Browse Tag: #Web Analytics

Conversion-attribution-model

Master Guide To Conversion Attribution Models

As a Digital Marketer, you would utilize various channels to advertise your business including Google, Facebook, Email and so forth. It’s significant for you to realize which sources are performing and at what level during the client venture.

Promoting attribution encourages you to comprehend the adventure of client contact focuses in detail, which further causes you to streamline advertising blend and drive more an incentive from your showcasing endeavors.

Let’s begin!

attribution-model

So What is Marketing Attribution?

Attribution is assigning credit for a conversion.

Marketing Attribution is the process of identifying sets of users activities in the form of touchpoints which leads to a conversion or sale.

In simple words, it’s the action taken by the client during their customer journey from seeing an advertisement to purchasing the product.

Conversion Attribution types

  1. Last Click Attribution Model
  2. Last Non-Direct Click Model
  3. Last Adwords Click Model
  4. The First Interaction Model
  5. The Linear Model
  6. Time Decay Model
  7. Position-Based Model Or U-Shaped
  8. Custom Attribution Model

Let’s understand each one in details!

1. Last Click Attribution Model

The most common type of attribution model is the Last Click Attribution Model. In this model, the entire credit is given to the last click which generated a conversion or a sale.

Last-click-model

The vast majority of the marketers go with this model since they need to know which keyword generates conversion or which website created conversion or through which source the genuine conversion occurred. This model will totally focus on the last touchpoint.

But you won’t understand which other touchpoints were part of the customer journey because to you, they would also be equally important to understand and optimize them in the funnel. You should look for “Last Non-Direct Click” on Google Analytics to measure the effectiveness of the campaign, here it ignores the direct click

This is important because the customer will likely interact with you many times before conversion occurs.

2. Last Non-Direct Click Model

The Last Non-Direct Click Model is more useful than a standard last-click model. 100% of the conversion value is still assigned to a single last interaction. But, with last non-direct click, it ignores any “direct” interactions that occur right before the conversion.

Last-non-direct-attribution

Direct Traffic is the point at which anybody goes directly to your website by entering your URL or clicking a bookmarked interface. So this guest definitely thinks about your company.

3. Last Adwords Click Model

Last-google-ads-click-model

In the Last Google Ads Click attribution model, the last Google Ads click—in this case, the first and only click to the Paid Search channel —would receive 100% of the credit for the sale.

4. First Interaction Model

First Interaction model gives all credit to the first click/first touch, that leads a user to a website.

This model applies to the customers if they don’t subscribe or fill the form or make a purchase on your website. This model encourages you to understand the starting point of the customer on your site which is additionally driving value to your business.

If you go first interaction attribution model, you actually don’t know which other touchpoints contributed to a conversion in the journey. So it isn’t so useful, to review the key factor which generated conversion.

First-contact attribution model can be utilized when your goal is building awareness and driving customers to your site, for this situation, you need to know from where the clients are entering your site. If you are looking to understand the conversion funnel, I won’t suggest going with a first interaction attribution model.

first-click-attribution-models

For example, if a customer first finds your business on Pinterest, then Pinterest gets all of the credit for any sale that happens after that interaction.

It doesn’t matter if the customer found you on Pinterest, then clicked a display ad a week later, and then went to your site directly. Pinterest, in this example, gets the full credit.

5. The Linear Model

A Linear attribution model gives equal credit to all the interaction of your customer in their customer journey. In this model we can understand all the interactions which actually generated conversion, this helps us to further define our marketing strategy.

linear-attribution-model

For example, a customer finds you on Instagram, signs up for your email list and later clicks an email link. The next week they go to your site directly and make an Rs1200 purchase. There are 3 interactions in this situation. Each interaction gets 33% of the credit, or a Rs 400 conversion value attributed to the channel when the purchase was made.

The only thing with this model is that we really don’t know which interaction point was the major contribution of the last activity, who ideally should get the maximum credit.  I would go with a linear attribution model if my goal is to understand which touchpoints are generating sales. Through this, I know all customer interaction which is driving value to the business and so it can be optimized.

