How to show Lighthouse Scores in Google Sheets with a custom function

Learn how to use machine learning to streamline your reporting workflows right within Google Sheets.

The post How to show Lighthouse Scores in Google Sheets with a custom function appeared first on Marketing Land.

Automation and machine learning have tremendous potential to help all of us in marketing. But at the moment a lot of these tools are inaccessible to people who can’t code or who can code a bit but aren’t really that comfortable with it.

What often happens is that there ends up being one or two people in the office who are comfortable with writing and editing code and then these people produce scripts and notebooks that everyone else runs. The workflow looks a bit like this:

I will show you a simple way to streamline this workflow to remove the steps where people need to run a script and format the output. Instead they can run the automation directly from within Google Sheets.

The example I will show you is for a Sheets custom function that returns the Lighthouse score for a URL like in this gif:

The method I will show you isn’t the only way of doing this, but it does illustrate a much more general technique that can be used for many things, including machine learning algorithms.

There are two parts:

  1. A Google Cloud Run application that will do the complicated stuff (in this case run a Lighthouse test) and that will respond to HTTP requests.
  2. An Appscript custom function that will make requests to the API you created in step 1 and return the results into the Google Sheet.

Cloud run applications

Cloud Run is a Google service that takes a docker image that you provide and makes it available over HTTP. You only pay when an HTTP request is made, so for a service like this that isn’t being used 24/7 it is very cheap. The actual cost will depend on how much you use it, but I would estimate less than $1 per month to run thousands of tests.

The first thing we need to do is make a Docker image that will perform the Lighthouse analysis when we make an HTTP request to it. Luckily for us there is some documentation showing how to run a Lighthouse audit programatically on Github. The linked code saves the analysis to a file rather than returning the response over HTTP, but this is easy to fix by wrapping the whole thing in an Express app like this:

const express = require('express');
const app = express();
const lighthouse = require('lighthouse');
const chromeLauncher = require('chrome-launcher');

app.get('/', async (req, res) => {
    // Check that the url query parameter exists
    if(req.query && req.query.url) {
        // decode the url
        const url = decodeURIComponent(req.query.url)    
        const chrome = await chromeLauncher.launch({chromeFlags: ['--headless', '--no-sandbox','--disable-gpu']});
        const options = {logLevel: 'info', output: 'html', port: chrome.port};
        const runnerResult = await lighthouse(url, options);

        await chrome.kill();

const port = process.env.PORT || 8080;
app.listen(port, () => {
  console.log(`Listening on port ${port}`);

Save this code as index.js.

Then you will also need a file called package.json which describes how to install the above application and a Dockerfile so we can wrap everything up in Docker. All the code files are available on Github.

    "name": "lighthouse-sheets",
    "description": "Backend API for putting Lighthouse scores in Google sheets",
    "version": "1.0.0",
    "author": "Richard Fergie",
    "license": "MIT",
    "main": "index.js",
    "scripts": {
        "start": "node index.js"
    "dependencies": {
        "express": "^4.17.1",
        "lighthouse": "^6.3"
    "devDependencies": {}
# Use the official lightweight Node.js 10 image.
FROM node:12-slim

# Our container needs to have chrome installed to
# run the lighthouse tests
RUN apt-get update && apt-get install -y \
  apt-transport-https \
  ca-certificates \
  curl \
  gnupg \
  --no-install-recommends \
  && curl -sSL | apt-key add - \
  && echo "deb stable main" > /etc/apt/sources.list.d/google-chrome.list \
  && apt-get update && apt-get install -y \
  google-chrome-stable \
  fontconfig \
  fonts-ipafont-gothic \
  fonts-wqy-zenhei \
  fonts-thai-tlwg \
  fonts-kacst \
  fonts-symbola \
  fonts-noto \
  fonts-freefont-ttf \
  --no-install-recommends \
  && apt-get purge --auto-remove -y curl gnupg \
  && rm -rf /var/lib/apt/lists/*

