Point of Sale Analytics
Analysis of the Point of Sale data enables retailers better analyze what is selling, when is it selling and where is it selling. Having access to this kind of information not only help retailers track their performance but also better forecast sales. For example if you knew in real time the impact of markdowns on black friday in the west coast you have three additional hours to fine tune your strategy for the east coast. While this sounds utopian, today’s new age tools can enable such analysis.
At one of the largest retailers, their merchandisers and buyers used to rely on traditional databases which provided them with daily and weekly reports. Which meant by time they got the information it was too late for them to react. They wanted to move away from their traditional data warehouse to a more real time analytical database which not only gave them live information but also enabled adhoc queries in seconds.
Deliver Actionable Impact

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For Merchandisers
  • With all data available in real-time, merchandisers can be more proactive in managing their business
  • Real-time access to data also allow merchandisers to test hypotheses and take corrective actions in timely manner
  • Merchandisers can observe trends before period closing and make strategic decisions armed with real data
For IT Department
  • With Sigmoid’s solution the IT staff can spend less time in data movement since the solution is Hadoop native
  • Since there is no cubing or pre-aggregation, the team need not spend time in creating cubes, aggregates, tables and data joins
  • Since the solution is completely scale-out the IT team can just add cores as the data volume increases

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For Analytics Team
  • All data and critical KPIs can be analysed within seconds based on real-time information instead of waiting for days to prepare reports
  • Analysts can drill down to any SKU or store level in seconds for granular anlaysis and observe trends over time
  • Since all the data is available, analysts have the flexibility to build their own reports without relying on other teams.
Point of Sale Analytics
Analysis of the Point of Sale data enables retailers better analyze what is selling, when is it selling and where is it selling. Having access to this kind of information not only help retailers track their performance but also better forecast sales. For example if you knew in real time the impact of markdowns on black friday in the west coast you have three additional hours to fine tune your strategy for the east coast. While this sounds utopian, today’s new age tools can enable such analysis.
At one of the largest retailers, their merchandisers and buyers used to rely on traditional databases which provided them with daily and weekly reports. Which meant by time they got the information it was too late for them to react. They wanted to move away from their traditional data warehouse to a more real time analytical database which not only gave them live information but also enabled adhoc queries in seconds.
For Merchandisers
  • With all data available in real-time, merchandisers can be more proactive in managing their business
  • Real-time access to data also allow merchandisers to test hypotheses and take corrective actions in timely manner
  • Merchandisers can observe trends before period closing and make strategic decisions armed with real data
For IT Department
  • With Sigmoid’s solution the IT staff can spend less time in data movement since the solution is Hadoop native
  • Since there is no cubing or pre-aggregation, the team need not spend time in creating cubes, aggregates, tables and data joins
  • Since the solution is completely scale-out the IT team can just add cores as the data volume increases
For Analytics Team
  • All data and critical KPIs can be analysed within seconds based on real-time information instead of waiting for days to prepare reports
  • Analysts can drill down to any SKU or store level in seconds for granular anlaysis and observe trends over time
  • Since all the data is available, analysts have the flexibility to build their own reports without relying on other teams.