Jared Huber

Three essential steps in dashboard design I learned from baseball ⚾ Baseball games are long, needing some snack / bio breaks. 🌭🥜 A good scoreboard helps us catch up quickly when we return to the stands. Watching my teenage son's baseball games inspired me to reflect on how dashboard developers can learn from simple sports scoreboards. Here are three key lessons that can help you develop more effective dashboards: ⚾1 - Know the Rules of the Game Just as a baseball scoreboard makes sense if you know the game’s rules, your dashboard should align with your audience's mental model of the "game" they are playing. Ensure your data presentation is intuitive and meaningful by understanding the dynamics at play in your audience's success. ⚾2 - Figure Out How the Game Is Won Your audience is aiming for success, whether it’s expanding market share, nailing project milestones, or stopping the spread of communicable disease. Understand their objectives and "opponents" to create a dashboard that reflects their goals and helps them track progress effectively. ⚾3: Make It Easy to See Who Is Winning Present the data clearly so your audience can see who is "winning" and by how much. And don't forgot test your dashboard with new users to ensure clarity. If a user can't easily assess how well the team is doing based on your dashboard, you may need to rethink your design or KPIs. Reflect back on your recent dashboards. Can you tell who is winning and by how much? If not, follow the principles above and you'll be knocking it out of the park in no time💥 Read my full article on Substack 👇🏻 #DashboardDesign #DataVisualization #BusinessIntelligence #PowerBI #Tableau #QlikSense

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🛑 ❗ Leaving technical names in your dashboard smacks of inconsideration for your audience. 👀 I’ve seen both inexperienced and more seasoned dashboard developers guilty of this underscore-toting offence and it makes me cringe every time! 😬 You can’t expect your business users to correctly guess what each graph is showing from alphanumeric-and-underscore soup. 🍜 Even for fairly straightforward terms like sales_num - the mature dashboard designer will ensure it is changed it to a properly capitalized and spaced business name label ---- before it ever rests on business users' eyes! 👩‍💼 👨‍💼 Check out my article for more info 👇

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How is Ocean Spray getting ready for AI? In this preview of our podcast with Neil Hampshire CIO and CDO of Ocean Spray Cranberries we discuss how companies are getting ready for AI and how you have to be very strategic about use cases to move fast without being reckless. This includes generative AI retrieval augmented generation (#rag ) models using internal data and “old fashioned” machine learning. #datastrategy #generativeAI #machinelearning #cdo #cio #oceanspray #cdotimes

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Let's talk about CROSS JOIN. What it is. What it most definitely is not. It is useful. It's not a conditional many-to-many join. The main thing -- the dangerous thing, usually -- about cross joins is that they form the Cartesian product of two tables. That is, every row in the left-hand table is matched to every row in the right-hand table. The number of rows in the outcome is the product of the number of rows in the two tables. CROSS JOIN is syntactic sugar. You can accomplish this by using a different join type. These are the same: SELECT a.*, b.* FROM a FULL OUTER JOIN b ON TRUE; SELECT a.*, b.* FROM a CROSS JOIN b; I've seen cross joins proposed as a method of "finding all pairs of football matches played" or "finding all pairs of cities with flights between them". For little examples like this, the output looks correct, because you're wanting a dense outcome set. But imagine two tables with 1 million (1,000,000) rows each. The product of these will have 1 trillion (1,000,000,000,000) rows, right around 125 rows for each person alive today. If you want non-dense many-to-many matches, use an INNER JOIN with your many-to-many bridging table. If your rows have arrays of matches (instead of a bridging table), use a LATERAL JOIN first to expand these rows. (LATERAL JOIN is written as an UNNEST in some SQL variants.) So what's a CROSS JOIN good for? (1) Widening rows with additional information. (2) Providing an exhaustive list of widened rows. One of the tables should be tiny, and contain columns relevant to every row of your other table. Consider a 1-row table. All it contains is a pair of timestamps, and you want to apply these timestamps to every row of your main table. CROSS JOIN is great for this. Your number of rows is unchanged, and you get your extra columns. Or consider a case where you've moved from having 1 warehouse of products to having 3, and you want to add a warehouse location to each row of your product catalog. A CROSS JOIN of your product catalog and your (very short) list of warehouses will do this immediately.

