The only transaction fees are those run by the processor you choose. With Magento, you can set up your own external payment gateway as well.
  • Hosting: You can host Magento on any server you choose. If you opt to host on Magento 2 Commerce Cloud, this includes both the Magento license and hosting. Pricing is not transparent, but the base cost of Magento 2 Commerce Cloud is around $3,333 according to eCommerce Guide — this linked article (written by two experienced platform consultants) has a very detailed breakdown of potential costs that both Shopify Plus and Magento 2 Commerce can incur.
  • Migration, Build, and Maintenance: As a general guideline, expect a $100k cost to a Magento 2 Commerce migration or build. Maintenance with Magento Commerce is an ongoing thing. You’ll likely pay a Magento developer on retainer to take care of what Shopify Plus folds into their license fee: patches, upgrades, module installations, and other maintenance needs. This will usually cost in the low-to-mid 4 figure range per month, but can go up to 5 figures per month for complex stores.

Now, let’s take a look at what these different pricing models gets you in terms of the platforms themselves.

User-Friendliness and Support

Shopify Plus

Built Primarily for Non-Devs

The basic version of Shopify is already designed to be user-friendly for busy eCommerce owners. Thus, it requires less development work in comparison to most other basic platforms.

Shopify Plus retains this principle, but adjusts them to enterprise-level needs by adding:

  • More API integrations
  • Access to theme code
  • Exclusive apps
  • Analytics reports

Shopify was designed for eCommerce businesses that are just getting started. Shopify Plus presents a similar solution that retains much of the core usability that people upgrading from Shopify to Plus are used to. Plus, more robust support and features.

Magento 2 Commerce

Built for Developers and Advanced Customization
Magento has some experience under its belt, but its users have to also. This isn’t a basic, user-friendly experience, which is fine for those more familiar with developmental coding.

In addition to the advanced features Magento provides out of the box, it can also be customized to suit specific needs. The tradeoff is that retailers running Magento Commerce typically have a dedicated development team to build additional features.

Overall, it’s a decent choice if you’re already skilled at developing. Magento can provide a more customized, luxury shopping experience, but requires much more time, effort and money to maintain.

Features

We want to make this simple for you to parse through.

Below, are what we see as the core feature differences to bear in mind when selecting between Shopify Plus and Magento 2 Commerce.

Shopify Plus

Shopify Plus adds:

  • Dedicated Shopify Plus account managers
  • Unlimited staff accounts
  • Wholesale channels
  • A Facebook community and Partners directory
  • A multi-store dashboard
  • Access to Shopify’s Liquid theme language for code-level changes
  • Shopify Scripts editor which allows you to customize checkout
  • Shopify Flow (Shopify’s eCommerce automation platform, which uses a visual builder)
  • Shopify Launchpad — a tool to automate sales campaigns and product launches
  • Bulk customer data import tools.

Compared to Magento, Shopify Plus has features that make it a lot more frictionless to get a store up and running.

Magento 2 Commerce

That said, compared to Shopify, Magento makes it easier to manage complexities such as:

  • Multiple brands
  • Multiple vendors
  • Stores across multiple countries
  • Promotions and discounts using a built-in promotions engine
  • Bigger product catalogs with complex attribute combinations
  • Different product types (Magento supports 7 core product types while Shopify has 2)
  • Native handling of product bundles and product attributes
  • International currencies and global shipping

In other words, if you have thousands of products and potential combinations of attributes, Magento is a clear winner. If you’re launching products in multiple stores, in multiple countries, with multiple promotions, currencies, and languages: Magento is way better for that than Shopify Plus.

Scalability

Scaling needs differ between different retailers. Are you scaling primarily for more traffic and sales? For more products, marketplaces, or vendors? Or for a combination?

Shopify Plus

Shopify Plus is a great choice when “scalability” translates to readiness for more traffic and orders.

Shopify Plus’ platform and hosting is designed with scalability in mind, thinking about the fluctuation of traffic and transactions for eCommerce. This is one of the main advantages of the platform.

The casual developer doesn’t have to worry about infrastructure and can focus on strategy instead without wondering if performance will suffer for it thanks to Shopify Plus’ fully-hosted platform.

While your store is on Shopify’s servers rather than your own, those servers will be ready for whatever comes.

Magento

When scaling your business means scaling products and marketplaces along with traffic and transactions — Magento Commerce is the better choice.