# Create and change to the app directory.
WORKDIR /usr/src/app

# Copy application dependency manifests to the container image.
# A wildcard is used to ensure copying both package.json AND package-lock.json (when available).
# Copying this first prevents re-running npm install on every code change.
COPY package*.json ./

# Install production dependencies.
# If you add a package-lock.json, speed your build by switching to 'npm ci'.
# RUN npm ci --only=production
RUN npm install --only=production

# Copy local code to the container image.
COPY . ./

# Run the web service on container startup.
CMD [ "node", "--unhandled-rejections=strict","index.js" ]

Build the docker image and then you can test things locally on your own computer like this:

First start the image:

docker run -p 8080:8080 lighthouse-sheets

And then test to see if it works:

curl -v "localhost:8080?"

Or visit localhost:8080? in your browser. You should see a lot of JSON.

The next step is to push your image to the Google Container registry. For me, this is a simple command:

docker push

But you might have to setup the docker authentication first before you can do this. An alternative method is the use Google Cloud Build to make the image; this might work better for you if you can’t get the authentication working.

Next you need to create a Cloud Run service with this docker image.

Open Cloud Run and click “Create service”

Name and adjust settings. You must give your service a name and configure a few other settings:

It is best to pick a region that is close to where most of the audience for your sites live. Checking the site speed for a UK site from Tokyo won’t give you the same results as what your audience get.

In order for you to call this service from Google Sheets it must allow unauthenticated invocations. If you’re worried about locking down and securing the service to prevent other people from using it you will have to do this by (for example) checking from an API secret in the HTTP request or something like that.

Next you must select the container you made earlier. You can type in the name if you remember it or click “Select” and choose it from the menu.

Then click “Show Advanced Settings” because there is further configuration to do.

You need to increase the memory allocation because Lighthouse tests need more than 256Mb to run. I have chosen 1GiB here but you might need the maximum allowance of 2GiB for some sites.

I have found that reducing the concurrency to 1 improves the reliability of the service. This means Google will automatically start a new container for each HTTP request. The downside is that this costs slightly more money.

Click “Create” and your Cloud Run service will be ready shortly.

You can give it a quick test using the URL. For example:

curl -v ""

Or visit in your browser.

The next step is to write some Appscript so you can use your new API from within Google Sheets.

Open a new Google Sheet and the open up the Appscript editor.

This will open a new tab where you can code your Google Sheets custom function.

The key idea here is to use the Appscript UrlFetchApp function to perform the HTTP request to your API. Some basic code to do this looks like this:

function LIGHTHOUSE(url) {
  const BASE_URL = ""
  var request_url = BASE_URL+"?url="+encodeURIComponent(url)
  var response = UrlFetchApp.fetch(request_url)
  var result = JSON.parse(response.getContentText())
  return(result.categories.performance.score * 100)

The last line returns the overall performance score into the sheet. You could edit it to return something else. For example to get the SEO score use result.categories.seo.score instead.

Or you can return multiple columns of results by returning a list like this:

[result.categories.performance.score, result.categoryies.seo.score]

Save the file and then you will have a custom function available in your Google Sheet called LIGHTHOUSE.

The easiest way to get started with this is to copy my example Google Sheet and then update the code yourself to point at your own API and to return the Lighthouse results you are most interested in.

Enhance your spreadsheet know-how

The great thing about this method is that it can work for anything that can be wrapped in a Docker container and return a result within 30 seconds. Unfortunately Google Sheets custom functions have a timeout so you won’t have long enough to train some massive deep learning algorithm, but that still leaves a lot that you can do.

I use a very similar process for my Google Sheets addon Forecast Forge, but instead of returning a Lighthouse score it returns a machine learning powered forecast for whatever numbers you put into it.

The possibilities for this kind of thing are really exciting because in Search Marketing we have a lot of people who are very good with spreadsheets. I want to see what they can do when they can use all their spreadsheet knowledge and enhance it with machine learning.

This story first appeared on Search Engine Land.

The post How to show Lighthouse Scores in Google Sheets with a custom function appeared first on Marketing Land.

