New ecommerce-focused Google Analytics reports could help merchants identify issues with shopper journeys and the checkout process.
The Google Analytics 4 purchase journey report shows the funnel from when a would-be customer starts a web session through purchase. And the newer checkout journey report displays the checkout funnel in four detailed steps.
Both reports show where shoppers abandon the buying journey. The data could identify problems in a store’s navigation or point out opportunities for tests or optimization.
Checkout Journey Report
Found under Reports > Monetizationin GA4, the checkout journey report shows the number and percentage of users who start the checkout process on an ecommerce site or app and then complete each subsequent step.
GA4 introduced the checkout journey report in September 2023. Click image to enlarge.
It uses a closed funnel method, focusing only on shoppers who started at the “Begin checkout” step.
The report can identify bottlenecks or issues in the checkout flow. For example, a business with a massive drop-off after the shipping step could have a technical or pricing problem with the available delivery options.
Checkout Steps
For the checkout journey report, data is collected from four GA4 events.
begin_checkout for the “Begin checkout” step.
add_shipping_info for the “Add shipping” step.
add_payment_info for the “Add payment” step.
purchase for the “Purchase” step.
Merchants will add these events to the checkout flow. Google offers implementation instructions for desktop and mobile devices to ensure the proper GA4 event is specified at each checkout stage.
gtag("event", "begin_checkout", {...
Checkout Dimensions
When its report loads, the checkout journey will show the flow by “device category,” i.e., mobile or desktop. But the report may also include other dimensions. Here is the complete list:
Device category,
Country,
Region,
City,
Language,
Age,
Gender,
Browser.
Thus marketers can find checkout glitches for a specific group of shoppers.
The table in the checkout journey report is initially divided by device category, but other dimensions are available. Click image to enlarge.
Purchase Journey Report
The GA4 purchase journey report provides insights into shopper drop-offs at each step of the funnel, although with less detail during the checkout. The two reports can work together to identify optimization opportunities.
The purchase journey report is located in GA4 at Reports > Monetization.
The purchase journey report shows buyers’ actions from session start to purchase, although the report for checkout journeys is more detailed. Click image to enlarge.
Purchase Steps
The purchase journey report gathers data from five GA4 events:
session_start marks the start of a session.
view_item is triggered when a product is viewed.
add_to_cart is triggered when an item is added to the cart.
begin_checkout for the “Begin checkout” step.
purchase or in_app_purchase for the “Purchase” step.
Like the checkout journey report, the GA4 events for collecting purchase journey data will need to be set up and added to the appropriate pages of an ecommerce website.
Some ecommerce platforms include some or most of these events in their GA4 integration. For example, Shopify’s GA4 integration automatically adds the view_item, add_to_cart, purchase, and several other events.
Purchase Dimensions
As of October 2023, the purchase journey report had the following analytics dimensions, two fewer (age and gender) than the checkout journey report:
Device category,
Country,
Region,
City,
Language,
Browser.
Using the Reports
The reports and funnels described here are helpful only if ecommerce marketers use them to optimize the buyer’s journey. Here’s an example.
Monitor the funnel. Start by watching the funnel, paying attention to how promotions, days of the week, or holidays impact buyers’ journeys.
Find drop-offs. Any point in the purchase or checkout funnel where shoppers drop off is a potential problem or opportunity.
Investigate. Examine drop-off points and hypothesize on the underlying cause. For example, loads of shoppers leaving at the shipping step could indicate the cost is too expensive relative to the average order value.
Take action. Address the potential cause of a drop-off and implement a solution. This could be a test at the add_shipping_info step that reduces the shipping cost.
Watch and iterate. Did the test work? Are more shoppers arriving at the next step? Measure the results. If the drop-off continues, develop a new hypothesis and solution.
Keep optimizing. Include optimizing the buyer’s journey as a routine marketing activity.
Can’t Find the Reports?
Add purchase journeys and checkout journeys from the report library if they do not appear under Reports > Monetization.
“Ecommerce Europe” is an association representing 150,000 companies selling goods or services online to consumers in that continent.
The association’s “European E-Commerce Report 2023” (PDF) encompasses 37 countries and includes data and trends surrounding internet penetration, e-shoppers, and B2C ecommerce sales. According to the report, total B2C ecommerce in Europe grew by 6% in 2022, reaching €899 billion (U.S. $944 billion), up from €849 billion in 2021.
The info in the report stems from direct collaboration, interviews, and questionnaires with national ecommerce associations across Europe.
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According to the data, 76% of internet users in Europe shopped online in 2022, increasing to a projected 78% in 2023.