In terms of server capabilities, Magento Commerce Cloud is comparably prepared for volume fluctuations to Shopify Plus’ servers. If you are hosting Magento Commerce yourself, you’ll need to prepare for fluctuations accordingly.

As the running theme here has been: it’s going to take more work on your end if you want to use Magento Commerce, but you’ll be able to do a lot more in terms of managing your online retail empire.

Multiple Brand and Multiple Store Management

Magento allows you to manage multiple stores from one interface, while Shopify Plus involves managing multiple stores as their own entities under the same account. In terms of capability and cost: Shopify Plus can’t really stack up to Magento’s multi-store architecture.

For example, Magento’s dashboard allows you to set product attributes like name and price at store and global levels. You’ll need to find a workaround to do this with Shopify Plus and this will likely be a plugin that adds to the monthly cost.

Additionally, Shopify charges for the gross merchandising volume (GMV) of each additional store. So that additional cut of revenue to Shopify needs to be factored in when planning an expansion; not so with Magento.

Extensions and Apps

Both platforms have a dedicated marketplace of apps and extensions that add functionality, visual changes, and other options to your store.

Shopify Plus

As a SaaS offering, Shopify Plus has an ecosystem of third-party apps that require their own separate licenses. When comparing the native functionality of apps and extensions, users often report more and better functionality with Magento’s extensions.

You will need to weigh the costs of additional licenses with Shopify Plus to enabling that same functionality on Magento Commerce with a developer or a matching extension.

There are a lot of apps that provide services that aren’t found natively in Shopify, such as Recharge, which provides monthly billing for subscription businesses. However, users tend to prefer Magento’s native subscription billing over Shopify’s.

Magento 2 Commerce

Magento has its own robust marketplace for extensions (and services). These allow for functionality that you simply can’t do in Shopify Plus.

For example, with certain Magento extensions you can:

  • Turn your Magento store into a multi-vendor marketplace. (Meaning: vendors can upload their products to your store and manage orders on its front end through individual portals.)
  • Add more robust customer support functionality
  • Enable accounting and finance within the platform
  • Enable custom shipping and fulfillment solutions natively

In other words, there’s a lot more you can do with Magento compared to Shopify Plus — but those capabilities should be needs for your business.

Summary and Conclusion

Shopify Plus vs Magento 2

When to Choose Shopify Plus

Shopify Plus is the option for those newer to the eCommerce web-developing world, or who want to be a little more hands-on in customizing their website without extensive developer knowledge. Shopify Plus is easy to use, affordable, and very difficult to break.

For retailers willing to work within the features provided directly by Shopify or provided by Shopify Apps, Shopify is a great choice. You can work with an agency and build a great looking storefront quickly and focus more of your time on customer experience, demand generation, and retention.

You don’t need to place as much time and resources into development and hosting with Shopify Plus as you do with Magento Commerce. If your needs are not that complex and you prefer to focus on product and marketing, Shopify Plus is likely the right solution.

When to Choose Magento Commerce

Magento’s advantages over Shopify Plus were summed up nicely by John Moss of English Blinds, one of the eCommerce CEO’s we heard from:

“For us, the multi-store, language, and payment method options that are possible under Magento Commerce but not Shopify Plus was the clincher that saw us decide in favor of Magento Commerce. Shopify Plus’s multiple instances of ‘equivalent’ features just don’t offer the same level of functionality,” he said

“Unlimited product variants in Magento Commerce with a cap of 100 product variants in Shopify Plus is something else to bear in mind if you keep a large inventory,” he continued. “Magento Commerce is also much more flexible in terms of integration platforms while Shopify Plus only works with Shopify’s own API integrations, which might well be sufficient for many, but was a downside for us and limited our potential future scalability.

“Finally,” he said, “Magneto Commerce’s option for open-source code versus Shopify Plus’ proprietary alternative was the icing on the cake. Again, this might not be an issue or something most businesses will need, but having the option allows for superior flexibility and future growth.”

In other words: If flexibility and control over your website’s development are important, Magento 2 Commerce is the clear winner.

Are you planning a move from your current eCommerce website to a more robust platform like the ones discussed here? While we have written about some of the complexities in migrating ecommerce platforms, we strongly encourage you to chat with us before starting the process.

Talk to one of our enterprise eCommerce experts today by clicking here or filling the form below.

