Sales Trends and Forecast v.15

The tool to calculate sale trends and make prediction for future sales statistically. Sales Forecast. Sales prediction

198€

The tool does not require extra dependencies beside standard Odoo apps.
Current version: 15.0.1.0.3

Enterprise
Community
Odoo.sh

If future sales are a black box for you, you might hardly make profitable decisions right now. How many items to purchase? Which products require aggressive advertising? Where are the best markets for us for the next year? Luckily, statistics might help if you have enough historical data. This Odoo tool lets you generate sales by periods and apply statistical methods to forecast further periods.

Scientific approach for forecasting

The app assumes applying statistical methods to calculate historical trends and make a forecast. Make a few experiments with suggested solutions and coefficients to achieve the most accurate prediction

Focused analysis

Shrink considered sales for definite products, templates, categories, teams, a country, or customers: trends might be different in different markets or functional areas

Topical data

Apply time frames for historical data to check statistical reliability through 'predicting' actually passed intervals. All orders in the states 'Locked' and 'Sale Order' would be taken into account

Trends interfaces

Work with sales forecasts in a way you like: as an Odoo chart, as an Odoo report (pivot), as an Excel table

Widely applicable solutions

Analyze trends for both absolute quantities and revenues (in a company default currency). The app might be of especial use for markets experiencing seasonal changes: try to define statistical factors in your industry to make reliable forecasts

Sales trends analysts

Grant the right for forecast tools for any sales user (the group Other > Sales Forecast). To start analysis it is needed to push the menu entry Sales > Reporting > Sales Forecast. Be cautious: all sales of a current company will be under consideration.

Shrink sales by products, teams, countries
Different statistical methods for forecast
Chart of forecasts and historical sales
Odoo report for sales prediction
Odoo forecast sales
Excel table of sale trends

Statistical methods to forecast sales

  • The tool allows to calculate inventory demand trends based on a number of statistical methods. They have different complexity and might be suitable for a definite market or a specific business. The final choice of the method and related statistical parameters is up to end users
  • Autoregression (AutoReg) is the simplest but still widely used statistical method for time series forecast
  • Autoregressive Distributed Lag (ARDR) takes into account 'errors' in previous observations
  • Autoregressive Moving Average (ARMA) is a combination of both AR and MA methods. To apply the ARMA method use the MA method with auto regression coefficient (P coefficient) as 2
  • Autoregressive Integrated Moving Average (ARIMA) combines the methods AR and MA, but beside that it tries to make data stationary. It is appropriate to use for historical data with pure trend but without seasonal changes
  • Seasonal Autoregressive Integrated Moving-Average (SARIMA) enriches the ARIMA method with considering seasonal changes. It is one of the most complex and wide spread methods utilized for forecasting time series now
  • Simple Exponential Smoothing (SES) is similar to the AR method, but instead of relying upon linear function, it exploits exponential one
  • Holt Winter's Exponential Smoothing (HWES) enriches the SES method to work with time series trends and seasonal effects
  • For more technical details have a look at the page: https://www.statsmodels.org/stable/api.html

Usage requirements

  • You have enough historical sales data, since it is senseless to make forecast based on last 5 days of sales
  • Your sales are regular and they are not chaotic, meaning that your decisions do not have 100% impact on your sales and there is at least some correlation between market demand and your sales
  • You consider seasonal changes and/or trends, which you noticed but can't fully analyze. You understand which assumptions you try to check
  • You have clear understanding of how statistics works.
Based on applied statistical methods and parameters (especially P, D, Q, and seasonal coefficients) sometimes the app would not be able to reveal a trend. In such a case, make sure you have enough historical data and try to experiment with forecast settings

Configuration and Installation Tips for Sales Trends and Forecast Odoo v.15

Python dependencies

To guarantee tool correct work you would need a number of Python libraries: pandas, numpy, statsmodels, scipy, xlsxwriter. To install those packages execute the command:

pip3 install pandas numpy statsmodels scipy xlsxwriter

If you run Odoo on Python prior or equal to version 3.7, please install the following versions of the packages pandas==1.3.5, statsmodels==0.13.1

Frequently Asked Questions about Sales Trends and Forecast Odoo v.15

According to the current Odoo Apps Store policies:

  • every module bought for version 12.0 and prior gives you access to all versions up to 12.0.
  • starting from version 13.0, every module version should be purchased separately.
  • disregarding the version, purchasing a tool grants you a right to all updates and bug fixes within a major version.

