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If you’re running ads on multiple platforms— Facebook/Instagram (Meta), Google, TikTok, Pinterest, and LinkedIn —scaling isn’t just “increase the budget.” One of my pet peeve is clients who want to scale everything all at once so they can rapidly increase revenue. That's not how marketing works and that's that's the quickest way to spend too much and go into the red. Scaling is a decision system. Because the fastest way to kill performance is to: scale the wrong platform, scale before tracking is clean, scale before the funnel can handle it, or scale based on the wrong metric. This guide gives you a clear framework: when to scale, what to scale first, what metrics to watch, and how to scale without destabilizing results. Step 1: Decide what “scale” means for your business Scaling can mean different things: More volume at similar efficiency  (more leads/purchases at similar CAC/CPA) More efficiency at similar spend  (improve CAC first, then scale) More revenue at acceptable efficiency  (CAC can rise, but profit stays healthy) More pipeline  (B2B: qualified conversations and opportunities, not just leads) Before you touch budgets, define: Your target CAC/CPA Your “max allowable” CAC/CPA Your margin or payback constraints Your capacity constraints (sales team, fulfillment, appointment availability) If you don’t define guardrails, scaling becomes emotional. Step 2: Do NOT scale until these foundations are true 1) Your tracking is credible If conversion tracking is noisy, you’ll scale into chaos. At minimum, you need: one primary conversion that reflects real value (purchase / booked call / qualified lead) consistent counting (no duplicates, no inflated micro-events) a clear view of conversion rate by landing page 2) Your funnel isn’t the bottleneck If leads don’t close, scaling spend just increases disappointment. Make sure you know: lead-to-qualified rate qualified-to-close rate (or booked call rate) time to convert 3) You have creative capacity Most scaling stalls because creative fatigues. If you can’t produce new angles and iterations, you don’t have a scaling engine—you have a campaign. Step 3: Use the “Incremental Scale” rule (don’t scale everything at once) If you scale all platforms at once, you lose causality: you won’t know what worked you won’t know what broke attribution will get messy fast Default approach:  scale one platform or one lever at a time , then re-evaluate. Exceptions: seasonal windows (Black Friday, January enrollments) obvious under-spend with proven performance you have mature measurement (MMM, holdouts, geo tests) For most growth-stage companies: one lever at a time wins. Step 4: Pick what to scale first using a simple hierarchy Tier 1: Capture existing intent (usually Google) If people are already searching for a solution, scaling here tends to be the cleanest. Scale when: impression share is being lost (budget-limited) conversion rate is stable lead quality is consistent Watch: CPA/CAC Conversion rate Search impression share lost to budget Quality of leads  (not optional) Tier 2: Retargeting (Meta / Google / LinkedIn) Retargeting usually scales until it saturates. Scale when: frequency isn’t excessive incremental conversions are still increasing you have enough site traffic to support it Watch: frequency CPA incrementality  (is it just stealing credit?) Tier 3: Prospecting / discovery (Meta, TikTok, Pinterest, LinkedIn) This is where scaling gets more complex and creative-dependent. S cale when: your creative is producing consistent winners your conversion rate holds after increasing spend you have a testing system Watch: CPA/CAC CVR cost per click / CPM trends creative fatigue metrics  (frequency, CTR decline, rising CPM) Step 5: The “Budget Scaling Decision” scorecard (what to look at) Core metrics (all platforms) These are your universal decision metrics: CAC/CPA vs guardrails Green: at or below target Yellow: rising but still within max allowable Red: above max allowable Conversion rate stability: If CVR drops significantly after budget increases, your funnel or targeting can’t support the scale. Lead quality / downstream rate: For lead gen: do not scale based on raw leads.Track: % qualified booked rate close rate (where possible) Marginal return: Ask: “If I add the next $1,000, what do I reasonably expect back?” This is the real scaling question. Step 6: How to scale budgets (the safe mechanics) Rule of thumb: scale in controlled increments Increase budgets 10–20% at a time Hold for 3–7 days  (longer for B2B) Evaluate before the next increase Avoid doubling budgets overnight unless you’re in a short seasonal spike and can tolerate volatility. Scale the constraint , not the whole account Instead of “increase total spend,” identify what’s limiting growth: budget-limited campaigns winning ad sets top-performing audiences high-intent keywords best creative angles best landing pages Then add budget there , not everywhere. Scale by duplicating winners when needed Sometimes increasing budget on one campaign destabilizes it.In that case: duplicate the winner keep targeting/creative consistent split budgets. This can preserve performance while increasing volume. Step 7: Platform-specific scaling considerations Meta (Facebook + Instagram) Meta scales best when: you have multiple creative angles you can feed the algorithm consistent conversion signals you can handle creative refresh cycles Watch: CPA, CVR CPM and frequency creative fatigue (CTR decline + rising CPA) breakdowns by placement and audience Scaling lever options: increase budgets on winning ad sets broaden audiences gradually refresh creative weekly/biweekly depending on spend Google Google scales differently because intent is finite.If you’re already capturing most intent, you need to expand: new keyword themes new markets/locations new offers/landing pages sometimes YouTube or discovery-type expansion Watch: impression share lost to budget CPA/CAC and conversion rate query quality (don’t expand into junk intent) TikTok TikTok is creative-led.Scaling depends heavily on: UGC volume fast iteration strong hooks and offers Watch: CPA/CAC and CVR creative fatigue holdout performance by creative angle (what truly drives conversions) Pinterest Pinterest can scale well for: visual products lifestyle inspiration evergreen discovery Watch: click quality (time on site, pages/session) conversion lag (Pinterest often assists before it converts) assisted conversions in analytics LinkedIn LinkedIn is expensive but can be worth it for B2B.Scaling requires: strong ICP targeting clear offer (not generic “learn more”) tight lead qualification Watch: cost per qualified lead (not raw lead) booked meeting rate pipeline influence (where possible) job title/function targeting performance Step 8: The biggest scaling mistake: using the wrong “north star” metric For ecommerce Use: Contribution margin-aware CAC MER (blended) as a directional metric cohort LTV as you scale For lead gen Use: cost per qualified lead cost per booked call and if possible, cost per closed deal For B2B Use: cost per qualified conversation opportunity creation rate pipeline per dollar (directional is fine) If you scale on raw CPL or ROAS alone, you’ll often scale low-quality volume. Step 9: A simple scaling plan you can run every week Weekly scaling meeting agenda (30 minutes): What platform had the best marginal return last week? Which campaigns are budget-limited and  hitting quality targets? Where did conversion rate drop (landing page, offer, audience)? What creative is fatiguing, and what’s replacing it? Choose one scaling move  for the next 7 days. This prevents random scaling and keeps learning clean. Bottom line: Scale one lever at a time, using guardrails and marginal return If you’re running ads across Meta, Google, TikTok, Pinterest, and LinkedIn, scaling should follow a disciplined system: define CAC guardrails validate tracking + funnel scale one lever at a time watch conversion rate and quality downstream invest where marginal returns are strongest That’s how you scale without blowing up performance.

Most businesses don’t have a marketing problem. They have a message-market mismatch  problem. You’re saying one thing. Your best customers are thinking another. And the gap shows up as: expensive acquisition, low conversion rates, inconsistent lead quality, and churn that feels “mysterious.” That’s what Voice of Customer (VoC)  fixes. This guide explains what VoC really means, how to assess it using data you already have, and how to translate it into revenue improvements across marketing, sales, and product. What is “Voice of Customer” (VoC)? Voice of Customer is the real language, motivations, fears, and decision criteria  customers use when they: realize they have a problem, search for solutions, compare options, buy, and decide whether to stay or leave. VoC is not a brand brainstorm. It’s evidence. You’re looking for: the words customers use to describe the problem (and the cost of it) what they tried before what “good” looks like to them what almost stopped them from buying what made them trust you If you can capture and use that language, conversion rates increase—because your marketing finally sounds like the buyer’s brain. Why Voice of Customer drives revenue (the direct line) 1) VoC increases conversion rate (same traffic, more customers) When landing pages, ads, and emails use customer language: you reduce confusion, remove friction, and increase relevance. Even small conversion gains have huge revenue impact. 2) VoC reduces CAC by improving targeting and message match Paid acquisition becomes cheaper when: your ads attract the right people, and repel the wrong ones. VoC tells you what intent looks like. 3) VoC increases close rates by improving sales enablement Sales calls improve when your team knows: top objections, proof needed, and what triggers urgency. VoC turns “handling objections” into “removing objections before they happen.” 4) VoC reduces churn by clarifying expectations and improving onboarding Many churn problems are expectation problems. VoC tells you what customers thought they were buying—and where reality didn’t match. 5) VoC improves product and offer design VoC reveals what customers value most: speed, simplicity, trust, outcomes, support, risk reduction, compliance, status, comfort. You can price and package around value instead of guessing. How to assess Voice of Customer: the 5-source method You do not need a giant research budget. You need patterns. Use at least 3 of these sources to build a credible VoC view. Source 1: Reviews (your goldmine) Where to look: Google reviews industry review platforms (G2/Capterra/etc. for B2B) Amazon / marketplaces (DTC) testimonials and emails What to extract: exact phrases for the problem and outcome “I was worried about…” “I chose you because…” “I almost didn’t because…” Tip:  The best VoC lines are the emotional “before” and the concrete “after.” Source 2: Sales calls and lead conversations Where to look: call recordings intake notes chat logs initial consult forms What to extract: the trigger event (“why now?”) objections (“I’m not sure this will…”) decision criteria (“I need it to…”) competitor comparisons (“I’m also looking at…”) If you don’t record calls, start. It’s one of the highest ROI habits you can build. Source 3: Support tickets and complaints Where to look: Zendesk / Help Scout email support inbox returns and refund reasons implementation issues (B2B) What to extract: points of confusion missing expectations product gaps friction and anxiety moments Support is often the most honest place in your business. Source 4: Surveys (post-purchase + churn) Surveys are useful if they’re short and well-aimed. Best moments: immediately after purchase after onboarding after support interaction at cancellation or non-renewal High-impact questions: “What problem were you trying to solve?” “What almost stopped you from purchasing?” “What convinced you we were the right choice?” “What would have made this an easier decision?” “What surprised you (good or bad) after purchase?” Source 5: On-site behavior (what people do  reveals what they care about) Look at: top landing pages by conversion pages visited before conversion scroll depth / drop-off points internal site searches CTA click patterns Behavior tells you where the story is missing, where trust breaks, and what questions remain unanswered. A simple VoC scoring framework (so it becomes actionable) Once you gather VoC data, organize it into a table with these columns: Trigger event  (why now) Desired outcome  (what success means) Top pain  (what’s expensive or frustrating) Objections / fears  (what blocks purchase) Proof needed  (what builds trust) Language / exact quotes  (customer words) Where it appears  (review, call, ticket, survey) Frequency  (how often it shows up) The goal is not to capture everything.The goal is to identify the top 5–10 patterns that drive 80% of buying decisions. What to do with VoC: turn it into revenue moves Here are the most direct ways to translate VoC into measurable results: 1) Rewrite your homepage and top landing pages using VoC language headline becomes the customer’s problem or desired outcome subhead becomes the “why us” proof objections get answered near the CTA proof appears earlier (not buried) 2) Build a “proof system” If customers need proof, give it to them: case studies in the format they trust reviews near the decision points certification/compliance language (if relevant) process transparency (“what happens after I sign?”) 3) Improve paid and organic content relevance VoC tells you: what topics attract buyers (not lurkers) what phrasing matches search intent what hooks convert 4) Upgrade sales scripts and objection handling Create a simple one-pager: top 7 objections best responses best proof to show for each one 5) Reduce churn with expectation alignment Use VoC to improve: onboarding emails setup guidance “what to expect” language proactive support content Common VoC mistakes (and how to avoid them) Asking leading questions  (“What did you like about us?”) Better: “What made you choose us over the alternatives?” Collecting feedback but not deploying it. VoC must become copy, offers, pages, scripts, and tests. Using internal language instead of customer language. Customers don’t buy features. They buy outcomes and risk reduction. Ignoring the “no” audience. VoC should also clarify who you’re not  for. That improves lead quality. The fastest VoC assessment you can do in one week If you want a simple plan: Day 1:  Pull 50 reviews/testimonials + tag themes Day 2:  Review 10–15 sales calls or intake notes Day 3:  Pull 50 support tickets/complaints + tag themes Day 4:  Run a short post-purchase survey (or analyze existing) Day 5:  Build a VoC message matrix and update 1 landing page + 1 ad angle Even one week of structured VoC work can unlock better conversion. If you want VoC tied to measurable growth A strong VoC assessment should end with deliverables you can use: a VoC findings report (top themes + supporting evidence) a messaging matrix (by persona/segment) landing page rewrite recommendations ad angles and email themes derived from VoC a testing roadmap tied to conversion and CAC That’s how VoC becomes revenue—not a research document. Contact Orr Consulting if you need assistance with your VOC measurement or implementation.

