Growth Strategy Formulation

"You need a data strategy" is sound advice. Yet it tends to land in the boardroom with the elegance of a lead balloon. The problem? It’s often confused with an operational IT plan. Say "data strategy" in a meeting and watch executives squirm. While everyone will acknowledge that it's an important topic, the term conjures up images of confusing technical diagrams, visions of tedious roles and responsibility alignments, and a deep fear of creating the next armada of soul-crushing governance committees. The core problem? Treating data strategy as an operational deep-dive exercise, and not as devising the engine that powers every business decision that matters. The good news? Effective data strategy is simple. All it takes are three questions that cut through the noise and drive action: First: Where does data actually matter to your business? If the answer is "everywhere", that's probably correct, but it’s not a strategy. Stop trying to boil the ocean and focus. The strongest data initiatives start with precise pressure points – specific problems where better information drives immediate value. Treat data like a scalpel, not a sledgehammer. Don't analyze everything. Analyze what matters most. Second: What's really blocking progress? New flash: It's rarely a lack of data, technology or data governance frameworks. The real culprits are usually organizational silos, hastily grown tech stacks, and–most tellingly–leaders who treat analytics as validation for decisions they've already made. Valuable data, however, creates change. If your data isn't making anyone uncomfortable, you're doing it wrong. Third: How do we turn insight into action? Too many dashboards and fancy reports are where insights go to die. Give your teams clear guidelines and air cover to act on data – and expect them to wield this power. When teams and managers can act on real-time signals – and aren't punished for data-driven failures – you'll see undeniable results. Remember: Most (data) strategies fail because they avoid organizational conflict. Like any good strategy, success lives in clearly making the hard decisions of what not to do. The most effective data strategies aren't the most complex. They target critical business needs, are clear on how to knock down barriers, and enable quick action. This requires understanding how data powers the business to win. Start small, test fast, iterate at lightspeed and scale what works. In a market where everyone claims to be "data-driven," the winners aren't the ones with the thickest strategy documents – they're the ones making better decisions, faster, every single day. They're not writing their data strategy. They're executing it.

In 66 months, I helped grow Gong from $200k ARR to $7.2B in valuation and worked alongside some of the planet's best sales leaders. Here's the 6 biggest lessons I learned: 1. Overinvest in great marketing early on. I’m still shocked at how few startups do this. Sales with no (effective) marketing early on to pave demand and provide air-cover is a brute-force way to build. 2. Measure twice, cut once when hiring leaders. Your first leadership hires will have cascading effects on your company that ripple through many years. Their fingerprints will weigh heavy on everything from your sales motion, to company culture, to the people they hire, whether you want it to or not. Even after they’re gone. Recruit and hire accordingly. 3. Beat the hell out of what’s working. Finding what works in growing a startup is like drilling for oil. You’re going to drill a number of "wells" and come up dry. But soon, you’ll find one to go DEEP with. Drill it for all it’s worth. Don’t screw around trying to find too many other oil wells when you haven’t even maxed out your best one. 4. Hire salespeople who thrive on ambiguity. Not just those who CAN do that, but those who LOVE to do it (because they'll be doing this for a while as your market evolves). Do this, and you’ll accelerate your learning curve to a repeatable sales motion. Hire entrepreneurial reps. 5. Inject risk into the business as you scale. As you scale, your “portfolio” of growth initiatives should contain more and more risk. It's as if you're a fund manager. Early on, find what works and cling to it. But as you grow and you’re able to rely on several well-established growth vectors, start to introduce risk into your portfolio. Examples: Experimenting with channel partnerships, international, new segments of the market or use cases. 6. Realize the "growth at scale" playbook is different than the "scale up" and "startup" playbooks. What got you to $50M or $100M will not get you to the next level by itself. The path to $100M, and going beyond that (“growth-at-scale”) are two very different situations demanding different means of growing. Early on, nothing matters but (the right) customer acquisition, controlling churn, and making your product absolutely amazing. But if you’re going to continue growing at a fast rate, several other methods have to start firing: high net dollar retention (NDR), multi-product and multiple streams of ARR, going hard and fast on international expansion, and crossing the chasm into “low tech” industries. This list is non-exhaustive. For those of you who have ridden that tornado, what would you add? P.S. Turn "open opps" into paying customers at any phase of growth with these 10 closing motion scripts: https://lnkd.in/gtxYd9Vs

