Roundtable Discussion; The Future of Mineral Sands. Watch the video here.
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this is all interesting. LSAI are primed for the future. MS is a leader in this sector and is fully aware of the obstacles.
From ‘where’ to ‘why’: Marketers’ use of location data becoming increasingly sophisticated
But numerous operational challenges stand in the way of full utilization.
Greg Sterling on February 24, 2020 at 3:00 pm
According to data from 451 Research, 98% of marketers surveyed said they were now working with location data in some form. Beyond this, they’re moving from basic uses (geo-targeted ads) to increasingly sophisticated use cases such as audience insights, personalization and attribution.
Changing location-data mindset. Time is a key variable in how companies think about the utility of location. “Instead of trying to reach consumers at the moment when they cross a threshold into an advertiser’s location, modern campaigns focus on re-engaging infrequent visitors, finding new customers to win market share, or rewarding loyal ones,” writes 451 in a report called “Finding Real Enterprise Value in Location Data,” commissioned by Cuebiq.
The report identifies five stages of sophistication regarding location-data utilization:
Planning. These companies are just getting started, either by exploring different options or putting together ideas or proofs of concept to determine what might work in their organization.
A defined set of goals and plans, focused on an organized process for leveraging location data, and a solid understanding of the benefits (and how to measure them).
Managed processes that is based on a formal program for incorporating location data into marketing plans.
Strong, quantifiably measured program, with metrics that measure business outcomes.
Fully mature, leading-edge company that uses location data for sophisticated tasks like attribution, audience targeting and analytics, and considers itself to be best in class among its competitors.
While many marketers surveyed expressed a desire to integrate online and offline data, there are numerous operational challenges standing in the way. This is partly about the limitations of their technology infrastructures and partly about the challenges of integrating data sets with differing collection methodologies.
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