Most marketing measurement models operate on a simple assumption: effects are additive.
Campaign A drives 100 leads, Campaign B drives 200, so the total impact is 300.
But in reality, marketing often defies this logic.
Some efforts multiply the effects of others.
And in some cases, combined initiatives create outcomes that are greater than the sum – or even the product – of their parts.
These are known as additive, multiplicative, and synergistic effects.
Consider a glass of cold milk and an Oreo cookie. Each is perfectly enjoyable on its own. But together, they create something unexpectedly better.
The same principle applies to marketing: when initiatives are strategically integrated, the outcome can be amplified far beyond what any single effort could achieve on its own.
Which raises a few important questions:
Let’s start by defining the terms.
Let’s start with a quick visual before getting into the details:
Definition: The total effect is simply the sum of individual efforts.
Marketing example: If Campaign A drives 100 leads, and Campaign B drives 200 leads, then the combined result is 300 leads. No interaction – just stacking results.
Limitation: This assumes each tactic works in isolation and doesn’t influence the effectiveness of others.
Definition: The total effect is the product of factors, one enhances or scales the other.
Marketing example: If awareness increases by two times, and conversion rate increases by 1.5 times, the combined impact on sales is 2 x 1.5 = 3x. Changes in one variable amplify the other.
Limitation: It still assumes predictable, mathematical interaction, which often oversimplifies real-world marketing dynamics.
Definition: The combined effect is greater than the sum or product of individual parts – a case of “1 + 1 = 3”.
Marketing example (Les Binet-style): Long-term brand building primes an audience emotionally, while short-term performance-focused campaigns convert that primed audience into buyers.
Each alone performs OK. But together, they reinforce and amplify each other – leading to non-linear, sometimes exponentially better results.
Since we’re talking about Les Binet, let’s go even deeper and throw in a time-decay element.
Binet emphasizes that brand campaigns build the brand through every impression but battle the daily erosion of market share – with DR campaigns funding short-term brand defense as well.
Key insight: Marketing activities often interact in mutually reinforcing ways that can’t be reduced to simple math.
Limitation: Hard to model, and requires additional experimentation.
Dig deeper: Advanced analytics techniques to measure PPC
Get the newsletter search marketers rely on.
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The concept of incrementality is getting more interest these days as marketing budget distribution is under greater scrutiny.
In general, this is a good thing.
For marketing budgets to be spent effectively, brands need to know:
In this way, incrementality casts a keen critical eye on additive effects and some multiplicative effects (especially toward the bottom of the funnel, since brand campaigns likely would produce conversions on their own that direct response campaigns partly cannibalize).
While incrementality testing in a silo is a powerful way to establish causality between a cause and a marketing effect, it misses the point in terms of potential synergies across channels.
Yes, it’s an important component of good marketing analysis, but it needs reinforcements to determine optimal budget distribution.
Dig deeper: Incrementality testing in advertising – Who are the winners and losers?
Advertising platforms (e.g., Google Ads, Meta Ads) use additive effects (mostly).
That’s right, advertising platforms generally use simple attribution models like last-click attribution, which assume that the last interaction is the sole contributor to a conversion.
These platforms usually treat the effects of individual ads or campaigns in isolation, assuming an additive effect.
Multi-touch attribution (MTA) uses synergistic effects (mostly).
Indeed, MTA takes into account the entire customer journey and assigns value to multiple touchpoints.
It assumes that the interactions between various marketing channels and touchpoints work together synergistically, meaning combined.
Salesforce uses additive effects.
More specifically, Salesforce’s attribution models often focus on assigning credit to various touchpoints based on lead or sales data.
They tend to follow additive effects, treating each interaction as having an individual contribution without fully factoring in the synergistic interaction between channels or activities.
Shopify uses additive or multiplicative effects (based on the model).
Shopify often uses attribution models that can range from simple last click or first click (additive) to more complex models that might include weighted attribution (multiplicative).
Shopify’s attribution doesn’t inherently assume synergy but can be configured to weigh different touchpoints more complexly.
