Best Practices for Digital Marketing Analytics

In #datastorytelling, you often want a specific point to stand out or “POP” in each data scene in your data stories. I’ve developed a 💥POP💥 method that you can apply to these situations: 💥 P: Prioritize – Establish which data point is most important. 💥 O: Overstate – Use visual emphasis like color and size as a contrast.   💥 P: Point – Guide the audience to the focal point of your chart. The accompanying illustration shows the progressive steps I’ve taken to make Product A’s Q3 $6M sales bump stand out. Step 1️⃣: Add headline. One of the first things the audience will attempt to do is read the title. A descriptive chart title like “Products by quarterly sales” is too general and offers no focal point. I replaced it with an explanatory headline emphasizing the increase in Product A sales in Q3. The audience is now directed to find this data point in the chart. Step 2️⃣: Adjust color/thickness I want the audience to focus on Product A, not Product B or Product C. The other products are still useful for context but are not the main emphasis. I kept Product A’s original bold color but thickened its line. I lightened the colors of the two other products to reduce their prominence. Step 3️⃣: Add label/marker I added a marker highlighting the $6M and bolded the label font. You’ll notice I added a marker and label for the proceeding quarter. I wanted to make it easy for the audience to note the dramatic shift between the two quarters. Step 4️⃣: Add annotation You don’t always need to add annotations to every key data point, but it can be a great way to draw more attention to particular points. It also allows you to provide more context to help explain the ‘why’ or ‘so what’ behind different results. Step 5️⃣: Add graphical cue (arrow) I added a graphical cue (arrow) to emphasize the massive increase in sales between the two quarters. You can use other objects, such as reference lines, circles, or boxes, to draw attention to key features of the chart. In terms of the POP method, these steps align in the following way: 💥 Prioritize – Step 1 💥 Overstate – Step 2-3 💥 Point – Step 4-5 Because data stories are explanatory rather than exploratory, you need to be more directive with your visuals. If you don’t design your data scenes to guide the audience through your key points, they may not follow your conclusions and become confused. Using the POP method, you ensure that your key points stand out and resonate with your audience, making your data stories more than just informative but memorable, engaging, and persuasive. So next time you craft a data story, ensure your data scenes POP—and watch your insights take center stage! What other techniques do you use to make your key data points POP? 🔽 🔽 🔽 🔽 🔽 Craving more of my data storytelling, analytics, and data culture content? Sign up for my newsletter today: https://lnkd.in/gRNMYJQ7

If you are looking for a roadmap to master data storytelling, this one's for you Here’s the 12-step framework I use to craft narratives that stick, influence decisions, and scale across teams. 1. Start with the strategic question → Begin with intent, not dashboards. → Tie your story to a business goal → Define the audience - execs, PMs, engineers all need different framing → Write down what you expect the data to show 2. Audit and enrich your data → Strong insights come from strong inputs. → Inventory analytics, LLM logs, synthetic test sets → Use GX Cloud or similar tools for freshness and bias checks → Enrich with market signals, ESG data, user sentiment 3. Make your pipeline reproducible → If it can’t be refreshed, it won’t scale. → Version notebooks and data with Git or Delta Lake → Track data lineage and metadata → Parameterize so you can re-run on demand 4. Find the core insight → Use EDA and AI copilots (like GPT-4 Turbo via Fireworks AI) → Compare to priors - does this challenge existing KPIs? → Stress-test to avoid false positives 5. Build a narrative arc → Structure it like Setup, Conflict, Resolution → Quantify impact in real terms - time saved, churn reduced → Make the product or user the hero, not the chart 6. Choose the right format → A one-pager for execs, & have deeper-dive for ICs → Use dashboards, live boards, or immersive formats when needed → Auto-generate alt text and transcripts for accessibility 7. Design for clarity → Use color and layout to guide attention → Annotate directly on visuals, avoid clutter → Make it dark-mode (if it's a preference) and mobile friendly 8. Add multimodal context → Use LLMs to draft narrative text, then refine → Add Looms or audio clips for async teams → Tailor insights to different personas - PM vs CFO vs engineer 9. Be transparent and responsible → Surface model or sampling bias → Tag data with source, timestamp, and confidence → Use differential privacy or synthetic cohorts when needed 10. Let people explore → Add filters, sliders, and what-if scenarios → Enable drilldowns from KPIs to raw logs → Embed chat-based Q&A with RAG for live feedback 11. End with action → Focus on one clear next step → Assign ownership, deadline, and metric → Include a quick feedback loop like a micro-survey 12. Automate the follow-through → Schedule refresh jobs and Slack digests → Sync insights back into product roadmaps or OKRs → Track behavior change post-insight My 2 cents 🫰 → Don’t wait until the end to share your story. The earlier you involve stakeholders, the more aligned and useful your insights become. → If your insights only live in dashboards, they’re easy to ignore. Push them into the tools your team already uses- Slack, Notion, Jira, (or even put them in your OKRs) → If your story doesn’t lead to change, it’s just a report- so be "prescriptive" Happy building 💙 Follow me (Aishwarya Srinivasan) for more AI insights!