Your marketing results aren't consistent. Because you're not building systems. [Watch this ping pong ball contraption] Look at that kid. Failed dozens of times. Adjusted. Tested. Improved. Until the system worked perfectly. Every. Single. Time. Your growth strategy? Probably the opposite. 𝗧𝗵𝗲 𝗵𝗮𝗿𝗱 𝘁𝗿𝘂𝘁𝗵: Most B2B companies build growth on quicksand, not foundations. 𝗪𝗵𝗮𝘁 𝗜'𝗺 𝘀𝗲𝗲𝗶𝗻𝗴 𝗲𝘃𝗲𝗿𝘆 𝘄𝗲𝗲𝗸: → CEOs demanding results in 30 days → Marketing leaders jumping from tactic to tactic → Teams chasing vanity metrics → Agencies promising quick fixes → Everyone wondering why growth never lasts Last month, I sat across from a founder who'd been through four agencies in 18 months. Each one promised quick results. Each delivered a spike. Each spike faded. He looked exhausted when he asked, "Why can't we just make something that works consistently?" The answer was simple: They were building sprints when you needed marathons. 𝗧𝗵𝗲 𝐁2𝐁 𝗚𝗿𝗼𝘄𝘁𝗵 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: 1️⃣ 𝗕𝘂𝗶𝗹𝗱 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 - Clear ICP definition - Documented buyer journey - Proper tracking infrastructure - Consistent messaging foundation - Baseline metrics established 2️⃣ 𝗧𝗲𝘀𝘁 𝗠𝗲𝘁𝗵𝗼𝗱𝗶𝗰𝗮𝗹𝗹𝘆 - One variable at a time - Document everything - Minimum 30-day tests - Success/failure criteria defined - Learning prioritized over results 3️⃣ 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗮𝗻𝗱 𝗦𝗰𝗮𝗹𝗲 - Improve what works (don't replace it) - Fix conversion bottlenecks - Eliminate what doesn't work - Document the playbook - Add fuel only to proven engines I'll never forget working with a B2B SaaS company that was furious their growth was "stuck" after 60 days. We dug into their history: They'd never run any marketing program longer than 90 days before declaring it "didn't work" and trying something new. No wonder nothing stuck! We committed to building one channel properly. Six months later, their LinkedIn content machine was generating 42 qualified leads monthly. Not sexy, but sustainable. Two years later? Still working, still predictable, still growing. Your growth machine takes patience to build. Each component matters. Each adjustment improves results. But once it works, it works consistently. ---- ❤️ 𝐈𝐟 𝐲𝐨𝐮 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐭𝐡𝐢𝐬. ♻️ 𝐭𝐨 𝐲𝐨𝐮𝐫 𝐧𝐞𝐭𝐰𝐨𝐫𝐤. 🔔 Follow me for more helpful and entertaining videos to improve your go-to-market approach. 🤟

More leads don't always mean more growth. Sometimes, they just mean more wasted budget. I recently worked with a fast-growing gifting and floral commerce brand that had a common scaling challenge: High traffic. More leads. But declining conversions and rising CAC. The problem wasn't a lack of marketing efforts. It was a lack of data-driven decisions. Here's what we discovered: ❌ Lead qualification was based only on form submissions ❌ Multiple campaigns were running without clear attribution ❌ Every lead received the same nurturing journey ❌ Mobile users were bringing traffic but not converting The solution? We stopped treating every lead equally. Using behavioral data, we built a smarter lead scoring system based on intent signals like: → Pages visited → Time spent on the website → Category interest → Repeat visits Then we: ✅ Shifted budget toward high-performing channels ✅ Created personalized nurture journeys ✅ Optimized the mobile experience using real user behavior The outcome after 6 months: 📈 52% improvement in lead quality 📉 41% reduction in CAC 🚀 67% increase in revenue per lead 📱 Mobile conversion improved significantly The biggest lesson? Growth is not about generating more leads. It's about understanding the right leads. How are you using data to improve your growth strategy? #DataAnalytics #GrowthStrategy #LeadGeneration #MarketingAnalytics #DigitalMarketing #CRO