How to make your data sing

Stop reporting absolute numbers and put your data into context with ratios to engage your stakeholders with the smaller, but important, data points.

The post How to make your data sing appeared first on Marketing Land.

It is amazing; the horrible job many digital marketers do when reporting their work to clients. This includes both internal and external clients. Just think about how many marketing presentations and reports you’ve seen that simply contain screenshots from Google Analytics, Adobe Analytics, Adwords, Google Console, or reports from a backend ecommerce system. This isn’t the way to influence people with your data.

The biggest issue is that most marketers are not analytics people. Many marketers do not know how to collect all of the necessary data or how to leverage that data, and to a lesser degree, know how to present it in a meaningful way. Typically, this is the job of a data analyst. The same way purchasing a pound of nails, a hammer and a saw doesn’t make you a carpenter, gaining access to your analytics reporting tool does not make you a data analyst. This is why many reports contain those convoluted screenshots, and present data out of context, contributing little to no meaning. 

Data out of context

Many reports merely report the facts (the data) with a number and no context. Data out of context is just data. For example, simply making a statement that Adwords generated 5,000 sessions to a website last month is meaningless without context. The number 5000 is neither a good nor a bad data point without a reference point or a cost factor. It’s not until you add in other factors (open the box) that you can demonstrate whether or not your efforts were a success. If the previous month’s Adwords campaign only drove in 1,000 sessions, then yes without other data, 5000 sessions looks good. But what if the cost to drive those additional 4,000 sessions was 10 fold the previous month’s spend? What if the previous month, Adwords drove 5,000 sessions but at double the spend?

It is only by adding in the additional information in a meaningful way that marketers can turn their reporting from a subjective presentation into an objective presentation. In order to do this, stop reporting absolute numbers and put your data into context with ratios. For example, when assessing Cost per Session, toss in a 3rd factor (goal conversion, revenue, etc.) and create something similar to “Cost per Session : Revenue”.  This will put the data into context. For example, if every session generated costs $1 : $100 (Cost per session : revenue) vs. $2.25 : $100 (Cost per session : revenue) the effectiveness of a marketing spend becomes self-evident. In this example, it is clear the first result is superior to the second. By normalizing the denominator (creating the same denominator) the success or failure of an effort is easily demonstrated. 

Data is boring

Yes, presenting data is boring. Simply looking at a mega table of a collection of data will cause many to lose interest and tune out any message you might be trying to present. The best way to avoid this is to make your data sing!

Make your data sing

Just like in the marketing world, the easiest way to grab someone’s attention and make your message sing is with imagery. Take all that great data in your mega table, and turn it into an easy to understand graph, or when necessary, simplified data tables. Even better, (if you can) turn it into interactive graphs. During your presentation, don’t be afraid to interact with your data.  With some guidance, your audience can dive into the data they are most interested in.

Learn to use data visualization tools like Data Studio, Tableau, DOMO, Power BI and others. Leveraging these tools allows you to take boring data and not only give it meaning but to make the data sing, which will turn you into a data hero.

Interacting with your data

Back at the end of July 2019, my firm acquired an electric vehicle. We wanted to know if the expense was worth it. Did the cost savings of using electricity over gasoline justify the difference in the ownership cost of the vehicle (lease payments +/- insurance cost and maintenance costs).

Below is a typical data type report with all the boring detailed data. This is a mega table of data and only those truly interested in the details will find it interesting. If presented with this table most would likely only look at the right-hand column to see the total monthly savings. If presented with just this data, many will get bored, and will look up and start counting the holes in the ceiling tiles instead of paying attention.

The following graphs demonstrate many of the ways to make this data sing, by putting all of the data into context through interactive graphics.

The above graph (page 1 of the report) details the cost of operating the electric vehicle. The first question we were always curious about was how much it was costing us to operate per 100 km. By collecting data on how much electricity was used to charge the car, how many kilometers we drove in a given month and the cost for that electricity, we are able to calculate the operating cost. In the graph you can easily see the fluctuation in operating costs, with costs going up in winter months (cost of operating the heater in the car) and again in June & July (cost of running the AC). You can also see the impact of increases in electricity prices.