If your e-mail and SMS strategy doesn't emphasize content that is meant to educate the consumer, you are likely missing out on a lot of revenue. The truth is, 95% of visitors to an DTC brand's website will not purchase on the first touch, and require some sort of nurturing to make a purchase. Often times that nurturing doesn't need to be a discount or lower price, it just requires education. We've seen significant improvement in performance across all types of flows and campaigns when education has been a primary focus. Yes, education can be done via SMS too, using short, snippy soundbytes that remind the user why they showed interest in your product in the first place, and why they should care about your brand in particular. It matters because messages with educational content simply have higher open rates, engagement, and drive more sales. But first, let's clarify what it's not: • It's not just selling a product • It's not sending boring newsletters • It's not ignoring your audience's needs • It's not using complex jargon • It's not spamming inboxes • It's not focusing only on your brand • It's not neglecting engagement • It's not one-size-fits-all content Here's what it really is about: • Providing value to your audience • Sharing useful tips and insights • Building trust with your readers • Encouraging two-way communication • Creating a loyal following • Making learning enjoyable • Offering solutions to real problems • Keeping content relevant and fresh If you want to boost your email & SMS marketing, focus on educational content. → It increases engagement. → It builds customer loyalty. → It drives conversions. Your business will thrive from it.

🚀 𝗠𝗮𝗸𝗲 𝗬𝗼𝘂𝗿 𝗘𝘅𝗰𝗲𝗹 𝗥𝗲𝗽𝗼𝗿𝘁𝘀 𝗦𝗽𝗲𝗮𝗸 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 💡 Data alone doesn’t guide decisions—𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗱𝗼𝗲𝘀. I see it all the time—teams spending hours compiling spreadsheets, yet decision-makers are still left asking, “𝘞𝘩𝘢𝘵 𝘥𝘰𝘦𝘴 𝘵𝘩𝘪𝘴 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘮𝘦𝘢𝘯 𝘧𝘰𝘳 𝘶𝘴?” The missing link? 𝗦𝘁𝗼𝗿𝘆𝘁𝗲𝗹𝗹𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗱𝗮𝘁𝗮. Raw numbers are powerful, but numbers paired with narrative drive action. Here’s how you can transform your Excel reports from static tables into compelling business stories: 1️⃣ 𝗩𝗶𝘀𝘂𝗮𝗹 𝗖𝗹𝗮𝗿𝗶𝘁𝘆: Use charts and conditional formatting to highlight trends, outliers, and key metrics. A single color-coded chart can communicate more than 100 rows of numbers. 2️⃣ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀: Numbers without context are noise. Add commentary fields or notes explaining why a metric is moving, not just that it moved. 3️⃣ 𝗔𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗙𝗼𝗰𝘂𝘀: Frame insights around decisions. What should the business do based on this data? Every report should answer a question, not just present numbers. 4️⃣ 𝗡𝗮𝗿𝗿𝗮𝘁𝗶𝘃𝗲 𝗙𝗹𝗼𝘄: Organize your sheets and dashboards like a story—start with the headline metric, follow with supporting data, and close with a clear takeaway. 💬 𝘿𝙖𝙩𝙖 𝙞𝙨 𝙤𝙣𝙡𝙮 𝙖𝙨 𝙪𝙨𝙚𝙛𝙪𝙡 𝙖𝙨 𝙩𝙝𝙚 𝙨𝙩𝙤𝙧𝙮 𝙞𝙩 𝙩𝙚𝙡𝙡𝙨. 𝙒𝙝𝙖𝙩’𝙨 𝙮𝙤𝙪𝙧 𝙛𝙖𝙫𝙤𝙧𝙞𝙩𝙚 𝙬𝙖𝙮 𝙩𝙤 𝙢𝙖𝙠𝙚 𝙖 𝙙𝙖𝙩𝙖 𝙥𝙤𝙞𝙣𝙩 𝙩𝙚𝙡𝙡 𝙖 𝙨𝙩𝙤𝙧𝙮? #DataStorytelling #BusinessIntelligence #DataDrivenDecisionMaking #AnalyticsForBusiness