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. 

12 Cognitive Biases E-commerce Marketers Need to Know

Understand how customer brains work – these are the most important cognitive biases for e-commerce marketers.
The post 12 Cognitive Biases E-commerce Marketers Need to Know appeared first on Neuromarketing.

12-cognitive-biases

Understand how customer brains work - these are the most important cognitive biases for e-commerce marketers.

The post 12 Cognitive Biases E-commerce Marketers Need to Know appeared first on Neuromarketing.

What Can You Learn From Running an A/B Test for 2 Years?

We just concluded an A/B test on Analytics-Toolkit.com that has been left to run for just over 2 years. And it failed, as in failing to demonstrate a statistically significant effect based on the significance threshold it was designed for. Has it been …

We just concluded an A/B test on Analytics-Toolkit.com that has been left to run for just over 2 years. And it failed, as in failing to demonstrate a statistically significant effect based on the significance threshold it was designed for. Has it been a waste of time, though, or can we actually learn something from […] Read More...

The 5 Worst eCommerce A/B Testing Mistakes to Watch out for 

Make sure your eCommerce A/B Testing results are 100% accurate with our checklist!

Do you want to use A/B testing to increase the conversion rate on your eCommerce site?

Before you start running one of those tests, it’s a good idea to make sure that you set it up correctly.

A rigorously-run test can increase conversions, but if the parameters are flawed then the decisions you make based on the test could be too.

In this post, we’ll outline the worst eCommerce A/B testing errors that we see online stores make. Use this as a reference to make sure that any A/B testing you do returns accurate results. That way you can make better data-driven decisions that actually increase conversions.

Note: Want our CRO experts to do A/B testing to increase the conversion rate for your eCommerce business? Learn more about our services and get in touch.

What Are the Worst eCommerce A/B Testing Errors?

We’ve written in the past about the most common reasons A/B tests don’t perform well. Namely:

Here, we’re outlining the worst technical errors that can invalidate your results. These are:

  • Technical issues with the actual test
  • Making site changes during the test
  • Traffic source changes
  • Conflicting tests
  • Not accounting for user and site-specific factors

If you are going to put time into doing A/B testing to improve your site, it’s important to take the specific things about your site into account.

These are the 5 eCommerce A/B testing mistakes to avoid (beyond just setting up your analytics goals) that we commonly see while helping our clients with their conversion optimization.

#1. Technical A/B Testing Issues

Here are the things to consider when setting up an A/B test (whether you’re using Optimizely, VWO, or another platform) to make sure it yields valid and actionable results.

Didn’t Exclude Return Visitors

If people are experiencing 2 different versions of your eCommerce website, a test will be invalid. We often see this issue happen with returning visitors after a site changes their design, layout, or other elements.

A ‘Negative Response’ is the possible outcome created when return visitors to the site see the new treatment and are now lost (i.e. navigation change) or confused (i.e. page layout test). The user now has expectations about the site that we might not be meeting with the new treatmenteven if it is better.

For instance: Below is a familiar pattern we see when the test variation (purple) overtakes the control (green). This often happens when a site’s returning visitors are allowed into the test. These returning visitors prefer the control because it has a “continuity of experience” (it’s the version they’re used to).

This results in making the variation appear to perform poorly until the initial group of returning visitors exit the test. In the test below, it took roughly 12 days for this returning visitor bias to abate. 

Many tests do not run long enough (see below). If returning visitors are excluded, the true result—a big win—will never be seen. Even worse, you may end up implementing a losing variant and harming sales.

Note: For businesses with loyal client bases who need to know how a treatment will impact their existing users, you can remove returning visitors from the data after the fact.

Didn’t Run a Test Long Enough

One of the most common ways we see eCommerce businesses run tests improperly is not giving them a chance to run for long enough. The reasons for this vary from not knowing better to succumbing to the pressure to get results quickly.

Whatever the reason, not running a test long enough will rob you of the truth, so you might as well have not run the test in the first place.

We’ll revisit how long to run these tests in a moment.

Run a Test with Enough Participants and Goal Completions

The more variations a test has, the more participants it will need. Your sample size needs to be large enough to demonstrate user behavior.

Consider 100 conversions per variation to be a minimum, and only after the test has run long enough (see above) and other criteria has been met (see below)

Don’t Turn Off Variations While Testing

Turning off a variation can skew results, making them untrustworthy. 