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The Bygone Era of Legacy BI - Dashboards are Dead! If you've ever felt like you’re stuck in a time loop every time you open a dashboard, you're not alone. Dashboards, those flashy displays of KPIs and metrics, were supposed to be the knight in shining armor for data-driven decisions. Yet, here we are, years later, still shackled by their limitations. A stagnant adoption rate of 30%, an average report turnaround time of 4.5 days, and poor data experiences reported by 84% of frontline business workers make it painfully clear: DASHBOARDS are DEAD! ☠ Unpacking the Hidden Costs of Legacy BI Let’s get real for a moment. When was the last time your data team celebrated a dashboard? More likely, they’re cursing the operational nightmare it has become. Reports show that 92% of data workers spend their time on tasks outside their roles, while 68% of data teams lack time to implement profit-driving ideas. Your team isn't just buried in data—they’re drowning in it. Consider this: 50% of your data team’s headcount budget is wasted on remedial tasks instead of actual data analysis. Imagine hiring a Michelin-star chef only to have them spend their days peeling potatoes. The hidden costs of maintaining these dashboards extend far beyond just financials—they’re a productivity black hole. Read more in the link to CDO TIMES independent research on how you can leverage AI to achieve productivity gains and ultimately hand the keys over to your business teams to ask questions about your data and get petabyte scale data insight on an individual level. #aianalytics #aidriveninsights #cdo #datastrategy #cdotimes #AIstrategy #digitalstrategy

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The thirst of data in all organizations is insatiable. While everyone argues over which LLM is the best, pragmatic data leaders are and should be concerned about how to serve data and semantic intelligence to these thirsty models. It’s time to talk about platform interoperability. That is the surest answer to this predicament that every CDAO finds him/her/them in. It’s a topic that does not get as much of a voice as it should.

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We often think of GENAI as a fairly consistent performer independent of the human thoughts and opinions that we sprinkle in. But here's something intriguing to consider: Can the time of year influence the outputs we get from the AI models? Both ChatGPT and Claude tell us "As an AI, I don't experience emotions, motivation, or physical states like laziness or fatigue, so my performance remains consistent regardless of the time of year. My responses and functionality are designed to be the same, whether it's January or July." While AI doesn’t have feelings like humans, the data it was trained on very likely reflects seasonal behaviors and trends. Here's why I think this matters: 🔺 AI’s training data was generated by people, and people’s behaviors shifted depending on the time or season of year. 🔺 Think about the topics that peak at certain times of the year such as fitness in January or holiday planning in December. The models we interact with today might reflect those same trends, even if they don’t have “awareness” of the time as humans do. This brings us to an interesting idea: Your AI prompts might yield different or more relevant responses depending on when you ask them! Let’s dive deeper: 👉 During the holiday season, you might find AI responses more centered around gift-giving, family dynamics, or end-of-year budgeting tips. 👉 In early spring or summer, advice on outdoor activities or vacation planning might come more naturally from your prompts. 👉 Even financial advice might be more tailored during tax season or around the end of a fiscal year when people are more likely to search for related topics. The takeaway? There could be better times of the year to get more ideal outputs for certain types of requests. Seasonality in data doesn’t just affect our strategies; it may also influence the type of insights and advice AI models provide us. What are your thoughts? Have you noticed differences in the AI outputs you receive depending on the time of year?👇 #AI #AITrends #GenerativeAI #Prompts #Contentcreator #DataTrends #Seasonality #PromptEngineering #AIInsights #TechnologyLeadership #Chatgpt #ClaudeAI #OpenAI #Anthropic

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Dear Retailers (#2): Your A/B testing strategy is not enough. You may find a winner, e.g., conversion/sales/AOV is higher via your A/B test, but you won't know what the impact is on how you're making your customer FEEL. You may get the conversion TODAY, but will you get a repeat purchase? A few examples: 🚥 If your shopper has issues trying to checkout, and it takes multiple tries, will she shop with you again? 🚥 If your shopper comes back to her shopping cart a few days later, and it's been emptied - will she make the effort to start over, and go find the items she was interested in again? 🚥 If you make it easy to buy, but hard to return, will she come to you again? In a time when customer loyalty is at an all-time low, every touchpoint of shopping with your brand matters. That means every click matters, every message matters, your policy matters...the return process matters. An interaction with your customer service chatbot or agents matter. So what should you do? Make sure your website CX strategy includes 3 key things: ✨ The Customer POV: user testing, voice of customer, CSATS (e.g., a human touch). ✨ Data analysis: the qualitative as well as the quantitative. A/B testing, funnel analysis, and heuristic testing. ✨ Shop your own site. Not kidding- everyone on your team, including your execs, should shop the site (and your competition) and note the friction points & opportunities. Remember, how your shopper feels during and AFTER the transaction will influence whether she shops from your site again. -Jessie PS. I help retailers & brands improve customer experience, driving improvements to revenue & profitability. If you'd like some help finding quick-wins or to successfully drive change, let's connect.

