What are the benefits and challenges of using attribution models for e-commerce ROI analysis?

1 What is e-commerce ROI?

E-commerce ROI is the ratio of net profit to marketing costs for your online store. It tells you how much money you earn for every dollar you spend on marketing. For example, if you spend $100 on marketing and generate $300 in net profit, your e-commerce ROI is 3:1 or 300%. E-commerce ROI helps you evaluate the effectiveness and efficiency of your marketing strategy and optimize your budget allocation.

4 What are attribution models?

Attribution models are methods of assigning credit to different marketing channels and touchpoints for influencing a customer's purchase decision. They help you understand how your customers interact with your online store and how your marketing efforts contribute to your e-commerce ROI. There are various types of attribution models, such as last-click, first-click, linear, time-decay, and position-based. For example, with last-click attribution, the last channel or touchpoint that the customer used before making a purchase would get all the credit for the sale. With first-click attribution, the first channel or touchpoint that the customer used to discover your online store would get all the credit for the sale. With linear attribution, all the channels and touchpoints that the customer used along their journey to purchase would each get equal credit. With time-decay attribution, the channels and touchpoints that are closer to the purchase would get more credit than the ones that are farther away. And with position-based attribution, the first and last channels and touchpoints that the customer used would get more credit than the ones in between.

5 How to choose an attribution model?

Choosing an attribution model depends on your business goals, marketing strategy, and data availability. There is no one-size-fits-all solution, and you may need to use different models for different purposes. When selecting an attribution model, consider your customer journey, marketing objectives, and data quality. How long and complex is your customer journey? How many channels and touchpoints do your customers use before making a purchase? What are your marketing objectives and key performance indicators (KPIs)? How accurate and reliable is your data? How do you collect and integrate your data from different sources and platforms? How do you measure and optimize your marketing campaigns and channels? How do you align your marketing efforts with your business goals? How do you deal with data gaps and limitations?