A hard truth about startup growth teams: Being on all sides of the table (operator → investor → board member → full-stack fractional CMO), I've noticed founders often build their growth teams backwards. The typical approach: - Hire specialists for each channel - Focus solely on marketing metrics - Create departmental walls - Chase "best practices" blindly Here's why this fails: - Burns cash 2-3x faster than you gain market understanding - Creates silos that kill early-stage agility - Forces premature channel commitments - Misaligns incentives (vanity metrics vs. real growth) What actually works: 1. Start with strategic alignment - Map company metrics to marketing activities - Build systems for cross-team collaboration - Create clear feedback loops between product and marketing - Focus on scalable processes over hasty campaigns 2. Hire a strategic generalist first - Look for someone who can craft strategy AND execute - Prioritise data-driven decision making over channel expertise - Find people who can teach and enable others - Value business acumen over marketing-only experience 3. Get the foundations right - Deep customer understanding before channel selection - Cross-functional collaboration (marketing + product + sales) - Data infrastructure for measuring true growth (not vanity metrics) - Clear stakeholder communication (drop the marketing jargon) After working with hundreds of startups, here's the truth I keep coming back to: The cost of fixing a poorly structured growth team is always higher than the time it takes to build it right. The most successful founders I work with focus on the bigger picture: Building teams that operate as scalable growth systems. How are you structuring your growth team for scale? ♻️ Found this helpful? Repost to share with your network. ⚡ Want more content like this? Hit follow Maya Moufarek.

Building a startup is quite a journey. But my work as a Startup Strategy Expert has shown me that success is based on STRATEGIC MOVES and SHARP DECISION-MAKING. Dear Founder, as you focus on building a successful startup in 2025, let these strong factors drive you 👇👇👇 1️⃣ Obsess about the Problem — Match it with a Strong Value-Creating Idea. There are too many problems in the world to solve. So it’s clearly not just about identifying a problem; it’s about narrowing it down to something urgent, specific, and underserved. It must then be matched with your solution — one that creates tangible value for customers, with a strong ability to scale. 2️⃣ Laser-Focused Market Understanding. A great product in the wrong market will fail. You need to deeply understand your ideal customer — who they are, their pain points, and their decision-making process. Don’t guess. Don’t assume. Get the right answers on how to serve them. Be obsessed with your customer. The closer you are to their reality, the better your product & marketing will resonate. 3️⃣ A Resilient & Coachable Founding Team. The ability to learn, adapt, execute, and iterate quickly is too critical for startups. Assess your team’s strengths and weaknesses honestly. Be open to feedback, even when it challenges your beliefs. 4️⃣ Early Traction is GOLD! Your first customers are your strongest proof of concept. They validate that your product has a market and people are willing & able to pay for it. Treat your early adopters like royalty. Their feedback and testimonials will fuel your growth. 5️⃣ Don’t wait till chaos erupts before you ask for HELP! Please don’t! It’s too expensive. Work with Startup Advisers & Experts; Venture Coaches; Experienced Founders; Fundraising Experts; and Reliable Mentors! Prioritize the right direction and guidance to get things right and build something you can truly be proud of! Give your startup the best chance to WIN! I launched my Ask Me Anything (AMA) Sessions last week and the response has been MIND-BLOWING! It's been such a busy and fulfilling week, supporting everyone who's booked an AMA session to discuss questions aligned with my #Top10 Areas of Expertise (see flyer below) 👇👇 👇 🚨 Book your AMA Session here: bit.ly/AMAwithIfeoluwa or through my website directly: strategywithifeoluwa.com Glorious Light. Great Grace!