6. Time Decay Model

Time-decay-attribution-model

The time rot attribution model gives the most extreme credit to the interaction/touchpoint which was nearer to the point of conversion. It gives a different value to each touchpoint from the point of interaction to the point of conversion with the last touch getting the maximum and the first touch getting the minimum. This model eliminates which interaction really guided a customer to a website. It’s not a recommended attribution model.

7. Position-Based Model Or U-Shaped

Position-based-attribution-model

A position-based Attribution model is also known called as U-Shaped Attribution Model. In this model, the primary touch and the last touch is credited with 40% each as the value and the remaining 20% is divided between the other touchpoints.

In this model, all the interactions get credit, though first and last touchpoint is considered as the key drivers for actions, so they are credited with 40% each as the credit.

The other interactions among first and last are additionally significant interaction when we are taking a gander at the shopper venture, so offering credit to first and last disregards the significance of other touch focuses, as they are similarly significant for the activity to occur. Won’t recommend going with the Position-based attribution model.

8. Custom Attribution Model

Custom Attribution Model is an attribution model where you would custom be able to set the credit value for the basis of each interaction on your understanding.

If we have defined credit value for each touchpoint as below, as we want to give a bit higher credit to the first touchpoint as it starts the consumer journey and then we have given low credit to the rest of the touchpoints which are in between the first and last touchpoint. Finally, for the last touchpoint, we have given maximum credit, as that touchpoint is driving the conversion.

custom-attribution-model

To set up this model, you would require developers to do as such. Also basis the results you have to keep optimizing the efforts. It’s one of the best from the above all but would need technical guidance to set up, which might also consume some time.

So How to choose the right Conversion attribution model for your business?

It’s vital to choose the right conversion attribution model for your business from which you can effectively optimize your marketing efforts based on multiple touchpoint data, which leads to higher ROI. You can consider the following factors before choosing the attribution model for your business.

Sources Contributing Towards Conversion

Check the sources which are contributing towards conversion. Google Analytics guides you to understand which sources are performing for your website. Have a look at the below sources which show how each source is performing.

Sources-contributing-to-actions

Check Different TouchPoints for Conversions

Check different touchpoints that are part of the consumer journey prior to the conversion. Google Analytics allows you to check the multiple touchpoints of the journey.

touch-points-for -conversion

Time is taken by Users

Know how much time it takes for users to convert after their first interaction with your website. This will help you to understand the duration and then you can map it with different touchpoints in the entire journey.

google-analytics-time-lag-report

Google Analytics helps you to understand the time to convert users under Time Lag Report.

Define Campaign Objective

Define the campaign objective which will help you to choose the right attribution model for your business. If your objective is to generate awareness for your brand, then the first touch attribution model is effective to measure the entry point for your customer. If your objective is leads or sales, you can go with last touch or linear attribution model. If you go with the last touch, it will help you to identify the last touch which is driving maximum results, basis which you can effectively optimize the touchpoint.

If you are going with linear, which I also prefer because, it helps me to understand each touchpoint in the entire consumer journey, which further helps me to build an effective strategy focused on each touchpoint.

Run Experiments & Optimize

Every touchpoint in the journey has a role to play, so you need to experiment continuously with different strategies including your ad copies, bidding strategies, targeting aspects, etc so that you know how significantly it’s helping you to improve your conversions regularly.

Wrapping Up

Selecting the right conversion attribution model is important for your business, this will help you to effectively improve your performance and reduce marketing efforts for all the touchpoints in the entire consumer journey. Set up your marketing attribution model today and let me know how much value it’s adding to your business!

Importance of Web Analytics for Business

Web Analytics may be defined as a system that collects, process and reports a web site data which can be used to get insights about customers and how they interact with a business’s site.

Using Analytics reports we get access to valuable data that helps the business to achieve their goals and objective. Most of the brands use such data to create strategies to achieve their goals.

So today, we are going to discuss Web Analytics and why it is important for business?

Importance of Web Analytics

1. Access to Accurate Data to Understand the Traffic

Access to Accurate Data Source: Pixabay
Access to Accurate Data

Web Analytics is all about data and reporting data but not all data is useful. Google Analytics provides valuable data which can be used to discover hidden trends and insights thus it is very important for a business.

However, this data alone can also mislead a business if irrelevant data is not filtered out. Google Analytics filter helps in refining the data and provide you with data that is important and relevant for your business.

