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Getting Better Insight into the Competitive Retail Sector with Data Analytics
By Alexandra Gray, Head of Research, Mirvac
So too does social media data, which offers an ability to synthesize the voice and attitudes of customers—both positive and negative—in their local community environment. The availability of reliable expenditure data at a category level has been a step change in gauging the underlying spending patterns of our customers. We can now more accurately understand sales leakage to other retail competitors, including online stores, enabling us to pivot and adjust our retail mix. We are exploring mobility datasets that enable us to zero in more effectively on where our customers come from and the patterns of when they frequent our centres, both day of week and time of day. Understanding the origin of customers and when they frequent, is particularly valuable for trade areas with transient populations including the worker, student or tourist visitor; alongside a resident catchment. While the benefits of better understanding of our customers is substantial, expanding our capability with data analytics offers additional value. We are exploring ways to target key customer groups, track the effectiveness of campaigns and the true return on investment of campaign spend. By learning with greater frequency and accuracy we can adjust and apply insight across other assets in the portfolio. Front-end visualisation tools are just as vital as the data itself. While some are available through proprietary portals, more and more are brought in-house for us to consume through business intelligence platforms. Also visualising geospatial information from both open source and proprietary data through cloud-based Software-as-a-Service platforms like Carto means we can build customisable and engaging location intelligence applications, which synthesize huge amounts of data, scalable across the organisation. Information silos begin to break down, internal learnings and our capability with data increases, time is expedited, and cost is reduced as dependency on consultants decreases. Still the challenges of moving to a data-savvy environment are many. Datasets in mobility, expenditure, social media for example, are relatively new and require careful evaluation and consideration of cost and benefits, given limited resources. They also require embedding in an organization’s digital architecture, strategy, and processes for decision making. New skillsets and talent are required for back-end programming and development work, while front-end development skills and interpreters that liaise with business stakeholders are also just as vital. At Mirvac, we know there will never be a one-stop shop for data and information. For us, it is about joining the dots. As we make these step changes to using big data and analytics to curate our experience-led retail spaces, a high performing and engaged culture that encourages everyone to ‘be curious’, is the real vital ingredient to success.