Product analysis is key for businesses with large or heterogeneous product stock. Analysis allows you to check if you are making appropriate warehouse purchases and confirm that customers are seeing the correct stock when they look at your product directory. It also answers many other pressing questions. There are several tools that will get the job done through three main methods: ABC, XYZ, and BCG. To decide on the right option for you, it’s necessary to look closer at a variety of different tools.

Are your warehouse purchases on the right track? Are you showing your customers the right goods in the product directory? Standard product analysis comes up with a bunch of answers, yet there’s also a comprehensive approach to the issue.

This time, we’ll tell you how we mixed up product analytics and descriptive analytics to get deeper insights into business customers’ needs and boost their overall sales.

Without further ado, let’s get right to the point. And the point is: most companies don’t do product analytics whatsoever! A small share opts for old good Excel, an even smaller share employs dedicated inventory management tools with embedded stock movement analysis. Lack of quality control in terms of product grid leads to lost sales and shrinking margins whereas deal prices go up.

In daily marketing routine, we have to analyze various product groups, reveal existing deficiencies and suggest viable scenarios to increase revenues. All groups are different, and you need to perform all-around analysis based on the current sales status.

Our approach not only involves the standard algorithm of product grid analysis but also adds predictive and descriptive analytics. This combination allows the marketer to effectively identify issues in procurement procedures and the product grid.

Let’s review these tools in more detail.

Step 1. Standard product grid analysis

First off, we look into the sales dynamics of a specific product group within the product grid. Dynamics are gauged based on sales revenue, quantity of items sold and profit.

Step 2. ABC analysis

Check out my previous posting for more information.

Step 3. XYZ analysis

The XYZ analysis is an indispensable tool to split the stock into multiple categories based on demand predictability.

Step 4. ABC+XYZ matrix

By the juxtaposition of the previous two methods, we find out which goods generate greater profits and sustainable demand. That is, we unveil the key drivers of your business!

Step 5. BCG analysis

We perform the BCG analysis: assess product groups and define primordial methods to optimize the product grid, procurement and warehouse stock.

Assessing the metrics

Now that we blended descriptive analytics into product analytics, what has changed in the big picture?

The standard ABC analysis encompasses six major parameters to monitor product grid status. The key technique is to split the goods into A, B, and C categories.

The extended view now includes over 35 product grid metrics.

In the highlights:

  • Average and median showings
  • Deviation from average
  • Analysis of sales frequency and total sales sum within specific price intervals.

All these parameters can be juxtaposed to form various information tables and 17 major charts.

Case study

How does this work in practice?

In a nutshell: there is a business that invests heavily into advertising, yet sales and margins fall behind. The owner is looking for culprits. Sound familiar?

How does the tool help? A director/procurement manager/advertising pro/marketing agency rep opens up product analytics and views the big picture in a snap:

  • Over 50% of product groups belong in the C category, i.e. they sell poorly and gather dust at the warehouse
  • Over 50% reveal poor showings of average sales deviation
  • A good share of products reveal poor margins
  • Many products are placed in the low price group.

In a competitive market with high bids in paid advertising, CPO (cost per order) may outweigh the margins – leading to lost revenues.

What will be the course of action in this case?

  • Procure more best-selling products and shrink the C category
  • Procure anchor goods belonging within higher price intervals to boost average spend, margins, etc.

This is how a melting pot of marketing techniques within a single BI helps detect and remediate sales issues and make informed decisions.

Stay tuned for more postings unveiling new functionality!