Sales Lift compares purchase outcomes for an exposed group and a control group within an agreed observation window. Pharma studies may use available anonymised pharmacy purchase data and partner matching. The result is a difference within that study design; it should not automatically be extrapolated to the whole market or treated as causal when groups are not comparable.
How it works
- 01Agree KPI and study design
- 02Build comparable groups
- 03Run campaign and observe purchases
- 04Calculate difference and limitations
One eligible audience, two comparable groups
Study design
Agree on purchases, buyers or sales value as the KPI. Set baseline and follow-up windows, test and control criteria and minimum sample size before launch.
Reading incrementality
Distinguish percentage points, relative uplift and absolute purchases. A simple exposure-purchase match shows association, not necessarily added effect.
What is fixed, and when
- 01Before the campaign
Set the KPI, baseline, test and control groups, matching rules and purchase window.
- 02During the campaign
Show ads to the test group and record exposure. Keep control free from planned exposure.
- 03After the campaign
Compare purchases in the agreed window and examine external factors.
Published example
In a 2023 medical device case, purchase conversion in the test group was 34% higher than control. This is one campaign result, not a forecast for other brands.
“+10%” and “+1 pp” describe different quantities
What Sales Lift measures
The study asks whether people exposed to the campaign bought more than a comparable unexposed audience. The primary KPI can be buyer rate, purchases, frequency, units or sales value, depending on the brand objective and available data. It is fixed before results are seen.
Why control is designed in advance
Before media runs, define who can be exposed, who remains in control, the baseline and matching rules. Once a campaign has ended without this design, a comparable genuinely unexposed group cannot be reliably created after the fact.
What the report contains
The report describes the sample, groups, pre and post periods, purchase source, primary KPI, observed difference and relevant external factors. Absolute values and relative uplift are shown separately so a percentage is not mistaken for percentage points or total brand sales.
Where the study is useful
Sales Lift can test offline impact from a launch, competitor-buyer strategy, repeat-purchase effort or audience comparison. Feasibility is checked anew for every category, purchase volume, reach and campaign schedule.
Limitations
Low purchase volumes, weak matching, incomparable groups and unavailable data can make Sales Lift unsuitable. Seasonality and promotions also matter.
Questions
How does Sales Lift differ from Brand Lift?
Sales Lift measures purchase behaviour using sales data. Brand Lift typically surveys awareness, perception or intent. They answer different questions and can be used together.
Can Sales Lift be ordered after a campaign has ended?
No. Pharmatic's standard Sales Lift must be designed before launch, with test and control groups, a baseline, KPI and purchase window. A valid unexposed control cannot be created retrospectively. A retrospective sales analysis is a different, weaker study.
What data are required?
The study needs ad exposure data, available anonymised purchase data and an agreed partner matching route. Group size, purchase frequency and category coverage are checked before launch.
What if most sales happen in offline pharmacies?
Partner purchase data can make this measurable. We check category coverage and whether enough purchases are observable for a group comparison.
Does the result equal total brand sales growth?
No. It is a difference in the agreed sample and metric. Wider extrapolation requires additional assumptions and calculations.
Can promotions or seasonality affect the result?
Yes. We account for promotions, distribution changes and seasonality in study design and explain material external events in the report.