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How ColgatePalmolive Accelerated Adcampaign Optimization - Adverity Industrial IoT Case Study
How ColgatePalmolive Accelerated Adcampaign Optimization
Colgate-Palmolive's Online Acceleration Center of Excellence in London was focused on transforming its digital offering in markets throughout the EU. However, reporting on key digital advertising parameters was largely manual. Local media teams logged into various ad platforms, collected data, and inserted them into Excel templates to create bi-weekly reports. These reports were then sent to brand managers in respective markets and the local agency teams, with no automated flow of information. The process was slow and time-consuming, involving over 25 people in the EU region. Furthermore, the data was practically out of date by the time it arrived with the analysts and decision makers. The reports were distributed via email, clogging up inboxes and increasing the possibility of a data discrepancy.
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A76ers’ Data Intelligence SLAM-DUNK - Adverity Industrial IoT Case Study
A76ers’ Data Intelligence SLAM-DUNK
The Philadelphia 76ers, a part of Harris Blitzer Sports & Entertainment’s (HBSE) portfolio, had a data ecosystem consisting of over 130 data sources. Managing and expanding this data infrastructure was becoming increasingly difficult and time-consuming. The process of connecting to a new data source could take weeks, severely limiting the bandwidth of the data team. The fixed timelines surrounding live events made flexibility and agility of data operations paramount. The existing data consolidation procedure was not scalable and was preventing the team from fully focusing on uncovering the insights the data could provide.
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IKEA Lays the Foundation for Future Growth by Unlocking Insights Within Its Data - Adverity Industrial IoT Case Study
IKEA Lays the Foundation for Future Growth by Unlocking Insights Within Its Data
IKEA Austria was facing challenges in consolidating data from various sources, which was crucial for understanding the needs of its customers and preparing for future growth. The company was dealing with multiple data sources and using the services of several agencies, which led to data silos and unavailability of data. Data quality was also a significant issue, with different KPIs and naming conventions used for campaigns on different channels, making reporting on campaign performance extremely difficult. The company was also facing challenges in terms of data accessibility, with global teams at IKEA having to wait for days, even weeks, for the information they needed.
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