Article

7min read

Four Ways to Use GA4 to Power Your Web Experimentation Programs

We invited Oliver Walker from our partner Hookflash to talk us through the practical ways you can use GA4 with your experimentation. 

Although many people are talking about GA4 as a different platform from the previous version (Universal Analytics), conceptually it lets you do largely the same things. Its primary functions are to help you to understand and optimize your media; to understand and optimize your website; and to understand and segment your website visitors into audiences. However, with GA4 several features can really help you to power an experimentation program.

Here we’ll outline how to use GA4 to its full potential to drive results for your testing program.

Understanding User Behavior

At its core, Google Analytics has always been great for helping website owners to understand their website traffic. Whether it’s where they started their journey or where they ended their digital journey, or whether they sought help halfway through, there are a few options to know about. What we know about GA4 already is that it’s not the most intuitive tool in the world so here are some quick tips on that front:

  • Landing Pages – use Explorations – although there is a default report for landing pages…it’s not the best. Not just because there’s a known bug resulting in an empty row, but also because it doesn’t have the most useful metrics, i.e. bounce rate or engagement rate. If you build a report in Explorations, you can use a different dimension (called “Landing page + query string”) and choose the dimensions you’d find useful:

  • Exit rate – similar to the above, you no longer get Exits (or Exit Rate) in the default Pages & Screens report. Again, rebuilding the report in Explorations gives you both the ability to add Exits as a metric, and you can choose your preferred pages dimension. The default dimension in the Pages and Screens report does not include query strings but if you’d prefer to use the one that does, choose the dimension “Page path + query string”.
  • Site search – and finally, where’s the Site Search report gone!? There’s no longer a default report for this but you can rebuild this in Explorations. You can understand which search terms were most often looked for, by building an Exploration with the dimension of “Search term” and the metric “Event count”.

Understanding User Flow

What Universal Analytics was not particularly good at is visualizing how people traverse through a website. The flow reports were horribly sampled and just merely teased you as to what you could have had. GA4 has on-the-fly path exploration reports that can be used and tweaked, very flexibly. You can find these within Explorations too, just choose Path Exploration and then  tweak, as per the following:

  • Get the pages view – for some unhelpful reason, the default view is Event Name, within each step. In the visualization, click the drop-down underneath Step +1 and change Event Name to be your preferred page dimension to get a view of how users move from page to page.
  • Double-click the page you are interested in to see where users go next. You can also click the +15 more (or whichever number) link at the bottom of each column to get the longer tail
  • Choose a dimension to “breakdown” by lets you easily compare routes through the site for different users, for example mobile vs. desktop or for each of the different browsers. Likewise, you can use segments here to review a certain audience type, e.g. non-UK traffic or Purchasers.

Audience targeting & triggers

Speaking of audiences, this was always a great feature of Universal Analytics and when Google Optimize was in its pomp, the ability to share audiences from UA to Optimize was one of its prime features. With GA4 you get the same ability to build audiences and to share audiences natively with other Google Marketing Platform (GMP) plus some neat additional elements:

  • The ability to use user behavior to trigger new types of goals. For example, if you’re a publisher and you want to engage people to read a certain number of articles in a particular time frame, it’s possible to create an audience for this and then have that set of behavior trigger a new event. It’s called audience triggers. And this becomes a powerful new metric with which to optimize your testing campaigns, by importing that conversion into your chosen testing tool
  • The ability to export audiences from GA4 to other platforms. Namely, this is something that the new Google Analytics Data API supports. This is big news. Whilst it’s to be expected that other platforms will catch-up, at the moment AB Tasty is the only one to have published their mechanism for pulling GA4 audiences into their platform:

This is generally a great leap forward as GA4 also has the concept of users being added, and removed from audience groups, whereas most testing tools don’t have this feature.

Advanced analysis using BigQuery

The final area where GA4 really steps forward beyond its predecessor is that all GA4 accounts have a native integration with Google BigQuery. Whilst the integration itself is free, it’s worth noting that you do incur costs by storing or processing data in BigQuery, although a good partner will be able to advise on what that might look like for you. 

