Dear Hivers
To harvest
What ? data are mainly collected 4 different types:
personal or descriptive (name, age, position in the company, address, email, phone number, etc.)
transactional or commercial (last purchase, type of purchase, amount, etc.)
relational (number of contacts, visits and follow-up by which salesperson, interactions with the company, participation in events & fairs, etc.)
behavioral (preferences, attitude on social networks, any detail that helps to better understand the person)
How ? Harvesting is not the sole preserve of salespeople
the web is a valuable source (request for information, request for quotation, subscription, download, exchanges on social networks, etc.)
invoices and all accounting data provide valuable information on the purchasing habits and behaviors of your customers
the after-sales service also provides a whole series of information on the customer experience (complaints, opinions, suggestions, feedback during events).
Harvesting is a crucial phase that should never be underestimated. Because if your database looks like a Swiss cheese, you will find it difficult to use your data; you might even draw the wrong conclusions.
To organise
To be useful, your customer database must allow you to make the right decisions at the right time. after harvest we need to divide and use data.
Too much info kills info!
It is therefore a question of segmenting your file by type of customer, according to their value and their potential but also according to the range of products purchased, by size and geographic location, according to their habits, according to the sales channels they prefer. , etc.
The criteria largely depend on your industry.
Level 1 of data mining (extracting information from a database) is the segmentation of your customers listed in your files. You will then observe that the margin rate of a small customer often appears higher than that of a large one. But in absolute value, the margin on the large customer weighs more! Establish this distinction for at least two semesters.
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