Most customer personas are useless. They’re often a name, a stock photo, and a list of traits that feel true but don’t change what you do on Monday. A revenue-driving persona does one thing well: It makes decisions easier —messaging, offers, channels, landing pages, sales scripts, and what not to waste money on. This guide shows you how to build customer personas that are practical, specific, and tied to growth outcomes. What is a customer persona (the version that matters)? A customer persona is a decision tool  that represents a high-value buyer segment. A useful persona answers: Who is this person (and what situation are they in)? What triggers them to look for a solution now? What are they afraid of choosing wrong? What convinces them you’re credible? How do they decide (and what slows them down)? Where do they look for information before they buy? If your persona doesn’t change your targeting, creative, landing pages, or sales process, it’s not a persona—it’s a biography. Why customer personas are so important 1) Personas improve conversion because they reduce mismatch Most “marketing problems” are mismatch problems: wrong audience wrong message wrong offer wrong proof wrong channel wrong timing Personas clarify what “right” looks like. 2) Personas save budget (especially in paid media) When you know who you’re targeting, you stop buying: low-intent traffic the wrong keywords broad audiences that don’t convert content topics that attract non-buyers 3) Personas make your messaging sharper Great messaging is not “creative.”It’s specificity : the right words for the right buyer in the right moment. 4) Personas improve product decisions Your best customers often buy for different reasons than you assume.Personas bring those reasons into the open—so product, pricing, and packaging get smarter. 5) Personas align teams (marketing + sales + leadership) Without personas, everyone has a different mental image of “the customer.”With personas, your company stops arguing about opinions and starts aligning around reality. Persona vs. ICP vs. segmentation (quick clarification) Segmentation  = how your market breaks into meaningful groups (behavior, need, context) ICP (ideal customer profile)  = the type of company/account that is most valuable (B2B) Persona  = the buyer inside that segment/account (the decision-maker, influencer, or end user) You can have one ICP and multiple personas (common in healthcare and B2B). The 7 building blocks of a revenue-driving persona For each persona, capture these: Context & role: Who they are and what they’re responsible for. Primary goal: What they’re trying to accomplish (in business terms, not feelings). Trigger event: What makes them search now? (New regulation, budget pressure, life change, pain spike, deadline.) Top 3 pains (ranked): What is most expensive, risky, or frustrating for them. Decision criteria: What they care about most when choosing (speed, trust, price, outcomes, compliance, ease, support). Objections & fears: What would make them hesitate, delay, or choose a competitor. Proof needed: What evidence convinces them: case studies reviews certifications demos peer recommendations data guarantees If you only have demographics and “likes Instagram,” you don’t have a persona. How to create personas: a step-by-step process Step 1: Pick 1–3 high-value segments (don’t boil the ocean) Start with the buyers who: generate the most profit retain longest refer others have the shortest time-to-value If you try to build 10 personas at once, none will be actionable. Step 2: Gather real data (don’t guess) Use at least two sources: Internal data CRM: lead source, close rate, deal size, cycle length Support tickets: recurring issues, confusion, questions Sales call notes: objections and “why us” Site analytics: which pages drive conversion External / voice-of-customer data 5–10 customer interviews (best option) post-purchase surveys review mining (Google, G2, Amazon, etc.) sales recordings or chat logs (if available) Step 3: Run 5–8 short interviews (the fastest high-ROI move) You don’t need 50 interviews to get signal.You need patterns . Ask questions like: “What was happening in your life/business that made you look for a solution?” “What were you considering instead?” “What almost stopped you from buying?” “What convinced you we were credible?” “What would have made this an easy yes sooner?” “How did you find us?” Record, transcribe, and tag the themes. Step 4: Identify patterns and name the segments Look for repeats in: triggers decision criteria objections proof needs time pressure budget logic Then name the persona based on behavior and context, not personality: “Time-Pressed Decision Maker” “Risk-Reducing Buyer” “Cost-Conscious Optimizer” “Outcome-Driven Specialist” Step 5: Build the one-page persona (keep it usable) Make a single page per persona: top pains (ranked) trigger events key objections + responses proof needed preferred channels (where they research) messaging angles that work offers that convert them Your goal is adoption. If it’s too long, nobody uses it. Step 6: Turn personas into actions (this is where most teams fail) For each persona, create: a landing page angle 3 ad angles 5 content topics a sales script outline (objections + proof) and 1 lead magnet or offer If you don’t translate personas into assets, the persona work dies in a folder. Step 7: Validate in-market (fast testing) You validate by testing: ad messaging (CTR + conversion rate by angle) landing page conversion by persona angle sales call outcomes by talk track email response rates by segment Personas are not “done.” They evolve as data changes. A simple persona template (copy/paste) Persona name: Who they are (role/context): Primary goal: Trigger event: Top pains (ranked): 1)2)3) Decision criteria: Top objections/fears: Proof needed: Where they research: Messaging that resonates: Offer that converts them: What to avoid saying/doing: Common persona mistakes to avoid Making too many personas  (start with 1–3) Writing demographics instead of decision drivers Skipping triggers and objections  (the true conversion levers) Creating personas without tying them to metrics Not operationalizing personas into ads, landing pages, and sales enablement If you want personas that drive growth, start with a small sprint A persona sprint doesn’t need to be a massive project. In many businesses, 2–3 weeks of focused work produces: 2–4 personas tied to real segments a messaging matrix by persona a content and offer plan and a testing roadmap If you want help building customer personas that actually change performance, Orr Consulting can lead the research, synthesize patterns, and turn them into actions that show up in conversion metrics—not just slides.