For instance: Let’s say you have four total variations (three treatments and the control). Each variation receives 25 percent of traffic. After 10 days, one treatment is turned off and from that point on, each variation receives 33 percent of traffic. Then you again turn off another variation, leaving each remaining variation with 50 percent of the traffic. 

The example below shows how when the green variation was turned off, the control improved, just like it did at the start of the test when it benefitted from some people buying right away (the control was for a free shipping offer):

The control again lifts off when the pink variation is turned off showing the control (orange) improve for a third time when the mix of new and returning visitors shifts to include more new visitors. The variation (this time the control) disproportionately benefits since it does well at converting the first time buyers who saw the free shipping offer.

This graph would look very different if the control never saw those three bumps in conversion rate. Because the control is the baseline variation, the result of the winner (blue variation) would be more clear and confident, and the test would not have had to run so long. 

The above scenario is extremely common, and at a surface level seems benign, however, the reality is that the differences in the variations themselves may create a case where the test is corrupted by changing the weight of the remaining variations. 

Often a variation is favored by different types of buyer mindsets, such as a spontaneous shopper vs an analytical one. If one variation is preferred over the other, changing the weight of the remaining variations will result in the variation favored by spontaneous people to suddenly improve. The other variations, favored by more analytical people, will not see as much improvement until their buying cycle has concluded, perhaps days or weeks later. 

Since we never know who likes a variation for what reason (Was it the hero image? The testimonials? Product page? Overall user experience?) the safest thing to do is not to eliminate any variations. 

Custom Code vs. Test Design Editors

After trying to set up a few tests via any test design editor, you may find that the test treatments do not render or behave as you expected across all browser/device combinations. 

While design editors hold great promise for “anyone” to be able to set up a test, the reality is there is only a narrow range of test types (i.e. text-only changes) that can be done through a test design editor alone. Custom code is required to have it work well and consistently across browser types and versions.

The best practice is to write custom code because most modern websites have dynamic elements that visual editors can’t identify properly. Here are some specific cases that visual editors can’t detect: 

  • Web page elements that are inserted or modified after the page has been loaded, such as some shopping cart buttons, button color, Facebook like buttons, Facebook fan boxes and security seals like McAfee
  • Page elements that change with user interaction, such as shopping cart row changes when users add or remove elements, reviews, carousels, and page comments. 
  • Responsive websites that have duplicated elements, such as sites with multiple headers (desktop header is hidden for mobile devices and mobile header is hidden for desktop computers). 

In the beginning, you may be able to avoid running complex tests that require custom code. Eventually, you will graduate to a level of testing that demands it. Know that this requires a front-end developer to set up the tests that you will want to run. 

Run the Test at 100% Traffic

Today, many purchases online involve more than one device or one browser (i.e. researching on a smartphone, then purchasing on a laptop).

However, test tools are limited to tracking a user on a single browser/device combination. This means that someone who sees one variation of a test on mobile may come back to purchase on desktop and be provided another variation.

Showing a variation more often than another will give it the advantage since it is more likely to be seen with continuity by users who switch from device or browser. This is called “continuity bias.”

To avoid continuity bias during the testing process, we recommend you run tests at 100 percent of traffic and split that traffic evenly between variations.

When less than 100 percent of traffic is sampled for a test, the result (in today’s cross-device world) is that the control will be served more often than the variations, thus giving it the advantage.

For instance: A user visits your site from work and is not included in a test because you are only allowing 50 percent of people to participate. Then, that same user goes home later in the buying cycle and gets included in the test on their home computer. The user is then more likely to favor the control due to continuity bias.

Side note: This may be a good time to look at your past results of tests that were run with less than 100 percent of user participation and see if the Control won more than its fair (or expected) share of tests. 

Equal Weighting of Variations

For the same reasons as mentioned above with running a test at 100 percent, you also want to ensure that all variations are equally weighted (i.e. testing four variations including the control should see 25 percent of traffic go to each). If the weights are not equal there is a bias—as outlined above.

