Sizing a Playbook Audience

Every Playbook opens with a recommended audience size already filled in. Dataro calculates that number from your organization's giving history for the campaign type and your own cost per contact (if applicable), and you can override it whenever your budget or channel calls for a different figure.

Dataro ranks every eligible donor by how likely they are to respond, then works down that ranked list calculating whether contacting one more person is worth what it costs. The recommendation is the point in the list where the answer becomes no.

Below the size field is a toggle called Always maintain audience size. It answers a question the number alone cannot: what should happen when donors drop out of your audience?

Donors drop out for ordinary reasons: exclusions remove people who do not meet the Playbook's requirements, contact suppressions and opt-outs remove people you are not allowed to reach, and the data changes between one week's prediction refresh and the next.

Toggle on means your number is honored regardless of who drops out. If your budget covers 10,000 donors, Dataro gives you the best 10,000 available, backfilling from the next-best donors on the ranking as people are removed so the audience stays at 10,000.

Toggle off means you keep those 10,000 donors and no others. Exclusions shrink the list and nothing replaces them, so you might end up mailing 8,400.

We recommend leaving the toggle on, and turning it off only when you are running a controlled test and need the audience composition held fixed.

Consider the situation the toggle prevents. An organization is recommended 5,000 donors, so they use exactly 5,000. Their normal volume for that campaign is 17,000, so they mail the remaining 12,000 without Dataro targeting, because those donors were never part of the ranked recommendation. Dataro is then measured against the whole campaign, where two thirds of the volume had no targeting behind it at all, and the result does not tell you how well the ranking worked. The fix is straightforward: if you normally mail 17,000, override the size to 17,000 and turn Always maintain audience size on. You get your full volume ranked best-first, and the comparison against last year is a fair one.

Every Playbook arrives with sensible exclusions already applied, and they are the usual reason a Playbook audience is smaller than a count you pulled yourself. These are the published sets.

Each set reflects a piece of fundraising judgment. The churn-save requirements exist because the intervention is a phone call: without an active phone number there is no way to run it, and a donor who has already been called in the past three months should not be called again. The requirement for three lifetime transactions filters out donors who never established a regular giving habit.

The upgrade exclusion works the same way. A churn score below 0.5 means you only ask donors who are reasonably stable to increase their gift, because asking a donor who is already close to cancelling for more money is likely to lose them altogether. Reactivation waits 90 days past the last payment so you are not chasing a failed transaction that is about to retry on its own.

The recommendation optimizes for return on investment. It does not account for your print deadline, your channel mix, or the number the board approved in March. When those constraints matter more than the economics, click Need a custom recommendation? Reach out on the Playbook you are sizing.

Sizing guidance on its own is often too wide to plan against. A range of 500,000 to a million is technically correct for a campaign type, but it does not tell you what to mail. A custom request brings three inputs into one answer: what Dataro knows about how your file ranks, what the expert consultants say about that campaign type, and what you are trying to achieve. You are asked for six things:

The two most useful fields are previous campaign size and goal. Previous size anchors the answer in what your organization already does rather than in theory, and the goal tells us what to optimize for, because a request that asks for the most revenue gets a different answer from one that asks for the best response rate. The last field is worth filling in as well: print deadlines, a mail house minimum, a segment your CEO has promised to a major donor, or a region you cannot contact this quarter all change the recommendation, and none of it appears in your data.

The request routes to the Dataro product team, who review it against your models and the consultant guidance for that campaign type and come back with a bespoke recommendation, with your CSM copied on the response so they can help you interpret it and act on it. Dataro also reviews the requests that come in to see which sizing questions arise most often, so that automated campaign sizing can answer more of them directly.

Most sizing questions do not need a request. If you know your number, type it in and turn on Always maintain audience size. We recommend a request when the question is still open:

• The Dataro recommendation is far from your usual volume and you want to understand the gap before committing.
• You are running a campaign type for the first time and have no previous size to anchor on.
• You are running across several channels at once and the single cost per contact assumption does not hold.
• You have a revenue target and want to know whether the audience can plausibly support it.

Why is my recommended size smaller than what I normally mail?

Because the recommendation stops at the point where each additional contact costs more than it returns, and your usual mail volume may include donors the model rates as unlikely to respond. We recommend overriding the size up to your normal volume and turning on Always maintain audience size, which gives you your full volume ranked best-first.

Where does the cost figure come from?

The Cost Per Piece field in your organization settings. Dataro multiplies it by your audience size to get campaign cost, then uses that in the expected-value calculation. If nobody has updated Cost Per Piece since postal rates went up, your recommended sizes will be too large.

Can I see why a specific donor made the cut?

Open their donor profile and look for Show prediction reasons, which lists the top five factors driving their score. The Playbook itself shows you the ranked list, not the per-donor reasoning.

If Dataro backfills, am I contacting worse donors?

You are contacting the next-best donors on the same ranking, which is the group you would have selected next yourself. Backfill never reaches outside the eligible pool or past the exclusions, so the replacements meet the same requirements as every other donor in the audience.

My Playbook audience is smaller than the count I pulled from my CRM. Why?

Exclusions are almost always the reason. Check the recommended set for that Playbook in the table above, and remember that a direct mail Playbook drops every donor without a valid postal address, which can be a large share of a file.