What a client means by “are we on track?” is rarely “did the number go up.” They mean: against the thing we agreed in kickoff, will we land it? Most client dashboards, including good ones, answer the first question and quietly skip the second. Adding dashboard pacing to goal fixes that, and it takes one tile rather than a new section.
The gap shows up in the five minutes before a review call. You open the dashboard, see 84 leads for October against 71 in September, and you still have no idea whether to open the call with good news or a plan. Somebody agreed to 120 leads this month. Nothing on the page knows that.
A rising line still tells you nothing about sufficiency
Period-over-period is a comparison of the account against itself, which is useful for spotting direction and for the kind of context covered in benchmarks that come from the account rather than the industry. It is a poor answer to a commitment question. A metric can be up 18% month over month and badly behind plan, or flat and comfortably ahead because the target was conservative. Direction and adequacy are independent, and dashboards almost always render only the first.
This is why review calls drift into mental arithmetic. The account manager divides in their head, usually wrong under pressure, and offers a hedge: “we’re roughly where we’d expect.” Clients hear that as a maybe. Meanwhile someone on the client side has a spreadsheet with the real target in it, and they are doing the same division while you talk.
Dashboard pacing to goal needs a target, a day count, and nothing else
The calculation is simple enough that its absence from dashboards is mostly a design oversight. Take the agreed goal for the period, multiply by days elapsed divided by days in the period, and compare the actual figure to that expectation.
Suppose the October goal is 120 leads and today is the 25th of a 31 day month. Linear expectation is 120 × 25/31, which is about 97 leads. You have 84. The tile reads 87% of pace, 13 leads behind. Same arithmetic on budget: a €20,000 monthly spend commitment with €14,100 spent by the 25th gives 87% of pace and roughly €2,000 of under-delivery to recover in six days.
Those two sentences are the entire feature. No forecasting, no confidence interval, no projected end-of-month figure dressed up as a prediction. A projection invites argument about the model. A pacing figure states a position and a date, and the client can check it on the back of an envelope.
Three things make the tile trustworthy rather than decorative:
- State the goal on the tile. “84 of 120 leads” is readable. “87% of pace” alone makes the reader hunt for the denominator.
- State the day position. Day 25 of 31 removes the main objection, which is that the comparison is unfair early in the period.
- Use the gap in units, not only a percentage. “13 leads behind” is actionable in a way that 87% is not, because it maps onto what you would actually do this week.
Linear pacing breaks in two predictable places
Mid-period launches are the first. A campaign that went live on 9 October has not had 25 days to hit a 31 day goal, and a naive tile will show it drowning. Pace against days the campaign has actually been live, or against the flighted plan if the media plan has one. If the plan front-loads 60% of budget into the first two weeks for a retail push, linear pacing will declare a problem in week three that does not exist. Pace against the flight, and if your export does not carry flight dates, pick the start date deliberately and write it on the tile.
Revised budgets are the second and messier one. A client adds €5,000 mid-month and the goal changes. If you silently update the target, last week’s pacing figure and this week’s become incomparable, and someone will notice. Keep the revision visible, which is the same discipline as annotating dips before clients ask about them: the tile shows the current goal, and a short note records that the goal moved on the 14th and why. Clients are fine with a moving target when the movement was their decision and it is written down.
Also worth saying out loud: pacing only works where a real goal exists. Inventing one so the tile has something to divide by is worse than leaving the tile out. For a metric nobody committed to, the honest dashboard shows the number and the trend.
Put the pacing figure next to its metric
The instinct is to build a summary strip across the top with every pacing figure in it. That separates the pacing number from the chart it describes, so the client reads the chart, forms an impression, then scrolls back up to check it. Keep the pacing figure in the same KPI tile as the metric, or directly above the chart for that metric. On a multi-channel report, where metric mashups cause their own confusion, pace each channel against its own goal and resist a blended one unless the client actually signed up to a blended target.
One pacing tile per committed metric, usually two or three for a whole report. That is consistent with keeping tile counts tight, which matters more than most people expect for how a dashboard reads on a call: six tiles genuinely beat fourteen.
The last piece is making it survive the month. If reports are generated from a reusable template rather than rebuilt each cycle, the goal and the pacing row live in the template, so the figure appears the same way in every client’s report and nobody recalculates it by hand at 9am before a call. That is the part Screebl is built around, templates filled from one campaign export, and the pricing page shows which plan fits the number of clients you report on.
