Predictive analytics

2016-04-09

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Look into the future

Analyze data about your customers and sales.

Easy to use interface

  • Drag & Drop loading of files. Basicaly any .csv separated with commas.
  • Automatic recognization of formats inside.
  • Needed fields: Date of event/transaction/buy, Client / Customer identification and event/transaction value/volume/amount.

Intelligent parametrization

  • All parameters (like formats, patterns, time spans) will have suggestions.
  • Automatic suggestions for recognizing fields.

Readable and understandable output

  • Visualy rich and nice graphs and tables
  • Pre-formated tableau reports.
  • .csv file out possibilities.
  • Possible connection to other services (Keboola, Tableau, …)

Automatic segmentation

  • Automaticly suggest segmentation rules

Segment Migrations

  • Month to month or year to year customer segmentation changnes.
  • New best performing customers, who was good but now not performing well?
  • One of the best indicators of future sales.

Prediction of next buy

  • What is the probability that customer will buy on his next visit?

Behaviour analysis

  • What is the Customer Lifetime Value?
  • How he usualy acts?

Behavioral patterns

  • Finding patterns in customers actions – like this customer buys 50 USD credit every week, sometimes he doesnt buy regulary, but now he didnt buy for a month.

We are focusing on predictions of future actions of your customers

Predictions Use Cases:

  • Retention / Churn analysis – when you want to know if/when a customer leaves you and close account.
  • Segmentation – how often individual customers segments buy at your e-shop and for how much. How likely they will buy in next month, …
  • Direct Marketing – Precisely target your campaigns to relevant customers
  • Fraud Detection – Does this new operation correspond to previous behaviour?
  • Better decision-making – When you know the future better you can make better decisions