To truly evaluate the big question “Was acquiring an electric vehicle worth it?” we’d need to estimate how much gasoline would have been consumed by driving the same distance against the average cost for gas during the same months. On page 2 of the report the data is now starting to sing as the difference in the savings of electrical over gas becomes clear. The chart becomes interactive and allows the user to hover over any column to reveal the data details.

To make the data truly sing, we’d need to not just compare the operating costs, but the costs of ownership. Do the savings in the operating costs justify the price difference between the vehicles? We know that the difference in lease costs, insurance and annual maintenance is in the range of $85-$90/month

The above graph (page 3 of the report) demonstrates, the impact of plummeting gas prices and the reduced driving done during April 2020 due to the COVID-19 shutdown. In April 2020 a mere monthly savings of approximately $41 dollars was achieved. Therefore, there were no savings in owning a more expensive electric vehicle over an equivalent gas-powered vehicle (the difference in lease costs and insurance, etc. is in the range of $85-90/month). While it might not be sing, it definitely was screaming out when we saw it. 

Check out the entire report for yourself.  It is accessible here so you can view all the pages/charts. The report is interactive allowing you to hover given months to see data details or even change the reporting date range.

By embracing not only data visualization but the visualization of meaningful data, we as marketers can raise the bar and increase engagement with our audience. Think of the four pages of this report, which page talks most to you? Which way of presenting the data makes it sing for you? Odds are it was not the first table with all the detailed data.

The post How to make your data sing appeared first on Marketing Land.

Soapbox: Is my data telling me the truth?

How email security programs affected my perception of data integrity.

The post Soapbox: Is my data telling me the truth? appeared first on Marketing Land.

As marketers, we face the overwhelming challenge of demonstrating proof that our tactics are effective. But how can we convince management if we are not convinced of our own data?

Here’s the reality, which I recently learned for myself: If you’re running email marketing, it’s very likely that your performance reports are not disclosing the full truth… inflated CTRs (click-through rates) and open rates being the main culprits. 

Email security programs – loved by recipients, hated by senders

Barracuda. SpamTitan. Mimecast. Email bots that serve a single purpose: to protect users from unsafe content. These programs scan inbound emails and attachments for possible threats, including viruses, malware, or spammy content by clicking on links to test for unsafe content.

For email marketers, this creates several challenges:

  • Inflated CTRs and open rates due to artificial clicks and opens 
  • Disrupting the sales team’s lead followup process as a result of false signals
  • Losing confidence in data quality (quantity ≠ quality)

Real or artificial clicks?

In reviewing recent email marketing performance reports, I noticed an unusual pattern: Some leads were clicking on every link in the email…header, main body, footer, even the subscription preferences link — yet they were not unsubscribing. Not only that, but this suspicious click activity was happening almost immediately after the email was deployed. I speculated that these clicks were not “human”, but rather “artificial” clicks generated from email filters. 

Hidden pixels are your frenemy

To test my hypothesis, I implemented a hidden 1×1 pixel in the header, main body, and footer section in the next email. The pixels were linked and tagged with UTM tracking — and only visible to bots.

Sure enough, several email addresses were flagged as clicking on the hidden pixels.

All that brings me back to the question of whether or not marketing data can be trusted. It’s critical to “trust, but verify” all data points before jumping to conclusions. Scrutinizing performance reports and flagging unusual activity or patterns helps. Don’t do an injustice to yourself and your company by sharing results that they want (or think they want) to hear. Troubleshoot artificial activity and decide on a plan of action:

  • Use common sense and always verify key data points
  • Within your email programs, identify and exclude bots from future mailings
  • Share results with management, sales, and other stakeholders

A word of caution… 

Tread carefully before you start implementing hidden pixels across your email templates. Hiding links might appear to email security programs as an attempt to conceal bad links. You could be flagged as a bad sender, so be sure to run your email through deliverability tools to check that your sender score isn’t affected.

