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Data Specification

The Alviss AI application has a set of strict requirements on the types of data it can work with. This section will run you through the file formats, conventions, and assumptions that
this application is operating under. The application supports models, data, and insights on a granular level.

  • Alviss AI is a flexible platform that allows you to add various data sources you need for your specific business.
  • We support Sales, Price, Media, Customer Experience, Brand, Visits, Events, Macro, Competitor, and Weather data out of the box.
  • Each of these data sources needs to adhere to a specification in order for the platform to understand them.
  • While it’s possible and recommended to add all the data sources you can get your hands on, the only requirement is Sales. This means you can start out simple and move to a more complex setup later.

Data explanation

Alviss AI needs a number of data sources to function properly. The main data sources supported are:

  • Sales: The most important file, and actually the only one required. It contains the number of units sold and the price the consumer paid for them.
  • Distribution: Contains information about distribution like number of stores, sales agents, offices, etc.
  • Brand: Information about your brand, like awareness, liking, penetration, consideration, etc. This is also where Customer Experience related tracking goes.
  • Events: This captures all kinds of events, which extend over a given period of time. Could be events like Force Majeure or other extraordinary events.
  • Visits: This is information about footfall in stores, visits to a website, or any other measurement of traffic.
  • Macro: This data type supports all kinds of macroeconomic data, like unemployment rate, consumer confidence, consumer price index, interest rates, and currency exchange rates.
  • Media: Media investments and media groupings for all media related impressions and campaigns.
  • Extra: Additional data that does not fit the other file categories.
  • Customer Experience: Investments and efforts to improve Customer Experience, such as spending on customer service training, technology upgrades, user interface enhancements, or other initiatives aimed at enhancing the customer journey. Note that CX metrics like NPS or VOC should be included in the Brand file.
  • Weather: Include weather data such as rain, wind and temperature that could be relevant for the model.
  • Competitor Brand: Tracks metrics related to Competitor Brand, such as competitor brand awareness, market share, customer perception, and brand equity. This data helps benchmark your brand’s performance against competitors.
  • Competitor Media: Captures Competitor Media activities, including competitors’ advertising campaigns, media spend, channel preferences, and impression data. This allows for analysis of competitors’ marketing strategies and visibility in the market.
  • Competitor Price: Contains Competitor Price data, such as pricing strategies, discounts, and promotional offers of competitors. This information is crucial for understanding competitive positioning and informing your own pricing decisions.

Note

These data sources have a specific File Format that needs to be adhered to in order for the application to understand them.

Note

The data sources need to have a coherent data Periodicity meaning that the values need to be observed and registered in the same interval.