What is adstock?
Adstock is the modelling term for the carryover advertising effect - the observation that the influence of an ad does not stop when the impression ends. Someone who sees a campaign today might search, compare, and finally convert a week later. In aggregate, this means a given week’s conversions are driven partly by that week’s spend and partly by a fading memory of the spend that came before it. Adstock captures that memory mathematically.
The mechanism is a simple decay. Each period retains a fraction of the previous period’s accumulated adstock and adds the new spend on top. A high decay rate means impact lingers for many weeks; a low rate means it fades almost immediately. The shape varies by channel: brand video and upper-funnel display tend to carry over for longer, while high-intent search converts close to the point of exposure. Modelling this carryover is essential to understanding the true commercial contribution of each channel, and it pairs naturally with the diminishing-returns behaviour of the Hill function used to describe saturation.
How does advertising carryover work?
Advertising rarely produces an instant, one-to-one response. Exposure plants awareness and intent that ripen over time - a process media planners describe as the carryover advertising effect. Picture a single burst of spend on a Monday: a portion of the resulting conversions land that day, a smaller portion on Tuesday, fewer still on Wednesday, and so on, forming a decaying tail rather than a single spike. Adstock models that tail by carrying a percentage of each period’s effect forward into the next.
The practical consequence is that the conversions you record in any week are a blend of recent and older spend. If two channels deliver the same number of conversions but one creates them slowly and the other harvests them instantly, naive analysis will treat them as identical - and badly misallocate budget between them. Understanding carryover is therefore closely tied to thinking about incremental return on ad spend, which isolates the revenue advertising genuinely caused from the revenue that would have arrived anyway.
Why do short reporting windows undervalue demand creation?
Most reporting and attribution windows are short - a few days, sometimes a single click session. Adstock guarantees that a meaningful share of a channel’s real impact lands after that window closes. The conversions are counted, but credited to whatever channel happened to be in front of the customer at the moment of purchase. Demand-creation channels, whose payoff is inherently delayed, are therefore chronically under-measured, while last-click harvesting channels collect credit for demand they did not create.
Left unchecked, this distortion compounds. Budgets shift toward channels that look efficient inside the window, starving the upper-funnel activity that fed them in the first place - and the harvesting channels then quietly weaken as the demand pipeline dries up. Planning that accounts for carryover avoids this trap. It is also why scaling a winning channel often disappoints: as spend rises, each additional pound reaches less responsive audiences and returns less, the dynamic explained by saturation curves and budget ceilings. The two effects work together: carryover stretches impact across time, saturation caps how much impact extra spend can buy.
How ElenIQ models adstock
ElenIQ applies an adstock transformation to historic spend before fitting its response models, so each period’s effect carries a decaying contribution from earlier spend rather than treating every week in isolation. The decay is estimated from the data, channel by channel, so demand-creating media is credited for the delayed conversions it produces instead of having that value silently reassigned to last-click channels.
Layering adstock on top of saturation curves lets ElenIQ forecast the fuller, time-shifted impact of a budget change before the spend is committed - true to the platform’s forecast-led, marginal approach to media planning. Rather than reacting to what a short window happened to capture, you can compare the carryover-adjusted return of each channel and decide where the next pound works hardest. Explore how it fits a full plan with Dex, ElenIQ’s forecasting engine, or weigh efficiency directly with the difference between marginal and average ROAS.
Related terms
- Hill function - the curve used to model how response flattens near saturation.
- iROAS - the incremental revenue advertising actually creates, net of baseline demand.
- Marginal ROAS vs average ROAS - why the efficiency of your next pound differs from your blended average.
Frequently asked questions
What is adstock?
Adstock is the carryover effect of advertising - the way the impact of an ad persists after exposure rather than vanishing immediately. In media modelling, this period’s response depends partly on current spend and partly on a decaying memory of previous spend, which is why advertising can keep driving conversions well after the impression was served.
What is the carryover advertising effect?
The carryover advertising effect is the same idea as adstock: a portion of the demand created by advertising arrives later than the exposure itself. Each period retains a fraction of the prior period’s adstock, so a single burst of spend produces a tail of delayed conversions that decays over subsequent days or weeks.
Why do short reporting windows undervalue demand creation?
Because adstock spreads impact across time, conversions that an ad genuinely caused can land outside a short attribution or reporting window. Channels that create demand - rather than simply harvest it at the point of intent - look weaker than they are, so budgets drift toward last-click harvesting channels and away from the demand creation that feeds them.
How does ElenIQ model adstock?
ElenIQ applies an adstock transformation to historic spend before fitting its response models, so each period’s effect includes a decaying contribution from earlier spend. Combined with saturation curves, this lets ElenIQ forecast the fuller, time-shifted impact of a budget change rather than only the conversions that fall inside a narrow window.