As the saying goes, “There are three kinds of lies: lies, damned lies, and statistics.” Sigh.

With different solutions circulating within the email marketing community, this is likely the “best solution out of the bad ones”. It all depends on what works best with your scenario and business model. 

Godspeed, marketer! 

The post Soapbox: Is my data telling me the truth? appeared first on Marketing Land.

Making Marketing Analytics Simple And Easy To Understand

Does the thought of marketing analytics make you cringe? Does it seem overwhelming and time consuming? Many business owners find analytics and reporting a cumbersome task and one they put off until absolutely necessary. If this is you, or you’d like some advanced tips on measuring data, this is the article for you. We look […]

Making Marketing Analytics Simple And Easy To Understand

Does the thought of marketing analytics make you cringe? Does it seem overwhelming and time consuming?

Many business owners find analytics and reporting a cumbersome task and one they put off until absolutely necessary. If this is you, or you’d like some advanced tips on measuring data, this is the article for you.

We look at making marketing analytics simple and easy to understand so it’s something you want to do, not grudgingly have to do.

First, let’s define marketing analytics.

Marketing Analytics Is…

Marketers (and business owners) use marketing analytics to evaluate the success of their marketing initiatives.

These analytics make up the processes and technologies to measure their performance.

Bottom line – marketing analytics tell you if your marketing programs are working.

You want to gather your data from all of your marketing channels and consolidate it into one common view. From here, you can decide how to drive your future marketing efforts.

To increase your lead generation and ultimately your conversions, you’ve got to know how to interpret your data.

Many business owners think marketing analytics are best left to the experts. We’re here to tell you that you are the expert. No more worries about metrics. You can do it.

To create your report, you want to attend to these items first:

  • Ask yourself what you want to learn.
  • Find the report that answers that question.
  • Put it into your overall marketing analytics.
  • Include a balanced assortment of reports.
  • Assess your strategies.
  • Then, you can use your report to change or revise your marketing strategy.

Here’s how to make marketing analytics simple and easy to understand.

Take Little Bites

When gathering your data, you often have access to multiple metrics. In the beginning start small.

A good place to begin is with page views, conversions and visitor information.

You want to track the most important information first. After you get accustomed to analytics and reporting, you can dive deeper for more metrics.

Marketing experts put much of their emphasis tracking conversions. Why?

This is a much more accurate number for you to gauge your success. Conversions track actual customers doing something on your website, like signing up, downloading information or buying something.

Your conversion rate focuses on dollars and the value of your visitor.

Be the Master

The true analytics expert knows which metrics and data matter and which ones don’t matter so much.

The fact is you don’t need to track everything. It’s too hard to stay on top of it all.

For example, if you want to focus on lead generation, your most important data is page views and your opt-in rate.

Understand Your Data

It also helps to narrow your focus to the most relevant metrics so you know what data to capture.

Here are some areas to look at depending on your business:

Ecommerce businesses can look at conversion rate, total revenue, orders completed, average order value, drop off rate and where that happens and full on cart abandonment.

A business to business company might look at page visits, page views, conversion rate and leads generated.

A business to consumer company might focus on conversion rate, click-through rate and orders completed.

Remain Objective

It’s easy to selectively look at your data and search for things that confirm a hypothesis. You might have something in mind you want to confirm and find data that validates it, but that leads you to ignore all of the contrary information.

Don’t get caught up looking for metrics that confirm what you expect and disregard all other data.

Be objective and look at the data from multiple angles.

For example, many people think a high bounce rate is due to the fact that visitors didn’t like your page. But you have to ask these questions:

  • What is happening?
  • Why is it happening?

Your first instinct is to attribute a high bounce rate to people not liking your page. Yet, there are many other reasons your landing page may have a high bounce rate:

  • Your content is superb and meets the users’ needs, and you only have one call to action that people take and then “bounce” off.
  • The landing page was simply to collect an email address, thus they bounce when they were done.
  • Your page load time is too high.
  • Your page doesn’t meet users’ needs.
  • Users landed on your page from a Google Ad campaign, and your page didn’t match the ad.