If you searched “Who’s the best marketing consultant in Ohio?” you’re probably not looking for a generic list of names. You’re looking for someone who can drive growth without wasting time or budget , and who can explain performance in plain English. Here’s the honest truth: There is no universal “best” marketing consultant.  The best consultant is the one whose approach matches your business model, growth stage, and the type of outcomes you need. So instead of publishing a random directory-style list, this guide gives you a decision checklist  you can use to choose the best marketing consultant in the Cleveland–Akron area for your  company—whether you’re in healthcare, professional services, ecommerce, or B2B. (And if you want a local option: Orr Consulting is Cleveland-based and works with growth-stage organizations that want strategy and analytics tied to measurable business results.) The Cleveland reality: what makes marketing harder here (and why that matters) Cleveland and Akron are full of companies with real traction—healthcare, services, manufacturing-adjacent B2B, regional retail, and fast-growing local brands. That also means a few consistent challenges show up: Longer sales cycles  in many B2B and service categories High trust requirements  (especially healthcare and professional services) Regional competition  that isn’t “national famous” but is very sticky locally Offline conversions  (calls, referrals, booked appointments) that don’t show up cleanly in dashboards The “best” marketing consultant is the one who can work inside these realities—not just run tactics. The “best marketing consultant” checklist (save this and use it in interviews) 1) Strategy: Can they explain how  your business wins? Ask: “What’s your working hypothesis for what drives growth in a business like mine?” A strong consultant should be able to speak to: who your best customers are (or how they’ll find out) what message will convert them which channels should be prioritized first what needs to happen in the first 30–90 days If you only hear “we’ll do SEO, social, and ads,” you’re not getting strategy—you’re getting a menu. 2) Measurement: Do they treat analytics like truth—not decoration? Ask: “How do you define success, and how do you know the data is real?” A strong consultant should talk about: tracking integrity (what counts as a conversion) funnel stages (lead → qualified lead → booked → closed) dashboards that support decisions (not vanity metrics) what’s measurable today vs what’s directional If the consultant can’t explain measurement clearly, results will always be guesswork. 3) Prioritization: Do they know what to stop doing? Ask: “In the first 30 days, what would you likely pause or cut?” The best consultants create leverage by removing waste: campaigns that don’t convert content that doesn’t match intent initiatives that look busy but don’t move pipeline tools and reports that are noise If everything is a priority, nothing is. 4) Operating cadence: Do they run a clear weekly rhythm? Ask: “What happens every week so we stay on track?” Look for a simple structure: what changed what we learned what we’re testing next what decisions leadership needs to make If the consultant can’t describe a weekly operating rhythm, you’ll drift. 5) Communication: Do they make you feel clarity—or confusion? Ask: “How do you communicate progress to a CEO or operator?” The best consultants can translate marketing into business terms: CAC / cost per qualified lead conversion rate by stage revenue influence where possible what’s working, what’s not, what happens next If you leave meetings feeling foggier than before, that’s a red flag. 6) Fit: Do they understand your industry and constraints? Ask: “What industries do you do your best work in?” A strong answer includes: the kinds of businesses they’ve seen succeed what patterns they’ve observed how they adapt to constraints (capacity, compliance, seasonality) This matters a lot for healthcare and regulated services, which are common in Cleveland. 7) Ethics and credibility: Will they tell you “no”? Ask: “What do you refuse to do?” A consultant is not a magician, and they should be honest about: what they can’t guarantee what depends on the offer/sales process what’s risky or misleading If someone promises perfect outcomes without understanding your business, don’t hire them. Red flags: you should walk away if you see these They measure success in clicks/impressions with no tie to qualified leads or revenue They won’t show you how decisions are made They rely on vague “trust the process” language They can’t explain what they changed and why They push tactics before clarifying goals, customers, and measurement What it looks like when you hire the right  consultant The best engagements tend to produce: a clear strategy and prioritized roadmap cleaner analytics and reporting you can trust smarter budget decisions and fewer random marketing projects improved lead quality (not just lead volume) a repeatable testing system (offers, messaging, conversion improvements) If you’re looking in Cleveland/Akron: what Orr Consulting does Orr Consulting is based in Northeast Ohio (Cleveland/Akron area) and provides: fractional CMO leadership marketing strategy and planning marketing analytics, dashboards, and measurement channel strategy and oversight (not “random tactics”) The focus is simple: make marketing accountable to numbers and outcomes , so you know what to do next—and why. If you’re not sure what you need, start with a short diagnostic call to determine the best first step. If you’re evaluating marketing consultants in Cleveland or Akron, use the checklist above—and if you want a second opinion, book a short diagnostic. You’ll leave with: your top 3–5 priorities what to fix first and what “success” should mean for your business

Why Social Media Business Strategies Matter You might be thinking, “I already post on social media. Isn’t that enough?” Not quite. Posting regularly is just the start. Without a strategy, your efforts can feel like shouting into the void. Social media business strategies help you focus your energy where it counts. Here’s why they matter: Targeted Reach : You want to connect with the right people, not just anyone scrolling by. Consistent Messaging : Your brand voice should be clear and recognizable across platforms. Measurable Results : Strategies let you track what’s working and what’s not. Resource Efficiency : Time and budget are precious. A plan helps you use both wisely. For example, a healthcare brand I worked with shifted from random posts to a content calendar focused on patient education and testimonials. The result? A 40% increase in engagement and a steady stream of new inquiries. Crafting Effective Social Media Business Strategies Building a strategy isn’t about guessing what might work. It’s about understanding your audience, setting clear goals, and choosing the right tactics. Here’s a step-by-step approach: Define Your Goals What do you want from social media? More leads? Brand awareness? Customer loyalty? Be specific. For instance, “Increase qualified leads by 20% in six months” beats “Get more followers.” Know Your Audience Who are they? What problems do they face? Where do they hang out online? Use data and insights to create detailed buyer personas. Choose the Right Platforms Not every platform fits every business. For growth-stage brands, focus on where your audience is most active. This is where social media platforms for business come into play. LinkedIn might be gold for B2B, while Instagram could be better for DTC. Develop Content Themes Mix educational, promotional, and engaging content. For healthcare, that might mean health tips, patient stories, and behind-the-scenes looks at your team. Create a Content Calendar Plan posts ahead to maintain consistency. Use tools like Hootsuite or Buffer to schedule and monitor. Engage and Respond Social media is a two-way street. Reply to comments, join conversations, and show your brand’s human side. Analyze and Adjust Use analytics to track performance. What posts get the most clicks? Which ads convert? Adjust your strategy based on real data. What is the 50 30 20 Rule for Social Media Marketing? If you’re wondering how to balance your content, the 50 30 20 rule is a simple, effective guideline. It breaks down your social media content into three categories: 50% Value-Driven Content : This is the meat of your strategy. Share tips, insights, how-tos, and educational posts that help your audience solve problems. For example, a B2B software company might post tutorials or industry trends. 30% Engagement Content : These posts encourage interaction. Think polls, questions, contests, or user-generated content. They build community and keep your audience involved. 20% Promotional Content : This is where you highlight your products, services, or special offers. Keep it subtle and customer-focused, not pushy. Why does this work? Because people don’t want to be sold to all the time. They want value and connection first. Following this rule helps you build trust and keep your audience coming back. Maximizing Paid Social Media Campaigns Organic reach is great, but paid campaigns can turbocharge your growth. When done right, paid social media ads deliver targeted traffic and measurable ROI. Here’s how to get the most out of your budget: Start with Clear Objectives Are you aiming for brand awareness, lead generation, or sales? Your ad creative and targeting depend on this. Use Precise Targeting Platforms like Facebook and LinkedIn offer detailed targeting options. Narrow down by demographics, interests, job titles, or behaviors. Test Multiple Creatives Don’t put all your eggs in one basket. Run A/B tests with different images, headlines, and calls to action. Optimize Landing Pages Your ad is only as good as the page it leads to. Make sure your landing page is relevant, fast, and easy to navigate. Monitor and Adjust Track key metrics like click-through rate (CTR), cost per lead (CPL), and conversion rate. Pause underperforming ads and scale winners. For example, a healthcare client used LinkedIn ads targeting hospital administrators with a whitepaper offer. After refining their audience and messaging, they cut their CPL by 35% and doubled downloads. Building Authentic Connections Through Social Media At the heart of every successful social media strategy is authenticity. People want to connect with brands that are transparent, honest, and relatable. Here’s how to build that trust: Show Your Human Side Share stories about your team, your values, and your journey. Behind-the-scenes content works wonders. Be Transparent If you make a mistake, own it. If you’re launching a new product, be clear about what it can and can’t do. Listen Actively Monitor comments and messages. Respond promptly and thoughtfully. Encourage User-Generated Content Let your customers tell your story. Share their reviews, photos, and testimonials. Stay Consistent Authenticity isn’t a one-off. It’s a continuous commitment. When you build genuine relationships, your audience becomes your biggest advocates. That’s priceless for growth-stage brands aiming for long-term success. Your Next Steps to Social Media Success You’ve got the blueprint. Now it’s time to act. Start by reviewing your current social media efforts. Are you clear on your goals? Do you have a content plan? Are you measuring results? If not, take small steps: Audit your existing profiles and content. Define or refine your target audience. Choose one or two platforms to focus on. Plan your content using the 50 30 20 rule. Experiment with a small paid campaign. Engage authentically with your followers. Remember, social media is a journey, not a sprint. With the right strategies, you’ll turn your social channels into powerful growth engines. Ready to transform your social media presence? Let’s get started today.

If I had a dollar for every bad agency I've dealt with...well I'm sure you know the end of that sentence. Firing an agency is rarely about one bad month. It’s usually about a pattern: you keep paying, they keep reporting, and your confidence in the numbers quietly drops to zero. This post is a practical framework you can use to decide whether to: keep the agency and tighten management, restructure the relationship, or replace them. No drama. No vague “they don’t get our brand.” Just clear signals. The first question: is the agency failing… or is the system or product/service failing? Before you fire anyone, separate two problems: A) Execution problem The agency is capable, but: goals were unclear, tracking is broken, offers and landing pages are weak, sales follow-up is inconsistent, the product/service has quality or customer service issues, or the budget is too low to produce signal. B) Ownership problem You don’t have senior marketing leadership. So the agency is basically making strategy decisions by default. Most “agency failures” are actually ownership failures. If nobody on your side is accountable for the strategy, the agency will fill the void—whether they should or not. Fire them immediately if any of these are true 1) You don’t own your accounts If you can’t log into Google Ads, Meta, GA4, Tag Manager, or the CRM—stop. That’s not normal. If they run any platform on their accounts - fire them immediately! 2) They can’t clearly explain what’s happening and what they’ll do next If every call feels like: a list of tasks, a few charts, and a vague “we’ll keep optimizing,” …you’re not getting leadership. You’re getting activity. 3) They use “the algorithm” as an excuse Automation is real. That’s why management matters more than ever. If they can’t explain: what signals they’re feeding the system, what they changed, what they learned, and what they’re testing next, you’re paying for someone to babysit a dashboard. 4) Reporting is built around vanity metrics If success is measured in: impressions, clicks, CTR, “engagement,” or “leads” with no definition of lead quality, you’re being managed to the wrong outcomes. 5) You discover they’re misleading you Examples: counting junk conversions as wins (button clicks, page views) hiding brand spend inside “non-brand” taking credit for organic or existing demand refusing to show search terms / placements / actual inputs Trust is the only non-negotiable. If it’s gone, end it. Strong signals you should replace them (even if they’re “nice”) 6) They can’t speak to unit economics A growth partner should know: your margin, your CAC targets, your payback window, your capacity constraints, and what “good” looks like. If they don’t ask these questions, they can’t optimize toward the business. 7) They are not proactive with creative and landing pages If the landing page is the bottleneck, an agency should say so—even if it’s “not their job.” If they never bring: new angles, new offers, new tests, CRO insights, performance will plateau. 8) You keep hearing, “We need more budget” with no plan Sometimes you do need more budget. But a credible ask looks like: “Here’s what’s working,” “Here’s what’s capped,” “Here’s the test plan,” “Here’s the expected return range.” If it’s just “spend more,” that’s not strategy. 9) They can’t show what is incremental This is huge in the AI era. If you’re running Performance Max, retargeting, or branded search, the agency must be able to explain: what is incremental vs cannibalized, where the spend is truly going, and what it’s adding beyond existing demand. If they can’t, you’re likely paying for attribution games. 10) You’re constantly educating them on your business It’s normal to onboard - and this can take up to 6 months for very complex businesses or very large organizations. This is why I turn down clients in extremely large organizations/Fortune 500's who want 6 weeks of maternity leave converge. It’s not normal to still feel like they don’t understand: your best customers, what makes someone qualified, your sales process, what you will and won’t accept as a lead, and what makes you different. If they don’t understand your business, they can’t build a performance system. A simple scorecard: keep, fix, or fire Rate each category 0–2 (0 = no, 1 = somewhat, 2 = yes) Clear goals tied to revenue/profit Accurate tracking and meaningful conversions Transparent access to accounts and data Reporting that drives decisions Strong testing roadmap (ads, offers, landing pages) Proactive communication and clear next steps Ability to explain incrementality (esp. PMax/brand/retargeting) Lead quality alignment with sales / intake Score interpretation 13–16:  Keep them. Tighten expectations and scale what works. 9–12:  Fixable. Add stronger leadership/oversight or reset the scope. 0–8:  Fire or replace. You’re paying for noise. If you’re on the fence: run a 14-day “audit sprint” before you fire them If you want to be fair (and avoid switching costs), do this: Ask for these in writing: Full admin access to all platforms Current conversion definitions and what’s counted as a “primary conversion” Last 60 days of changes made (bidding, targeting, creative, landing pages) Search terms report (Google) / placements (PMax/Display/YouTube) where applicable Budget allocation by campaign type (brand vs non-brand vs retargeting) Their next 30-day test plan and what success will look like If they refuse, delay, or can’t produce it clearly… you have your answer. What to do instead of “firing” (sometimes the smarter move) Sometimes the best fix is not replacing the agency. It’s adding senior oversight. A fractional CMO can: set the strategy, define conversions and reporting, manage the agency, and hold the system accountable. When that happens, many agencies magically “get better,” because someone is finally steering the ship. If you want help deciding, start with a short diagnostic If you send: your monthly spend range, your business type, and what “success” should mean (qualified leads, purchases, pipeline), you can get a quick, objective read on whether the issue is: agency execution, tracking, offer/landing page conversion, or overall ownership. Book a 15-minute fit call or request a Google Ads / growth audit.

