Wizaly is a relatively new entrant in the field of algorithmic revenue attribution – a function that will be essential for guiding artificial-intelligence-driven marketing of the future. Let’s take a look at what they do.
First a bit of background: Wizaly is a spin-off of Paris-based performance marketing agency ESV Digital (formerly eSearchVision). The agency’s performance-based perspective meant it needed to optimize spend across the entire customer journey, not simply use first- or last-click attribution approaches which ignore intermediate steps on the path to purchase. Wizaly grew out of this need.
Wizaly’s basic approach to attribution is to assemble a history of all messages seen by each customer, classify customers based on the channels they saw, compare results of customers whose experience differs by just one channel, and attribute any difference in results to that channel For example, one group of customers might have seen messages in paid search, organic search, and social; another might have seen messages in those channels plus display retargeting. Any difference in performance would be attributed to display retargeting.
This is a simplified description; Wizaly is also aware of other attributes such as the profiles of different customers, traffic sources, Web site engagement, location, browser type, etc. It apparently factors some or all of these into its analysis to ensure it is comparing performance of otherwise-similar customers. It definitely lets users analyze results based on these variables so they can form their own judgements.
Wizaly gets its data primarily from pixels it places on ads and Web pages. These drop cookies to track customers over time and can track ads that are seen, even if they’re not clicked, as well as detailed Web site behaviors. The system can incorporate television through an integration with Realytics, which correlates Web traffic with when TV ads are shown. It can import ad costs and ingest offline purchases to use in measuring results. The system can stitch together customer identities using known identifiers. It can also do some probabilistic matching based on behaviors and connection data and will supplement this with data from third-party cross device matching specialists.
Reports include detailed traffic analysis, based on the various attributes the system collects; estimates of the importance and effectiveness of each channel; and recommended media allocations to maximize the value from ad spending. The system doesn’t analyze the impact of message or channel sequence, compare the effectiveness of different messages, or estimate the impact of messages on long-term customer outcomes. As previously mentioned, it has a partial blindspot for mobile – a major concern, given how important mobile has become – and other gaps for offline channels and results. These are problems for most algorithmic attribution products, not just Wizaly.
One definite advantage of Wizaly is price: at $5,000 to $15,000 per month, it is generally cheaper than better-known competitors. Pricing is based on traffic monitored and data stored. The company was spun off from ESV Digital in 2016 and currently has close to 50 clients worldwide.