Take into account that the faOtools team does not control those policies. For all questions, please contact the Odoo Apps Store representatives directly.

The easiest approach is to use the Odoo store built-in workflow:

1. Open the module's page and click the button Deploy on odoo.sh

2. After that, you will be redirected to the GitHub page. Login to your account and click 'Create a new repo' or use the existing one. Please, make sure, that your repository is private. It is not permitted to publish the apps under the OPL-1 license. If necessary, create a new repo for your Odoo.sh project

3. Then, go to odoo.sh and click on the deploy button, submit the decision in the pop-up window and click 'Continue'. The action will trigger the installation process.

These steps would install the app for your project production branch. If you wanted to deploy the apps for other branches or update the module, you should undertake the following actions:

1. Upload the source code for the app from the Odoo store

2. Commit the module to a required GitHub repository. Make sure that none of the app folders/files are ignored (included in the .gitignore of your repo). Repositories are automatically created by odoo.sh, which might add by default some crucial items there (e.g. /lib). You should upload all module directories, subdirectories, and files without exceptions

3. Deploy a target branch of the odoo.sh project or wait until it is automatically built if your settings assume that.

  1. Unzip the source code of the purchased tools in one of your Odoo add-ons' directories;

  2. Re-start the Odoo server;

  3. Turn on the developer mode (technical settings);

  4. Update the apps' list (the apps' menu);

  5. Find the app and push the button 'Install';

  6. Follow the guidelines on the app's page if those exist.

Yes, sure. Take into account that Odoo automatically adds all dependencies to a cart. You should exclude previously purchased tools.

A red/orange warning itself does not influence features of the app. Regretfully, sometimes our modules do not pass standard automatic tests, since the latter assumes behavior which is in conflict with our apps goals. For example, we change price calculation, while standard Odoo module tests compare final price to standard algorithm.

So, first of all, please check deployed database features. Does everything work correctly?

If you still assume that warning influences real features, please contact us and forward full installation logs and the full lists of deployed modules (including core and third party ones).

Regretfully, we do not have a technical possibility to provide individual prices.

No, third party apps can not be used on Odoo Online.

Yes, all modules marked in dependencies are absolutely required for a correct work of our tool. Take into account that price marked on the app page already includes all necessary dependencies.  

The price for our modules is set up in euros. The Odoo store converts prices in others currencies according to its internal exchange rate. Thus, the price in US Dollars may change, when exchange rate changes.

Odoo demonstration databases (live previews)

For this app, we might provide a free personalized demo database.

No phone number or credit card is required to contact us: only a short email sign up which does not take more than 30 seconds.

By your request, we will prepare an individual live preview database, where you would be able to apply any tests and check assumptions for 14 days.

Bug reporting

In case you have faced any bugs or inconsistent behavior, do not hesitate to contact us. We guarantee to provide fixes within 60 days after the purchase, while even after this period we are strongly interested to improve our tools.

No phone number or credit card is required to contact us: only a short email sign up which does not take more than 30 seconds.

Please include in your request as many details as possible: screenshots, Odoo server logs, a full description of how to reproduce your problem, and so on. Usually, it takes a few business days to prepare a working plan for an issue (if a bug is confirmed) or provide you with guidelines on what should be done (otherwise).

Public features requests and module ideas (free development)

We are strongly motivated to improve our tools and would be grateful for any sort of feedback. In case your requirements are of public use and might be efficiently implemented, the team would include those in our to-do list.

Such a to-do list is processed on a regular basis and does not assume extra fees. Although we cannot promise deadlines and final design, it might be a good way to get desired features without investments and risks.

No phone number or credit card is required to contact us: only a short email sign up which does not take more than 30 seconds.

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