COVID-19 Mobility Movement.

  • >80 %
    2-Week Prediction Accuracy of Store Footfall & Revenue
  • 100 %
    Australian Coverage across 291 Sub-Regions

COVID-19 has induced a level of disruption and uncertainty into the marketplace with incomparable effect. The aberration of normal life has problematised marketing confidence and willingness to spend within media platforms.

Telstra requested of Resolution: an analysis of available data signals in order to relativise their stores’ performances, across different regions, with reference to “the new normal” induced via the pandemic.

Through data manipulation and bespoke algorithms, these signals have been integrated into a dashboard and cross-matched against the Vita store locations. This has given the client the ability to interrogate COVID-19 data on a suburb-by-subject, state-by-state or national basis; and infer store performance relative to the uncertainty induced during the pandemic.

How can we help you achieve Remarkable Results?

  • Challenge

    Telstra requested of Resolution: an analysis of available signals in order to relativize their stores’ performances, across different regions, with reference to “the new normal” induced via the pandemic
  • Solution

    Engineered a bespoke algorithm to quantify “Abnormality” levels per suburb, per state, and per nation. Based on Google’s raw data with weighted modifiers that are self-taught by the algorithm (supervised A.I.). Cross-mapped signals across relevant Telstra store locations with the client’s internal metrics. Dashboarded for ease of use.

Predictive A.I. Model and Dashboarding

This “uncertainty” was quantitatively defined using a custom-built algorithm. Data signals provided by Google were converted into a newly defined metric: “Abnormality Factor” – allowing Resolution to quantitatively determine how abnormal a population is behaving on a suburb-by-suburb basis.

This metric was been mapped onto individual Telstra store locations with noted 1-2 week “time lags” between Abnormality Factor and an individual store’s foot traffic and revenue data. Accounting for the time lag, the correlation factor between these metrics was recorded at above +0.8. This allowed Resolution to accurately predict a store’s performance 1-2 weeks in advance and quickly inform the client of any marketing potential or waste accordingly. This helped to counteract the uncertainty and volatility of human behaviour rendered by COVID-19; and ensure that marketing spend still maintained a positive ROI during the pandemic.
This is so fantastic! We’ll definitely use this data to guide our store selection!
Alex Peisker , National Marketing Manager , Vita Group

Topics

  • Case Study
  • Health
  • Programmatic
  • Google
  • Google Ads
  • Google Agency of the year
  • Google Marketing Platform

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