Data-Driven Attribution and How it Differs across Google Products
According to Gartner, about 74% of CMOs expect to spend more on digital advertising in 2021 than they did in 2020. But how can you assess your channels to know exactly where to invest more? Which ads make potential customers move to the next step of the funnel?
The solution is hidden in attribution — how the value of a conversion is distributed across channels that move the user through the funnel. However, some attribution models show you only part of the picture. And these gaps in data might be critical. After all, according to the rule of seven touches, the actual purchase frequently happens only at a customer’s eighth interaction with a brand. However, all steps affect one another and eventually lead to the conversion. So how can we objectively assess the conversion path?
As an ad giant, Google offers multiple attribution solutions, from standard attribution models to advanced options with the possibility to track multiple channels. In particular, several products allow you to set up a Data-Driven Attribution model that will help you dive deep and accurately credit marketing channels.
But how can you decide which service will best fit your business? What’s the difference between Google Ads and Search Ads 360? In this article, we review and compare the most popular products that offer Data-Driven Attribution.
Choose the attribution model that best suits your business goals. In OWOX BI, you can connect any standard attribution model to your reporting, set up a data-driven model based on OWOX conversion forecasting, or a custom model to fit your needs and your sales funnel.
Table of contents
- What’s Data-Driven Attribution?
- Data-Driven Attribution with Google Analytics 360
- Data-Driven Attribution with Google Ads
- Data-Driven Attribution with Search Ads 360
- Attribution with OWOX BI
What’s Data-Driven Attribution?
Data-Driven Attribution (DDA) by Google focuses on your advertising account’s data as a unique starting point for analysis. Unlike standard models with predefined formulas, DDA uses algorithms to analyze every case differently and assess the mutual influence of channels in the funnel, even if it is complicated, inconsistent, and multi-step.
To satisfy various business needs, Google offers DDA in a range of services. The differences between these services are in the data analyzed, the algorithms applied, and the level of customization. Some of them are designed only to track ad clicks and optimize keywords and paid campaigns, whereas others provide a full analysis of a customer’s online journey.
Before selecting a particular product, consider the following:
- What’s your advertising budget?
- What are your business goals?
- How many conversions do you have on average every month?
Now, let’s take a closer look at what products Google offers that include Data-Driven Attribution.
Data-Driven Attribution with Google Analytics 360
With Google Analytics 360, you can use Multi-Channel Funnels (MCF) Data-Driven Attribution based on the Shapley Value method. This algorithm analyzes the path of your users through existing touchpoints, then creates an alternative variant where one of the touchpoints is missing. This shows you exactly how a specific channel influences the probability of a conversion.
Data-Driven Attribution assesses data from organic search, direct traffic, and referral traffic along with all the data that you’ve imported to Google Analytics, including data from other Google products (e. g. Google Ads, Campaign Manager 360). With DDA in Google Analytics 360, you get an overview of all users’ online actions in your funnel and how each channel influences conversions. This option is most suitable for large websites with high volume of conversions.
Let’s check Google Analytics 360’s minimum requirements for using DDA along with the pros and cons of DDA in this tool.
- A Google Ads account with 15,000 clicks and 600 conversions during the past 30 days
- Ecommerce Tracking or Goals must be set up
If you meet these requirements, you can start using DDA in Google Analytics 360. To keep using it, you have to meet the following minimum conversion threshold for the past 28 days:
- 400 conversions of each type with a path length of at least two interactions
- 10,000 interaction paths in a specific view
Pros of DDA in Google Analytics 360:
- Get a full analysis of a customer’s online journey
- See which ads, keywords, and campaigns have the biggest impact on conversions
- Distribute credit for revenue based on past data for a conversion
- The amount of credit assigned to each touchpoint depends on order of touchpoints
- Data analysis starts immediately, and the report on your first model becomes available within 7 days
Cons of DDA in Google Analytics 360:
- High cost of an account: starts at $150,000/year
- Hidden calculation logic: no explanation in the report
- Requires a consistently high number of clicks and conversions
- Doesn’t include offline data (phone calls, transactions in CRM)
- Requires a Google Ads account
See also: Google Analytics Attribution Models: Detailed Review and Comparison.
Data-Driven Attribution with Google Ads
The default attribution model in Google Ads is last click, but if you meet the minimum requirements you can configure Data-Driven Attribution. By default, data-driven attribution analyzes all clicks on your ads but not the entire customer journey. Based on these clicks, the model compares users who purchase to those who don’t and identifies patterns among those ad interactions that lead to conversions. To increase the number of conversions, you can use an automated bidding strategy that’s optimized based on information from the DDA model.
This product is suitable for medium-sized and bigger businesses that need to optimize marketing campaigns and keywords.
To learn more about DDA in Google Ads, see this official YouTube video on using data-driven attribution for Google Search.
Now, let’s get to the minimum requirements and compare the advantages and disadvantages of using DDA in Google Ads.
