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Google Says No Correlation Between Impressions And Search Volume

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Google Says No Correlation Between Impressions And Search Volume


Google’s Search Advocate John Mueller says the impressions your site receives for a keyword is not an indication of the search volume for that keyword.

This is stated on Twitter in response to a question regarding whether impressions data in Google Search Console can be used to estimate search volume.

For example, if you have a page ranking in the first position for a particular keyword, and it’s receiving 1,000 impressions per month, does that mean the keyword’s search volume is 1,000 monthly queries?

No, that’s not how it works, Mueller says.

Impressions Are Not Related To Search Volume

First, Mueller clarifies how impression data differs from search volume data:

“The impressions are the impressions your site received in search. It’s not necessarily all the impressions shown to all users. It’s not the search volume. Also, all tools guess & simplify search volume, so the numbers you see in search volume tools will always be wrong.”

Syed Sufiyan, the Twitter user who posed the initial question, presses further.

He has a page that ranks in position one for a certain keyword. So he asks if the impressions the page receives is indicative of the amount of searches being conducted for that keyword.

Sufiyan states:

“Thanks for the clarification, but still I’m confused!
For Instance:
I have a keyword/query (Suppose “Buy Shoes”) in the Search Console that is ranking on 1st position and getting 1000 impressions in one month so the search volume should be 1000 too?”

Sufiyan is assuming, since the page ranks first, that his page is being shown to everyone who enters the keyword into Google.

Therefore, according to his reasoning, the number of impressions shown in Search Console could be used as a way to figure out the keyword’s monthly search volume.

Mueller quickly dismisses that theory:

“Not necessarily. Just because you’re ranking 1st in some cases, doesn’t mean the page is always shown.”

Even though rank trackers show that a page is ranking first for a specific keyword, it’s not accurate to assume it’s being shown for 100% of searches.

So the impression data for a page ranking #1 is not the same as the search volume of the keyword it ranks for, since the page isn’t shown to all searchers.

There are a number of reasons why a page wouldn’t be shown to all searchers, despite ranking number one for a keyword.

The layout of the search results page can impact how many impressions the organic links receive.

For example, if there’s a bunch of Google Shopping and Google Ads results shown, the searcher mayhave to scroll down a bit before seeing the organic links.

In a case like that, an impression wouldn’t be recorded for the page in the first position if the searcher never scrolls down far enough to see it.

Another reason could be personalization and the fact that search results are not identical for all users.

The key takeaway here is that impressions are not a reliable indicator of search volume.

Source: @JohnMu On Twitter


Featured Image: marc gusev/Shutterstock





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A Comprehensive Guide To Marketing Attribution Models

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A Comprehensive Guide To Marketing Attribution Models

We all know that customers interact with a brand through multiple channels and campaigns (online and offline) along their path to conversion.

Surprisingly, within the B2B sector, the average customer is exposed to a brand 36 times before converting into a customer.

With so many touchpoints, it is difficult to really pin down just how much a marketing channel or campaign influenced the decision to buy.

This is where marketing attribution comes in.

Marketing attribution provides insights into the most effective touchpoints along the buyer journey.

In this comprehensive guide, we simplify everything you need to know to get started with marketing attribution models, including an overview of your options and how to use them.

What Is Marketing Attribution?

Marketing attribution is the rule (or set of rules) that says how the credit for a conversion is distributed across a buyer’s journey.

How much credit each touchpoint should get is one of the more complicated marketing topics, which is why so many different types of attribution models are used today.

6 Common Attribution Models

There are six common attribution models, and each distributes conversion value across the buyer’s journey differently.

Don’t worry. We will help you understand all of the models below so you can decide which is best for your needs.

Note: The examples in this guide use Google Analytics 4 cross-channel rules-based models.

Cross-channel rules-based means that it ignores direct traffic. This may not be the case if you use alternative analytics software.

1. Last Click

The last click attribution model gives all the credit to the marketing touchpoint that happens directly before conversion.

Last Click helps you understand which marketing efforts close sales.

For example, a user initially discovers your brand by watching a YouTube Ad for 30 seconds (engaged view).

Later that day, the same user Googles your brand and clicks through an organic search result.

The following week this user is shown a retargeting ad on Facebook, clicks through, and signs up for your email newsletter.

The next day, they click through the email and convert to a customer.

