Some of the insights and predictions you can find in DataLakeHouse to take the guesswork out of business decision making.

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The sole purpose of collecting data is to derive useful insights and predictions from it that can help you make the best business decisions possible. What data you’re collecting and what you’re hoping to discover from it are largely dependent on the industry and department you’re in. For example, if you’re in retail, the information you care about is most likely not going to be the same as an organization in the transportation and logistics sector. This is why having a data model specifically built for your industry is absolutely necessary.   

Aside from getting a holistic view of your business that will enable you to determine how specific operations affect other factors (which is a pretty big deal, if I do say so myself!), here’s a look at the kind of insights and predictions you can expect to get from DataLakeHouse, based on the industry and department your in:

Retail & Restaurants –

  • Possible causes of shrinkage 
  • Predetermination of SKUs to keep in stock and when they should be ordered 
  • Best & worst performing locations & distribution channels
  • Upselling performance of staff members
  • Key areas of concern for improving service & offerings
  • Highest and lowest selling items
  • Best customers & the best ways to reach them 
  • Product & service suggestions for customers 
  • Suggestions for menu items & product components that require pricing adjustments
  • Internal & external factors affecting consumer spending

Transportation & Logistics – 

  • Which drivers are most efficient
  • Options for mitigating safety issues 
  • Optimal routes for lowest fuel spend & on-time deliveries
  • Key areas of concern for improving customer service
  • Determine the best ways to keep up with demand
  • How to prevent high turnover
  • Number of active & working trucks within specific timeframes 
  • Number of trucks in need of repairs

Banking & Finance – 

  • Predicting loan delinquency 
  • Customer churn prediction
  • Credit card fraud detection
  • Credit scoring for loan approvals & denials
  • Predicting trends & sentiment analysis for traders and investors 
  • Issues with ID & biometric authentication in mobile banking apps that require attention
  • Key areas of concern for improving service & offerings
  • Recommendations for increasing customer retention

Marketing & Sales – 

  • Where your best traffic is coming from in terms of conversions
  • Best platforms for gaining consumer engagement & loyalty 
  • High and low performing content 
  • Customer demographics of highest and lowest spenders for more accurate targeting
  • Best customers & the best ways to reach them 
  • Product & service recommendations for target customers 
  • Improve targeting strategies
  • Suggestions for menu items & product components that require pricing adjustments
  • Best & worst selling products & services 
  • Competitive analyses
  • Create alignment with buyer personas
  • Determine the best ways to improve return on advertising spend (ROAS) 
  • Recommendations for increasing customer retention
  • Internal & external factors affecting consumer spending
  • Possible ways to improve customer sentiment 

… And that’s not even the tip of the iceberg 🤯 Really, I could go on and on!

To learn more about some of the insights and predictions DataLakeHouse can offer your business, contact one of our data experts for a demo 👇

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