The goal is to assess why you have a high bounce rate before arbitrarily deciding you have to redo your entire page.

Know the Value

You’ve probably searched Google for “What’s a good conversion rate?” That isn’t necessarily the same information for everyone.

You want to understand the value of your analytics for your industry. Don’t stack your business up to businesses in other industries because their “good” conversion rate may not be yours.

Your Google search should instead be for, “What’s a good conversion rate in my industry?” Once you’ve narrowed down the field, you really can compare rates.

Comparing to unlike industries sets you up for misplaced expectations.

Final Thoughts

Now that you know how to make marketing analytics simple and easy to understand, we want to leave you with a few more thoughts.

Take advantage of these advanced ways to break down your marketing into analytics you can understand.

If you don’t, you’ll end up with a bunch of marketing information cobbled together that has no relationship with one another.

To make the best decisions for your business, you have to take your entire marketing picture into account.

This means your social media insights, your Google analytics and your emails stats. It means taking a look at all of your marketing efforts in one place so you can decide how to proceed.

Use your marketing analytics to make sound business decisions and drive your future marketing. Use them to refine and test your lead generation to increase your profits.

Tie your marketing efforts to your leads to your bottom line, and you’ll quickly see what’s working and where you can improve.

So, say goodbye to marketing analysis paralysis. Use these advanced tips to make it work for your business.

Are you ready to squeeze more profit out of your website by analyzing your marketing metrics? That’s terrific! We’re here to help you optimize your website so it works fluidly for your website visitors. In fact, we promise you we’ll do just that.

 With our guarantee, you can rest assured we will increase your profits through landing page optimization.

 If you’re ready to work with the leader in landing pages and conversion rate optimization, contact us today.

We’ll provide you with our FREE site performance analysis so we can work on your landing page conversion rates.

Image: Kazuend


Google Analytics: How to Set Up a Simple Goal

Google Analytics provides a great feature for website owners to be able to track specific campaigns, also called a goal. It can be places on pages, forms, or anything you are wanting to track for to see if a campaign has an effective website conversion. It also tracks how the visitor arrived to the area…

The post Google Analytics: How to Set Up a Simple Goal appeared first on Diamond Website Conversion.

google-analytics-thumbnailGoogle Analytics provides a great feature for website owners to be able to track specific campaigns, also called a goal. It can be places on pages, forms, or anything you are wanting to track for to see if a campaign has an effective website conversion. It also tracks how the visitor arrived to the area you want to convert.

This works great after you’ve tried A/B Testing so you can verify the results from live traffic. In this article, you’ll learn how to set up a simple goal in Google Analytics.

Google Analytics: How to Set Up a Simple Goal

Please note, if you haven’t added your site to Google Analytics, then you can’t take advantage of the goal tool until you do. Aside from adding your site to Google Analytics, you will also need to apply the generated tracking code to your website.

The first step is in creating a simple goal is by clicking on your site in the Google Analytics dashboard. On the right hand side, scroll down to the area called Conversions. If you click on it, the area will expand and show you other links. Look for the area called overview as shown below.


Now, you can either do this and be led to set up a simple goal or you can also click the Admin tab at the top. Image is below. In order to view the image larger and much better, you will have to right click on the image to open it in a new tab or window.


On the last column under View, is an area called Goals. You’ll click that and be led to the page that has an area much like the image below.


Click on the red button to create a goal. Once you have, you will need to name your goal and tell it hat type of tracking you want. In the case of this tutorial, and it being how to set up a simple goal, we’ll choose the first option called Destination. This is great for contact forms or lead generation forms. Once you have selected the option on how you want to track your goal, then click the blue button that says Next Step. See the example image below to see how you should proceed.


In the next step, you tell it what page you are wanting to land on. You do not put the full URL. See the image below for how this step should go.