So where does BigQuery help? The data schema provided by integrating GA4 and BigQuery is raw-level data – that means each row is effectively an event, with a time stamp, and all the associated parameters. It lets you have a greater degree of flexibility over what you analyze, provided you’re able to query the data (using SQL, or your friendly AI-driven chat tool.) For example:

  • If you want to understand how long it takes a user to complete a particular flow or set of actions. Worth noting that Google Analytics does batch events so this isn’t perfect, but it is easier than within the interface
  • If you want to look at user flows at an even greater level of detail, for example, how users traverse through the site having landed at a particular page
  • If you want to stitch together any data that GA didn’t capture but that also exists in Google Cloud, e.g. following a lead to submission through to outcome.
  • If you want to conduct a deeper analysis within your post-experiment analyses. All testing platforms will pass events and parameters to denote whether a user was part of an experiment and the variation they saw, so GA4 is a powerful additional tool to deep-dive into results

It’s not all doom and gloom

Yup, GA4 does have some limitations, it’s a big change to a tool that lots of people loved and it’s hard to pick-up. BUT when you start to understand certain concepts and familiarize yourself with capabilities, there are lots of features to help you with your experimentation program.

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Article

7min read

Understanding shopping engagement software: How do virtual shopping assistants work?

Every visitor shopping online wants to find a product that precisely meets their expectations quickly and efficiently. To achieve this, you can offer your potential customers purchasing advice to guide them throughout their buying journey.

In this article, you will discover the different forms of virtual shopping assistants available in e-commerce and the advantages they bring to you and your customers.

What are virtual shopping assistants?

Virtual shopping assistants, enabled by shopping engagement software, provide your shoppers with support in their product selection through an interactive and personalized exchange. By asking precise questions, your customers can find products that align with their wishes and needs more quickly.

This approach is based on the purchase advice provided in brick-and-mortar retail, aiming to overcome the impersonal components of online shops and enhance the individual user experience.

How do virtual shopping assistants differ from faceted search?

With faceted search, your customers can filter their search results in the online shop to view the products that interest them. For example, when searching through an e-commerce apparel shop they can use faceted navigation to select features, such as women’s blue capris in size 40, providing a user-friendly experience.

However, customers need to already know exactly what they want to buy to filter accordingly. If a customer is uncertain about their purchase or unsure about the specific product features they desire, they require support in the form of virtual shopping assistants.

What kinds of virtual shopping assistants are available?

There are various formats of virtual shopping assistants in e-commerce that can be integrated at different points of the customer journey. Let’s take a closer look at two categories: person-to-person communication tools and automated tools that can handle multiple customer inquiries in real time.

Virtual shopping assistants with human-to-human communication

Below, we present two examples of virtual shopping assistants that utilize human-to-human communication:

Live chat

Live chat is a messenger tool that allows your customers to directly contact an employee of your online shop. Typically integrated as a pop-up window on the company website, it facilitates one-to-one communication, resembling the experience of brick-and-mortar retail.

Video consultation

Video consultation is a rising trend in the e-commerce industry. 

Customers visiting your e-commerce site may still be exploring their needs, making phone, chat or email interactions insufficient. With video consulting, customers can engage in face-to-face conversations with an employee of your online shop, ask questions, and receive individual advice on your products and processes. 

For instance, customers can share their screens and present their ideas and inspiration to the sales representative, leading to a more targeted sales pitch. This combination of online shopping with personalized attention replicates the experience of boutique purchases and ultimately boosts customer loyalty and satisfaction. 

The advantage: Your customers receive immediate, personalized answers to their questions about products and processes while they browse your shop. Especially for complex products that require explanation, customer-oriented live chat can positively influence purchase decisions. Additionally, you can offer appointments for individual purchase advice.

Virtual shopping assistants with AI-based tools

Now, let’s explore two examples of online consulting software that utilize AI-based tools for real-time interactions with multiple customers at once.

AI-based chatbots

Chatbots using artificial intelligence can respond to hundreds of customer inquiries simultaneously and in real time. 

