The multi-touch attribution (MTA) landscape is complex, spanning a plethora of statistical models and a wide variety of vendors. Equally, brands are fully aware of the importance of accurate attribution to understand their audience and deliver on their business goals. After all, the average consumer visits a retailer’s site 9 times before purchasing and the majority of shoppers use multiple channels on their path to purchase. So what should businesses look for when assessing MTA vendors?
Attribution models range greatly in their efficacy and complexity, beginning with simple rules-based models such as last-click. Many vendors still use rules-based models as standard and these can certainly serve a purpose as an out-of-the-box solution. This is especially the case if brands can apply some level of customization to these models, too.
Nonetheless, there is a widespread understanding that these models simply cannot reflect the multifaceted paths to purchase that the modern consumer takes.
Data-driven attribution (DDA) provides a much more accurate look at individual customers at scale. It can achieve this by processing billions of data points to identify patterns that lead people to take certain actions. By comparing and contrasting the marketing channels that they have interacted with, it can isolate and quantify the importance of each factor in the decision-making process.
There are critical business questions that more sophisticated attribution can help you answer. For example:
Although rules-based attribution vendors tend to offer less expensive solutions, the investment in DDA will reap rewards through its increased accuracy.
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