Most “in-house vs fractional” articles repeat the same tired points: cost, flexibility, experience. That’s not what decides success. The real question is this: Do you need a full-time operator  inside the building—or do you need a senior growth system  installed, measured, and steered? This refreshed guide gives you a clean decision framework that’s useful even if you’re already leaning one way. Start here: What problem are you actually trying to solve? Pick the closest scenario: A) You have marketing motion, but it’s not accountable You’re spending money. The team is busy. Results feel random. You can’t explain CAC, pipeline impact, or what to stop doing. Best fit:  Fractional CMO (or fractional + analytics lead) B) You have product-market fit, but no repeatable growth system Sales are inconsistent. Your funnel leaks. Messaging is fuzzy. Channel performance varies wildly. Best fit:  Fractional CMO first (to build the system), then hire in-house into a clear role C) You have scale and complexity (and need daily leadership) Multiple product lines, multiple markets, frequent cross-functional coordination, constant decisions, internal politics. Best fit:  In-house CMO (or VP Marketing) + potentially fractional support for specialized work D) You have execution capacity problems, not leadership problems You know what to do. You can’t ship fast enough. Best fit:  Hire execution (in-house or freelancers), not a CMO The “Operating System” test (this is the difference most teams miss) I cannot count the number of times I have been approached to be a Fractional CMO to step in an "run Google Ads" or "get more leads." A CMO—fractional or in-house—is not a channel manager. They’re responsible for an operating system: Strategy : who you win with + why you’re different Budget : where to invest, where to pause, what to test Measurement : what counts, what doesn’t, and what drives profit Execution leadership : getting the right work done in the right order If you don’t have that system, your agencies and specialists end up making strategy decisions by default. A fractional CMO can build and steer this system quickly. An in-house CMO can sustain and evolve it daily. You will likely get more leads or lower CAC with a competent CMO, but that is the outcome of their work, not the primary objective. When an in-house CMO is the right move Hire in-house when you need depth + proximity + daily ownership . You’re a strong candidate for in-house if: Marketing decisions are needed every day , across departments You have multiple stakeholder groups (sales, product, ops) and alignment is a constant job You’re scaling teams (content, lifecycle, paid, partnerships) and need a leader who can recruit and manage Your biggest constraint is internal coordination and execution velocity , not strategy clarity Red flag:  If you hire in-house before the strategy and measurement are clean, you may just hire someone into confusion. When fractional CMO is the better first hire Fractional works best when you need senior clarity and leverage  without full-time overhead. You’re a strong candidate for fractional if: You don’t have a single owner of strategy + budget + measurement Your current marketing feels like “a bunch of tactics” You need a roadmap, better reporting, and tighter conversion—fast You need someone who can manage agencies and freelancers  with senior oversight You’re not ready to pay for a full-time executive, or you don’t have enough scope to keep them productive What fractional is not :  a cheaper version of an in-house CMO. Most times, Fractional CMO's cost more money in "hourly" pay (but it's a part-time and you don't pay benefits). It’s a different design: higher-leverage leadership, often paired with execution resources. Fractional CMOs by design have tremendously more experience than any in-house CMO because they have worked in a double digit number of companies. (If competent) fractional CMO's know how to come in and stabilize money bleed or fix broken paid campaigns. They come in, clean everything up, scale your business to the point where you need an inhouse CMO. The 2026 reality: “Marketing leadership” now includes data + AI systems This is where the old comparisons are outdated. Whether your growth is paid, organic, or partnerships—modern marketing performance relies on: clean conversion signals, reliable attribution (even if imperfect), consistent creative testing, and smart use of automation (e.g., Performance Max, Meta’s Advantage+, AI-assisted content systems). If your organization is weak in measurement and decision-making, hiring full-time doesn’t fix it automatically. A fractional CMO is often the fastest way to: reset tracking, stop waste, define what “good” is, and build a repeatable testing system. Cost isn’t the point, but here’s the cost model that actually matters Most people compare: Salary vs fractional retainer Better comparison: Total cost of leadership + execution + waste reduction In-house cost reality A true in-house CMO cost is not just salary. It includes: benefits, taxes, incentives onboarding ramp time team hiring needs agency oversight time opportunity cost if strategy is wrong for 2–3 quarters Fractional cost reality A fractional CMO is typically: lower fixed cost faster time-to-impact but requires execution resources (in-house team, freelancers, or agencies) The ROI often comes from: stopping the wrong spend improving conversion rate and lead quality building a plan that prevents 6 months of wandering As I have said to other clients. Pretend you pay me $100,000 over the course of the contract and I increase your digital annual paid spend from $100,000 to $300,000. Don't look at just the $400,000. Instead, look at revenue. if revenue went from $10mm to $20mm during that time was the expense worth it? Those are round numbers, but decisions must be made in terms of margin, ROI and final outcomes. And those outcomes will take time. I turn down clients EVERY time they come to me wanting quick fixes or rapid scaling. I can scale, and scale quickly, but it should be done strategically and with long term goals in mind. Decision matrix: In-house vs fractional in one minute Choose Fractional CMO  if you need: a strategy reset measurement cleanup budget allocation decisions better conversion and message-market fit senior oversight of agencies/freelancers a 90-day roadmap that’s tied to numbers Choose In-house CMO  if you need: daily leadership inside the org heavy cross-functional alignment team building and hiring (Fractional CMOs do this as well) ongoing internal execution velocity long-term brand + product + go-to-market leadership at scale (typically longer than 2 years/post scaling, post M&A, etc.) Choose a Hybrid  if you need: fractional leadership now + an internal marketing manager to execute fractional to build the system, then hire a full-time head later into a clear structure For many growth-stage companies, the best sequence is: Fractional → System → Hire in-house into clarity. How to avoid the two common failure modes Failure mode 1: Hiring in-house too early You hire a CMO into: broken tracking unclear positioning unclear priorities messy handoffs with sales Result: lots of activity, slow confidence, delayed impact. Fix:  Install strategy + measurement first (fractional is often ideal), then hire. Failure mode 2: Hiring fractional and expecting hands-on execution of everything Fractional is leadership. If execution capacity is missing, performance stalls. Fix:  Pair fractional leadership with: internal marketing manager specialist freelancers or a lean agency stack What to ask in interviews (to make the decision obvious) Ask either candidate these questions: “What are the first three things you audit in week one?” “What do you define as a primary conversion—and why?” “How do you decide what to stop doing?” “How do you know if paid results are incremental vs cannibalized?” “What does your first 30–60–90 day plan look like?” “What metrics belong on the CEO dashboard?” If they can’t answer clearly, you’re not hiring leadership—you’re hiring vibes. The bottom line If you need daily internal leadership , hire in-house. If you need clarity, accountability, and a growth operating system , fractional is often the highest-ROI move—especially before you commit to a full-time executive hire. And if you’re unsure, the hybrid approach is usually the safest: fractional leadership + internal execution , then scale into a full-time head when the system is working. Contact Orr Consulting today if you need more clarity.

