Case Study: Launching an advertising campaign for Mounblan

  • ROAS from 3 to 89
  • sales generated by advertising 600+
  • telephone enquiries 375+

Client — Mounblan, a company that sells telecommunications equipment to businesses and individual customers in Ukraine.

At the time of the inquiry, there was absolutely no advertising activity on digital channels. The company had not previously used paid promotion and reached out to us for its first advertising campaign.

In particular, the basic marketing infrastructure had not been set up:

  • No Google Ads accounts were created;
  • No Google Merchant Centre account for product ads;
  • Google Analytics was not set up;
  • There is no tracking of conversions and e-commerce events.

As a result, the company was unable to analyse user behaviour on the website, evaluate the effectiveness of its marketing channels, or make data-driven decisions.

Project objectives

The main goal of the ad campaign was:

  • Attracting B2B customers who purchase telecommunications equipment for their businesses;
  • testing demand for specific product groups;
  • generating a steady stream of inquiries and orders.

Separately, the client set the task of identifying product groups that could serve as the basis for regular corporate purchases.

Our team’s mission

Our task was not only to launch advertising campaigns, but also to build a comprehensive marketing infrastructure. We were supposed to:

  • build an advertising structure;
  • set up accurate analytics and conversion tracking;
  • lay the groundwork for scaling up advertising;
  • ensure transparent monitoring of advertising investment effectiveness.

As a result, the client was to receive not just advertising but a comprehensive customer acquisition system capable of performing detailed analysis and optimising campaigns.

Work Completed

1. Building an advertising infrastructure

Since the client had not previously used paid advertising, the first step was to establish a comprehensive advertising and analytics infrastructure.

The following was completed:

  • An advertising account has been created in Google Ads;
  • Created and configured a Google Merchant Centre account to upload a product feed;
  • Google Analytics 4 has been set up;
  • Integration has been implemented across all systems to ensure accurate data transfer.

This has made it possible to build a unified ecosystem in which advertising campaigns, analytics, and product data work in sync.

2. Implementation of e-commerce

To obtain detailed analytics on user behaviour on the website, comprehensive e-commerce event tracking has been set up.

Specifically, the following was implemented:

  • Tracking product views;
  • The event of adding an item to the cart;
  • The event marking the start of the order placement process;
  • The purchase completion event.

All key conversions were imported into Google Ads, allowing the advertising system’s algorithms to optimise campaigns based on specific user actions.

In addition, we implemented value-based conversion segmentation so that advertising algorithms could prioritise higher-margin sales.

3. Launching advertising campaigns

To identify the most effective source of sales, several types of advertising campaigns were tested:

  1. Performance Max (PMax) — the primary advertising campaign format.
  2. Standard advertising campaigns — for comparing results.
  3. Search campaigns — for commercial queries related to products.

Why was Performance Max chosen?

Performance Max is a modern campaign type in Google Ads that allows you to display ads across all Google advertising channels at once:

  • search;
  • YouTube;
  • contextual media network;
  • Gmail
  • Google Discover.

The key advantage of this format is a high level of automation and machine-learning-based optimisation, which allows you to find potential customers more quickly.

In our case, the following signals were sent to the system for optimisation:

  • relevant search queries;
  • users who have already visited the site;
  • behavioural characteristics of potential customers.

We chose PMax as the primary campaign type because the client’s main goal was to quickly acquire new customers and test demand for different product categories.

At the same time, standard advertising campaigns were used to test the effectiveness of “hot” search queries, when users are already actively searching for a specific product.

4. Advertising Campaign Segmentation

To avoid mixing products with different profit margins and levels of demand, the advertising campaigns were divided into several segments.

Core product groups
These are the products in highest demand among B2B customers.
They have been placed in separate campaigns, which has enabled us to optimise advertising more precisely for ROAS.

Related products (Upsell)
These are products with lower profit margins but a high likelihood of generating additional sales.
Such products were launched as part of PMax campaigns to test their potential for attracting new audiences.

Test categories
Specific product groups that were not previously sold online.
Separate campaigns were created for these to gauge demand.

If a category showed consistent sales, it was moved to a separate permanent campaign.

Results of the advertising campaign

Following the launch of the advertising infrastructure and the optimisation of Google Ads campaigns, we established a stable customer acquisition channel for Mounblan.

Overall results of advertising campaigns

  • 2.8+ million ad impressions
  • 73,000+ website visits
  • 600+ sales generated by advertising
  • 375+ telephone enquiries
  • 950+ recorded conversions

A key outcome was that the advertising campaigns successfully attracted B2B clients who purchase telecommunications equipment for their businesses. A significant proportion of these clients contacted us by telephone to seek advice on the equipment before making a purchase.

Thus, the project’s key objective—to establish a reliable channel for attracting corporate clients through online advertising—has been achieved.

Trends in advertising effectiveness

As the advertising campaign ran, it was gradually optimised thanks to the accumulation of data and the use of machine learning algorithms in Google Ads.

The key metrics showed a positive trend:

  • The CTR rose from 1.5% to over 2.6–3.2%

  • The number of conversions has increased more than fourfold
  • The cost per lead has fallen by approximately 63%

  • An increase in ROAS from 3 to 89

This was made possible by:

  • The segmentation of product categories;
  • The optimisation of the product feed;
  • Data collection in Google Analytics 4;
  • The operation of the Performance Max campaign algorithms.

Insights following the launch of the advert

After several months of work, we identified several important patterns.

  1. Performance Max campaigns have become the primary source of sales
    The system’s algorithms have effectively identified new audiences among B2B clients.
  2. Some product categories showed significantly higher demand
    After testing, they were spun off into separate ad campaigns for scaling.
  3. Phone inquiries have become an important sales channel
    A significant portion of B2B customers prefer to consult with a representative before making a purchase.

Project Summary

As a result of this project, a comprehensive online customer acquisition system was developed for Mounblan:

  • An advertising infrastructure has been established;
  • Analytics and e-commerce have been implemented;
  • Several types of advertising campaigns were tested;
  • Effective product categories have been identified.

This enabled the business to launch a new sales channel and generate a steady stream of B2B customers from Google Search.

Plan for Future Work

  1. Scaling Effective Campaigns
    • Transferring successful test categories to regular PMax campaigns
    • Budget Optimisation for ROI and ROAS
  2. Expanding Audiences
    • Creating lookalike audiences based on existing B2B customers
    • Retargeting for potential customers who viewed products but did not make a purchase
  3. Optimising the product feed
    • Improving product descriptions, prices, and images
    • Testing seasonal and promotional offers
  4. Analytics and Reporting
    • Regular monitoring of Google Analytics 4
    • Automated dashboards for monitoring key KPIs
  5. Search for new B2B segments
    • Testing new product categories and bundled offers
    • Assessment of the Potential for Regular Corporate Procurement
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