Managing Digital Media Budgets Based on Business Performance Objectives

Maxime Vivos, Lead SEA at Converteo, is responsible for strategic and operational expertise in the SEA channel. He supports our clients with all their SEA-related issues, particularly in the implementation of maturity projects (Value Management, Omnichannel, Product Segmentation and Scoring, Incrementality Testing, Audits, Benchmarking, etc.).

Key Takeaways

• The growing trend toward automation of digital campaigns leads to a loss of transparency and control over digital acquisition channels. In return, it offers advertisers new ways to optimize their campaigns and enhance management tools. This trend has given rise to a new opportunity: value management, which is highly favored by media agencies, with Google at the forefront.
• However, before embarking on such projects, numerous questions arise… What do we mean by “management,” and what do we define as “value”? Are we talking about campaign segmentation? Is value necessarily margin? How do we define this value, potentially reprocess it, and integrate it into media buying platforms? And most importantly, how do we measure the impact it can have on media performance?
• Value management is a subject that is easy to grasp but will require advertisers to accurately identify their business priorities, master their data, and implement methods that are becoming increasingly technical and complex.

An Economic Context That Forces Advertisers into a Race for Profitable Growth

In addition to this economic context, media and technological trends are making it increasingly difficult for advertisers:

We are witnessing significant media inflation, with a constant rise in digital budgets over the past few years and increasingly intense competition among advertisers. The competition is particularly fierce in SEA, for example, which is a channel with finite potential and is often the first digital lever invested in by many advertisers.

There is also a growing challenge regarding the control and reporting of digital media performance, due to new restrictions (iOS 17 with LTP, or the DMA and consent management by GAFAM…) and the excessive automation of media platforms, leading to a loss of control and transparency in tools.

With less data and fewer levers available in the platforms, optimizing digital campaigns now relies less on the interfaces of media buying platforms and more on the data we are able to inject into them.

In this context: “How can we ensure that we provide the right management rules to the algorithms that drive the campaigns?”

This challenge is vital, as it is the advertisers’ ability to take ownership of this key subject that will differentiate them from their competitors, in an environment that is constantly evolving both technically and legally.

Two Complementary Work Axes to Deploy Our Value-Driven Management Vision

At Converteo, we have identified two different but complementary approaches that frequently arise in our discussions with our partners. We are convinced that it is by working on these two approaches concurrently that an advertiser will be able to significantly improve their performance.

The Conversion Approach

In this approach, we aim to enhance the value of conversions directly measured by your advertising platforms (such as Google Ads) using your business performance data to better guide management tools.

To achieve this, we must identify the business indicators that we want to associate with the performance of media campaigns.

We naturally consider margin, but it can also involve in-store sales, product turnover rates, or inventory levels. More rarely, it might include product popularity or categorization between marketplace products and proprietary products, as well as the ability to attract new customers rather than just repeat purchases.

Advertisers with business models relying on lead forms are also included. Conversion can be valued according to the type of lead (e.g., home insurance, motorcycle insurance, car insurance) or according to the stages of the customer journey completed, weighting this value based on parameters provided at each stage of the form (for example, whether the user is looking for an apartment or a house to buy in the real estate sector, or whether they are searching for tires of a specific size and diameter in the tire sector).

It is the advertiser’s responsibility to identify their business priorities, and we are here to assist them in this choice.

We can then implement a technical bridge between the advertiser’s data lake and their advertising account (Google Ads, Facebook Ads, etc.). This solution must be both technologically robust to protect data confidentiality and sustainable in light of regulatory advancements.

• Enhancing your conversions with business indicators will allow you to directly manage your bidding strategies according to the performances that matter for your business.

The Segmentation Approach

This type of project aims to segment the advertiser’s campaigns based on their first-party data, particularly through the enrichment of the product feed.

The goal of this approach is to control the distribution of each segment according to the value they are likely to generate.

For this first step, a technical ecosystem must be built directly around the source feed or the advertiser’s feed management tool, in order to enhance product attributes (SKUs) with additional indicators (inventory levels, margin rates, price competitiveness, catalog exclusivity, etc.).

These data points are then available to account managers in structuring their campaigns to encourage the concentration of budget and time on high-value products. The most common segmentation is the “High / Medium / Low” structure described by Google in its article on Shopping for Business Objectives.

We strongly recommend that advertisers complement this approach with a fine measurement of cross-sell effects to anticipate and control any potential side effects related to the new campaign segmentation, specifically ensuring that the products sold are indeed those highlighted by the advertising platform (e.g., is the product sold really the one promoted by the campaign?).

• Segmenting your campaigns will allow you to centralize your attention and efforts on the products and services that add significant value to your business.

The Importance of Framing and Preparation in Maturity Projects

As mentioned, value-based management, whether approached through the Valuation of Conversions or Campaign Segmentation, raises many questions:

• What data do I have available, and at what level of granularity?
• What use case have I identified for this data? If I want to use product scoring to value my conversions, I have different technical prerequisites compared to segmenting campaigns based on this indicator.
• Do I have the technical capability and legal validation to share this data with third parties (Google, Facebook, etc.)?
• Do I have the capacity for data hosting and processing, as well as the ability to join it with a media element (e.g., click ID or campaign structure element)?
• Does my team have the bandwidth to design and implement a test that will allow me to measure the project’s impact on my channel?

The first step will be to define all the hypotheses we want to test, prioritize them, and frame the human and technical requirements necessary for their deployment.

Mastering Risks to Transform This Key Opportunity into Positive Impacts

Like any opportunity of this significance, it carries its share of risks for advertisers.

• A poorly framed test, with biased results, could lead an impatient advertiser to manage their first digital budget based on incorrect and potentially harmful indicators for the business.
• Conversely, inconclusive and insignificant tests may prevent an advertiser from making decisive choices, allowing competitors to overtake them.

The topic of value-based management, positioned between media and data, requires new cross-functional skills that neither advertisers nor agencies are accustomed to addressing comprehensively. Converteo supports its clients across all these projects: technical and operational framing, building dedicated data lakes, deploying testing protocols, and large-scale implementation.