LV= reduces data processing hours and time to high-quality insights for decision-making
Industry
Finance
Company size
Large
Region
EMEA
Destinations
Power BI
Adverity Insights
Key results achieved by Liverpool Victoria (LV=)
Up to 10 hours saved per week in manual data processing
Automating the data integration process LV has reduced the time it takes to process data from multiple data sources
Access to real-time insights
A streamlined data integration process has removed the lag between the data and insights, LV now has access to insights much faster
More accurate decision-making
Without the need for manual data manipulation, they gained increased confidence in the accuracy of their decision-making
Challenges
Having accurate and timely data is important to the success of a marketing data and analytics team, this enables them to deliver meaningful insights that help the business make real-time decisions.
However, for LV’s marketing data and analytics team, this was not easy to achieve. They were working with data from multiple sources, manually extracting and cleansing it, and organizing it onto spreadsheets. This involved large amounts of manual work, which was time-consuming and prone to human error resulting in disparities when reading the data to provide meaningful and timely insights. Paul Mabb, LV’s Trading Manager - Marketing Analytics expressed that “Merging data from different sources with a singular output was extremely difficult or near impossible.”
"Adverity has enabled us to present and interpret our data in a way that aids cognitive understanding, our insights are much clearer."
Paul Mabb
Trading Manager - Marketing Analytics, Liverpool Victoria (LV=)
Adverity's impact
With Adverity’s large library of pre-built connectors, LV= now automates the integration of all its marketing data from multiple data sources. They utilize Adverity’s transformations to clean and harmonize the data, allowing them to confidently report multi-channel marketing performance with high-quality insights.
LV= has seen a decrease in time spent managing data, saving up to 10 hours a week on manual data wrangling. This has significantly reduced the duration it takes for them to visualize and extract insights from their data, enabling quicker and more accurate decision-making regarding their channel mix and marketing spend.
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