Data-driven attribution modelling allows you to connect the dots in scattered customer journeys and gain an accurate view into which digital channels and marketing campaigns are performing best. This means you can forget about wasted spend and invest only in strategies that yield solid ROI.
Our data science team can develop a bespoke model for you that will track conversions on as many marketing touchpoints as you need and help you fully document the role each of these plays in the customer journey. And we can do this at a fraction of the price of a Google 360 Analytics account.
We have 6-month roadmap for implementing data-driven modelling systems for our customers:
Phase 1: Data preparation
Our first task is to assess the levels of data maturity at your organisation, devise the best conversion tracking strategy and understand your goals and desired outcomes. Then we can start the data preparation process (warehousing, consolidation and validation) and develop a ‘first version’ data-driven attribution model. This can take up to 2 months with detailed reports provided after every milestone.
Phase 2: Intelligence
At this stage, we’ll further tweak and improve your data analytics system and move on to active analysis. You will start receiving a steady flow of actionable insights and regular intelligence about your customers’ journeys, conversions and various campaign performances.
Phase 3: Predictive modelling
Our team can also set up predictive analytics models that deliver powerful insights into campaign ROI, customer lifetime value, churn rates and more. This advanced level of modelling allows you to become a truly data-driven organisation with a significant competitive edge in your industry.
Data-driven attribution (DDA) is an attribution model in Google Ads that gives credit to touchpoints leading up to a conversion. So, instead of passing all credit to the last ad a user clicks, DDA uses data from your account to determine which ads, keywords and campaigns play the biggest role in achieving your conversion goals.
Yes. DDA is a setting in Google Ads but you can create your own data-driven attribution model using data from Google Analytics. In fact, a custom model is more flexible than the Google Ads version and the one we build for our clients uses data from every channel – not only Google Ads – to provide an overview of which campaigns and assets contribute to your conversions.
Definitely. Data-driven attribution prevents you from pulling assets and campaigns that contribute to conversions. Users rarely convert on the first ad they see or blog post they read but pulling these assets cuts off leads at the source. DDA calculates the contribution of each touchpoint leading up to the conversion so you can see the true value of each asset and identify underperformers.
If you sell a variety of related products, you’ll often find that customers click on multiple ads before making a purchase. With data-driven attribution, you may find that customers who first click on a product category ad (eg: women’s Nike running shoes) and, then, go on to click a product listing ad (PLA) for a specific product are more likely to convert than users who only click on the PLA.
In this case, data-driven attribution credits the first ad accordingly to prevent you from undervaluing its role in the conversion.
In Google Analytics, you can create a Multi-Channel Funnels (MCF) Data-Driven Attribution model that uses data from your Analytics account to credit touchpoints throughout the customer cycle. You can also pull in data from Google Ads and other platforms to attribute value across the entire funnel – so you can measure the true value of social media campaigns, blog posts and every other touchpoint.