Google Ads is not hard because it is “mysterious.” It is hard because it is unforgiving . A few small setup mistakes can quietly bleed budget for months. A few missing measurement pieces can make “good” results look bad (or bad results look good). And a few structural choices can lock an account into mediocrity no matter how much you spend. I have audited Google Ads accounts managed by solo freelancers, boutique agencies, and large agencies. The pattern is consistent: most underperformance is not about clever hacks. It is about fundamentals that were skipped, rushed, or never revisited. Below are the biggest reasons agencies mess this up, the most common failure points I see in audits, and what “good” actually looks like. 1) Google Ads is now an engineering system, not a “set it and forget it” channel Modern Google Ads is a mix of: machine learning (bidding and targeting automation), creative and asset performance, landing page behavior, tracking integrity, and customer economics. Many agencies still operate like it is 2016: build campaigns, pick keywords, write ads, and wait. That approach fails because Google increasingly rewards accounts that provide clear signals : clean conversion tracking, high-quality creative and assets, structured campaigns with strong intent separation, and a steady cadence of optimization. When those signals are weak, the algorithm “learns” the wrong thing fast. 2) Most agencies are built to scale labor, not outcomes This is the uncomfortable truth. A lot of agencies are optimized for: onboarding quickly, managing many accounts per person, reporting activity, and retaining clients. They are not optimized for: rigorous measurement, deep research into your customer and market, landing page collaboration, or aggressive clean-up when something is not working. Google Ads rewards depth. Agency operating models often reward speed. 3) The #1 root cause of failure: broken or misleading tracking If conversion tracking is wrong, every “optimization” is a guess. Common audit findings: primary conversions are set to low-intent events (page views, time on site, button clicks) duplicate conversions firing (inflated results, then performance collapses later) calls not tracked properly (or tracked with poor attribution) lead forms tracked, but not qualified leads offline revenue never connected back (for service businesses and high-ticket sales) GA4 and Google Ads are not aligned on what counts as success If the account is not trained on the right outcomes, Smart Bidding will chase noise. You can spend $200K and still not know what you bought. What good looks like: One clear primary conversion that represents real business value, plus secondary conversions for diagnostic visibility. Clean deduping. Call tracking. A path from lead to qualified lead to closed revenue whenever possible. 4) Campaign structure is often either too messy or too “pretty” I see two extremes: Overbuilt structure Hundreds of ad groups, dozens of match types, endless micro-segmentation. It looks organized, but it starves campaigns of data. Nothing learns fast enough. Underbuilt structure One search campaign, broad keywords, one landing page, and “let Google figure it out.” That turns into irrelevant queries, confused messaging, and inflated CPCs. What good looks like: Simple structure with strong intent separation. Usually: brand protection (low-bid exact match) non-brand high intent (tight theme, clear promise, aligned landing page) mid-intent discovery (more flexible, but still controlled) remarketing that is not cannibalizing your best traffic Performance Max used intentionally, not as a default 5) Ignoring Performance Max in the age of AI leaves a huge lever unused Some agencies either avoid Performance Max entirely because it feels like a “black box,” or they treat it as a lazy default and let it run without strategy. Both are mistakes. In the current version of Google Ads, Performance Max is one of the most direct ways to benefit from Google’s AI across inventory (Search, YouTube, Display, Discover, Gmail, Maps). If you are not testing it intentionally, you are often forcing Search campaigns to do jobs they are not designed to do, like prospecting, remarketing, or creative-led discovery at scale. The problem is not that Performance Max is “good” or “bad.” The problem is that it needs clean inputs and clear boundaries. Without that, it will happily spend your money in places that look great on paper and do not move the business. Common agency failure modes: They refuse to use Performance Max at all, so scaling stalls once Search demand is capped. They run it with weak assets and generic messaging, then blame the channel when results are soft. They let it cannibalize brand and high-intent Search traffic, so it “wins” attribution without adding incremental value. They optimize to low-quality conversions, which trains the system to find more low-quality leads. What good looks like: Performance Max has a specific job (incremental growth, remarketing, new customer acquisition, or ecommerce scale). Brand is protected and separated, so you can see what is truly incremental. Conversion tracking is clean and aligned to real value, not noisy micro-events. Assets are built like a campaign: multiple angles, strong proof, enough variety for the system to learn. Audience signals are used as starting points, not constraints—and performance is reviewed with an incrementality mindset, not just ROAS screenshots. Used well, Performance Max is one of the few tools in Google Ads that actually behaves like an AI-native growth system. Ignoring it is increasingly a competitive disadvantage. 6) Match types and search terms are mismanaged (or ignored entirely) Broad match can work. Broad match can also destroy your account. Many agencies either: avoid broad match entirely (and miss volume), or lean on broad match without guardrails (and pay for garbage). The biggest red flag: no disciplined search terms review . If nobody is reviewing search terms weekly, you are paying for queries you would never knowingly choose. What good looks like: A thoughtful approach: use exact and phrase for core intent test broad only when tracking is strong and negatives are disciplined maintain negative keyword hygiene as a living system, not a one-time task 7) Bad creative and weak assets are treated like a minor detail Agencies often treat ads as “copywriting,” then move on. But Google rewards: message match (query → ad → landing page) strong assets (sitelinks, callouts, structured snippets, images where applicable) consistent testing (not constant random changes) Weak ads are not just a brand issue. They raise CPCs and lower conversion rates. What good looks like: A few clear angles tested on purpose: problem-aware (what pain are we solving?) outcome-driven (what changes after using you?) proof-led (reviews, credentials, guarantees, outcomes) objection handling (pricing, time, eligibility, process) 8) Landing pages are treated as “not our job” Google Ads performance is often limited by: slow load times weak above-the-fold clarity generic messaging missing trust points forms that are too long or too vague no segmentation by intent or service line If your landing page is not doing its job, your ads are forced to carry the full burden. What good looks like: A conversion path that fits the buyer: one promise one audience one primary action proof near the CTA minimal friction and analytics that reveal where users drop off 9) Reporting shows activity, not truth Many clients receive reports full of: impressions, clicks, CTR, CPC and maybe “conversions” that do not map to revenue Meanwhile, the real questions go unanswered: Which campaigns drive qualified leads? What is the cost per qualified lead? What is the conversion rate by landing page? What is the lead-to-close rate by source? What is the actual return? What good looks like: A reporting system tied to business outcomes, with a short list of KPIs that drive decisions. Why this keeps happening Most Google Ads mistakes are not because the manager is unintelligent. They happen because: Incentives are misaligned.  Agencies are rewarded for retention and margin, not rigor. Tracking is hard and often political.  It touches websites, CRMs, call systems, and sales teams. Google pushes automation.  Automation works best with clean inputs. Most accounts do not have them. Clients rarely see the engine.  They see a dashboard, not the underlying structure and assumptions. A practical “Google Ads sanity check” you can run this week If you want a quick gut-check, answer these: Can you explain exactly what your primary conversion is and why it matters? Are you confident conversions are not duplicated or inflated? When was the last time someone reviewed search terms and added negatives? Is brand traffic separated from non-brand? Do your ads match your landing page promise clearly? Do you have separate landing experiences for distinct services or intents? Can you tie leads back to qualified leads and closed revenue? If Performance Max is running, can anyone tell you what it is truly driving? Are you seeing “learning limited” warnings because the structure is too fragmented? Does your reporting tell you what to do next, or just what happened? If Performance Max is not running, is that a deliberate choice backed by data—or just fear of the black box? If it is  running, can you prove it is incremental and not cannibalizing Search? If more than a few of these are “not sure,” your account likely has foundational leakage. The Orr Consulting approach (and why it usually finds money on day one) When I come in as a fractional CMO or consulting partner, I start with an audit because most accounts are carrying avoidable waste. A strong audit typically covers: measurement and conversion integrity campaign structure and intent separation SEO, AEO, and GEO audit along with search terms and negative keyword system bidding strategy alignment to the real goal audience and geo targeting logic (especially for local and regional businesses) creative and asset coverage landing page performance and message match budget allocation and marginal returns by segment The goal is not to “make it look cleaner.” The goal is to make it make money , and to make performance explainable. Ready to stop guessing? Google Ads can be a growth engine, but only when the fundamentals are right. Most uwhy-so-many-agencies-keep-screwing-up-google-ads-and-what-to-do-insteadnderperformance is fixable. You just need someone to look at the system like a business operator, not a dashboard manager. If you want Orr Consulting to audit your account, you will walk away with: a prioritized fix list (fast wins first) a clear restructuring plan (if needed) tracking recommendations you can hand to your web or analytics team and a forward plan tied to qualified leads and revenue, not vanity metrics If you want an audit , send your monthly spend range and your business type (local service, healthcare , ecommerce , or B2B). I’ll tell you what I would prioritize first.