Media mix modeling (MMM) is a more sophisticated statistical approach to assessing the overall impact of various marketing activities (TV, print, digital, etc.).
It captures synergistic effects, where the combined impact of multiple channels can result in an effect that’s greater than the sum of individual contributions, while not explicitly reporting on those effects.
MMM accounts for the interdependence between different marketing activities, capturing nonlinear relationships.
Dig deeper: Marketing attribution models: The pros and cons
You may already have some of these campaigns set up in isolation, but here’s a quick breakdown of how to assess the campaigns and their attendant effects.
In isolation, without lower-funnel campaigns to influence, branding campaigns won’t show much face value.
The effects of this campaign in a silo are almost purely additive.
In this scenario, branding is expected to take on a multiplicative role when paired with a direct response campaign.
The key idea is that their combined impact should be greater than the simple sum of what each delivers in isolation.
If the results from Test 3 exceed the combined performance of Tests 1 and 2, that confirms it: marketing effects aren’t merely additive – they’re multiplicative.
With greater scale, I would expect branding campaigns to enhance direct response performance in a non-linear fashion, showing synergistic effects as opposed to multiplicative.
Dig deeper: PPC experimentation vs. PPC testing – A practical breakdown
Any attribution method assuming additive effects is mostly inaccurate by design.
Advertisers should make sure they use more advanced models accounting for multiplicative or – even better – synergistic effects.
Capturing synergistic effects will definitely require some additional experimentation. However, optimizing
Most marketing measurement models operate on a simple assumption: effects are additive.
Campaign A drives 100 leads, Campaign B drives 200, so the total impact is 300.
But in reality, marketing often defies this logic.
Some efforts multiply the effects of others.
And in some cases, combined initiatives create outcomes that are greater than the sum – or even the product – of their parts.
These are known as additive, multiplicative, and synergistic effects.
Consider a glass of cold milk and an Oreo cookie. Each is perfectly enjoyable on its own. But together, they create something unexpectedly better.
The same principle applies to marketing: when initiatives are strategically integrated, the outcome can be amplified far beyond what any single effort could achieve on its own.
Which raises a few important questions:
Let’s start by defining the terms.
Let’s start with a quick visual before getting into the details:
Definition: The total effect is simply the sum of individual efforts.
Marketing example: If Campaign A drives 100 leads, and Campaign B drives 200 leads, then the combined result is 300 leads. No interaction – just stacking results.
Limitation: This assumes each tactic works in isolation and doesn’t influence the effectiveness of others.
Definition: The total effect is the product of factors, one enhances or scales the other.
Marketing example: If awareness increases by two times, and conversion rate increases by 1.5 times, the combined impact on sales is 2 x 1.5 = 3x. Changes in one variable amplify the other.
Limitation: It still assumes predictable, mathematical interaction, which often oversimplifies real-world marketing dynamics.
Definition: The combined effect is greater than the sum or product of individual parts – a case of “1 + 1 = 3”.
Marketing example (Les Binet-style): Long-term brand building primes an audience emotionally, while short-term performance-focused campaigns convert that primed audience into buyers.
Each alone performs OK. But together, they reinforce and amplify each other – leading to non-linear, sometimes exponentially better results.
Since we’re talking about Les Binet, let’s go even deeper and throw in a time-decay element.
Binet emphasizes that brand campaigns build the brand through every impression but battle the daily erosion of market share – with DR campaigns funding short-term brand defense as well.
Key insight: Marketing activities often interact in mutually reinforcing ways that can’t be reduced to simple math.
Limitation: Hard to model, and requires additional experimentation.
Dig deeper: Advanced analytics techniques to measure PPC
Get the newsletter search marketers rely on.
MktoForms2.loadForm(“https://app-sj02.marketo.com”, “727-ZQE-044”, 16298, function(form) {
// form.onSubmit(function(){
// });
// form.onSuccess(function (values, followUpUrl) {
// });
});
The concept of incrementality is getting more interest these days as marketing budget distribution is under greater scrutiny.