- 3,000 ad interactions in supported networks in the past 30 days
- 300 conversions in the past 30 days
To continue using this model, you have to meet the following minimum conversion threshold for the past 30 days:
- 2,000 ad interactions
- 200 conversions
Pros of the DDA model in Google Ads:
- Helps you optimize keywords and paid campaigns
- Helps you optimize bidding
- Shows which ads play the most important role in reaching your business goals
Cons of the DDA model in Google Ads:
- Don’t get the entire overview of the online user journey
- Need to maintain the necessary level of conversions and clicks for 30 consecutive days before you can see data in Google Ads
- If your data drops below the required minimum, the attribution model will automatically be switched to Linear
Data-Driven Attribution with Search Ads 360
Search Ads 360 helps you manage marketing campaigns across multiple engines (Google Ads, Microsoft Advertising, Yahoo! Japan Sponsored Products, Baidu, and Yahoo! Gemini) due to native integration with the Google Marketing Platform.
By default, Search Ads 360 uses the last click attribution model, but you can also configure DDA if you meet the minimum click and conversion requirements. Unlike Google Analytics 360 and Google Ads, Data-Driven Attribution in Search Ads 360 analyzes activities in Floodlight, the conversion tracking system for the Google Marketing Platform. The attribution focuses on paid marketing campaigns and shows you how clicks on keywords influence conversions. You can also adjust or create a new bid strategy that will automatically optimize bids based on the model’s data.
The Search Ads 360 service is suitable for websites with a high number of conversions who need to optimize their paid campaigns.
Let’s see the minimum requirements for and the pros and cons of using data-driven attribution with Search Ads 360.
- 15,000 clicks in the last 30 days
- 600 conversions in the last 30 days
Pros of using DDA in Search Ads 360:
- Get reporting data in near real time
- Optimize bids automatically using Smart Bidding technology together with DDA
- Create up to five DDA models to compare data with different channel groupings
- Possible to upload offline conversions
- Accounts for cross-environment conversions
Cons of using DDA in Search Ads 360:
- Ignores search and display impressions
- Might be not fully accurate: Search Ads 360 uses machine learning and historical data to model the number of conversions if it’s not possible to measure all conversions
- Only tracks the number of conversions attributed to paid search
- Additional setup required to realize all advantages: Campaign Manager, a set of Floodlight activities, and Search Ads 360 Natural Search reporting
- Impossible to analyze conversions tracked by Google Ads, Google Analytics, or other conversion tracking systems
Attribution with OWOX BI
Google’s Data-Driven Attribution model is one algorithmic model that can ensure a granular approach to analyzing your data. Just like data-driven attribution by Google, OWOX BI ML Funnel Based Attribution assesses the effectiveness of your advertising campaigns and channels on the customer’s way through the funnel. It also provides you with real-time reports and allows you to import calculations to optimize bids.
Unlike the Google model, however, OWOX BI attribution is based on Markov chains — a sequence of events in which each subsequent event depends on the previous. Using this algorithm, OWOX BI attribution shows how difficult it is to move from one step to another: the higher the difficulty of moving on from a step, the greater the value a channel receives.
On top of that, due to transparent calculations, you get a solid understanding of the figures behind each report so you can safely reallocate your budget. Finally, in comparison with Google products, attribution by OWOX BI provides meaningful results with smaller amounts of data required for analysis.
Let’s take a look at what you get with OWOX BI attribution.
The minimum number of conversions depends on the number of sessions. For objective results, we recommend the following correlation between sessions and conversions:
Pros of OWOX BI ML Funnel Based Attribution:
- Track a user’s offline actions
- Control purchases and returns in your CRM
- Assess the effectiveness of each advertising channel
- Customize your funnel according to your business needs
- Exclude unmanaged channels from your assessment
- Compare funnel stages and evaluate their effectiveness
- Analyze data based on thousands of projects with machine learning
- Figure out a specific approach for each user cohort
- Get ready-made reports in OWOX BI Smart Data
- Use gathered data to manage bids and audiences
Book a free demo to see how the OWOX BI Funnel Based Attribution model can be useful to your business.
Google products that offer Data-Driven Attribution allow you to track different channels, determine which online ad is the most and least effective in Google Search, and analyze users’ online journeys in detail. Even though Data-Driven Attribution by Google is generally considered as one model, its implementation differs across products. To effectively measure data, you need to choose a service that fits your data type. Here are the primary focuses of each product:
- Google Analytics 360 tracks all user actions, clicks, and displays based on multiple channels and their interrelations in the funnel.
- Google Ads tracks ad clicks in Google Search.
- Search Ads 360 tracks Floodlight activities and paid campaigns.
With OWOX BI, you don’t have to select among several services. You can get the benefits of Data-Driven Attribution by Google with transparent calculations on top and fewer minimum requirements all in one product.
What does attribution mean in advertising?The goal of attribution in advertising is to define how the value of a conversion is distributed across channels that move the user through the funnel.
What is the attribution model?An attribution model is a set of rules that define how conversion credit is assigned to different touchpoints in conversion paths.
What is the attribution problem?The following difficulties may occur when working with attribution:
1. You need to collect data manually from various advertising platforms
2. You have to consistently update existing models: outdated models won’t fit the new business requirements
3. It’s difficult to change strategies fast if you have fixed budgets and partner contracts with advertising agencies