Not every startup can scale. I have worked with many founders, and I understand that the strategy that gets a startup to $1M ARR is not the same one that takes it to $10M ARR. Scaling isn’t just about doing more—it’s about doing things differently. You cannot scale if: ❌ You rely solely on founder-led sales. At $1M ARR, personal networks and hustle work. At $10M, you need a structured GTM engine with a repeatable sales process. ❌ You depend on one acquisition channel. Paid ads and outbound might get you started, but to scale, you need organic content, SEO, partnerships, and product-led growth. ❌ You focus only on new customers and ignore retention. The fastest-growing startups optimize Net Revenue Retention (NRR) above 100% by upselling, reducing churn, and increasing customer engagement. ❌ You stick to the same pricing model. What worked for early adopters won’t work for scaling. Startups that grow beyond $10M ARR continuously test and optimize pricing for usage, value, and expansion . ❌ You don’t build scalable systems and leadership. Hiring the right VPs, automating processes, and using data-driven decision-making is what separates startups that plateau from those that scale efficiently. Scaling is a mindset shift. The tactics that got you to $1M will hold you back if you don’t evolve. Is your startup ready to scale beyond $1M? 🚀 #StartupGrowth #ScalingStrategies #BusinessSuccess

Most brands are playing the wrong game. They’re moving the Queen. They should be moving all of the pieces on the board. Let me explain. Marketing-led growth gets all the attention. It’s sexy. It’s visible. Founders obsess over it. But marketing is just one piece. A powerful piece — but still one. Business engineering? It moves all the pieces in symphonic coherence, And wins the game. When I advise better-for-you CPG brands, this is the shift I push for. Most teams pour everything into: – ad creatives – influencer UGC – CRO – new channels Good tactics. But they’ll only take you so far. Here’s what separates the breakout brands: They engineer growth at the business level. They move: – pricing – packaging – cash flow – operations – channel strategy – product architecture They see the full P&L → and use it. Let’s get specific. Example 1️⃣ → Gateway SKU Engineering: A Clean supplements brand. $60/month subscription = Hero SKU. Too much friction. First purchase wasn’t converting. The team launched a $15 trial SKU. Low-risk. Easy buy-in. Result? Trial → subscription conversion jumped 4x. CAC down 35%. LTV up. No ad change required. Business lever. Example 2️⃣ → Cash Conversion Engineering Frozen functional food brand. Growing fast, but cash-strapped. They restructured terms with co-packers. Negotiated faster pay from wholesalers. Cash cycle dropped: 120 → 45 days. Millions unlocked. That cash funded more growth. No new ad creatives needed. Business lever. Example 3️⃣ → Operational Engineering Gut health beverage brand. Local retail only. Wanted national. Cold chain shipping was blocking DTC. Their team reformulated + repackaged → shelf-stable. Suddenly: – DTC viable – National retail opened – Margins improved Game changed. Business lever. ____________ This is why I believe: Business-engineered growth > marketing-led growth. ♛ Marketing moves the Queen. ♗♖♕♔♘♙ Business engineering moves all of the pieces on the board. If you want to build a moat → If you want to scale with durability → You need to think beyond ads and creatives. ☑️ You need to think like a business engineer. Curious → are you moving just the Queen? Or are you moving all of the pieces on the board? ___________________________________________ 🔰 Better-for-you brands = better health, longer lives. 👉 Follow me, Kunle Campbell, and let’s scale impact together.