Test Targeting

Test results are easily diluted (test will have to run longer) or contaminated by not targeting the test to the right audience. The most common issues of inappropriate test targeting are:

  1. Geo (i.e. including international visitors in a test that is USA specific)
  2. Device (i.e. including tablets in a mobile phone test)
  3. Cross-Category Creep (i.e. test for Flip Flops spreads into all Sandal pages)
  4. Acquisition vs. Retention (i.e. including repeat customer in a test for first-time customers)

If the right audience and pages are not targeted, then it will take much longer to see any significant results with confidence due to the noise of users who don’t care either way. That test result will indicate that the change is not significant, leaving you to stop the test and not gain the additional sales.

These are the most common technical reasons we see invalid tests. There are some other good habits we recommend though.

#2. NO eCommerce Site Changes During Testing

As a general rule: Avoid making other site changes during the test period.

This will cause you to see a statistical result from the test without knowing what to attribute it to.

We often see eCommerce stores that launch a website redesign while they are in an active test period which causes issues.

For instance: If you are testing a trust element like McAfee’s trust seal, avoid changes that may impact the trust of the site, including:

  • Site style changes
  • Other trust seals
  • Header elements (like contact or shipping information
  • Or any other site-wide “assurance” elements (i.e. chat)

The same line of thinking applies to other changes. If you are testing a pop-up window, don’t make a change to the site style, other opt-in boxes, etc.

When split testing, it’s usually best to test one element at a time. Making site changes during a test makes that ideal a lot less feasible.

#3. Traffic Sources Change and Muddy Conversion Data

In our experience, the different sources of traffic to your website will behave differently.

When there is a change in the distribution of traffic sources (i.e. paid search increases), test results will be unreliable until the test participants brought in have had a chance to go through their entire buying cycle. 

For instance: Paid search visitors may be less trusting and less sophisticated when it comes to the web. This traffic source often responds well to trust factors like trust seals.

Increasing paid traffic during the test may result in a sharp increase in conversions. But that increase is not sustained as the test continues for a longer period and the number of non-spontaneous visitors get factored into the results. 

If one version performs better for one traffic source but another traffic source starts getting mixed into the test: you’re seeing the mixed traffic response because of the change. This can make it hard to attribute the conversion increase you see to one source of traffic or the other.

#4. Conflicting A/B Tests Spoil Attribution

It’s easy to run more than one test at a time, however, tests may conflict with user impact. It is common to see the results of one test change when another test is started or stopped. This is typically the result of the tests sharing the same purchase funnel, or impacting the same concept.

Avoid running conflicting tests. If you are running more than one test, do a bit of analytics work to see how many people will be affected by both tests (i.e. users common to the two pages involved in the separate tests).

If it’s more than 10 percent, then you will want to strongly consider how the two tests impact the user’s single experience. By using common sense and good judgment, you and your team will be able to estimate which tests can be run at the same time.

Here, we typically recommend breaking eCommerce sites into 3 “funnels” or sections:

  • Top-of-funnel is finding a product
  • Mid-funnel is when the user is on the ‘Product Detail Page’ and ‘Adds to Cart’
  • Bottom-of-funnel is Cart through a checkout page conversion

You shouldn’t be running more than one test at a time in any one of these funnels, and KPIs should reflect the goal of each “funnel.” Especially when there is another test running in one of the other funnels.

#5. Not Taking User and Site Specifics When A/B Testing

Every eCommerce site is unique. So when you do A/B testing for eCommerce, take those particular factors into account.

Clients who work with us get individualized recommendations for their websites. Here are some important general guidelines:

1. Segment Traffic

When judging if you have enough goal completion, don’t forget to consider segmentation on a user persona level.

For example, an eCommerce store selling school supplies will have a big split between classroom teachers and parents who shop on the site. If the treatment only targets one group, or if it might impact each group differently, it’s important to take that into account.

2. Test Against the Buying Cycle

When looking at test results, a test must be run and analyzed against its buying cycle. This means testing a person from their very first visit and all subsequent visits until they purchase.

If you know that 95 percent of purchases happen within three days of the user’s visit, then you have a three-day buying cycle.

Your test cycle will be the number of weeks you test (you want to test in full-week periods) plus the full length of your buying cycle added on so the last participant let into the test has an adequate chance to complete their purchase.

3. Count Every Conversion (or at Least Most of Them)

If a participant has entered a test, their actions should be counted. This may sound obvious, but correct attribution is seldom done well, and this results in inaccurate testing.

In order to do this right, it’s important that all visitors are given the chance to purchase after entering a test. If a test is just “turned off,” participants in that test who have yet to purchase have been left out. 