When people search for help like that, does your brand even show up in the conversation? That is the problem I solve as a fractional CMO and data analyst for DTC and ecom brands. This article is about how search is shifting from keywords to conversations, how AI “answer engines” decide who to recommend, and how to position your brand so you are not quietly filtered out. Search is Becoming Conversation: The Need for a Clear Story AI assistants are not just search engines. They read, summarize, and judge everything they can find about you: Your website and service pages Your blog posts and case studies Your podcast interviews or webinars Your reviews and testimonials Your competitors’ positioning When a founder or CEO asks, “Who should we work with?”, the AI is not trying to be fair. It is trying to be confident. It will: Understand the job to be done. Things like “fractional CMO support,” “regulated industry,” “complex funnels,” and “data-driven.” Look for brands that clearly and consistently own that space. Recommend one or two, in plain language. If your positioning is vague, generic, and spread across old pages and random posts, you simply vanish. AI is ruthless about one thing: clarity. From SEO to AEO: Answer Engine Optimization For years, SEO revolved around keywords and rankings. “What do we want to rank for?” In the AI era, a better question is: In what types of answers do we deserve to be the example? That is the shift from SEO to AEO: Answer Engine Optimization. As a fractional CMO and data analyst, I now ask things like: What situations should trigger Orr Consulting as the default recommendation? How should an AI describe you or me in two sentences to a busy founder? What proof and patterns does it need to see so it can recommend us without guessing? Imagine AI as an overworked colleague who is trying to recommend the safest, smartest choice. Your job is to give it a story that is clear, consistent, and easy to quote. Why This Matters Even More in Healthcare and Regulated Industries If you are in healthcare, mental health, medtech, or any regulated space, the stakes are higher. AI tools are extra cautious about who they suggest. They look for: Clear proof of expertise in your domain Signals that you understand compliance, safety, privacy, and risk Evidence that you have done this before, not just “we love growth” copy That is why for my healthcare and health-adjacent clients, we do not just polish the website. We deliberately feed both AI and human buyers a consistent, evidence-based story: Who you help What problems you solve What outcomes you deliver Why you are a better and safer choice than a generic “growth marketing” agency When that story is strong, AI can confidently say something like: “You should talk to Orr Consulting. They specialize in data-heavy, often regulated businesses and offer fractional CMO support instead of a full-time hire.” That is the game now. Five Questions AI Needs to Answer About You, Without Guessing Whether you are a healthcare system, a telehealth company, a mental health group, or a B2B service provider, AI needs clean inputs. It wants to answer at least these five questions about you: 1. Who Are You For, Specifically? “Anyone who wants growth” is noise. AI responds to specifics like: Mid-sized healthcare organizations that need senior marketing leadership Mental health and telehealth providers with complex funnels Data-heavy, regulated businesses that want clarity and structure 2. What Problem Do You Solve That Others Avoid or Handle Badly? Not features. Outcomes. Things like: “Our funnel is leaky and unclear.” “We have agencies running campaigns, but no real strategy.” “Our data exists, but no one is using it for decisions.” If your content does not describe those pains in real language, AI will not connect you to them. 3. Why Should Someone Trust You With Something This Important? Healthcare and related fields are not just another vertical. AI will look for: Case studies and specific results Years of experience in similar contexts Credentials, training, and background A repeatable process instead of random wins If it cannot see these things on your site or in your content, it will keep looking. 4. What Is the Smallest Next Step to Working With You? “Contact us” is too vague. AI prefers something like: “Book a 45-minute Growth Triage call where we walk through your funnel, your data, and your current gaps and decide whether you truly need a fractional CMO or a different solution.” A clear, low-friction offer is much easier to recommend. 5. What Makes You Unique Enough to Remember? For Orr Consulting, that looks like: Fractional CMO and data analyst support for complex, regulated, and data-heavy businesses, not just quick-win DTC brands. Tie that to your real expertise. In my case: years in healthcare and health-related industries, advanced training in marketing, statistics, and psychology, plus deep hands-on work with analytics and performance. This gives AI a tight summary it can reuse. Who Is Actually Responsible for This Story in Your Company? Here is the pattern I see again and again: The CEO or founder is juggling operations, finance, hiring, and strategy. The marketing coordinator or agency is running campaigns, social, email, and ads. No one owns the AI-ready narrative that connects everything. So your marketing looks like this: Blog posts on random topics, written at different times in different voices Case studies that read like internal reports rather than external proof Website copy that shifts tone and focus from page to page Analytics that exist, but do not drive decisions In the old search world, this made you inefficient . In the AI world, this makes you invisible. This is the gap a fractional CMO is designed to fill. What a Fractional CMO Does Differently in an AI-First World A fractional CMO is not just a cheaper CMO or a consultant who drops off a slide deck. Done well, the role looks like this. 1. Turn Chaos into a Clear, AI-Ready Story Define who you serve and what they are trying to achieve Pick three to five “answer spaces” you want to own, for example: - Fractional CMO for healthcare - Growth strategy for telehealth - Data-driven funnel cleanup for mental health providers Rewrite your positioning, service pages, case studies, and key content so that humans and AI see the same message over and over 2. Architect Your Marketing System Around That Story Map out the path from first touch to first sale to retention Decide where AI tools help and where human judgment is non-negotiable Align paid ads, content, social, and email so they reinforce one another 3. Make Your Data Usable, Not Just Visible Clean up GA4 and other analytics so core questions have simple answers: - What channels bring our best-fit leads? - Where are we losing them? Build lean dashboards that people actually look at Use data to choose priorities, not just to decorate reports 4. Lead People and Vendors Toward the Same Goal Give agencies clear briefs tied to strategy Help internal teams understand what matters this quarter Say no to shiny new tools and yes to a small set of high-impact actions This is where fractional CMO work becomes very practical. It is not just ideas. It is decisions and structure. A Simple 90-Day “AI Ready Positioning” Sprint Here is how I usually structure a first engagement with a client that wants to be findable and recommendable in the AI era. Days 1–30: Diagnose and Clarify Deep dive into funnels, assets, messaging, and analytics Interview sales or clinical/business development teams to hear actual objections and questions Identify the top ten questions prospects ask that your site does not answer clearly Define two or three core positioning statements that everything else supports Days 31–60: Rebuild the Story and the Surfaces Rewrite key pages: - Home - Services / How We Work - Case Studies - Lead Magnets or Resources Create AI-friendly content patterns: - Q&A style pages - Clear “Who We Are For / Not For” sections - Short, outcome-focused case stories Align your paid search and social with the new positioning so your ads and content are not contradicting each other Days 61–90: Instrument, Test, and Hand Off Clean up tracking and reporting so you can see: - Lead quality - Channel performance - Cost per acquisition Test two or three core entry offers, such as: - A diagnostic call - A short roadmap project - A focused funnel audit Train your team and vendors on the new story so it stays consistent At that point, you do not just have “better copy.” You have a story that AI can recognize, that humans find believable, and that your team can actually execute. Who Orr Consulting Is a Fit For If any of this sounds familiar, you might be the type of organization I designed Orr Consulting for. I am a fit for you if: Your customers can't find you and/or don't convert because your funnels are not optimized. You have marketing activity, but not a clear owner of strategy and performance. You care about data and want marketing to be measurable, not just creative. You have enough complexity that a junior marketer or a one-channel agency is not enough. I am not a fit if: You want a low-cost social media poster without strategy. You want a one-time “SEO fix” and are done. You are looking for the cheapest option. How I Typically Work with Clients I am Linda Orr, PhD, a fractional CMO and data analyst. I work with clients across the United States and Canada. Typical ways we work together: 90-Day AI Ready Positioning Sprint: A focused project to clarify your story, rebuild key assets, and clean up your data. Ongoing Fractional CMO Engagement: A set number of hours per month to lead strategy, manage agencies, shape messaging, and keep your marketing accountable to results. Targeted Projects: Funnel and analytics audits, campaign strategy, or help diagnosing why your current marketing is not working. Your Next Step: A 45-Minute Growth Triage Call If you are reading this and thinking, “This is exactly the gap we have,” then here is a simple, low-pressure next step. Book a 45-minute Growth Triage call with Orr Consulting. On that call we will: Walk through your current funnel and positioning Look at where AI and humans are likely dropping you from consideration Identify the highest impact changes you can make in the next 90 days If we both agree it is a good fit, we can map out an AI Ready Positioning sprint or a fractional CMO engagement. If not, you still walk away with a clearer view of what is going wrong and what to tackle first. Quick FAQ for AI and Humans Alike What does a fractional CMO do? A fractional CMO gives you senior-level marketing leadership without the full-time executive salary. In my work, this includes strategy, funnel design, analytics, positioning, and leading internal and external marketing resources. How is Orr Consulting different from a typical agency? Agencies are built to execute. Orr Consulting is built to own strategy, data, and decision-making, then guide agencies and internal teams to execute the right work. I focus on complex and often regulated environments, not just quick-win campaigns. Where are you based? I am based in Cleveland, Ohio, and work remotely with clients across the U.S. and Canada. What is the best way to start? The best first step is the 45-minute Growth Triage call. It is structured, practical, and focused on your situation, whether or not we end up working together longer term. In an AI-driven world, it is not enough for your brand to exist online . You need to be the brand that both people and machines feel confident recommending. That is the work I do at Orr Consulting .

A practical summary of what each report says, plus the gaps, pros, and cons — and the SEO/AEO/GEO playbook we use to turn strategy into demand. Most “AI strategy” content falls into one of two buckets: (1) hype with no operating model, or (2) deep technical guidance with no business translation. The list below is popular because it spans both. But if you’re reading these reports, you’re likely asking a more practical question: How do we translate AI strategy into real growth — especially search visibility and lead flow? At Orr Consulting , we treat modern discovery as its own operating model: SEO + AEO + GEO . SEO  gets you found for high-intent searches (the classic “rank and earn traffic” problem). AEO (AI Engine Optimization)  helps your content show up in AI answers because it’s structured to be clear, citable, and trusted. GEO (Generative Engine Optimization)  strengthens the footprint that helps your brand appear in generative summaries and recommendations across platforms. The Orr Consulting SEO/AEO/GEO Playbook (high level) If you’re comparing SEO services or trying to build this internally, here’s the playbook we use: Audit the foundations  (technical SEO + analytics + indexing + site speed + structure) Map buyer intent  (what your customers actually search and ask AI tools) Build page architecture  (service pages + comparison pages + decision pages + FAQs) Create “answer-ready” content  (structured for both rankings and AI summaries) Add trust signals  (proof, authority, credibility, and conversion elements) Measure outcomes  (qualified leads, conversion rates, pipeline contribution) Refresh and compound  (content updates, internal linking, pruning, and iteration) If your real goal is growth , the missing playbook is discovery: SEO + AEO + GEO . If you’re comparing SEO services  or looking for an SEO consultant , start here: SEO + AEO + GEO Services → And if you like executive frameworks, this is a good companion read:  McKinsey 7S Strategic Planning Framework → Now, here are the 12 AI strategy playbooks everyone’s citing for 2026 — and what they miss. 1) McKinsey: The State of AI in 2025 What it’s about:  A global survey of organizations on how AI is actually being used, how far “scaling” has progressed, and what’s changing with agentic AI. Key takeaways (in practice): AI adoption is widespread, but enterprise-wide value capture is still uneven. “Agentic AI” is emerging, with a meaningful chunk of companies reporting they’re scaling agents somewhere (not just piloting). Pros Strong reality check: you can benchmark where you are versus peers. Useful framing on “scaling” vs “experimenting,” which is where most companies get stuck. Cons / what’s missing Survey insight ≠ implementation blueprint. It tells you what companies do, not how to build it step-by-step. Light on tech architecture decisions (data pipelines, evaluation systems, model governance) that determine whether scaling works. SEO translation (why this matters for buyers): McKinsey’s message is “pilots aren’t value.” In SEO terms: publishing content isn’t a strategy.  You need a system that scales into measurable outcomes. 2) BCG: The Widening AI Value Gap: Build for the Future 2025 What it’s about:  Research arguing the gap is widening between “AI leaders” and everyone else, plus a maturity model of capabilities. Key takeaways (in practice): A small group of companies are “AI future-built,” and they outperform on value outcomes (revenue and cost). BCG breaks maturity into a set of foundational capabilities across strategy, tech, people, and operating model. Pros Clear diagnostic: “Are we actually built to capture value, or just running experiments?” Good exec-facing language for prioritization and board-level framing. Cons / what’s missing Maturity models can become “checkbox theater” without a concrete delivery system (use-case pipeline, evaluation gates, change management). Less detail on unit economics (cost per task, inference budgets, adoption thresholds) that decide whether AI value is real. SEO translation: SEO also creates a “value gap.” Leaders build topical authority and convert demand; everyone else produces content and hopes. 