For example: Using exclude filter to see data related to your real prospects and not office staff.

2. Helps you to Understand Website Audience

Understand Website Audience Source - Pixabay
Understand Website Audience

A website that does not provide its visitors good user experience can not think of getting business using it. In order to improve user experience, we must understand a website audience, devices they use, the language they speak etc.

Web Analytics provides this data to business through its reports and thus help them understand their audience and develop strategies to improve their user experience when they visit the website. For example:

a. Technology Report: Provide data about which technology, browser and OS and network being used by a visitor.

b. Behaviour Report: Provide data about how a visitor is engaging with the website and their behaviour on the site.

c. Demographic Report: Provide data to understand and better know the audience of the site.

3. Understand Return on Investment

Understand Return on Investment  Source - Pixabay
Understand Return on Investment

Web Analytics help in knowing ROI by tracking the performance of social media campaigns, email campaigns, ad campaigns etc.

By default, Google Analytics tracks only traffic from 3 mediums that are organic, referral and direct. In order to track the performance of traffic from other sources and mediums link tagging is used.

This help in understanding the performance of campaigns and source and mediums used for the campaigns. By using this data, we can know the ROI from campaigns and optimise them to improve it.

4. Improve SEO

Improve SEO  Source - Pixabay
Improve SEO

Another important benefit of using Web Analytics is that it helps in improving SEO for the site. It Helps in identifying issues like slow loading, browser or OS issues.

Landing pages that are getting most of the organic traffic for the site.

Metrics like bounce rates, landing page report, exit page report etc can also be used to measure the quality of pages. Google Analytics can also help in identifying new opportunities.

For example: Identifying keywords for which you have a good position but poor CTR. Using this insight, a business can improve the content for that keyword and thus improve CTR.

In order to get access to this data, one must link Google Analytics with Google Search Console.

5. Improve PPC Performance

Improve PPC Performance Source - Pixabay
Improve PPC Performance

Another important benefit of using Web Analytics is that it helps in optimising the performance of Google ads by providing the enhanced remarketing capability, import of goals, analytics remarketing audience and ecommerce transactions directly into Google Ads account.

It can also help to track the behaviour of the customer on the website after an ad click or impression in order to use these features, one must link Google Analytics with Google Ads.

6. Identify Pain Points

Identify Pain Points Source - Pixabay
Identify Pain Points

When it comes to providing great user experience all the pain areas of the website must be rectified and Web Analytics helps a business in identifying them.

Reports like exit page reports, site speed report, device, browser and OS report etc. These reports help in identifying the pain area of the website and thus help in rectifying them to improve the user experience of the visitors.

7. Optimise Conversion Funnel

Optimise Conversion Funnel Source - Pixabay
Optimise Conversion Funnel

Using Web Analytics, we can set a number of goals which are important for the business these can be signing up for the newsletter, buying a product, register for a demo of product etc.

While creating a goal we write down each and every step that a user must take to successfully complete goal on the site.

Google Analytics through funnel visualization helps in identifying how many visitors who enter the funnel gets successfully converted(Complete the goal).

This helps a business to identify at which point of the funnel the customers are getting dropped out.

Using this data, a business can identify any issues that might be present on the site or particular pages of the site that are leading to drop out of customers from the funnel and thus solve these issues so that maximum number of customers in the funnel is successfully converted.

 

Data Reporting  Source - Pixabay
Data Reporting

8. Data Reporting

Refining and optimization of data are necessary before its use. Using Web Analytics, a business can not only refine the data but helps in the visual representation of this data so that it can be easily understood.

Google Analytics has a variety of viewing options like:

a. Data View: Tabular representation of data

b. Percentage View: Representation of data as a pie graph

c. Performance View: Bar graph representation of data.

d. Comparison View: It allows to see whether each metric in the table is performing above or below average.

e. Pivot View: Creates a pivot table.

Besides this Google Analytics allows creating custom reports a report that can be customized based upon needs.

Conclusion

Web Analytics is a very useful tool that not only helps in understanding our audience but also helps you discover business insights that might not be visible directly.

No business can ignore Analytics if they want to provide a great user experience to its visitors as well as gain access to business insights.

If you like my post or have any question or suggestion feel free to write to me about it in the comment section below.