Since it is common to see one particular variation do well with returning visitors, leaving out these later conversions will skew the test toward the variations that favor the less methodical type people.

4. Determine Your Site’s Test Cycle (How Long to Run a Test)

You likely have been involved in discussions about how long a test should run. The biggest factor in how long to run a test is your site’s test cycle. 

To find your site’s test cycle in Google Analytics, simply start with a segment like the one below where you define that you want to view only users who had their first session during a one-week period. Then set a condition where transactions are greater than zero.

This type of segment will tell you when people whose first visit was that week eventually purchased on your site.

You can start by looking at a range such as two months, then work backwards to figure out when 95 percent of the purchases in that two months were. In the example below, the site has a three-week test cycle because 95 percent of purchases for the two months occurred in the first three weeks from the beginning of the period you started tracking purchases:

You may be wondering, “Why 95 percent?” This is a simple rule of thumb and, from experience, we have rarely seen the final 5 percent of purchases change a test’s conclusions, however, we have seen the last 10 percent do so.

5. Use 7-Day Cycles

When testing, you most likely have to test against a full week cycle. This is because people often behave differently during different days of the week.

For instance: If your site sells toys for small children, your site’s reality might be that a lot of research traffic occurs on the weekend when the children are available for questioning (i.e. “Hey Ty, what’s the coolest toy in the world these days?”). 

Another reality for a toy site might be that often the “Add to Cart” button does not need to get hit until Tuesday evening, given that a lot of toys are not needed until the weekend when birthday parties are typically held. A test run from Wednesday through Sunday (five full days with lots of data) is still not enough.

The reality is, almost every eCommerce site (from the more than 100 eCommerce analytics we’ve done test analysis on) has a seven-day cycle. You may have to figure out which days to start and stop, but it’s there because of how user behavior varies throughout the week.

Therefore, if you don’t use a seven-day cycle in your testing, your results are going to be weighted higher for one part of the week than another.

6. Use the “Test Window”

The Test Window are essentially the steps we recommend to avoid skewing a test.

Step 1: Only let new visitors into the test. This way returning visitors later in their purchase cycle will not skew results and potentially set the test off to a false start. Get as many people into the test as possible.

Step 2: Don’t look at the test for a full seven days. If you don’t have a statistical winner at this point (most test tools will tell you the test has reached 95 percent confidence), let the test run for another seven-day cycle and don’t peak.

Step 3: Turn off the test to new visitors once you have a statistical winner (at seven-day intervals). Turning off the test to new visitors will allow the participants already in the test to complete their buying cycle. Leave the test running for a full buying cycle after you’ve closed the window.

Step 4: Report out on the test. To report out on the test’s overall results, you will simply look at your A/B testing tools report. Now, because you used the Test Window, you will be able to believe the results because:

  • Everyone in the test had a consistent site experience, spending it in the same test variation (no one seeing the control on a previous visit only to later experience a treatment). 
  • A full seven-day cycle was used so weekend days and weekdays were weighted realistically. 
  • Every user (or 95 percent of them at least) was allowed to complete their buying cycle.

Conclusion

If you are going to put time into testing to improve your eCommerce site, everything that you do will be invalidated if you aren’t paying attention to these vital A/B testing factors.

In our effort to be the best eCommerce agency, we study and rank the best eCommerce sites’ conversion rate optimization strategies in our Best in Class eCommerce CRO Report. We use our findings and apply them directly to our client’s sites so that their stores are as optimized as the best of the best (and we have case studies to demonstrate).

That said, every significant site change needs to be tested. And for that, the step-by-step guidelines we’ve shown you here will help ensure you get accurate results.

We know that conversion testing is time-consuming and often overwhelming. If you would like to increase your eCommerce site’s conversion rate, our CRO experts can help with set up and make A/B testing recommendations. Learn more here and get in touch.

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.

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The long wait is finally over! “Statistical Methods in Online A/B Testing” can now be found as a paperback and an e-book on your preferred Amazon store. Note that the Kindle edition is available for $2.99 or equivalent if you’ve alrea…

The long wait is finally over! “Statistical Methods in Online A/B Testing” can now be found as a paperback and an e-book on your preferred Amazon store. Note that the Kindle edition is available for $2.99 or equivalent if you’ve already purchased the paperback (through Kindle Matchbook). The book is a comprehensive guide to statistics […] Read More...