Google Shopping

The Foundation of Success. Lean 6 Sigma Marketing

We use clear and practical tools, combining the best practices existing in the paid search market, our team's experience, automation, and the LEAN 6 SIGMA methodology.

DMAIC Cycle

Before starting the setup or optimization of your advertising campaigns, we primarily strive to understand your business using Lean 6 Sigma tools, assess the strengths and weaknesses of your products and offers, your customers, and the competitive environment. As a result, we formulate a list of clear and measurable goals, defining the place of Google Shopping in the overall promotion system.

Impact on Profitability

We divide the entire promotion process into parts in the form of a sales funnel and measure how individual elements of Google Shopping advertising (products, categories, search queries, customer groups, etc.) affect the effectiveness of each stage of customer acquisition in your business, looking for both critical problems that "steal" your profit and unrealized potential. For large samples and complex projects, we use MSA or GAGE R&R — tools for measuring the variability, stability, and reliability of data.

Search for Losses and Growth Points

We look for the answer to the question of what is the cause of unsatisfactory results and what the process and each element of shopping advertising campaigns should look like to achieve maximum profitability both with the existing budget and when scaling. Using a set of tools, we identify cause-and-effect relationships and factors influencing the current state of affairs, and formulate hypotheses, ideas, and tasks for improvement.

Hypothesis Testing and Optimization

First and foremost, we use a priority matrix, proceeding to the implementation of those tasks that require minimal time and costs while having the maximum financial return. After achieving "quick wins," we ensure the launch of more long-term improvement programs.

Additionally, for items and ideas that require verification, we conduct managed experiments and test hypotheses, evaluating the effect using statistical analysis and A/B testing.

Self-Learning Algorithm

An algorithm that automatically analyzes the effectiveness of specific products, prices, stock, categories, audiences, and groups of search queries based on statistically significant data, capable of changing bids, budgets, and rules for displaying product ads in Google Shopping in real-time.

In parallel, the overall data array is assessed according to dozens of parameters and rules, with information received about failures, anomalies, or positive trends that should be considered as opportunities for improvement.

Sustaining Progress

It is important to regularly audit all successful solutions and results, controlling their repeatability. At the same time, it is necessary to compare dozens of key indicators with the current goals of the business. Therefore, every week our team analyzes the results, experiments, and the latest trends, reviews the strategy for using and promoting your products in Google Shopping monthly, and controls the correctness of work and the results of advertising campaign settings daily, both automatically and manually.