3) Accenture: The Art of AI Maturity What it’s about:  A maturity view of what separates “AI achievers” from others and which capability combinations matter. Key takeaways (in practice): High performance comes from bundles of capabilities (data, talent, responsible AI, operating model), not one-off tooling. Pros Useful for leadership alignment: “AI is not a tool rollout, it’s an operating capability.” Practical maturity questions that help teams self-assess. Cons / what’s missing It predates the current agentic and foundation-model era, so it is lighter on modern realities like model eval, retrieval, hallucination controls, and agent safety loops. Still tends to read like “transformation guidance” more than a build-and-ship playbook. SEO translation: Modern SEO is a bundled capability too: technical + content + authority + conversion + measurement. 4) Microsoft: The Strategic CIO’s Generative AI Playbook What it’s about:  A CIO roadmap built around leadership, human change, and technical readiness for becoming “AI-powered.” Key takeaways (in practice): Microsoft centers adoption on change management and IT readiness, not just model access. Pros Strong on the hardest part: workforce adoption, governance, and how IT should lead. Concrete language CIOs can use internally. Cons / what’s missing Naturally Microsoft-stack oriented (helpful if you are in M365/Copilot, limiting if you are multi-vendor). Less depth on measurement design (what to track beyond usage) and on model risk testing outside the Microsoft ecosystem. SEO translation: SEO only compounds when there’s an operating rhythm: publish, refresh, link, measure, improve. 5) Bain: Transforming Your Business With AI  (and related 2025 tech research) What it’s about:  CEO-level framing for moving beyond experimentation into business transformation, often via a small set of “hard questions.” Key takeaways (in practice): The core message is speed and focus: stop scattering pilots, start building repeatable value delivery. Pros Excellent “executive forcing function” to cut through AI sprawl. Bain’s broader tech research adds helpful macro context for leadership decisions. Cons / what’s missing Typically less concrete on operating mechanics (intake, prioritization, eval gates, rollback criteria, ongoing monitoring). You still need a delivery framework to convert “CEO clarity” into shipped outcomes. SEO translation: Focus wins. The fastest SEO gains come from building a small set of high-intent pages that rank and convert. 6) Deloitte: Tech Trends 2026 What it’s about:  A broad view of how orgs are scaling AI “for outcomes and impact,” including infrastructure and operating model implications. Key takeaways (in practice): Many organizations are discovering their infrastructure and operating models were not designed for production-scale AI. Emphasis on moving from pilots to measurable results, with AI reshaping how IT functions are structured. Pros Strong breadth: it connects AI to architecture, costs, org design, and tech debt. Useful for planning 12 to 24 months ahead, not just “next quarter’s pilot.” Cons / what’s missing Trend reports can be too wide to operationalize without an internal execution playbook. Less guidance on “how to prove ROI case-by-case,” especially in non-tech orgs. SEO translation: Your “infrastructure” is your site. Speed, structure, templates, and measurement are SEO multipliers. 7) Stanford HAI: AI Index Report 2025 What it’s about:  A data-driven state-of-the-field report: research trends, investment, performance, hardware, costs, policy, and responsible AI indicators. Key takeaways (in practice): It’s the best “ground truth” dataset for the macro AI landscape, including costs and capabilities over time. Pros Credible, quantitative, and useful for board decks and strategic context. Helps leaders avoid vendor narratives by anchoring on observable trends. Cons / what’s missing Not a corporate implementation guide. It won’t tell you how to redesign workflows, govern agents, or build an evaluation stack. Teams often struggle to translate macro data into next steps. SEO translation: AI-mediated discovery is growing — so AEO/GEO matters — but it still requires SEO fundamentals. 8) Amazon (AWS): CDO Agenda 2025 / Closing the AI Value Gap What it’s about:  A data-leader-focused report on scaling generative AI into business value, heavily emphasizing data readiness and governance. Key takeaways (in practice): Data issues show up as the most common barrier to scaling gen AI in surveyed organizations. Pros Practical for CDOs: concrete on data foundations, governance, and operating principles. Good bridge between “AI excitement” and “data reality.” Cons / what’s missing Data readiness is necessary, not sufficient: it doesn’t fully solve adoption, workflow redesign, or accountability for outcomes. Leans toward AWS framing, so you still need a vendor-neutral architecture view. SEO translation: In SEO, “data readiness” = clean tracking + clear intent mapping + outcomes reporting. 9) IBM: 2025 CDO Study: The AI Multiplier Effect What it’s about:  CDO survey research on how data strategy drives AI ROI, with a push toward “bringing AI to the data.” Key takeaways (in practice): Many CDOs report a shift toward applying AI across distributed data rather than relocating data into one place. Pros Strong on modern enterprise reality: fragmented data, multiple systems, and the need to move faster. ROI orientation is clear and useful. Cons / what’s missing Still requires governance, data product ownership, and quality measurement to avoid chaos. Less coverage on customer-facing risks unless paired with governance frameworks. SEO translation: SEO works when scattered pages are unified: consistent positioning, strong internal linking, and a clear structure. 10) Google: State of AI Infrastructure 2025 What it’s about:  Research on infrastructure readiness for gen AI at scale (cloud, security, cost, hybrid), based on surveys of tech leaders. Key takeaways (in practice): AI infrastructure is a core barrier and differentiator for production gen AI. Pros Useful for platform teams planning capacity, security posture, and architectural shifts. Helps leaders understand why old infrastructure plans don’t fit AI workloads. Cons / what’s missing Infrastructure alone doesn’t replace workflow redesign, adoption, or business-case discipline. Can over-index on platform choices vs operating choices. SEO translation: Slow sites and messy structure kill performance. Fixing fundamentals often beats “more content.” 11) NIST: AI Risk Management Framework (AI RMF) + GenAI Profile What it’s about:  A voluntary framework for AI risk management across Govern, Map, Measure, Manage, plus a GenAI companion profile. Key takeaways (in practice): A structured way to operationalize trustworthy AI. The GenAI Profile addresses genAI-specific risks and actions. Pros Best-in-class for governance, risk, and compliance alignment. Helpful for regulated industries and procurement guardrails. Cons / what’s missing It’s a framework, not a turnkey plan; still needs tooling and resourcing. Prevents failure, but doesn’t automatically create ROI. SEO translation: High-trust industries need “trustworthy content,” not fluff. That includes claims discipline, credibility signals, and clear sourcing. 12) World Economic Forum: Advancing Responsible AI Innovation: A Playbook (2025) What it’s about:  Nine “plays” to operationalize responsible AI, often emphasizing ecosystem collaboration. Key takeaways (in practice): Focus is operationalization: moving from principles to repeatable governance actions. Pros Helpful for leaders trying to make responsible AI real. Unifies stakeholders (legal, policy, product, security). Cons / what’s missing Less depth on implementing controls (eval methods, red teaming, monitoring). Can feel abstract without owners, workflows, and KPIs. SEO translation: Principles don’t rank. Execution ranks. The best SEO programs have a publishing + refresh + linking system. What’s missing across almost all of them Even the “best” reports tend to under-serve the messy middle: turning intention into a repeatable system. Here are the gaps that show up repeatedly: A true AI delivery operating model  (intake → build → evaluate → rollout → monitor → iterate) Measurement that proves value  (not activity) Evaluation and safety for agentic workflows Unit economics and cost controls Vendor-neutral architecture guidance How I’d use these (a practical stack) If you want a pragmatic “do this next” synthesis: Start with value + maturity reality checks: McKinsey + BCG Ground your assumptions with objective data: Stanford AI Index Build the data and platform foundation: AWS + IBM + Google infrastructure Lock in trust and risk governance: NIST AI RMF + WEF playbook Translate into IT leadership and adoption: Microsoft CIO playbook Keep planning honest: Deloitte Tech Trends The missing “playbook” for growth teams: AI discovery (SEO + AEO + GEO) Most reports above focus on internal AI capability. But for revenue growth, there’s also an external strategy: How do we show up when buyers search, compare, and ask AI tools who to trust? That’s what modern SEO has become. If you’re actively searching: “SEO services” “SEO consulting” “AEO agency” “GEO optimization” “where do I go for SEO” …you’re not looking for more theory. You want a system that produces qualified leads. And if you want the executive framework version of “why programs fail,” this is a strong companion. Want the faster path? Start with an SEO/AEO audit + 90-day roadmap If you want to stop guessing, the fastest path is an SEO / AEO audit + 90-day roadmap  that tells you: what’s broken (and what’s not) what to fix first (highest ROI) what pages to build (based on buyer intent) how to structure content so it ranks and converts how to measure it cleanly in GA4  Get started here → https://www.orr-consulting.com/seo-aeo-geo-services

If you want to grow your brand, you need more than just gut feelings and guesswork. You need data-driven marketing strategies that turn raw numbers into clear, actionable insights. I’ve seen firsthand how brands that embrace data don’t just survive—they thrive. They make smarter decisions, optimize campaigns, and scale faster. Let’s dive into how you can harness the power of data to drive growth in your marketing efforts. Why Data-Driven Marketing Strategies Matter Marketing used to be about intuition and creativity alone. Today, it’s about combining those with hard data. Why? Because data gives you a reality check. It tells you what’s working, what’s not, and where to focus your energy and budget. Imagine spending thousands on ads that don’t convert. Painful, right? Data-driven marketing strategies help you avoid that by: Identifying your best customers and targeting them precisely. Optimizing your ad spend to get the highest return. Personalizing your messaging to resonate with different segments. Predicting trends before they become obvious. Measuring success with clear metrics, not vague feelings. This approach is especially crucial for growth-stage brands in DTC, B2B, and healthcare sectors. You’re juggling limited resources and high expectations. Data helps you prioritize and execute with confidence. Marketing analytics dashboard on laptop screen Key Data-Driven Marketing Strategies to Implement Now Let’s get practical. What are some proven strategies you can start using today? 1. Customer Segmentation Not all customers are created equal. Segment your audience based on behavior, demographics, purchase history, or engagement level. This allows you to tailor your campaigns and offers to each group. For example, a healthcare brand might segment patients by condition severity or treatment stage. A B2B company could segment leads by company size or industry. 2. Predictive Analytics Use historical data to forecast future outcomes. This can help you anticipate customer churn, identify upsell opportunities, or optimize inventory. 3. Multi-Channel Attribution Don’t just look at last-click conversions. Understand how different channels contribute to the customer journey. This insight helps you allocate budget more effectively. 4. A/B Testing Test different versions of your ads, emails, or landing pages. Data from these tests shows you what resonates best with your audience. 5. Real-Time Data Monitoring Set up dashboards to track campaign performance in real time. This way, you can pivot quickly if something isn’t working. These strategies aren’t just buzzwords. They’re actionable steps that can transform your marketing from guesswork to precision. What is data-driven marketing? At its core, data-driven marketing means making decisions based on data analysis rather than assumptions. It’s about collecting, analyzing, and applying data to every stage of your marketing funnel. Think of it as having a GPS for your marketing journey. Instead of wandering blindly, you have clear directions based on real-time traffic and road conditions. Data-driven marketing involves: Collecting data from multiple sources like website analytics, CRM systems, social media, and paid ads. Analyzing data to uncover patterns and insights. Applying insights to optimize campaigns, messaging, and targeting. Measuring results to continuously improve. For example, a DTC brand might use purchase data to recommend products customers are likely to buy next. A B2B company could analyze lead behavior to prioritize sales outreach. The beauty of data-driven marketing is that it’s a cycle. You collect data, learn from it, act on it, and then collect more data to refine your approach. Digital marketing dashboard with performance charts How to Turn Messy Data into Clear Growth Opportunities Here’s the truth: data is messy. It’s scattered across platforms, inconsistent, and sometimes incomplete. But that’s where the magic happens—when you clean and organize your data, you unlock powerful insights. Step 1: Centralize Your Data Bring all your data into one place. Use tools like data warehouses or marketing platforms that integrate multiple sources. This gives you a single source of truth. Step 2: Clean Your Data Remove duplicates, fix errors, and fill in missing information. Clean data means reliable insights. Step 3: Analyze with Purpose Don’t just look at vanity metrics like clicks or impressions. Focus on metrics tied to your business goals—revenue, customer lifetime value, acquisition cost. Step 4: Visualize Your Data Use dashboards and reports to make data easy to understand. Visuals help you spot trends and anomalies quickly. Step 5: Act and Iterate Use insights to tweak campaigns, test new ideas, and improve targeting. Then measure again. This continuous loop drives growth. If you’re feeling overwhelmed, you’re not alone. That’s why partnering with experts who specialize in transforming messy data into clear, evidence-based strategies is a game-changer. Practical Tips for Scaling with Data-Driven Marketing Scaling your marketing efforts with data requires discipline and the right mindset. Here are some tips to keep you on track: Start small but think big. Begin with one campaign or channel and expand as you learn. Invest in the right tools. Analytics platforms, CRM systems, and automation tools are essential. Train your team. Make sure everyone understands the importance of data and how to use it. Set clear KPIs. Know what success looks like before you start. Be transparent. Share data insights openly with your team to foster collaboration. Don’t fear failure. Use data to learn from mistakes and improve. Remember, growth is a marathon, not a sprint. Data-driven marketing strategies help you pace yourself and make every step count. If you want to dive deeper into how to leverage data for growth, check out this resource on data driven growth marketing . Embracing Data-Driven Marketing for Long-Term Success Data-driven marketing isn’t a fad. It’s the future. Brands that master it will outpace competitors, build stronger customer relationships, and achieve scalable, profitable growth. By transforming your messy data into clear, actionable strategies, you’re not just improving marketing—you’re building a foundation for sustainable success. So, are you ready to take control of your marketing with data? Start today, stay curious, and watch your growth accelerate. Driving growth with data is within your reach. The key is to start small, stay consistent, and never stop learning.

