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Analyze your marketing data by AI & ML algorithms without a single-line of code.

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What is AI Marketer ?

AI Marketer is an AI-enabled marketing analytics tool that uses only a few clicks to generate insightful data. Its for online marketer to analyze marketing data by AI & ML algorithms without a single-line of code.

By using our preset marketing task, you can get answer from unstructured data in numbers, text, tables, and charts.

Website :

www.ai-marketer.tech

Update:

Updated the pages structure of Streamlit App, based on that all the functions are being moved to /pages folder, if you are not able to replicate the pages function, please update your streamlit version

How to start the streamlit server ?

streamlit run Home.py

Why we create AI Marketer ?

To help marketer with no statistic / data analytics background to analyze data and handling routine marketing task in just a few clicks

Tutorial :

https://youtube.com/channel/UCvmEPC9fUfY8L2-v9IV1i4w

Features :

Two Parts – Tasks / Module

Task:
→ Combine different modules to analysis and generate different graphs
Example: RFM model = Classification + Regression
Analyse CSV file and show the data into bar chart by analysed segment groups

Module:
→ independent function and method

Tasks Input Result
Price Analysis Product name and Country Code (Alpha-2) list and line chart show all the shops with name and price
Trend Forecast Product name and *Country Code (Alpha-2) Show the prediction of the upcoming month and seasonality

Line chart and list will be shown
RFM model Upload a CSV file Show the table after system made RFM Segment tags for each customer

Bar chart show the distribution of the RFM tags
Competitor Analysis Upload a CSV file Show the list of different shops with score in different aspects

Positioning Map: Select two aspects and located based on the relationship
Customer Segmentation Upload a CSV file Cluster to show to distribution of the customers

Elbow graph show the value of k

List and bar chart to show the performance of different customer groups

Bottom Section: All the statistics are shown by different customer groups
Review Analysis Upload a CSV file Filter the keywords that the customer mentioned

Line chart shows the trend of the topics over time

Topic Distance Map: show the similarity of different words
Google adWord Generator Type keywords combination A list of showing all the words combination with Match_type
Cart Analysis Upload a CSV file A list of showing the relationship of different products

(high probability → closer relationship)

*Optional, Default: the whole world

For your reference:
Country Code: https://www.iban.com/country-codes
Match_type: https://support.google.com/google-ads/answer/7478529?hl=en
Segment tags (analysed by the system):
Champions > Loyal Accounts > Potential Loyalist > New Active Account > Low Spenders > At Risk > Need Attention > About to Sleep > Lost

Road Map

Integration with 3rd parties datasource by API

Our product focuses on analysing the data which users need to upload. At this moment, we are required to upload a CSV file. In order to increase the usage and convenience, we propose to integrate with 3rd parties data source , e.g : Google Sheet , Zapier for better user experience.

Intended Outcome:

Users can get seamless integration with their datasource, instead of using manual input by uploading a local CSV file.

Suggested Integration :

Google Sheet , 2. Zapier , 3. Database

What packages do we use ?

AI Marketer is a non-profit open-source project, we build AI Marketer with a lot of help from other open source packages :

Front end :

Streamlit (https://streamlit.io/)

Machine Learning & AI packages :

PyCaret (https://pycaret.org/)

Transformers (https://huggingface.co/docs/transformers/index)

Bertopic (https://maartengr.github.io/BERTopic/index.html)

Prophet (https://facebook.github.io/prophet/)

SpaCy (https://spacy.io/)

Top2Vec (https://github.com/ddangelov/Top2Vec)

Others :

Google Trans (https://github.com/ssut/py-googletrans)

Plotly (https://plotly.com/)

Creator & Contributor

Super Chain (Github : Super-Chain)

LAU, Ching Ming, Samuel (Github : samuellau0802)

Motaz Saidani (Github : Motaz-Saidani)

Cat YUNG (Github : catyung)

We welcome your contribution anytime

Collabration & Contact

Please feel free to contact us at : support@ai-marketer.tech

Version

Beta