A business can generate leads and still be growing in the wrong direction That was the issue with RSA Logistics. The problem was not silence in the market. It was signal quality. They were attracting the wrong audience. Growth had become stagnant. Marketing spend was not translating into scalable revenue. Campaigns were active, but not commercially aligned. For a B2B logistics business, this matters. Because not every lead has the same value. A high volume of low-fit enquiries can make marketing look busy while quietly creating friction for sales, operations, and leadership. More conversations. Less relevance. More follow-up. Lower conversion quality. More pressure on the business. This is where many scaling SMEs misread the problem. They see weak growth and assume the answer is more demand. But sometimes the issue is not demand volume. It is demand quality. RSA Logistics needed a stronger growth system, not simply more marketing output. That meant stepping back and asking better leadership questions: Who is the business really trying to attract? Is the positioning clear enough for high-value B2B clients? Are campaigns built around the right decision-makers? Are channels supporting the commercial strategy, or just creating activity? Is marketing helping revenue scale, or just filling the pipeline with noise? Once those questions became clearer, the work changed. CMO Angels embedded senior marketing leadership into the business. The company was repositioned for B2B growth. Lead generation became more structured. Messaging, targeting, and channels were aligned. Performance acquisition was connected back to commercial outcomes. The results followed: 24% revenue growth. 36% return on investment. 81% brand awareness growth. Higher-quality B2B leads. A more predictable pipeline. But the real lesson is deeper than the numbers. RSA Logistics shows what happens when a business stops judging marketing by activity alone. Because activity can hide misalignment. A campaign can look successful and still attract the wrong customer. A lead funnel can look full and still create poor commercial outcomes. Brand awareness can increase and still fail to support the right market position. That is why senior marketing leadership matters inside scaling SMEs. Not to create more noise. To connect the system. Positioning shapes the type of demand you attract. Targeting shapes the quality of conversations. Messaging shapes buyer confidence. Campaign discipline shapes commercial efficiency. Optimisation shapes whether growth becomes repeatable. When those pieces are disconnected, growth becomes harder to control. When they are aligned, marketing becomes more than a set of campaigns. It becomes a growth function. The RSA Logistics case is a useful reminder for any B2B business trying to scale: The goal is not more leads. The goal is more of the right demand, moving through a system the business can actually convert, serve, and scale.

Analytics aren’t just numbers; they’re your roadmap to publishing growth. Data isn’t power, it’s potential. For publishers, the real value lies in transforming raw metrics into repeatable growth strategies that drive audience retention, revenue, and #SEO performance. Too often, publishers collect vast amounts of data but fail to extract meaningful takeaways. The key is understanding what content resonates, how audiences engage, and where opportunities for growth exist. Collecting data is easy; extracting insights is not. Without clarity, metrics like pageviews and bounce rates become distractions. For example, a 40% drop in returning visitors isn’t just a traffic issue—it’s a retention red flag. By using the right tools and refining strategies based on real data, you can turn numbers into growth. Here are actionable strategies to turn data into action: 1. Know Your Audience Beyond Pageviews Pageviews alone don’t tell the full story. Instead, track return visitors, time on page, and scroll depth to measure true engagement. Tools like Google Analytics 4 (GA4) and Parse.ly provide deeper insights. Cohort analysis can reveal trends, millennials may prefer video, while Gen X engages more with newsletters. For example, if mobile traffic spikes by 20% after 8 PM, push breaking news via mobile notifications to capture that audience in real-time. 2. Optimise Content Performance with Behavioural Data Understanding why some content performs well helps you replicate success. Use @Google Search Console and Semrush to analyse search visibility and Hotjar Digital Marketing Company to track user interactions. For example, if "AI in media" gets 3x more shares than "content trends," double down on AI-related content. Additionally, A/B test headlines (e.g., “5 Growth Hacks” vs. “Proven Tactics”) to see what improves click-through rates. 3. Track Conversions, Not Just Traffic Traffic alone doesn’t guarantee success—conversions do. Set up goals in GA4 to measure newsletter sign-ups, paid subscriptions, or product purchases. Identify which referral sources drive the highest conversion rates, and adjust your strategy accordingly. For example, premium subscribers from "how-to guides" tend to have a 15% higher lifetime value than general news readers, meaning content type matters when driving long-term revenue. To scale what works, automate reporting with Power BI Visualization or Looker Studio to save 10+ hours per month. Analytics only matter when they drive actions. The biggest mistake any publishers can make is to treat data as a report card instead of a playbook. Start by auditing one content category this week, setting up a conversion goal in GA4, and A/B testing a headline. Data doesn’t lie, but it won’t work unless you do something. What analytics tools are you using to grow your publishing efforts? Share your go-to platforms in the comment below. #DigitalPublishing #SEO #ContentStrategy #AudienceGrowth #DataAnalytics