A 30-60-90 day sales plan is a simple idea with a big impact: it’s a three-month roadmap  that spells out what a salesperson (or sales leader) should learn, do, and deliver in their first 30, 60, and 90 days. Instead of “go shadow someone and figure it out,” a good 30-60-90 day plan gives: Clear direction Concrete expectations Measurable progress markers A shared language for “how it’s going” Whether you’re bringing on a new rep, promoting someone into a strategic role, entering a new market, or layering in a new product line, a 30-60-90 plan is one of the fastest ways to shorten the time from “new” to “effective.” Why a 30-60-90 Day Sales Plan Matters A strong 30-60-90 day sales plan helps you: Onboard faster and smarter: New hires know exactly what “good” looks like in week 2, week 5, and week 10—without you reinventing the wheel every time. Align expectations: Sales leaders, RevOps, and marketing have a shared view of what should be happening at each stage. Spot issues early: If someone is off-track, you’ll see it by day 30 or 45—not month 6. Anchor strategy changes: When you launch a new motion (new ICP, new service, new geography), a 30-60-90 plan clarifies how reps should shift their time and behavior. Most impact scenarios: New AE / SDR / sales leader onboarding Expansion into a new segment or region Layering in a new product or service line Turning around underperforming teams or territories What a 30-60-90 Day Sales Plan Should Include The best 30-60-90 day sales plans are simple, specific, and measurable . At minimum, every plan should cover: 1. Clear goals for each phase Think in terms of SMART  goals: 30 days: Activity and learning goals 60 days: Pipeline and engagement goals 90 days: Revenue / closed-won and conversion goals 2. Actionable tasks Not just “learn the product,” but: Complete specific training modules Shadow X calls and demos Make Y calls / send Z outreach per day Run a certain number of discovery calls or demos 3. KPIs and benchmarks Examples: Number of qualified opportunities created Meetings booked and held Conversion from meeting → opportunity Early revenue targets (scaled to ramp expectations) 4. Regular check-ins and feedback loops Weekly 1:1s 30-, 60-, and 90-day review meetings Simple scorecards that track progress against the plan If it doesn’t fit on one page per phase  and into a single dashboard view , it’s probably too complicated. 30-Day Example: Learn, Observe, and Build Foundations In the first 30 days, the priority is not “crush your quota.” It’s learn fast, plug into the system, and start building early momentum. Objectives (First 30 Days) Understand the product, ICP, and sales process Build relationships internally (sales, marketing, CS, ops) Start light prospecting and early conversations Sample 30-Day Plan Learning & Orientation Complete onboarding on products/services and pricing Finish key training modules (industry, competitors, tools) Review top 10–20 existing deals (won and lost) to understand patterns Shadowing & Internal Alignment Shadow X discovery calls and Y demos with top performers Join cross-functional meetings (marketing/sales, RevOps) to understand how leads are generated and handed off Early Activity Begin light prospecting: e.g., 20–30 targeted outbound touches per day Send introduction messages to key accounts in your territory Build a starter list of target accounts or segments Suggested KPIs (30 days) Training completion % Number of calls shadowed Number of outbound touches Number of initial meetings booked (even if supervised) 60-Day Example: Build Pipeline and Own Conversations By days 31–60, the rep should be moving from “observing” to owning  more of the sales process. Objectives (Days 31–60) Take full ownership of prospecting and early-funnel conversations Build a healthy, realistic pipeline Begin running discovery calls and demos independently Sample 31–60 Day Plan Prospecting & Pipeline Hit daily/weekly outreach targets (calls, emails, social touches) Own a defined territory, segment, or list of accounts Add a specific number of qualified  opportunities to the pipeline Sales Process Ownership Start running full discovery calls solo Run some demos with a senior rep on standby for complex questions Begin to negotiate early-stage deals under guidance Refinement & Feedback Review 2–3 recorded calls per week with manager/coach Identify patterns in wins and losses in the growing pipeline Suggested KPIs (31–60 days) Qualified opportunities created Meetings booked and held Conversion rate from meeting → opportunity Pipeline value vs. 90-day ramp target 90-Day Example: Close Deals and Optimize By days 61–90, a rep should be closing their first deals  and starting to look like a fully ramping contributor. Objectives (Days 61–90) Close initial deals Hit agreed-upon ramp targets (scaled quota) Refine their own style, sequences, and territory plan Sample 61–90 Day Plan Closing & Negotiation Own deals from discovery through close (with support as needed) Run proposals and pricing conversations Learn and apply standard negotiation frameworks Optimization Refine personal outreach sequences and cadences Improve call talk tracks and demo structure based on early results Work with marketing/RevOps to improve lead quality or handoff, if needed Performance Review & Next-Phase Plan Formal 90-day review against plan Identify strengths, gaps, and next-quarter goals Adjust targets and territory plan based on performance and pipeline Suggested KPIs (61–90 days) Closed-won revenue vs. ramp target Win rate on qualified opportunities Average deal size and sales cycle length (for early deals) Common 30-60-90 Day Mistakes to Avoid Even strong teams trip over the same few issues: 1. Vague or unrealistic goals “Crush it” and “learn everything” are not goals. “Close $500K in the first 30 days” probably isn’t realistic. Fix it with: Ramp-aware targets Concrete activity and learning goals A clear definition of “on track” vs “off track” 2. Overstuffed plans A 17-tab spreadsheet with 180 tasks is not a 30-60-90 day plan; it’s a to-do list graveyard. Keep it focused: 3–5 core objectives per phase A small set of high-leverage activities The few KPIs that matter most 3. Set-and-forget The plan only works if you: Review it weekly in 1:1s Adjust it when reality doesn’t match assumptions Use it as a conversation tool , not just a document HR files away Pro Tips from Orr Consulting These are patterns we see across premium DTC, healthcare, and complex B2B sales environments. 1. Customize by role, segment, and deal size An outbound SDR, an AE closing mid-market SaaS, and a clinician-facing healthcare rep can’t use a cookie-cutter plan. Adjust: Activity expectations (volume vs depth) Learning requirements (product, regulatory, clinical, etc.) Ramp timelines based on sales cycle length 2. Tie the plan to real data, not guesses If you have historical data: Use average sales cycle , average deal size , and realistic conversion rates  to set ramp targets Integrate simple dashboards so reps can see if their activities → pipeline → revenue  are on track 3. Align marketing, sales, and operations Your 30-60-90 sales plan will break if: Marketing’s lead generation doesn’t match who sales is trained to sell to Ops or clinical capacity can’t handle the volume in certain segments Leadership keeps changing strategy mid-ramp without updating the plan Get everyone aligned on who you’re targeting, why, and how —and let that drive the plan. How Orr Consulting Can Help If your sales plans currently live in someone’s head—or a dusty slide deck—you’re leaving performance on the table. Orr Consulting can help you: Build role-specific 30-60-90 day plans  for your key sales positions Align sales, marketing, and operations around the same ramp expectations Integrate analytics and dashboards  so you can see ramp health in real time Design compensation and KPI structures  that support the plan (not fight it) If you’d like a second set of eyes on your existing sales onboarding or growth strategy: Book a 30-minute consult , and we’ll walk through your current ramp process and identify 2–3 changes that would make the biggest impact in the next quarter. Final Thoughts A 30-60-90 day sales plan isn’t about more paperwork. It’s about giving new (and newly promoted) reps a clear runway , and giving leadership a clear view  of whether the plane is getting off the ground. When you: Set realistic, stage-specific goals Focus on the right activities Build in feedback and data And align sales with marketing and operations ...your 30-60-90 day plan becomes more than an HR checklist—it becomes a reliable engine for growth.