Do you even need advertising? Goldtime X Convertal
Data
Innovation
Data
Innovation
Having won awards for Goldtime's work over the years, we started this time with a question that an agency rarely dares to ask: what if all of this isn't actually needed that much? We placed a question mark not only over the necessity of advertising, but also over our own role. We weren't looking for proof — we were looking for the truth.
Client
Goldtime / Megafort OÜ
Sector
Ecommerce
Period
2025
Award
TULImust finalist
Over the years, a familiar pattern kept repeating: the results of advertising campaigns improved every year. Yet the overall revenue of the online store did not grow at the same pace. While individual channels showed 50–70% growth, the total e-commerce performance moved by only up to 20%. This was the first sign that something was being overlooked in the measurement logic.
As a market leader, the brand holds a dominant share of both market position and consumer preferences. Logic based on that forces an uncomfortable question: do advertisements actually generate additional sales, or do they simply confirm demand that already exists? We decided to apply a different logic — not "how much did we sell?" but "how much more did we sell thanks to advertising?"
60%
Growth in incremental conversions from 35% to 60%
15K
Incremental online store additional revenue per month thanks to the project results
26%
Lower Marginal Growth Cost — meaning every euro generated more new sales
The specific goals were:
Measure the incremental impact of Google Ads — meaning the actual additional sales generated 1.1. The goal of the second phase was to define a numerical incremental growth target, which was set at 7,000 euros in incremental revenue per month from Google search ads.
Increase budget efficiency by at least 20% without losing visibility
The goal of the work was not "yet another optimisation" but an honest audit of marketing.
Process
Goals
We began the journey with Google Ads, which has historically ranked second in terms of online store revenue. In addition, search most directly reflects actual market behaviour, making it the purest form of demand testing. In such a context, it is possible to honestly measure whether advertising actually influences a decision or simply confirms what would have happened anyway. An "honest test" means here that the channel does not hide the impact of advertising — success cannot be attributed to visibility, emotion, or reach. If an ad works on Google, it is not because it was visually appealing or catchy, but because it helped a person make a decision they already wanted to make.
It is important to emphasise here that in the first phase, the brand keyword ("goldtime") was excluded from the analysis and the work, as its incrementality is inherently minimal. Purchasing brand keywords is something we use solely to "protect" our own brand in situations where competitors are bidding on it.
In spring 2025, we also began working with Marketing Mix Modelling, the results of which revealed that Google Ads was one of the most significant contributing factors. Since the always-on nature of marketing makes it difficult to assess the brand's organic impact with sufficient statistical model precision, we undertook the present work as one of the follow-up projects.
To drive a change in results, we applied our EPE (Elevate Predictive Efficiency) framework, which encompasses behavioural analysis, segmentation, and signal-based modelling, the creation of conversion value rules, and dynamic ads with IF-function-driven variable ad messaging.
Using EPE, we excluded, for example, visitors from the last 24 hours and frequent repeat visitors from all search campaigns. In total, we created 7 similar segment exclusions and timing logics. To establish a feedback loop that continuously improves the model, a custom EPE script has also been implemented on the account.
The EPE methodology can be applied across other channels as well, and we are actively moving in that direction. We see a particularly important role for it in Meta remarketing campaigns.
To understand the true incremental impact of advertising — rather than mere correlations — we used a combination of a geo-experiment and a causal impact model (Bayesian Structural Time Series) approach.
The Elevate Predictive Efficiency (EPE) framework operates as "layers" of causal analysis: it combines micro-level data on clicks and conversions, signal correlations, and repurchase probability to assess the likely incremental value of each advertising activity. EPE is built on machine learning, which identifies behavioural patterns and optimises ad bids in real time based on their estimated incrementality.
To validate the results, we used control periods and a time-decay model that assessed the impact of touchpoints over time — measuring how quickly the effect of an advertisement diminishes after the first exposure. This allowed us to eliminate incidental conversions and seasonal noise.
Let's get acquainted & achieve your goals together.
We are here to help businesses that want more. If you are ready for the next step forward — let's do it together.
