---
title: "Data Distributors Must Know: Get It Right and Profit!"
description: "Distributors must know certain data to profit. Through refined management and comprehensive data analysis, distributors can gradually improve operations by starting with basic data. Understanding customer details, product information, warehouse status, receivables, and team performance enables informed decisions and reduces guesswork."
author: "New Distribution"
publisher: "New Distribution"
email: "zhaobo258@gmail.com"
telephone: "+8615854817671"
published: "2017-12-17"
language: "en"
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# Data Distributors Must Know: Get It Right and Profit!

> Distributors must know certain data to profit. Through refined management and comprehensive data analysis, distributors can gradually improve operations by starting with basic data. Understanding customer details, product information, warehouse status, receivables, and team performance enables informed decisions and reduces guesswork.

Data distributors must know: get it right and profit!
For distributors, it is an inevitable trend to conduct comprehensive data aggregation and analysis through refined management. It may be difficult to achieve in one step, but you can start with some simple basic data and gradually improve management.
Distributors rely on downstream customers for business. Only by clearly understanding customer-related situations can they act with purpose:
1. The total number of current customers must be precise; phone verification is the simplest and most effective method.
2. Divide current actual customers into large, medium, and small categories, and know the counts for each.
3. Among the total customer base, what proportions have high, average, and poor sales quality?
4. From a relationship perspective, what proportions have good, average, and poor customer relations?
5. How many blank outlets remain? Are these new stores that haven't been approached, or former partners with whom cooperation has ceased?
6. How many customers have historical issues? Problems with new product distribution, display, and settlement often stem from unresolved historical issues.
Know detailed product information of partner manufacturers:
1. How many SKUs are there in total across all partner manufacturers?
2. Among all SKUs, what proportions are best-sellers, average sellers, and poor sellers (including dead stock)?
3. As of now, what are the actual sales figures for each manufacturer? This data must be compiled monthly.
4. As of now, what is the actual capital occupied by each manufacturer, including prepayments, inventory value, and various expenses advanced?
5. As of now, what are the amounts of products pending return, exchange, or disposal for each manufacturer?
Clear warehouse data influences distributor decisions on shipping and stocking:
1. What is the total warehouse area? After deducting aisles, loading/unloading zones, and office areas, what is the actual stacking area?
2. In the stacking area, how is space divided among normal goods, non-saleable goods pending return/exchange, various gifts, promotional materials, miscellaneous items, and large equipment? What is the ratio?
3. How long does a full inventory count take? This should be compared annually; strictly speaking, with the same area and quantity, the time should decrease year over year.
Management of supplier receivables:
1. As of now, what is the total amount of accounts receivable?
2. Of current receivables, how much is per normal contract terms, and how much is due to human factors or industry practices?
3. Of receivables, what proportion can be collected on time, and what proportion has issues or is overdue?
4. What is the ratio of receivables to total sales, and how does it compare to the same period last year?
Business team data management:
1. Among the sales team, what proportion maintains stable performance, and what proportion fluctuates significantly?
2. In terms of actual work status, what proportion can keep up with company development? What proportion needs enhanced management and supervision to keep up? How many are essentially candidates for elimination?
3. Based on historical turnover data, how many employees have worked less than six months, six months to one year, one to two years, and more than two years?
These data are basic operational data and are not complicated to collect. Data itself cannot directly solve problems, but it gives the boss a clear picture, reduces ambiguity, provides a basis for analysis and judgment in decision-making, and reduces impulsive decisions.
Source: Jiushi Distributor Home
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