With the emergence of large language model chatbots such as OpenAI’s ChatGPT and Google’s Bard, brands have the potential to revolutionize how they engage with their customers online.

Depending on how the tool is programmed, it can recognize natural language, generate suitable answers from text blocks and databases on your website, and even escalate queries to a human employee if necessary. This enables personnel-friendly automation of various processes. 

Guided Selling

Guided Selling involves guiding your customers through the product selection process to facilitate a confident purchase decision. This is particularly useful for potential buyers who may not possess enough knowledge about the products to make an informed choice.

For instance, when it comes to purchasing a stroller, expectant parents can feel overwhelmed by the countless models available. Guided Selling assists them in narrowing down the selection through targeted questions, leading to the ideal stroller. This can be seen in the example from babymarkt.de, who uses Guided Selling from AB Tasty to provide better shopping experiences for their customers.

This form of assistance, where a customer is guided step-by-step through the consultation process based on specific questions, is especially suitable for products that require explanation and mirrors the experience of a sales pitch in brick-and-mortar retail. Guided Selling can also be used for self-explanatory products, where customers can find the right product selection by selecting certain tags.

What makes Guided Selling special is that the results can be personalized to display suitable products based on the individual click and buying behavior of your customer. This ensures that your customer receives not only products that match their desired features and requirements but also their unique preferences.

Why is good customer engagement important in e-commerce?

Customers who feel well-advised are happy to come back. This applies to both brick-and-mortar stores and e-commerce shops. In addition, there are other reasons for using shopping engagement software like virtual shopping assistants.

Personalized shopping experience

When potential buyers walk into a brick-and-mortar store, they can approach the on-site sales consultants to find the right product. 

By integrating this service into your online shop in the form of live chats, video advice or Guided Selling, you enable your customers to recreate the feeling of an interactive, personalized shopping experience.

Shoppers become customers

Virtual shopping assistants help you convert potential buyers into customers. By putting customers in direct contact with your team or catalog, they get answers to their questions that can positively influence their purchase decision. 

For very personal products such as mattresses, a virtual shopping assistant tool helps visitors to find the one that exactly meets their needs from the multitude of models. 

A better user experience

Your visitors appreciate positive experiences throughout their customer journey. 

Support through virtual shopping assistants gives them a secure feeling when choosing a product and more frequently leads to a purchase decision. In addition, virtual shopping assistants make shopping easier: You present your customers with suitable solutions, they feel understood and the positive user experience is anchored in their memory.

Higher conversion

With virtual shopping assistants and shopper engagement software, you can reduce lost sales opportunities and thus increase your conversions. Sometimes potential buyers leave a shop because they didn’t find a product that is actually there. If they can easily ask a sales representative about the product via live chat, it will improve their shopping experience.

Your potential customers have already added products to their shopping cart, so why are they abandoning the checkout process? One possible reason: They had a question about a process that was not answered quickly enough. With an AI-based chatbot available during the checkout, these questions can be solved quickly and efficiently.

Higher customer satisfaction

The personalized service of a virtual shopping assistant creates an intimate atmosphere – a 1:1 exchange reminiscent of brick-and-mortar experiences. This not only strengthens potential buyers’ trust in your company but also their satisfaction. And satisfied customers turn into loyal customers. 

Fewer Returns

Implementing virtual shopping assistants in your shop reduces the risk of returns. The two most common reasons for returns are either that the product didn’t fit or they didn’t like it. 

With personal, targeted advice, you can help your customers to choose the right products that meet their wishes and needs as precisely as possible. This reduces your costs and makes your returns management easier.

Conclusion: Virtual shopping assistants make e-commerce more human

Virtual shopping assistants are a must-have in e-commerce. It offers advantages for you as an e-commerce marketer as well as for your customers. 

Live chats or chatbots, video advice and Guided Selling make it easier for potential buyers to select a product and improve their user experience. In a 1:1 exchange, they receive personalized answers to their questions – the online shop becomes more human. At the same time, you benefit from higher customer loyalty and fewer returns, which means you can increase your sales.