ABC and XYZ Analysis in PPC: How to Increase the Effectiveness of Advertising Campaigns

Written by
Olesia Holovko

Team Lead of Content for promodo.com

Written by
Evgeny Kolotylo

Middle Contextual Ads Specialist

PPC
February 25, 2026
11 mins
abc and xyz analysis
Content

Given the number of challenges and the growing competition businesses face today, Promodo is constantly looking for effective ways to optimize marketing strategies for our clients.

In this article, we’ll explain how Promodo’s PPC experts adapted ABC and XYZ analysis—traditionally an inventory and warehouse management tool—for paid advertising tasks. We will also share practical case studies and demonstrate the results achieved by optimizing products in PPC using this approach.

What is ABC XYZ Analysis

ABC XYZ analysis is a product classification method that combines two approaches: assessing the economic value of goods (ABC) and analyzing demand stability (XYZ). The result of the ABC XYZ stock analysis is a nine-cell matrix that helps prioritize products and make informed decisions regarding assortment and inventory management.

ABC vs XYZ Analysis

The difference between ABC and XYZ analysis is that ABC focuses on the economic value or revenue contribution of products, while XYZ evaluates the stability and predictability of their demand.

ABC analysis of product assortment groups items by their contribution to annual turnover or revenue:

  • A — a small portion of the assortment that generates the bulk of the income;
  • B — products with a medium impact on revenue;
  • C — products with a low impact on the overall financial result.

XYZ analysis assesses demand stability:

  • X — products with stable and predictable demand;
  • Y — products with moderate fluctuations in demand (e.g., seasonal);
  • Z — products with unstable or difficult-to-predict demand.

ABC and XYZ Matrix

ABC
XHigh profitability, stable demandMedium profitability, stable demandLow profitability, stable demand
YHigh profitability, unstable demandMedium profitability, unstable demandLow profitability, unstable demand
ZHigh profitability, random demandMedium profitability, random demandLow profitability, random demand


Combining these two approaches provides a more complete picture of product behavior. Unlike the classic ABC analysis, which is based on a single metric (such as sales volume or revenue), the ABC XYZ analysis also takes into account the risk associated with demand instability.

Why ABC and XYZ Analysis Is Important in Marketing

In marketing, resources are always limited: budget, team time, and the attention of both algorithms and users. ABC and XYZ analyses help allocate these resources more effectively, focusing not on the number of activities, but on their actual impact on business results.

The ABC method allows you to quickly identify which products, categories, or campaigns generate the largest share of revenue or profit. In marketing practice, this means having a clear understanding of what to scale, what to optimize, and what might be better to limit in terms of investment.

Combining ABC and XYZ analysis helps set priorities and plan budgets with risk in mind. For example, marketing activities with high value and stable performance should receive the main share of the budget, while less stable activities should operate in a test or limited format.

Google ABC XYZ Analysis for PPC Optimization

With extensive advertising experience, Promodo experts have rethought the classic approach of ABC and XYZ analysis for product assortment management and adapted it to the realities of PPC campaigns.

I applied this methodology in its classic form—dividing products into 9 categories—within a test. However, in practice, such granularity turned out to be excessive for PPC.

For example, in the feed, there are two products: one accounts for 7% of ad spend share, the other 3%. Considering that my KPI is set at 15% ad spend share, there is no point in separating them into different campaigns, as would be done in a classic ABC XYZ stock analysis.”  

Yevhen Kolotylo, Team Lead, PPC Department at Promodo

Therefore, at Promodo, instead of the classic 9 segments, we use 4 categories for more effective PPC strategy optimization. The B and Y categories are split and assigned to adjacent groups based on their performance metrics.

1.Group A/B: Top Sellers

The first group includes top-performing products. Typically, their number is small—about 5–10% of the total assortment—but they generate up to 80% of sales and profit.

Identification of A/B products is based not only on sales volume but also on their actual effectiveness for the business. Factors such as margin, operational costs, VAT, and alignment with key business KPIs are taken into account.

We recommend focusing the main advertising budgets on A/B group products, as they deliver the highest profit. Campaigns should be scaled to increase sales of top products. At the same time, it is crucial to ensure uninterrupted stock availability, using sales forecasts and demand analytics to avoid shortages or overstocking.

2. Group B/C: Selling but Below KPI

The B/C group includes products that incur significant advertising spend but still generate sales.

The main characteristic of this group is that the overall effectiveness of the products remains below the established business KPIs.

To manage this group, it is recommended to place B/C products in separate campaigns and control them with “tightened” strategies. This approach allows maintaining sales of these products without compromising the profitability of the main top-performing items, while also enabling gradual optimization of their effectiveness through tests and targeted adjustments.

