How to Prioritize Marketing Actions by Revenue Impact

Every small team has the same problem: forty good ideas and time for four. The usual way to choose is gut feeling, or whatever the last podcast recommended. This guide gives you a simple, repeatable way to rank marketing actions by the money they're likely to bring in, with worked examples you can copy.

The formula

Priority = Impact × Confidence ÷ Effort

It's a close cousin of two well-known frameworks: ICE (impact, confidence, ease), popularized by Sean Ellis for growth teams, and RICE (reach, impact, confidence, effort), developed at Intercom (Intercom's original post). The version here makes one change that matters for small businesses: impact is measured in money, not on a 1–10 scale.

Impact: dollars per month, if it works

Express every idea in the same unit: extra monthly revenue, or extra monthly gross margin when the idea involves ad spend, discounts or product costs. A 1–10 scale lets you rate "launch a podcast" an 8 without ever writing down why. A money figure forces you to.

Confidence: how sure you are, from 0.1 to 0.9

Confidence	When to use it
0.8–0.9	You've done this before and measured it, or your own data shows the effect
0.5–0.7	A proven tactic, and your data shows the gap it fixes (e.g. no cart recovery emails, a page stuck in position 11)
0.3–0.4	Proven for other companies; no evidence yet for yours
0.1–0.2	A hunch, a trend, "someone said it worked for them"

Never use 1.0. Nothing in marketing is certain.

Effort: person-days

Count the real time, including review, approvals and set-up, until the action is live. If something needs a developer, a designer or a supplier, include their time. Use half-days for small tasks.

Size impact with explicit assumptions

The heart of the method is one line per idea:

Baseline × expected change × value per conversion = monthly impact

• Baseline: a number from your data (visitors to a page, trials per month, abandoned carts). If you don't have it, write a realistic assumption and label it as one.
• Expected change: a conservative range. Use your past results when you have them; otherwise, use the low end of what you think is plausible.
• Value per conversion: what one extra sale, customer or lead is worth. For subscriptions, use a fixed horizon such as first-year revenue so all ideas are comparable. For e-commerce, use gross margin per order when costs are involved.

Write the assumptions where everyone can see them. The point isn't to be precise; it's to make every estimate arguable. "I think 3% of abandoned carts will come back" can be challenged and later checked. "This feels big" can't.

Rank on the low end of your range. Optimism is evenly spread across ideas; using the cautious figure keeps exciting ideas from jumping the line.

Worked example 1: a small SaaS

All numbers in this section are examples.

Baseline: 8,000 visitors a month, 2% start a trial (160 trials), 15% of trials become paying customers (24 a month), average revenue $40/month per customer. Value of one new customer = first-year revenue = $480 (assumption: we use one year for every idea).

A. Trial onboarding email sequence (assuming there isn't one) 160 trials × trial-to-paid rising from 15% to 16.5% (assumption: +10% relative) = +2.4 customers × $480 = $1,152/month. Confidence 0.5, effort 3 days.

B. Pricing page: recommended plan + FAQ Assume half of trials pass through the pricing page (80). +10% of those (assumption) = +8 trials × 15% = +1.2 customers × $480 = $576/month. Confidence 0.5, effort 2 days.

C. Rewrite titles of 6 pages with high impressions and low click-through rate 30,000 impressions a month at 1% CTR = 300 clicks (Search Console). CTR to 1.5% (low end of the hoped-for range) = +150 clicks × 2% = 3 trials × 15% = 0.45 customers × $480 = $216/month. Confidence 0.5, effort 1 day.

D. "[Leader] alternative" page Assume 300 searches a month (to confirm in a keyword tool) × 10% reaching our page once it ranks = 30 visits × 6% trial rate for high-intent visitors (assumption) = 1.8 trials × 15% = 0.27 customers × $480 = $130/month. Confidence 0.3 (ranking is uncertain), effort 2 days.

E. Launch a podcast Assume one extra customer a month after three months = $480/month. Confidence 0.2, effort 10 days to launch.

F. Redesign the website Assume +5% trial rate = 8 trials × 15% = 1.2 customers × $480 = $576/month. Confidence 0.3, effort 20 days.

