Adjusting Marketing Budgets Based on Performance Metrics

Most budget debates sound like this: Let’s put $100K into Channel X because last quarter ROI looked solid. Translation: You’re gambling on a single point estimate. I introduce confidence bands, an idea borrowed from finance, to make marketing spend a calculated risk, not roulette. How it works: 1️⃣ Model Return Distribution: ↳ Take the last 12 months of channel ROI. ↳ Build a simple 80 % confidence interval (CI). ↳ GA4 + BigQuery make this a two‑line SQL script. 2️⃣ Assign Risk Tiers: ↳ Channels with narrow CIs = predictable (low risk). ↳ Wide CIs = volatile (high risk). ↳ Create three tiers: Core. Growth. Experimental. 3️⃣ Allocate by Risk Appetite: ↳ Core gets stable funding. ↳ Growth receives incremental budget as long as ROI stays within band. ↳ Experimental gets capped spend, think venture bets with predefined exit rules. Result: Budgets adjust automatically to performance volatility, not politics. One e‑commerce client reallocated 15 % of ad spend from volatile display ads to a stable influencer program and saw a 26 % lift in blended ROAS, no additional dollars required. Executives love it because it turns marketing magic into disciplined portfolio management. Which risk tier currently eats most of your budget? A) Core (predictable) B) Growth (moderate risk) C) Experimental (high risk)

Spending $5M on clicks that lead to low conversion rates and a long payback period is not sustainable. Last week I audited $5M in paid search spend for a client. On the surface, things looked solid: 350K clicks, steady traffic, and positive feedback from the C-suite. But when I took a deeper dive, the reality was a bit diff. 𝗦𝘁𝗲𝗽 𝟭: 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗼𝘂𝘁𝗰𝗼𝗺𝗲𝘀, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗿𝗮𝗳𝗳𝗶𝗰 High traffic numbers can be misleading. It’s critical to evaluate how that traffic translates into actual business results. Discovery: Despite the $5M spend, we only drove 800 platform conversions, resulting in $3.5M in pipeline and $1.2M in closed-won ARR. → $6.25K per MQL → $15K per qualified opportunity → $50K cost to acquire a single customer, with a 36-month CAC payback period. This wasn’t hitting their growth targets. 𝗦𝘁𝗲𝗽 𝟮: 𝗥𝗲𝗮𝗹𝗹𝗼𝗰𝗮𝘁𝗲𝗱 𝗶𝗻𝗲𝗳𝗳𝗶𝗲𝗻𝗰𝗶𝗲𝗻𝘁 𝗯𝘂𝗱𝗴𝗲𝘁 Over $200K was spent without driving a single conversion, revealing inefficiencies that needed immediate attention. Discovery: 50% of the search budget ($2.5M) was allocated to non-branded campaigns, but these only accounted for 25% of total opportunities, with a cost-per-opportunity nearing $40K. → Non-brand CAC: $120K → Brand CAC: $35K Non-branded campaigns were clearly underperforming, costing far more to bring in leads. 𝗦𝘁𝗲𝗽 𝟯: 𝗔𝗱𝗷𝘂𝘀𝘁 𝗯𝘂𝗱𝗴𝗲𝘁 𝗮𝗹𝗹𝗼𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗯𝗶𝗱𝗱𝗶𝗻𝗴 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀 To resolve this, I recommended reallocating spend and resetting the bid strategy to focus on high-intent keywords. Discovery: A one-size-fits-all budget approach hides inefficiencies. We needed to direct more spend toward keywords and campaigns that consistently generated qualified leads. → Pause keywords that haven’t generated high-intent conversions in the past 90 days. → Optimize the bid strategy for high-intent conversions instead of TOFU metrics. 𝗦𝘁𝗲𝗽 𝟰: 𝗥𝗲𝘁𝗵𝗶𝗻𝗸 𝗰𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗺𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 The search ads were largely attracting low-intent prospects due to education-based keywords. It’s important to shift messaging to target higher-value audiences. Discovery: “What is” and “how to” queries attract traffic, but they often don’t convert into paying customers. → Focus on intent-driven queries that are aligned with decision-making stages in the buyer’s journey. 𝗦𝘁𝗲𝗽 𝟱: 𝗦𝗲𝘁 𝗿𝗲𝗮𝗹𝗶𝘀𝘁𝗶𝗰 𝗲𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 Whenever you make major adjustments to budget allocation and bidding strategies, there’s a stabilization period before performance can be accurately assessed. → Allow a few weeks for algorithms and bid strategies to stabilize before reevaluating results. TL;DR Budget cuts shouldn’t be reactive—they should be strategic.

We 1.5x'd a game design company’s ROAS and increased their new customers by 125% – while cutting ad spend by $20k/month. How? By shifting focus from booked meetings to closed customers. At first, the client was frustrated about a 25% decrease in meetings booked. Until I broke down the results for him. Here’s a snapshot: - Meetings: ↓ 25% - Cost/customer: ↓ 40% - # of contracts sent: ↑ 3x - # new customers: ↑ 1.25x - Ad spend: ↓ by $20k/month Here’s how we did it in 4 steps: (Plus 4 tips on how you can do the same) 1. Shifted budget allocation: We moved ad spend away from campaigns that were generating a lot of meetings but only converting 5% or less into contracts and customers. How To Do It: Measure results against # of customers and cost/customer, not just sign-ups or # of meetings booked. 2. Adjusted CPA targets: We're now willing to pay about 120-150% more per meeting in order to get a significantly lower cost per customer. How To Do It: Scrutinize each campaign individually, paying attention to those that generate real customers and what you’re paying for those customers (vs other measurable CPAs). 3. Excluded low-quality leads: We filtered out competitors and other non-converting leads, increasing our cost per meeting but dramatically improving our conversion rates and cost per customer. How To Do It: Be willing to see certain metrics (like total meetings) decrease if it means improving overall campaign effectiveness. 4. Optimized for customer acquisition: Instead of chasing meeting numbers, we're telling the algorithm to go after the type of leads that are likely to become customers. How To Do It: Have the discipline to reallocate ad spend from high-volume, low-converting campaigns to those that consistently produce customers. _______ A packed calendar of meetings is like a football team that gains tons of yards but never scores. It looks great on paper, but it doesn't win games – or grow your business. Screw the vanity metrics. Go for customers and conversions. Does this resonate?