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The U.K. has the highest share of internet users who buy online (95%), followed by The Netherlands (92%) and Norway (92%).
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The report also looks at data for the EU-27 member countries exclusively: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden.
Per the data, the top popular categories for E.U. e-shoppers in 2022 were clothing and accessories (for physical items) and streaming films (for digital goods).
Google has published new documentation for the GA4 Data Redaction feature that prevents accidentally sending personally identifiable information (PII) to Google. This makes it easier to conform to privacy laws and Google’s own policies.
Notable about the feature is that it will be turned on by default for new properties that are added to GA4 but existing properties will have to manually enable it.
Google’s GA 4 policies require that no PII data be sent through GA4 that Google could use to identify individuals.
Examples of PII includes (but is not limited to):
Email addresses
Personal mobile numbers
Social security numbers
Removing PII From URLs
One of the ways that PII could inadvertently be sent to Google is through URL paths and parameters that contain PII in them.
The Data Redaction feature in GA4 is a setting that is turned on by default for new properties added to GA4.
Existing properties will need to configure the data redaction feature in the web data stream settings.
GA4’s data redaction feature analyzes events prior to sending them to Google and strips out any PII that may be contained in the data.
According to the new documentation:
“The data-redaction feature helps to prevent the inadvertent collection of PII in the form of email addresses and URL query parameters.
Data redaction uses text patterns to identify likely email addresses across all event parameters and the URL query parameters that are included as part of the event parameters page_location, page_referrer, page_path, link_url, video_url, and form_destination.”
It should be noted that Google’s documentation advises that users should not consider their responsibility to remove PII to be completed with this solution.
The solution can not be considered complete because GA4 users are still obligated to make sure that there are no PII sent to Google in some other manner that the data redaction feature may not be able to identify and remove.
The new documentation states:
“It’s important to remember that while data redaction provides a powerful tool against inadvertently collecting PII, the ultimate responsibility for meeting regulatory requirements still lies with the entity collecting data.
To further help you meet that responsibility, this feature lets you test your configuration to understand whether the text patterns you identify are redacted as expected (learn more).”
You can also use Debug View to monitor in real time how Analytics collects events from your site.”
Now it’s just a setting within GA4.
Read Google’s newly published documentation for the data redaction feature:
ChatGPT remains one of the most talked about tools in the world of SEO.
Some users are finding ways to leverage the platform for content and SEO; others use it to create ads, optimize meta titles, create structured data, and be more productive overall.
And being more productive by integrating ChatGPT and Google Sheets together makes a lot of sense to me.
How To Integrate ChatGPT And Google Sheets
Integrating ChatGPT and Google Sheets can be achieved in a few ways.
While we’ll explore multiple ways to tie these two solutions together, the easiest method at the time of writing this post is to:
Open Google Sheets.
Click Extensions > Add-ons > Get add-ons.
Search “GPT for Sheets.”
You can also go directly to the website GPT for Work to install the add-on on Sheets – and you can use this same method to work with ChatGPT in Excel.
Add-ons make it simple to use ChatGPT with Sheets, but if the add-on becomes unsupported or stops working, you can use the methods below.
Different Ways To Integrate ChatGPT And Google Sheets
ChatGPT’s API allows developers to easily use the platform’s responses in their own code.
You can use Apps Script inside of Sheets to get this setup. First, you’ll want to:
Make note of your API key (Personal > View API keys from the top menu).
Open Google Sheets.
Go to Extensions > Apps Script.
ChatGPT has the code available for easy copying, which is outlined below:
Screenshot from Google Sheets Apps Script, August 2023
Code to copy:
const OPENAI_URL = "https://api.openai.com/v1/chat/completions";
const SECRET_KEY = "YOUR_OPENAI_API_KEY";
const SYSTEM_MESSAGE = { role: "system", content: "You are a helpful SEO expert." };
function callChatGPT(prompt, temperature = 0.9, maxTokens = 800, model = "gpt-3.5-turbo") {
const payload = {
model: model,
messages: [
SYSTEM_MESSAGE,
{ role: "user", content: prompt }
],
temperature: temperature,
max_tokens: maxTokens
};
const options = {
method: "POST",
headers: {
"Content-Type": "application/json",
"Authorization": "Bearer " + SECRET_KEY
},
payload: JSON.stringify(payload)
};
try {
const response = UrlFetchApp.fetch(OPENAI_URL, options);
const responseData = JSON.parse(response.getContentText());
if(responseData.choices && responseData.choices[0] && responseData.choices[0].message) {
return responseData.choices[0].message.content.trim();
} else {
console.error("Unexpected response format from OpenAI:", responseData);
return "Sorry, I couldn't process the request.";
}
} catch (error) {
console.error("Error calling OpenAI API:", error);
return "Sorry, there was an error processing your request.";
}
}
You’ll need to work your way through the code and change certain parameters. Primarily, you’ll replace “YOUR_OPENAI_API_KEY” with the API you jotted down previously.