Under a last-click attribution model, 100% of the credit for that conversion is given to email, the touchpoint that closed the sale.

2. First Click

The first click is the opposite of the last click attribution model.

All of the credit for any conversion that may happen is awarded to the first interaction.

The first click helps you to understand which channels create brand awareness.

It doesn’t matter if the customer clicked through a retargeting ad and later converted through an email visit.

If the customer initially interacted with your brand through an engaged YouTube view, Paid Video gets full credit for that conversion because it started the journey.

3. Linear

Linear attribution provides a look at your marketing strategy as a whole.

This model is especially useful if you need to maintain awareness throughout the entire buyer journey.

Credit for conversion is split evenly among all the channels a customer interacts with.

Let’s look at our example: Each of the four touchpoints (Paid Video, Organic, Paid Social, and Email) all get 25% of the conversion value because they’re all given equal credit.

4. Time Decay

Time Decay is useful for short sales cycles like a promotion because it considers when each touchpoint occurred.

The first touch gets the least amount of credit, while the last click gets the most.

Using our example:

  • Paid Video (YouTube engaged view) would get 10% of the credit.
  • Organic search would get 20%.
  • Paid Social (Facebook ad) gets 30%.
  • Email, which occurred the day of the conversion, gets 40%.

Note: Google Analytics 4 distributes this credit using a seven-day half-life.

5. Position-Based

The position-based (U-shaped) approach divides credit for a sale between the two most critical interactions: how a client discovered your brand and the interaction that generated a conversion.

With position-based attribution modeling, Paid Video (YouTube engaged view) and Email would each get 40% of the credit because they were the first and last interaction within our example.

Organic search and the Facebook Ad would each get 10%.

6. Data-Driven (Cross-Channel Linear)

Google Analytics 4 has a unique data-driven attribution model that uses machine learning algorithms.

Credit is assigned based on how each touchpoint changes the estimated conversion probability.

It uses each advertiser’s data to calculate the actual contribution an interaction had for every conversion event.

Best Marketing Attribution Model

There isn’t necessarily a “best” marketing attribution model, and there’s no reason to limit yourself to just one.

Comparing performance under different attribution models will help you to understand the importance of multiple touchpoints along your buyer journey.

Model Comparison In Google Analytics 4 (GA4)

If you want to see how performance changes by attribution model, you can do that easily with GA4.

To access model comparison in Google Analytics 4, click “Advertising” in the left-hand menu and then click “Model comparison” under “Attribution.”

Screenshot from GA4, July 2022

By default, the conversion events will be all, the date range will be the last 28 days, and the dimension will be the default channel grouping.

Start by selecting the date range and conversion event you want to analyze.

GA4 model comparison_choose event and date rangeScreenshot from GA4, July 2022

You can add a filter to view a specific campaign, geographic location, or device using the edit comparison option in the top right of the report.

GA4 Model comparison filterScreenshot from GA4, July 2022

Select the dimension to report on and then use the drown-down menus to select the attribution models to compare.

GA4 model comparison_select dimensionScreenshot from GA4, July 2022

GA4 Model Comparison Example

Let’s say you’re asked to increase new customers to the website.

You could open Google Analytics 4 and compare the “last-click” model to the “first-click” model to discover which marketing efforts start customers down the path to conversion.

GA4 model comparison_increase new customersScreenshot from GA4, July 2022

In the example above, we may choose to look further into the email and paid search further because they appear to be more effective at starting customers down the path to conversion than closing the sale.

How To Change Google Analytics 4 Attribution Model

If you choose a different attribution model for your company, you can edit your attribution settings by clicking the gear icon in the bottom left-hand corner.

Open Attribution Settings under the property column and click the Reporting attribution model drop-down menu.

Here you can choose from the six cross-channel attribution models discussed above or the “ads-preferred last click model.”

Ads-preferred gives full credit to the last Google Ads click along the conversion path.

edit GA4 attribution settingsScreenshot from GA4, July 2022

Please note that attribution model changes will apply to historical and future data.

Final Thoughts

Determining where and when a lead or purchase occurred is easy. The hard part is defining the reason behind a lead or purchase.

Comparing attribution modeling reports help us to understand how the entire buyer journey supported the conversion.

Looking at this information in greater depth enables marketers to maximize ROI.

Got questions? Let us know on Twitter or Linkedin.

More Resources:


Featured Image: Andrii Yalanskyi/Shutterstock



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