Can MMM and Incrementality testing measure the full sales impact of mid-funnel and top-of-funnel campaigns?

This question came up in a recent meeting with a senior marketing leader at a large ecommerce company.

The short answer

Yes. The full sales impact of mid-funnel and top-of-funnel campaigns can be measured with MMM and incrementality tests by separating immediate sales effects (0-14 days), delayed sales effects (15-60 days), and the lifetime value of media-driven customer acquisitions. In addition, Brand tracking provides supporting evidence for sustained changes in awareness, consideration, and preference.

Why do marketers ask this?

Campaigns that don't appear to generate strong immediate sales results receive constant scrutiny from finance and performance-focused marketers. Whether you call them mid-funnel campaigns, top-of-funnel campaigns, awareness campaigns, or branding campaigns, they all face the same challenge.

The reasons are simple:

• Marketers using attribution as the measurement backbone can see that performance campaigns appear to produce immediate, trackable conversions, while an awareness campaign may not generate a click or purchase within the reporting window.

• A Marketing Mix Model that is not configured to estimate delayed and long-term effects may provide a more balanced view of short-term performance but still miss the longer-term impact.

That creates an unfair comparison. A retargeting ad has a short time to sale. A video, TV, or upper-funnel social campaign may have a smaller immediate effect but larger delayed effects. If both are judged based on the immediate sales effects, the lower-funnel campaign usually wins.

In the meeting that prompted this article, the marketer described exactly this pressure. Awareness campaigns showed the lowest ROI in existing dashboards, but the team did not believe those numbers reflected their downstream impact. When teams optimized media ROI using those incomplete dashboards, reallocating spend from brand activity to campaigns with visible immediate sales effects looked like the easiest option.

This is not only a measurement problem. It is an organizational problem. Brand teams, performance teams, analytics, and finance can all be looking at valid but incomplete evidence. The solution is to separate the ways marketing creates value and measure each one on the right time horizon.

What effects should brand awareness measurement include?

Marketing measurement should separate at least four effects instead of forcing all value into immediate conversions.

1. Immediate sales effects (0-14 days). This is media's short-term sales effect and the most directly observable of the four. 

2. Delayed sales effects (15-60 days). Advertising can influence purchases weeks or months later, especially in categories with longer consideration cycles. These are the delayed sales effects of media.

3. Lifetime value of new customers. Some campaigns are designed to drive app installs, loyalty-program sign-ups, or other customer-acquisition events rather than immediate sales. Their value appears through the purchases those customers make over time. 

4. Brand KPI movement. Brand tracking surveys can measure awareness, consideration, and preference. Because survey samples are limited, week-to-week and even month-to-month results can be noisy. The data is most useful for identifying sustained directional change over time.

How do MMM and incrementality tests measure each effect?

1. Immediate sales effect (0-14 days). These effects are well captured by Marketing Mix Modeling (MMM) and incrementality testing. In fact, most marketing measurement focuses on measuring these effects. MMM is a time-series methodology that analyses whether changes in sales can be explained with changes in media spend, promotional activity, or other sales drivers, making it well suited for estimating short-term effects.

Similarly, many incrementality tests nowadays are geo hold-outs, where the sales decline is often observed within a short time period to estimate media ROI. As a visual example, below is an illustration of a two-week incrementality test. On the lower-left chart, you can see media spend falling to zero for the tested markets, whereas spend for the synthetic counterfactual remains active. On the upper-right chart, you can see the cumulative difference between the sales in the target market and the counterfactual, showing the lost sales within the two-week period in the market where the test was conducted.

2. Delayed sales effect (15-60 days). Delayed sales effects can be captured by MMMs that are calibrated with incrementality tests and configured with appropriate carryover parameters. Delayed effects are also visible in post-treatment windows of incrementality tests: after media spend returns to its previous level, the cumulative difference between actual sales and the counterfactual may continue to grow for some time before stabilizing.

3. Lifetime value of new customers. For large ecommerce businesses, acquisition-focused campaigns, such as app installs or loyalty programs sign-ups, can represent a substantial share of media spend, anywhere from 10-70% of total spend. One of the strongest method for estimating the full incremental ROAS (Full iROAS) is to model media-driven customer acquisitions separately, then apply a Customer Lifetime Value (CLV) specific to the customer's country, acquisition channel, and cohort. The ecommerce formula becomes:

• GMV = Gross Merchandise Value, a common ecommerce sales metric
• Incremental GMV = GMV caused by media
• Leads = Early-funnel acquisition events, such as an app install or loyalty-program sign-up
• Incremental leads = Acquisition events caused by media
• CLV = Customer Lifetime Value for a specific country, acquisition channel, and cohort

4. Brand KPI movement. Brand tracking can show whether awareness, consideration, or preference moved after a campaign, but it does not prove incremental sales by itself. Use it as supporting evidence alongside MMM, conversion lift, geo tests, or another causal sales measurement method.

How this looks in practice

Consider a hypothetical ecommerce brand that invests $1M in a brand awareness campaign. Its immediate short-term sales impact is $1.5M in incremental sales, suggesting an incremental ROAS of 1.5. A finance leader who knows the gross margin is 50% might stop here.

The broader measurement shows a different picture:

The short-term view reports an incremental ROAS of 1.5. The combined view reports an incremental ROAS of 3.5. More importantly, it shows exactly where the additional value comes from. The $2 million generated beyond the immediate sales effect would be missed if measurement focused only on immediate sales.

The purpose of this view is not to guarantee that every brand awareness campaign works. Some will not. It is to compare longer-horizon and performance activities using a complete measurement framework, then move budget toward the campaigns that create the most incremental value over the time horizon that matters to the business.

Related questions

How long should you wait before judging an awareness campaign?

Use a window that matches the effect and the category's purchase cycle. Immediate sales may be visible within 14 days, delayed sales can continue for 15-60 days, and customer value may develop beyond 60 days. Longer windows require stronger evidence because more outside factors can influence the result.

Can brand tracking prove that an awareness campaign generated sales?

Not by itself. Brand tracking can show whether awareness, consideration, or preference moved after a campaign, but it does not establish incremental revenue. Use it as supporting evidence alongside MMM, conversion lift, geo tests, or another causal sales measurement method.

How do you avoid double counting delayed sales and customer lifetime value?

Define non-overlapping outcomes and time windows before combining them. If the MMM already credits a later purchase to media, that purchase should not also be included in the CLV adjustment. A practical approach is to value only the customer revenue that falls outside the sales already captured by the immediate and delayed-effect models.

When is a long-term marketing effect too uncertain to include in ROI?

Leave it outside the ROI calculation when the result depends on unstable brand data, unsupported assumptions, or a model that cannot separate media from other demand drivers. Report the signal separately until stronger evidence is available.

How Sellforte helps

Sellforte combines Marketing Mix Modeling, incrementality testing, attribution, and customer value data to measure both immediate and delayed marketing effects. Marketing teams can compare channels using incremental outcomes, inspect the evidence behind each result, and plan budgets without automatically penalizing upper-funnel activity. Book a demo.

Authors

Lauri Potka is the Chief Operating Officer at Sellforte, with over 15 years of experience in Marketing Mix Modeling, marketing measurement, and media spend optimization. Before joining Sellforte, he worked as a management consultant at the Boston Consulting Group, advising some of the world’s largest advertisers on data-driven marketing optimization. Follow Lauri on LinkedIn, where he is one of the leading voices in MMM and marketing measurement.