Urban Ladder to measure its ads with Vizury's analytics

BANGALORE, INDIA: Vizury has announced its partnership with 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.

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 time slots 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. Companies can now get an in-depth understanding about their advertisement campaigns.

Vizury’s TV Analytics addresses three major problems faced in television advertising. The first problem is that they are based on input from predefined sample population which is then extrapolated. The sample sizes for these surveys are small and often extremely skewed.

The second problem is that the data provided by TRP is for the program or slot and is not for the brand. This means TRP cannot provide data specific to individual brands and micro-segments who view them, hence it’s not the right measure for ROI.

The third problem is user behaviour. Questions like: ‘to whom is my ad appealing (persona) and how are they interacting with the brand?’ remain unanswered. These metrics cannot shine light on customer Life-Time-Value and conversion behaviour.