Now, you can run the script and give it a try for yourself.
A quick test run of the =callChatGPT(“How can you help me?”) function will let you know if it’s working. The function should print out a list of items ChatGPT can help you with:
Screenshot from Google Sheets, August 2023
Inside your Sheets cells, you can call the Script using the following “callChatGPT(CELL-AND-ACTION-HERE),” and it will provide a response. Google might ask you to accept certain permissions, so be sure that you do if you want the script to work.
You may also utilize the function based on other cells, for example:
Put these keywords in cell A1: seo, chatgpt, google sheets.
In B1 cell input this function: =callChatGPT(“Provide a meta title for an article based on these keywords:” & A1).
You should receive a response like this:
ChatGPT response based on a single cell.
Tweak this formula based on your data, keywords, and other details.
Benefits Of Integrating ChatGPT With Google Sheets
Sheets is a product that I use quite often – it works great. But Sheets and Excel seem to lack innovations that allow you to use your data in new, exciting ways.
Integrating ChatGPT reduces the need to switch between both products and will boost your productivity in the process.
You can use the two together to:
Generate or translate text, which will allow you to create multiple posts on social media in a variety of target languages.
Create an ideas section for titles to help you come up with titles that are more clickable or user-friendly.
Summarize text that you can use for previews or snippets.
Make fast work of mundane tests, such as coming up with meta descriptions or product descriptions.
Tables help you visualize data and are great when reporting to clients, but they’re tedious to fill in. You can also use ChatGPT to generate tables for your data to better view and understand your data.
For example, you can create a table to monitor:
Title lengths.
Meta tag lengths.
Bounce rate changes.
When it comes to making sense of your data and analyzing it, you can have ChatGPT run the calculations for you and then create charts or tables around it.
Visualizing your data will make it easier to analyze and use it.
I’m sure you’ll find many great uses for ChatGPT and Sheets, but the following are some that I’ve found to be personally useful.
8 Ways To Use ChatGPT And Google Sheets Together
There are many ways to use ChatGPT and Sheets together, from tag generation to outlines and SEO research.
1. Generate Tags
Together, ChatGPT and Sheets make it easy to generate tags for products and build up your product tag library.
Just create a task for GPT, and it will generate tags for each product you select, saving you so much time in the process.
2. Clean Lists
Sheets and GPT can work together to help you clean up your lists.
Let’s say that you have a list of names. Because users input their names, some may be in all capital letters, and others may have emojis or inconsistencies in capitalization.
GPT can use the GPT_FILL function to clean up your name list and standardize it for easy use and organization.
Using the script, you can generate short product descriptions based on examples on your spreadsheet.
ChatGPT will analyze your example and generate descriptions that match the tone and style of your brand.
4. Generate Taglines, Ad Copy and Titles
With similar functions, you can use Sheet and ChatGPT to generate:
Ad copy.
Taglines.
Titles.
More.
ChatGPT can create ad copy that’s on-brand, captivating subject lines for emails, and other copy that will engage customers. With these tools, you can save your marketing team time and generate compelling content that converts.
5. Create Outlines
Creating outlines for blog posts can be time-consuming. Integrating ChatGPT into Sheets will save you time by generating outlines for your posts in seconds.
GPT can provide a structure for your posts and create outlines that will keep audiences engaged.
6. Keyword Research
With Google Sheets and ChatGPT, you can save time with keyword research. Just feed GPT a primary keyword and ask it to generate suggestions. The chatbot will generate a list of potential target keywords.
You can use these keywords as “seeds” for your research or, at the very least, review them to ensure they’re worth targeting.
7. Generate Schema Markup Suggestions And Internal Linking Ideas
Inside of Sheets, you can use GPT to make schema markup suggestions based on the content and type.
For example, if your contact displays your address and phone number, ChatGPT can provide schema markup suggestions to help search engines better understand the information on your page.
You can also ask ChatGPT to provide you with internal linking ideas. Just provide a page topic to get more related topics for internal linking.
Just input some data about your competitors and ask GPT to provide you with some insights.
You can even ask the chatbot to provide suggestions for missing topics or areas to expand in your content.
Just provide ChatGPT with some background on your content landscape, and it can provide suggestions right in Sheets.
ChatGPT And Google Sheets: Better Together
Integrating ChatGPT into Sheets can help enhance data analysis, save time, and streamline processes.
