Vizury’s solution determines the spike in website traffic and the period of impact for every ad slot across multiple channels, helping Urban Ladder identify and profile potential customers.
Vizury, a big data marketing company has announced its partnership with e-com player Urban Ladder to help measure the efficacy of the online furniture company’s television advertisements.
Vizury’s TV analytics solution determines the spike in website traffic and the period of impact for every ad slot across multiple channels, helping Urban Ladder identify and profile potential customers.
Using brand and third-party based behavioural data of visitors, Vizury creates customer personas that are most responsive to brand ads. For example, infotainment genre has better appeal to parents on Sunday evenings compared to other timeslots. Lifestyle and movies have better appeal to fashion enthusiasts on a Friday. The TV analytics solution also shows where these visitors are coming from, and which networks are the right channels to reach them. These insights are based on data mining campaign performance metrics such as source of the lead, moving averages, past engagement, etc.
Website visitors from campaigns such as mailers, display ads, social media outreach and others are isolated from this measurement using modelling techniques and algorithms. The algorithm monitors online behaviour and cross-references this with data on-boarded from all offline touch-points of the customer.
“As we increase our visibility on television, it is important to find the right tools to measure the effectiveness of the medium. Vizury’s new tool is useful to measure important data like traffic attribution to TV and plan optimal channel selection. We look forward to working with Vizury on this to help measure ROI on television effectively,” said Nikhil Ramaprakash, VP Marketing,Urban Ladder.
Vizury also recommends which channels and timeslots are working better to get maximum audience for the allocated budgets, as well as the frequency cap for cost optimization. The solution takes up the challenge faced by TRP (Television Rating Point) and GRP (Gross Rating Point) metrics for TV channels.