REaD Group and More Metrics have partnered to create a number of COVID-19 risk datasets that explore the risk factors and infection rates at a range of local geographies.
More Metrics has used existing and new datasets to create 14 risk measurements relevant to COVID-19, including Age and Household Composition.
More Metrics will update the data on a weekly basis to enable the track of infection rates at a local level over time across the UK.
Award-winning data and insight company REaD Group and data analytics specialists More Metrics have partnered to create a number of COVID-19 risk datasets that explore the risk factors and infection rates at a range of local geographies.
More Metrics has created a new set of data models that explore the impact of COVID-19. REaD Group can advise marketers on how to apply the available data to make sensible, sensitive decisions and inform their marketing strategy, supporting data-driven decisions and responsible marketing.
More Metrics uses a wide range of data to create models at both postcode and individual/solo level. These models can help brands ensure they are targeting their marketing messages, optimising contact with customers and increasing ROI. Data used to create these models is publicly available and generally focuses on health and wealth factors – ideal for the current situation.
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More Metrics has used existing and new datasets to create 14 risk measurements relevant to COVID-19, including Age and Household Composition: Mortality and Co-Morbidity; Economic Resilience; Risk Engagement and Infection Rates.
The comparison of risk factors and infection rates at a local level suggests that there are associations between the two. For example, the datasets have shown:
• High infection rates are dominated by London and occurring in locations with higher overcrowding risks and higher overall engagement risk (this could mean a less rigorous adherence to lockdown advice in these locations)
• One reason for the high infection rates seen in London is due to timing. London was infected early before lockdown measures came into force whereas many other areas were in lockdown before the infection took hold.
• When we account for this timing effect, we estimate that neighbourhoods across the country with a similar geo-demographic mix are just as likely to be affected as each other. Neighbourhoods with residents who live in more overcrowded conditions and/or use public transport more and/or have a higher proportion of workers in industries engaging with the general public are most at risk of high COVID-19 infection rates.
Brands and marketers will be able to use these datasets for:
• Screening to deselect vulnerable consumers for campaigns
• Attaching codes to inbound contact data to understand the consumer they are talking to
• Adding the data to models to ensure these factors are considered when selecting consumers for campaigns
The data is available at a range of different geographic levels: the application of each is dependent on usage. At the lowest level the models are created at OA (Output Area) level and can be attached to any individual or household with a postcode: the recommended level for most marketing applications. More Metrics will update the data on a weekly basis to enable the track of infection rates at a local level over time across the UK.
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About REaD Group:
REaD Group is a marketing data and insight company that gives brands the right to be personal. Data – particularly quality data and data quality –is at the heart of everything it does: REaD believes that there isn’t a marketing challenge that data cannot solve.
To genuinely engage customers, brands must create communications that are timely, relevant and permissioned. REaD uses its unrivalled data products, insight and expertise to helps its clients get closer to their customers, offering market-leading data quality and cleaning solutions and trusted marketing data.
About More Metrics:
More Metrics is a specialist in the application and delivery of Open Source Data, data which is non-personalised and typically provided by Government and other public bodies. This makes its output GDPR friendly and therefore quick and easy to use.
It has developed a modelling process over many years that analyses the millions of raw data fields to produce a range of postcode tagged data sets covering family finances, health and lifestyle and attitudes on key social issues.