“Our goal is to set up a Performance Max campaign with the right strategy and optimization for Target ROAS or Target CPA, to bring this group’s metrics in line with the established business KPIs.”

Yevhen Kolotylo, Team Lead, PPC Department at Promodo


3. Group X/Y: Spend and Traffic Without Conversions

Products in the X/Y group receive clicks and consume advertising budget but do not generate conversions. Despite their low performance, we do not recommend turning them off immediately, as they can be useful for testing and training algorithms.

To manage this group, it is advisable to isolate these products in separate campaigns. This allows for controlling spend while still giving them a chance to generate conversions (since there are no higher-priority products in the campaign from Google’s perspective). This approach enables analysis of user behavior, testing new strategies, and gradually optimizing campaigns without risking a drop in performance for the main product groups.

4. Group Y/Z: Zombies

The Y/Z group includes products that receive no impressions, clicks, or ad spend. These are also referred to as zombie SKUs. At first glance, this group seems to have no impact on campaign performance; however, our experience shows that the right PPC strategy and optimization for these products can drive sales of items that previously did not sell through advertising.

Zombie SKU:
How to Generate Profit from Products That Don’t Sell


How to Automate Assortment Analysis

The process of analyzing products promoted in advertising can be significantly simplified and automated. At Promodo, we developed our own solution, AdsHub, which allows collecting data, evaluating product performance, and segmenting items into groups by tagging each product according to its effectiveness.

There is, however, an important nuance. Each niche has its own specifics, seasonal demand fluctuations, and different business KPIs. Therefore, before automation, a manual analysis is necessary: evaluate the products, understand their effectiveness, and determine the segmentation logic. Based on these insights, an algorithm for automatic classification is created, taking into account the unique features of a particular business and enabling highly accurate management of advertising campaigns.

Advertising Automation for
an Auto Parts Store
with an assortment of 1 million products

How to Use ABC XYZ Analysis in PPC: Practical Case Studies

Case 1: Online Toy Store with 70,000 SKUs

Analysis Findings:

  • 10% of products generated 80% of revenue while consuming 50% of ad spend
  • 20% of products generated 20% of revenue while consuming 40% of spend
  • 10% of products consumed 10% of the budget but generated no sales
  • 60% of products were present in the feed but contributed almost nothing to sales

In each category and subcategory, the situation was nearly identical, which made manual optimization at the campaign level very challenging.

Solution:

Using the adapted ABC/XYZ analysis, the entire assortment was segmented into 4 practical groups with separate management logic for each campaign:

  • Group A/B — placed in dedicated campaigns with more aggressive budget scaling
  • Group B/C — moved to “tight” strategies focusing on achieving business KPIs
  • Group X/Y — isolated in separate campaigns to control spend and test alternative strategies to capture converting traffic. If no results are achieved, promotion of this group is discontinued
  • Group Y/Z — tested in separate campaigns without competition from priority products

Result:

  • Campaign efficiency for the first three groups increased by 35% due to budget redistribution and optimization
  • Group Y/Z revealed unexpected scaling potential
  • Overall store revenue increased by 20% while maintaining target KPIs

Case 2: Garden Equipment, Tools, and Machinery Store with 100,000 SKUs

Problem:

The store had a large number of categories with varying demand cycles. Some products were highly seasonal, others worked in waves or depended on weather conditions. Google algorithms struggled to adapt quickly to these changes within a single campaign.

As a result:

  • Products with extensive historical data continued to receive impressions even after demand dropped
  • Products with new or growing demand received insufficient traffic due to a lack of history

Objective:

Increase overall PPC campaign efficiency without losing sales volume during peak periods

Solution:

We restructured the campaigns as follows:

  • Implemented frequent tagging of products based on performance
  • Conducted regular analysis every 5 days using the previous 5 days’ data
  • Automated classification and segment updates using AdsHub

This allowed rapid traffic redistribution between subcategories based on current demand rather than historical data.

Result:

  • Campaign efficiency increased by 40%
  • Ad spend became much more controllable during low-demand periods
  • Campaigns adapted faster to seasonal changes without manual intervention

Conclusion

Promoting a business online in 2026 requires not only professional expertise but also flexibility and innovative solutions. Leveraging over 20 years of experience, Promodo experts go beyond standard practices to identify additional opportunities for optimizing campaigns and product assortments, increasing efficiency, and delivering more value to every client.

Do you want your business to generate higher profits?
Contact us, and we’ll help optimize your advertising campaigns!
Written by
Olesia Holovko

Team Lead of Content for promodo.com

Written by
Evgeny Kolotylo

Middle Contextual Ads Specialist

Published:
February 25, 2026
Updated:
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