Our services

 Tailor-made analysis of your data

Because we can’t improve what we don’t measure, DataTailors allows you to make the best decisions for your business.
We offer several packages, ranging from simple descriptive analysis (what happens to my data?) to customized predictive models using Artificial Intelligence tools such as Deep Learning and Shallow Learning. All our packages include a dashboard to easily view the results.
Feel free to contact us, the initial diagnostic is free and without obligation!

Our packages and services

  • BASIC
  • 3500

    monthly
  • CHF 3900, USD 4000
  • Descriptive analysis + diagnostic
  • Custom dashboard
  • Support and updates
  • Training
  • Renewable one-year contract
  • SILVER
  • 5500

    monthly
  • CHF 6200, USD 6400
  • Descriptive analysis + diagnostic + custom predictive model
  • Custom dashboard
  • Support and training
  • Training
  • Renewable one-year contract
  • GOLD
  • 6500

    monthly
  • CHF 7300, USD 7600
  • Descriptive analysis + diagnostic + custom predictive model + prescriptive analysis
  • Custom dashboard
  • Support and training
  • Training
  • Renewable one-year contract
  • CONSULTING
  • 220

    per hour
  • CHF 250, USD 260
  • Data strategy
  • Training
  • Data visualization
  • Analysis of existing stragies
  • Reports
Benefit from our free initial diagnosis!
We’ll gladly answer to all your questions. Feel free to call !
Phone
+33 970 445 390
E-mail
info(at)datatailors.ch

More Infos

All our packages include an easy-to-use custom dashboard. We also offer you the possibility to create a dashboard according to your company’s graphic identity. In addition to dashboards, we can also create custom reports and illustrations according to your needs. Here you will find an example of a dashboard created by DataTailors.

The descriptive analysis provides information on what happened and gives an overview of the company’s activity (for example: in the 2nd quarter of 2018, 60% of our turnover came from customers aged 45 to 55 and living in urban areas). It allows to monitor the company’s activity. Only the data collected by the company are used for the descriptive analysis. If you are not sure what can be done with your data, feel free to contact us for a free initial diagnosis.

Examples :

1. In the third quarter of 2018, 60% of our revenue came from customers aged 45 to 55.

2. During the last 2 months, 1% of the parts leaving the production line were defective.

3. The cold room temperature exceeded the maximum threshold twice in 4 days.

The diagnostic is to understand why certain events occur (for example, why 18-25 year olds do not buy our products?). For the diagnostic, we carry out correlation analyses and organize a meeting with all the people involved, because we believe that to aim for excellence, it is essential to combine a good data analysis with the experience of people working in the field.

Examples

1. Why don’t 18-25 year olds buy our products?

2. After investigation, it appears that only one machine is responsible for the defective parts. Is it necessary to carry out maintenance on this machine?

3. We learn that an employee is used to leaving the door open for a long time. It is therefore not necessary to carry out maintenance, but rather to raise awareness among employees.

Predictive analytics predicts what will happen in the future (for example, how many products will we sell in the next quarter?). It is based on Artificial Intelligence models that we build especially for your company. The more data are available and collected over a long period of time, the better the prediction model will be. As required, we can integrate external data into the predictive analysis model. To learn more about predictive models, you can read this article from our blog.

Examples of this

1. A 3% increase in terminations for Subscription A is expected next quarter.

2. Within 2 weeks, this machine has a 67% chance of breaking down.

3. At the current filling rate, temperature anomalies will increase by 3% during the week.

Prescriptive analysis makes it possible to know what actions to take to avoid an announced event.

1. It is customers aged 35 to 45 who have been customers for less than 2 years who will mainly terminate their subscription A.

2. If preventive maintenance is carried out on machines 7 and 9, the number of defective parts will not be 1% but 0.2%.

3. If the cold room filling rate is reduced by 20%, the temperature anomalies will be stable during the week.

Some examples

Descriptive analysis - segmentation
Predictive analysis - sales
predictive analysis - anomalies
predictive and prescriptive analysis - churn

Have a look to our blog!

blog