Idea	Impact ($/month)	Confidence	Effort (days)	Score
A. Trial email sequence	1,152	0.5	3	192
B. Pricing page fix	576	0.5	2	144
C. Low-CTR title rewrites	216	0.5	1	108
D. Alternative page	130	0.3	2	19.5
E. Podcast	480	0.2	10	9.6
F. Website redesign	576	0.3	20	8.6

What the table tells you: the redesign has the same raw impact as the pricing fix but scores 17 times lower, because it takes ten times as long and is less certain. The alternative page scores low on direct search alone; if you'd also use it in sales emails and paid search, add that to its impact and re-score. That's the method working: it makes you state why you believe something.

Worked example 2: a small e-commerce brand

Example numbers. 20,000 visitors a month, 1.5% conversion (300 orders), average order $55, gross margin 60%.

Idea	Calculation (assumptions labeled)	Monthly margin	Conf.	Effort	Score
Abandoned cart emails (if none)	Assume 600 abandoned carts with an email address × 3% recovered = 18 orders × $55 × 60%	$594	0.6	1	356
Gift bundles	Assume 30% of orders (90) take a bundle adding $15 each = $1,350 × 60%	$810	0.4	3	108
+$1,000/month on Meta ads	Assume ROAS of 2 = $2,000 revenue × 60% = $1,200 − $1,000 spend	$200	0.5	2	50
Gifting to 20 micro-creators	Assume $1,500 revenue × 60% = $900 − $400 product cost	$500	0.25	4	31

Two lessons. First, always subtract the cost of spend-based ideas: the ad budget looked like "+$2,000" until margin and spend were counted. Second, some ideas have side benefits that the number misses: creator gifting also produces photos and videos you can reuse in ads (with the creators' permission, and a clear #ad disclosure if they post in exchange for the product, as the FTC requires). Note side benefits next to the score rather than inflating the impact.

Quick wins vs big bets

Put your scored ideas on two axes: impact (high/low) and effort (low/high).

	Low effort	High effort
High impact	Quick wins: do now (cart emails, title rewrites, pricing FAQ)	Big bets: pick one at a time, with a test plan
Low impact	Fill-ins: batch them on a slow afternoon	Avoid: say no clearly

Typical quick wins: rewriting a homepage headline that doesn't say what you sell; titles and meta descriptions for pages with high impressions and low clicks; abandoned cart or trial emails if missing; a review request after delivery; internal links to your best-converting page.

Typical big bets: a free tool or calculator for your audience; an affiliate or partner program; a new customer segment with its own landing pages; a new product line sold to your existing customers; a founder-led content channel.

A healthy month spends most of its time on quick wins and keeps one big bet running, with a deadline and a success criterion. Big bets are where the step changes come from; quick wins pay for the time.

Common mistakes

• Counting traffic instead of revenue. "+2,000 visits" means nothing until you multiply by conversion and value.
• Ignoring margin and spend. Revenue from discounts and ads is not the same as revenue from email.
• Double counting. Two ideas improving the same page don't add up fully. Score the second one on what's left after the first.
• Confidence inflation. If every idea is 0.8, you're not using the scale. Most new ideas belong at 0.3–0.5.
• Forgetting time to impact. SEO pages can take months to rank; an email flow works next week. If cash matters this quarter, note the delay.
• Never re-scoring. After two weeks, update confidence with what you've learned. A test that shows nothing after its deadline is a stop, not a "maybe later".

Your prioritization sheet (copy these columns)

Idea	Page / channel	Baseline (source)	Expected change (assumption)	Value per conversion	Impact $/month	Confidence	Effort (days)	Score	Side benefits	Owner	Review date

Review it every Monday. Do the top three. Add new ideas at the bottom, score them, and let them earn their place.

For a ready-made sequence of actions to score, see our 30-day marketing plan.

How Toby does this for you

Toby's recommendation engine uses this same logic:

• Every recommendation carries an impact estimate written as a chain (baseline × rate = result), where the baseline is a number from your site or connected data, or a value clearly marked as an assumption. It also has a monthly value, a confidence level, an effort level and the agent in charge.
• Recommendations come from data signals (for example, pages in positions 8–15 in Search Console) and from a library of proven plays matched to your type of business.
• A critical review checks each recommendation before you see it: is it specific to your company, supported by evidence, sized for your scale, and is the first step ready? Generic ideas are rewritten or dropped.
• When you click Dismiss, you can give a reason, and future recommendations take it into account. When you mark one as done, Toby checks the result a week later.
• If a tool isn't connected, Toby doesn't invent numbers for it: estimates are given as relative ranges with the metric to watch.

Run the free growth audit to get your first three scored recommendations, or see pricing.