Do you even need advertising? Goldtime X Convertal
Data
Innovation
Having won awards for Goldtime's work over the years, we started this time with a question that an agency rarely dares to ask: what if all of this isn't actually needed that much? We placed a question mark not only over the necessity of advertising, but also over our own role. We weren't looking for proof — we were looking for the truth.
Client
Goldtime / Megafort OÜ
Sector
Ecommerce
Period
2025
Award
TULImust finalist
Over the years, a familiar pattern kept repeating: the results of advertising campaigns improved every year. Yet the overall revenue of the online store did not grow at the same pace. While individual channels showed 50–70% growth, the total e-commerce performance moved by only up to 20%. This was the first sign that something was being overlooked in the measurement logic.
As a market leader, the brand holds a dominant share of both market position and consumer preferences. Logic based on that forces an uncomfortable question: do advertisements actually generate additional sales, or do they simply confirm demand that already exists? We decided to apply a different logic — not "how much did we sell?" but "how much more did we sell thanks to advertising?"
60%
Growth in incremental conversions from 35% to 60%
15K
Incremental online store additional revenue per month thanks to the project results
26%
Lower Marginal Growth Cost — meaning every euro generated more new sales
Goals
The specific goals were:
Measure the incremental impact of Google Ads — meaning the actual additional sales generated 1.1. The goal of the second phase was to define a numerical incremental growth target, which was set at 7,000 euros in incremental revenue per month from Google search ads.
Increase budget efficiency by at least 20% without losing visibility
The goal of the work was not "yet another optimisation" but an honest audit of marketing.
Process
We began the journey with Google Ads, which has historically ranked second in terms of online store revenue. In addition, search most directly reflects actual market behaviour, making it the purest form of demand testing. In such a context, it is possible to honestly measure whether advertising actually influences a decision or simply confirms what would have happened anyway. An "honest test" means here that the channel does not hide the impact of advertising — success cannot be attributed to visibility, emotion, or reach. If an ad works on Google, it is not because it was visually appealing or catchy, but because it helped a person make a decision they already wanted to make.
It is important to emphasise here that in the first phase, the brand keyword ("goldtime") was excluded from the analysis and the work, as its incrementality is inherently minimal. Purchasing brand keywords is something we use solely to "protect" our own brand in situations where competitors are bidding on it.
In spring 2025, we also began working with Marketing Mix Modelling, the results of which revealed that Google Ads was one of the most significant contributing factors. Since the always-on nature of marketing makes it difficult to assess the brand's organic impact with sufficient statistical model precision, we undertook the present work as one of the follow-up projects.
To drive a change in results, we applied our EPE (Elevate Predictive Efficiency) framework, which encompasses behavioural analysis, segmentation, and signal-based modelling, the creation of conversion value rules, and dynamic ads with IF-function-driven variable ad messaging.
Using EPE, we excluded, for example, visitors from the last 24 hours and frequent repeat visitors from all search campaigns. In total, we created 7 similar segment exclusions and timing logics. To establish a feedback loop that continuously improves the model, a custom EPE script has also been implemented on the account.
The EPE methodology can be applied across other channels as well, and we are actively moving in that direction. We see a particularly important role for it in Meta remarketing campaigns.
To understand the true incremental impact of advertising — rather than mere correlations — we used a combination of a geo-experiment and a causal impact model (Bayesian Structural Time Series) approach.
The Elevate Predictive Efficiency (EPE) framework operates as "layers" of causal analysis: it combines micro-level data on clicks and conversions, signal correlations, and repurchase probability to assess the likely incremental value of each advertising activity. EPE is built on machine learning, which identifies behavioural patterns and optimises ad bids in real time based on their estimated incrementality.
To validate the results, we used control periods and a time-decay model that assessed the impact of touchpoints over time — measuring how quickly the effect of an advertisement diminishes after the first exposure. This allowed us to eliminate incidental conversions and seasonal noise.
Let's get acquainted & achieve your goals together.
We are here to help businesses that want more. If you are ready for the next step forward — let's do it together.