Before hitting the blue button that says Create Goal, make sure to click the link that says Verify this Goal. This helps to make sure that your goal will work and checks it against your previous 7 days of stats on Google Analytics. In the case that you just joined and don’t have 7 days of stats, then proceed by clicking the button to create the goal. You can always check after a few days if the goal is actually working.

Once this has been set up, you won’t have to mess with it any more. You can just sit back and analyze how your goal is doing. Simple, right? There are other ways you can set up a goal in Google Analytics, like how long visitors are staying on your site (called Destination), by how many pages visits (Pages/Screens per Visit), or Event (like from watching a video.)

Have you taken advantage of setting up a goal in Google Analytics? Did you find it easy?

The post Google Analytics: How to Set Up a Simple Goal appeared first on Diamond Website Conversion.

What Do You Do After You First Apply Google Anayltics to Your Website?

When you get into creating and managing a website, at some point you’re going to hear about Google Analytics, especially being told you need to have it on your website. Regardless if you’re a blogger, a small business owner, or a big corporate business, you do need a tool to measure your site’s progress. Google…

The post What Do You Do After You First Apply Google Anayltics to Your Website? appeared first on Diamond Website Conversion.

google-analytics-thumbnailWhen you get into creating and managing a website, at some point you’re going to hear about Google Analytics, especially being told you need to have it on your website. Regardless if you’re a blogger, a small business owner, or a big corporate business, you do need a tool to measure your site’s progress. Google Analytics just happens to be a good one that is also free to use.


What Do You Do After You First Apply Google Anayltics to Your Website?

The majority of users may look in on their stats once a day or once a week. Google Analytics provides quite a bit of statistics. You can even set campaigns to analyze traffic from your website and some of your social network handles.

It’s quite alright to take a frequent look at your stats, but if you’re just looking at them and wishing your traffic to improve, then you’re missing out on what Google Analytics can do for you. It takes analyzing what’s going on and planning a campaign to drive attention to those areas of your website that you want people to see.

The great thing about most stats programs, including Google Analytics is that they provide exactly what information you need to know about your visitors. You can even find out if you’re targeting the correct audience, and at what times they hit your website.

Once you’ve installed Google Analytics on your website, you should let it do it’s job in collecting information. After about 3 weeks to a month, you should have a nice tentative spread of your website’s traffic.

When installing Google analytics to your website for the first time, some of the most important stats you should look at are:

  • Pageviews
  • Percentage of new visitors
  • Percentage of returning visitors
  • Bounce rate
  • How you are acquiring your visitors (where are they coming from)
  • Keywords

While there are a TON of other stats, your first time through should be to gather this information and start to put together a first campaign.

Your keywords, acquisition, and your bounce rate with each campaign you plan will change in time depending on how you adjust your website conversion plan.


Before you even look at your stats, you really should already have a list of keywords that you’ve been wanting to work on for your website. If your analytics in Google are not coinciding with your intended list, then you’ve got homework to do in creating content around those keywords. Don’t worry, some people have websites for a few years before realizing that they’ve been missing out on capitalizing on being more laser focused on their keyword strategy.


If your website is brand new, you might not have too much information on how you’ve been acquiring your visitors. You will have a small idea, and can use those stats to either focus on those places that are sending you traffic, or working on trying to get traffic from new sources. It might take making sure your website is properly listed on search engines, creating social network handles, and sharing your content.

Bounce Rate

Bounce rate gives you a percentage of how many of your website visitors are only viewing one of your pages, and then leaving. Your bounce rate should never be high. In fact, your strategy should be in converting those visitors to fill out your lead forms, buy your product, share and comment on your blog posts, or even subscribe to your newsletter.

If you can put a plan together that gives you a low bounce rate, great acquisition sources, and above all, making a return on investment, you’re on the right path to great website conversion. The great thing is that Google Analytics is free to use… so what are you waiting for? Go forth and find out how your website is performing!

Do you use Google Analytics in your website conversion strategy? Do you still struggle with deciphering those stats and putting a plan together? If not, what advice do you have for newbies just hooking their website’s up to Google Analytics?

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