Data alone can often feel impersonal and hard to relate to but professionals have found an interesting way around it - at least in the consulting world. I found it interesting that Bain & Company tackles this by using "customer journey mapping" - an approach that transforms data into vivid narratives about relatable customer personas. The process starts by creating detailed personas that represent key customer groups. For example, when working on the UK rail network, Bain created the persona of "Sarah" - a suburban working mom whose struggles with delays making her miss her daughter's events felt all too real. With personas established as protagonists, Bain meticulously maps their end-to-end journeys, breaking it down into a narrative arc highlighting every interaction and pain point. Using techniques like visual storyboards and real customer anecdotes elevates this beyond just experience mapping into visceral storytelling. The impact is clear - one study found a 35% boost in stakeholder buy-in when Bain packaged its conclusions as customer journey stories versus dry analysis. By making customers the heroes and positioning themselves as guides resolving their conflicts, Bain taps into the power of storytelling to inspire change. Whether mapping personal experiences or bringing data to life, leading firms realize stories engage people and shape beliefs far more than just reciting facts and figures. Narratives make even complex ideas resonate at a human level in ways numbers alone cannot.

Data without a story is just a spreadsheet. A story without data is just an opinion. Ever wondered why some presentations leave you stunned while others put you to sleep? The answer might be simpler than you think: It's all about how you present your data. Let's dive into a masterclass on data visualization, courtesy of Hans Rosling's iconic TED talk. Rosling starts with a bombshell: Swedish top students know statistically significantly less about the world than chimpanzees. Wait, what? He goes on… Rosling used a simple quiz: → 5 pairs of countries → Each pair: one country has twice the child mortality of the other → The task: Identify which country in each pair has higher mortality The results from his students were…shockingly bad. Why this story works: Simplicity: The test is easy to understand Contrast: Humans vs. Chimpanzees (unexpected comparison) Personal connection: We all think we're smarter than chimps Just like startups need to solve high-intensity problems, your data needs to address high-intensity curiosities. Rosling didn't pick random facts. Instead, he chose a topic that matters (child mortality), a comparison that shocks (educated humans vs. random guessing), and results that challenge assumptions (We're not as informed as we think). This is the "Intensity Imperative" of data storytelling. How to Apply This: 1/ Find the Unexpected What data point in your industry would surprise even the experts? Where do common assumptions fall apart when faced with real numbers? 2/ Make It Personal How can you frame data so your audience sees themselves in the story? What universal human experiences can you tap into? 3/ Simplify, Then Simplify Again Can you explain your key data point in one sentence? If not, keep refining until you can. 4/ Use Vivid Comparisons Instead of abstract numbers, how can you relate your data to everyday concepts? Example: "This much carbon dioxide would fill 1 million Olympic-sized swimming pools" 5/ Build Tension, Then Release Start with a question or premise. then let the data reveal the answer dramatically.

Data is everywhere, but turning it into a story that sticks? That’s the challenge — and the opportunity. I recently teamed up with ILTA — the premier membership organization for legal technologists — to share my thoughts on their blog for how Legal Marketers can use data visualization to create clear, engaging, and impactful narratives. In this post, you’ll learn: - The five key data patterns: Change, Clustering, Relativity, Ranking, and Correlation. - How to turn complex datasets into visuals that resonate. - Practical tips for crafting visuals that drive action. Whether you’re in legal marketing, analytics, or just looking to elevate your data game, this guide is packed with insights to help you make data-driven storytelling your superpower. You'll find the blog post here: https://lnkd.in/gxHuMgaQ Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

