To reiterate from the previous post, attribution helps marketers get the most from their marketing efforts, by understanding the customers’ journey and identifying valuable touch-points that lead to conversions. This information is critical to creating more effective ad campaigns and boosting revenue. Data-driven attribution is the state-of-the-art attribution technology that enables companies to accurately analyse marketing performance and optimise campaigns to achieve maximum ROI.
What Is Data-Driven Attribution?
Unlike the rule-based attribution models discussed in the previous post, data-driven attribution doesn’t use a pre-defined model to assign credits to each touch-point. Instead, it uses machine learning technology to create a custom model for each business based on data that reflects the actual customers’ journeys.
Traditional rule-based attribution only evaluates paths that lead to conversions. In contrast, data-driven models consider both the converting and non-converting paths. This enables marketers to assess how each touchpoint increases the likelihood of a customer converting rather than merely allocating credits to the conversion path touch-points based upon predefined rules. As a result, data-driven processes provide a more comprehensive and accurate attribution evaluation.
What Are the Benefits of Data-Driven Attribution?
The main benefit is that it helps marketers better understand how customers interact with their brands across various channels and marketing programs, and how each touchpoint contributes to conversion. With a clear view of the entire customer journey, marketers can quickly analyse the performance of every touchpoint to determine how effective each step of the campaign is.
Data-driven attribution requires a robust platform that can quickly automate the analytics and provide useful reports for internal sharing. Gathering the data is just the first step in making sound marketing decisions. Until that data transforms into actionable items that the marketing team can leverage and improve upon, its value will not be fully realised. That’s why the reporting section of your attribution platform is a vital element to assess before signing on to a specific solution. Reports should be easy to understand to ensure your entire company can make sense of the findings and get on board with your marketing efforts.
Here are some ways that your marketing team can benefit from a quality data attribution platform:
Analyse your complete omnichannel campaign performance. Use reporting to gain a quick overview of your campaign performance, along with more detailed reports to understand how each channel and campaign affects the next.
Refine your budgeting strategies. Take action on the data you receive by adjusting your goals and optimising spending. With the precise information provided, you’ll be able to set new budget targets at every level of the campaign — down to the individual channels and ad programs.
Get one global perspective. When omnichannel is the norm, it’s important to have a tool that helps you visualise the global view of your marketing efforts, while also making it possible to zoom into the details, as needed. Customise your view to set specific metrics that reflect your goals. That will align your analysis with your priorities to ensure that you get the most value out of your efforts.
How Does Data-Driven Stack Up?
A Google study showed that data-driven attribution helped marketers grow conversions by 30% to 60% while reducing cost-per-conversion rates by 20% to 30% after adding this model to its AdWords product. This number increases as you expand your toolset to include platforms, like AdRoll, that can manage omnichannel marketing efforts in one integrated view.
In the past, attribution models were selected based on perceived consumer behaviors and could vary wildly from one marketer to the next, even within the same industry. Meanwhile, most ad campaigns default to last-click attribution, giving full credit to the last ad that a consumer clicks before conversion. Neither of these methods is ideal for getting accurate data or significantly improving conversion rates.
While other attribution models use basic analytics data, they only provide a template and often fail to account for important steps in the marketing funnel. With data-focused attribution, marketing teams can precisely map their unique attribution touch-points based on real customers’ historical information. This helps to ensure that the correct level of credit is assigned to each touchpoint.
What Do I Need to Know Before Implementing Data-Driven Attribution?
Switching from standard attribution to a data-driven model can have a lasting and impactful effect on your ad campaigns. While other models contain built-in bias for specific steps on the customer journey, data-driven attribution allows you to understand which among these touch-points are performing the best given your sales or conversion goals.
This model does require a certain amount of traffic to predict these paths accurately. The volume and quality of the information that you use are essential to creating a successful model, so it requires a significant amount of data to get started. Comprehensive and reliable analytics are the critical elements of a valuable attribution model. Here are some questions to ask before getting started:
How many visitors and conversions do we have?
How many channels and which programs do we want to include?
How long is the average customer journey?
What is the typical duration of the conversion path?
Is the data consolidated, and has it been cleaned?
With high-quality data fuelling your attribution strategy, your analytics will continue to improve over time, yielding better and more actionable results each subsequent month.
Attribution Platforms to Consider
When it comes to choosing your attribution platform, consider the following two options which provide vast tools for marketers looking to use data to make informed marketing decisions.
1. Google Analytics Attribution (Beta)
The new Attribution Beta tool, accessible near the bottom of the navigation menu in Analytics, supports data-driven attribution in addition to the other attribution models available in the multi-channel funnel. Data-driven attribution uses your company’s actual data to create a custom attribution model that is unique to your brand and audience. However, to create the data-driven attribution model, Google needs to collect data from at least 600 site conversions in a 30-day period. Here is a side-by-side comparison of MCF and the new Attribution Beta from Google Support. You can learn more about the Attribution Beta on this page.
2. AdRoll’s Attribution Platform
AdRoll’s marketing platform offers valuable cross-channel attribution tools that help marketers get to know their customers better. You can personalise and optimise your customer journeys across all marketing channels with Adroll’s powerful pixel that automatically captures UTM-tagged channels. Then, track your key performance indicators with high-level reporting and get granular insights that help you make data-driven decisions. With data collection and easy-to-understand reporting all in one place, you can do more in less time.
If you are looking for a platform that lets you instantly see your campaign results and make real-time changes to improve the customer experience and achieve your marketing goals, look no further. You can learn more about AdRoll’s attribution platform here.
Get Started With Data-Driven Attribution
The value that data-driven attribution contributes to your ad campaigns can provide sizable returns that increase the longer you use it. It’s a good idea to start small with the tools offered by Google and Facebook through their ad platforms. Use these tools to optimize your campaigns within their respective marketing channels. Once you become comfortable with these tools, you can expand to realise the full benefits of data-driven attribution when it’s applied across multiple channels.
While shifting from standard attribution to a data-driven model is straightforward, you’ll likely need to adjust certain items in your ad campaigns. Re-evaluate the keywords that you use along the buyers’ journeys, adjust your bids (especially for search-based ads), and give the attribution model time to flourish. With data-driven attribution, you’ll see results grow stronger as time passes, especially as you continue to refine your strategies.