Once you have an API key, integration is simple, and you’ll have access to a number of functions that you can use to analyze information, create charts, generate ideas, and more.
However, for simplicity, it’s easier to use add-ons that take care of the integration without scripts.
Once you connect ChatGPT and Sheets, you’ll be able to crunch numbers and ask the chatbot to begin helping you handle tedious tasks.
Even generating metadata or creating titles can be immensely helpful. You can even have ChatGPT help with creating redirects or add rules to robots.txt for you.
Example Formulas
Here are some example formulas you may want to use:
Input main keyword in the A1 cell and some secondary keywords in the B1 cell.
In C1 input: =callChatGPT(“Based on this keyword ‘”&A2&”‘ as the main keyword, and these ones as secondary keywords: “&B2&”, recommend an SEO friendly meta description. Make sure the length of your recommendation is a maximum of 150 characters, including the spaces.”).
In D1 input: =callChatGPT(“Based on this keyword ‘”&A2&”‘ as the main keyword, and these ones as secondary keywords: “&B2&”, recommend an SEO friendly meta title. Make the length of your recommendation to be a maximum of 55 characters, including the spaces.”).
In E1 input: =callChatGPT(“For a page to rank well in search engines on the topic of ‘”&A2&”‘, what would be your page content outline? Include these secondary keywords: “&B2&”, Provide the page outline with proper headings and structure. Output the outline only. Do not include a page title.”).
BONUS with script:
In F1 input: =callChatGPT(“Write SEO friendly FAQschema JSON, limited to 5 questions and answers, for an article with these keywords: ‘”&A2&”, “&B2&”‘ and this outline: (“&E2&”). Add the script opening and closing tags for Json”)
Screenshot from Google Sheets, August 2023
Voilà – now you have an outline, meta title, meta description, and FAQ schema that goes with your keywords.
Tip 2: Use AI Call Data To Inform Your SEO Strategy & Maximize Your Potential
You can use AI to pull important data from your clients’ phone conversations more efficiently and apply these insights to your marketing strategies with CallRail’s Conversation Intelligence®.
Rather than getting bogged down with tedious manual tasks, let AI do the heavy lifting for you and spend more time on the things that really move the needle.
AI-powered tools such as CallRailʼs Conversation Intelligence can assist with sales or customer service conversations in real time.
If an agent is unsure how they should follow up on a call, for example, a generative AI model could analyze the call, compare it against the wealth of other calls it has already analyzed, and make a data-based recommendation on the next steps.
Conversational Intelligence is also a great tool for automating call summaries and aggregate trends.
It allows you to coach your clients on lead follow-up with time-saving call summaries. Plus, through call sentiment analysis, you are able to pinpoint the calls that require your clients’ immediate attention, enabling them to respond at a faster rate.
You can even utilize this technology to help you find new keywords to run campaigns against or adjust your strategy for keywords you’re already targeting.
An AI-powered tool could also recommend changes or update bids automatically, by analyzing the calls that came from these campaigns and determining whether the lead converted.
Want to learn more about making data-based recommendations with generative AI, as well as empowering the other tools in your marketing stack? Download CallRail’s new ebook.
Tip 3: Humanize Your Business & Strengthen Client Connections
By adding AI to your clients’ inbound phone calls, you can form more meaningful connections.
The data you’re able to access with this technology reveals a whole new layer to target consumers, digging deeper into their strongest needs and desires.
And by adjusting your campaign strategy to meet users where they are, you create a lasting impression that will keep them wanting more.
By tapping into AI’s ability to optimize your clients’ marketing and sales conversations, you can help them connect better with more customers.
AI exposes the quality of your clients’ connections and helps you make them more robust, satisfying, and human, rather than making them more robotic.
For marketing agencies specifically, conversational AI makes it possible to act on data you wouldn’t have otherwise had access to while automating tasks like:
Call transcription.
Summaries.
Keyword spotting.
Trend analysis.
Although the traditional phone call might appear to be teetering on the brink of obsolescence, conversations remain relevant, thanks to AI’s newfound ability to tap into their invaluable wealth of user data.
Get your free copy of CallRail’s new ebook to find out more about how these rare insights can help you explore new marketing opportunities and take your agency to the next level.
Unleashing The Power Of Conversational AI
Embracing modern tools has the power to transform the challenges associated with phone calls into opportunities.
Call tracking makes it not just possible but easy to connect incoming calls to marketing campaigns and lead records.
But more remarkably, conversational AI can unlock those rich, qualitative insights hidden inside the raw audio data of the call.