August Revenue is N120 Million..... ❌ That's not how to report revenue. When it comes to closing the month-end, one thing management always wants to know first is: “How did we make money this period?” If you can make management see not only what was earned, but also why it was earned, how it compares to past performance, and where future opportunities lie, then you are not just reporting, you are adding value. My Approach ✔️ Step 1: Start with the headline number Always open your report with the revenue figure for the period. Keep it simple and clear. Example: Our total revenue for August 2025 was N120 million. ✔️ Step 2: Compare with relevant benchmarks A single number means little in isolation, that's why the real insight comes from comparing it against: ▪️ Previous Month (Actual) – Shows short-term growth or decline. ▪️ Budget/Target for the Month – Reveals if the company is on track. ▪️ Previous Year (Same Month/Period) – Shows long-term growth trend. This is where you bring the story alive. Suppose August 2025 revenue was N120 million. ▪️ July 2025 actual revenue was N100 million → Growth of 20% month-on-month. ▪️ Budgeted revenue for August was N125 million → Achieved 96% of target. ▪️ August 2024 revenue was N90 million → Growth of 33% year-on-year. Interpretation: Revenue grew strongly compared to last month and last year, showing an upward trend. However, it fell slightly short of the budget, meaning assumptions on product demand or pricing may have been a little optimistic. ✔️ Step 3: Go Deeper with Product Analysis Management wants to know what is driving the numbers. Break revenue down by product or service line. ▪️ Which products grew the fastest? ▪️ Which ones are underperforming? ▪️ Did price changes, discounts, or promotions affect sales? ▪️ Was the increase driven by volume (more units sold) or by higher prices? Example (for August 2025): ▪️ Product A: N60m revenue (up 25% vs last month):-growth driven by higher sales volume after a new marketing campaign. ▪️ Product B: N40m revenue (flat vs last month):- price discount boosted sales but reduced margins. ▪️ Product C: N20m revenue (down 10% vs last month):- customers switching to competitors due to pricing. Step 4: Highlight Growth Trends and Drivers Your report should explain not just the what, but the why. ▪️ Was growth driven by increased demand, new customers, or higher pricing? ▪️ Were there seasonal factors (festive periods, back-to-school, holidays)? ▪️ Did external factors like exchange rates, inflation, or regulation affect revenue? This helps management make informed decisions, whether to double down on what works or to fix what’s broken. Important! Clear revenue reporting gives management quick insight, supports wise decisions, ensures accountability to budgets, and guides strategic planning. Remember, revenue is not just a number; it’s the heartbeat of a business. I hope this helps.

We used to track 22 metrics for a client. Guess how many the CEO cared about? If you guessed zero, you are the winner! Ding, ding, ding! Winner, winner, chicken, dinner! Not one single metric was compelling to him. Yet, the marketing and comms teams spent hours every week creating beautiful reports...just to have them ignored. We helped them transform their approach to measurement in 90 days, leading to their CEO actively seeking out their reports and asking strategic questions about the data. In this article, I detail how we did that and provide some thoughts on: 1️⃣ How to identify metrics your CEO actually cares about 2️⃣ A step-by-step plan to transform your measurement approach 3️⃣ Real examples of teams that doubled their budgets measuring what matters 4️⃣ The secret to predicting business trends through PR data The best part? You don't need fancy tools to get started. You just need to hone your storytelling skills for internal use. #PRmetrics #Communications #measurement #PESOModel #PublicRelations

90% of data analysts show pretty charts. Only 10% know which chart tells the right story. But here's the brutal truth: They don't want to know what happened. They want to know what to do about it. 𝐓𝐡𝐢𝐬 𝐦𝐢𝐧𝐝𝐬𝐞𝐭 𝐬𝐡𝐢𝐟𝐭 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐞𝐬 𝐠𝐫𝐞𝐚𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐭𝐬 𝐟𝐫𝐨𝐦 𝐠𝐨𝐨𝐝 𝐨𝐧𝐞𝐬: Good analysts report: "Sales dropped 15% last quarter." Great analysts recommend: "Sales dropped 15% in Region A. Shift budget to Region B, where conversion is 3x higher." Good analysts show: "Customer churn increased"   Great analysts advise: "Churn spiked after the pricing change. Reverting would save $2M annually." 𝐓𝐡𝐞 𝐜𝐡𝐚𝐫𝐭 𝐭𝐲𝐩𝐞 𝐬𝐭𝐢𝐥𝐥 𝐦𝐚𝐭𝐭𝐞𝐫𝐬. 𝐁𝐮𝐭 𝐨𝐧𝐥𝐲 𝐢𝐟 𝐢𝐭 𝐝𝐫𝐢𝐯𝐞𝐬 𝐚𝐜𝐭𝐢𝐨𝐧: Bar Chart → Compare performance, identify winners to scale Line Chart → Spot trends early, predict what's coming Scatter Plot → Find correlations that unlock opportunities Heatmap → Highlight problem areas that need immediate attention 𝐇𝐞𝐫𝐞'𝐬 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲: Your stakeholders have 50 dashboards already. They don't need another one. 𝐓𝐡𝐞𝐲 𝐧𝐞𝐞𝐝 𝐲𝐨𝐮 𝐭𝐨 𝐭𝐞𝐥𝐥 𝐭𝐡𝐞𝐦 𝐚 𝐬𝐭𝐨𝐫𝐲: - What's broken - Why it matters - What to do next Stop being a reporter. Start being an advisor. The best visualization isn't the prettiest one. It's the one that gets a decision made. ♻️ Share this with an analyst ready to level up 𝐏.𝐒. I share data storytelling insights and career tips in my free newsletter. Join 19,000+ readers → https://lnkd.in/dUfe4Ac6