Sales Trends and Forecast v.12
The tool to calculate sale trends and make prediction for future sales statistically. Sales Forecast
When this tool should be used
- 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 how statistics works.
Scientific approach for forecasting
Forecast as many intervals as you like, but remember that prediction for the next 10 years would be hardly reliable.
Based on your historical data and applied coefficients, sometimes Odoo is not able to reveal trends and make forecasts. In that case only historical data would be shown in reports. But even historical trends might have an analytical use.
Statistical methods for forecast
It is the simplest but still widely used statistical method for time series forecast.
Autoregressive Distributed Lag (ARDR)
The moving average method takes into account 'errors' in previous observations.
The autoregressive moving average method 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)
The method which also combines the methods AR and MA, but also 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)
The SARIMA method 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)
The SES model usage is similar to the AR method, but instead of relying upon linear function, it exploits exponential one
Holt Winter’s Exponential Smoothing (HWES)
The HWES method enriches the SES method to work with time series trends and seasonal effects.
Experiment with various statistical models
Topical data under consideration
Apply time frames of historical data which is used as an analytic basis. Forecast periods are ones which follow after the end of defined frame. In such a way you make check statistical reliability through 'predicting' actually passed intervals.
As sales per periods all sales orders in the states 'Locked' and 'Sale Order' are taken into account.
Sales forecasting interface
The right for trends analysis might be granted to any sales user, but be cautious: all sales of a current company will be under consideration.
Configuration and Installation Tips for Sales Trends and Forecast Odoo v.12
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
Sales trends and forecast configuration
Frequently Asked Questions about Sales Trends and Forecast Odoo v.12
According to the current Odoo Apps Store policies:
- every module bought for the version 12.0 and prior gives you an access to the all versions up to 12.0.
- starting from the version 13.0, every version of the module should be purchased separately.
- disregarding the version, purchasing a tool grants you a right for all updates and bug fixes within a major version.
Take into account that faOtools team does not control those policies. By 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.
Unzip source code of purchased tools in one of your Odoo add-ons directory
Re-start the Odoo server
Turn on the developer mode (technical settings)
Update the apps' list (the apps' menu)
Find the app and push the button 'Install'
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.
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.
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