This technology helps you tap into how potential users might want to interact with your client’s product and the questions that they may have – you can then use conversational AI tools to help route them to relevant information.
With the following tips, you’ll learn how to start using this advanced form of AI to supercharge your clients’ phone conversations and boost user experience.
Leverage Your Conversation Data With CallRail & Build A Winning Marketing Strategy
Enhanced by the power of AI technology, the phone call is steadily reclaiming its relevance as a potent medium for consumer engagement.
It’s time to embrace the conversational revolution and recognize calls for what they are: a gold mine of intelligence waiting to be tapped.
So, if you’re ready to start mining gold from phone conversations, CallRailʼs Conversation Intelligence is the leading AI tool for uncovering the hidden gems of data concealed within every interaction.
Start your 14-day free trial to access the key insights that not only illuminate consumer preferences and behavior, but also pave the way for growth.
Plus, download CallRail’s new ebook to learn more about leveraging phone calls to improve your marketing strategies and unlock new opportunities.
How an online shopper finds a product or store impacts conversions. Thus optimizing for sales might start well before a prospect reaches a product detail page.
Conversion optimization is complicated, as the authors of “Leading Online Shoppers to the Finish Line,” a 2023 Shopify and Boston Consulting Group study, found. For starters, ecommerce merchants use varying attribution methods and buyer-journey definitions.
For example, conversion optimization typically focuses on the checkout but differs on, say, page 1 or page 3. Some methods include mobile-first payments, while others don’t.
To be sure, the checkout process is the most significant in an ecommerce conversion. But it’s not the only driver of sales.
Traffic sources — i.e., paid versus organic search — impact conversions and provide top-of-the-funnel insights.
Organic and Paid
Most online shops employ both paid and organic traffic to attract potential customers. But which one works best?
The channels can have vastly different costs per conversion. Marketers generally disagree on which source — organic or paid — works best.
Part of the disagreement stems from a marketer’s economic interest. For example, an article published in March 2023 on a site that sells paid search tools cited a 2009 guest post — yes, 14 years old — from Moz stating that paid search converts 35% better than organic. This dated citation implies search engine optimization isn’t important or effective.
More recently, the Boston Consulting Group study, which considered sales data from more than 220,000 ecommerce stores, concluded that organic traffic sources in general — think search, social, and word-of-mouth — outperformed paid traffic sources.
Your business should likely use both but not mindlessly. Understand how traffic sources interact and work together to drive sales.
Traffic Measurement
Many if not most ecommerce conversions stem from multiple shopper interactions, whether it’s first-time or repeat buyers.
Regardless, optimizing traffic sources starts with measuring and analyzing. It requires capturing information to understand how the source impacts sales.
Optimizing traffic sources starts with measuring and analyzing.
Segment conversions by traffic source. Track the traffic source for each sale. Use a first- or last-touch attribution, but keep all the touch-point data along the buyer’s journey. Experiment with multiple attribution periods, such as 28, 14, or 7 days.
Your traffic segments could be:
Direct,
Referral,
Organic search,
Paid search,
Organic social media,
Paid social media,
Other advertising,
Affiliate marketing,
Email marketing,
Direct mail.
Measure conversion rates by customer type. Building on your traffic segments, track new versus repeat customers. For example, how many returning customers query Google for your store’s brand or products and then click your ad in search results to reach the store?
Get some form of multi-touch attribution. Merchants should measure how traffic sources work together and how customers access the various channels before purchasing. For instance, a customer might first come through a social media ad, then return to sign up for the newsletter, and finally convert after clicking an email offer.
Track micro-conversions. A newsletter subscription is a micro-conversion that impacts future sales. How more or less likely is a prospect to buy if she is an email subscriber?
Monitor customer cohorts. Assemble the metrics above and build customer cohorts to analyze over time. Pay attention to each cohort’s average order value, lifetime value, and return on investment.
Use What You Measure
Use the traffic-source info to make marketing and operational decisions. Here are examples.
Planning. If email marketing leads to more repeat sales, find ways to get more subscribers. Or if organic search traffic converts higher, emphasize SEO.
Allocating budget. If the goal is new customers, invest in paid social if it drives more of those buyers.
Changing offers. If new customers from paid social have a lower average order value, bundle or upsell products.
Respond to cohorts. If a cohort, such as repeat customers from direct traffic, has higher lifetime values, try to replicate the journal of those shoppers.
Finally, iterate. Continue to measure and tweak the relationship between traffic sources and sales. Did your data-driven decisions last month have the expected outcome? Are changes necessary?
In short, traffic sources shape conversions. Tracking those sources and their impact is vital for ecommerce conversion optimization.