Companies use Octolis to build a customer 360 database and leverage it for better marketing activation and analytics.
Main features
Import various data sources
Organize data into “Entity based” datasets
Transform your data with normalization rules and computed fields
Send your data to your marketing tools
Analyse your data by plugging your reporting tool
One core concept: the “dataset”
In Octolis, a dataset is a data table which merge the data from several data sources.
One dataset for each business entity
Usually, our customers create one "dataset" for each business entity (contacts, orders, order items, products, customer tickets, web events, ...).
Import > Connect data sources to each dataset
You can add / delete easily the various source files of each dataset.
There are several types of data sources
CSV files deposited every X on an FTP server
API calls
Direct connectors with some tools (like Mailchimp, Shopify, Zendesk...)
The import of CSV files works in an incremental way. You have to deposit each day the modified or created lines, and not the complete stock.
For each dataset, there is a tab “Sources” from which you manage the different data sources.
Dedupe > Define how data sources are merged into dataset records
Data from different sources are deduplicated, which is critical for contacts of course, but often useful for other business entities like Products or Companies.
Transform > Add normalization rules & computed fields to your dataset
You can apply normalization rules, and add calculated fields on each dataset, cf. Transform a dataset
Activation > Send datasets to third party tools
From the menu “Syncs”, you can create a workflow to send one dataset to some third-party tools like a CRM tool or an Ads platform.
Analyse > Connect your reporting tool to analayse your datasets
The data is stored in an independent DB (Postgres) on which you could plug a reporting tool like Metabase.
For mature customers, we recommend to use a datawarehouse like BigQuery as repository for reporting tools.