In general, this is a good thing.
For marketing budgets to be spent effectively, brands need to know:
In this way, incrementality casts a keen critical eye on additive effects and some multiplicative effects (especially toward the bottom of the funnel, since brand campaigns likely would produce conversions on their own that direct response campaigns partly cannibalize).
While incrementality testing in a silo is a powerful way to establish causality between a cause and a marketing effect, it misses the point in terms of potential synergies across channels.
Yes, it’s an important component of good marketing analysis, but it needs reinforcements to determine optimal budget distribution.
Dig deeper: Incrementality testing in advertising – Who are the winners and losers?
Advertising platforms (e.g., Google Ads, Meta Ads) use additive effects (mostly).
That’s right, advertising platforms generally use simple attribution models like last-click attribution, which assume that the last interaction is the sole contributor to a conversion.
These platforms usually treat the effects of individual ads or campaigns in isolation, assuming an additive effect.
Multi-touch attribution (MTA) uses synergistic effects (mostly).
Indeed, MTA takes into account the entire customer journey and assigns value to multiple touchpoints.
It assumes that the interactions between various marketing channels and touchpoints work together synergistically, meaning combined.
Salesforce uses additive effects.
More specifically, Salesforce’s attribution models often focus on assigning credit to various touchpoints based on lead or sales data.
They tend to follow additive effects, treating each interaction as having an individual contribution without fully factoring in the synergistic interaction between channels or activities.
Shopify uses additive or multiplicative effects (based on the model).
Shopify often uses attribution models that can range from simple last click or first click (additive) to more complex models that might include weighted attribution (multiplicative).
Shopify’s attribution doesn’t inherently assume synergy but can be configured to weigh different touchpoints more complexly.
Media mix modeling (MMM) is a more sophisticated statistical approach to assessing the overall impact of various marketing activities (TV, print, digital, etc.).
It captures synergistic effects, where the combined impact of multiple channels can result in an effect that’s greater than the sum of individual contributions, while not explicitly reporting on those effects.
MMM accounts for the interdependence between different marketing activities, capturing nonlinear relationships.
Dig deeper: Marketing attribution models: The pros and cons
You may already have some of these campaigns set up in isolation, but here’s a quick breakdown of how to assess the campaigns and their attendant effects.
In isolation, without lower-funnel campaigns to influence, branding campaigns won’t show much face value.
The effects of this campaign in a silo are almost purely additive.
In this scenario, branding is expected to take on a multiplicative role when paired with a direct response campaign.
The key idea is that their combined impact should be greater than the simple sum of what each delivers in isolation.
If the results from Test 3 exceed the combined performance of Tests 1 and 2, that confirms it: marketing effects aren’t merely additive – they’re multiplicative.
With greater scale, I would expect branding campaigns to enhance direct response performance in a non-linear fashion, showing synergistic effects as opposed to multiplicative.
Dig deeper: PPC experimentation vs. PPC testing – A practical breakdown
Any attribution method assuming additive effects is mostly inaccurate by design.
Advertisers should make sure they use more advanced models accounting for multiplicative or – even better – synergistic effects.
Capturing synergistic effects will definitely require some additional experimentation. However, optimizing
It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English. Many desktop publishing packages and web page editors now use Lorem Ipsum as their default model text, and a search for ‘lorem ipsum’ will uncover many web sites still in their infancy.
It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English. Many desktop publishing packages and web page editors now use Lorem Ipsum as their default model text, and a search for ‘lorem ipsum’ will uncover many web sites still in their infancy.
The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making
The point of using Lorem Ipsum is that it has a more-or-less normal distribution of letters, as opposed to using ‘Content here, content here’, making it look like readable English. Many desktop publishing packages and web page editors now use Lorem Ipsum as their default model text, and a search for ‘lorem ipsum’ will uncover many web sites still in their infancy.
It is a long established fact that a reader will be distracted by the readable content of a page when looking at its layout. The point of using Lorem Ipsum is that it has a more-or-less normal distribution
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