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👉 Did you already go through Joint Business Planning (JBP) or are you in the midst of it? JBP is such an important time for brands and retailers to both share their goals and ideas, be transparent and build out a joint omnichannel strategy for the year. We had so many learnings from interviewing brands and retailers about how to have better JBP conversations. Listen to some of those on our latest podcast... Thank you David Feinleib for having Nate Pinkston and I on to talk about the latest The Digital Shelf Institute & Microsoft Advertising research paper! #digitalshelf #commerce #partnership #content #omnichannel

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🚀 Upcoming: Kevin Visscher on Defying Legacy in Modern Commerce 🚀 In a few days, Kevin Visscher will discuss at the Yugabyte conference, how to build omnichannel, borderless commerce with Distributed SQL—a bold step in defying legacy systems and embracing adaptability. Join us to learn: 🔹 Why legacy tech holds retailers back 🔹 How adaptability across borders is the future 📅 Don’t miss this chance to rethink your commerce strategy for true resilience and growth! #ContextualCommerceistheNewBlack #NerdsAretheNewBlack #RetailInnovation

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Your Data Infrastructure (or lack thereof) Is Costing You BIG TIME This simple adjustment led to 110% more purchases and a 33% reduction in Cost Per Purchase. What was the change? Was it new creatives? Nope. Was it new copy? Nope. Was it simplifying their offer? Nope. The real game changer? Hiring our team of specialists to optimize the D A T A infrastructure & strategy Your Data Infrastructure is the foundation of ALL your marketing and growth activities & a robust first-party data strategy is crucial for your growth efforts. Here's the issue. . . Marketing and growth teams are stretched thin— managing clients, creating content, testing creatives, developing strategies—the list goes on. And what inevitably happens is that the very foundation of all of their efforts is left unmanaged. The consequences of neglecting your data infrastructure and data strategy include: > Erratic ad performance > Rising acquisition costs > Missed growth opportunities All of which directly impact your bottom line. After the release of iOS 14.5, brands have adopted a variety of strategies to overcome tracking and data challenges, typically falling into three main categories: Bucket 1: Ignore the need for effective first-party data systems & endure rollercoaster ad performance. Bucket 2: Use standard CAPI through platforms like Shopify. Better than nothing, but still limited and will never deliver optimal performance. Bucket 3: Rely on tracking, CAPI or attribution tools just because a well known podcast or thought leader recommends it. Spoiler alert. . .most of these tools are just glorified tag managers. Most of our clients come to us from Bucket #3—using tracking, CAPI, or attribution tools recommended by influencers or podcasts. When they put these popular solutions to the test against us, we've never been outperformed. Upgrade your data strategy today with audienceOS & join our clients who experience: ✅ More consistent ad performance ✅ Lower costs per acquisition ✅ Enhanced ability to scale Bottom line, an optimized data strategy & infrastructure are no longer 'nice-to-haves'—they’re essential for consistent, predictable growth. Don’t let your data infrastructure be your Achilles’ heel. Invest in your data infrastructure today & unlock massive growth and stability for your brand or clients. Comment below or send me a DM & let's see how much more profit we can help you squeeze out of your paid acquisition efforts.

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Back in my retail days my team helped capture the “life of an email” in a multi-paged document 📄 that articulated the many teams, hand-offs, approvals, etc. that were required in order to take an email from conception to completion… We’re talking dozens of hours 🕙 spent on photography, designing, editing, copyrighting, proofing, slicing, etc. -- not to mention the associated financial resources required! 💰 All of this to get one perfect specimen to send out for one and done use... ONE AND DONE!! 🤯 (ex/ a full file email about handbags sent on an arbitrary Tuesday at 6am with a 10% open rate) What if there was a better way?! There is 😊 Find out in 45 seconds 📺 Movable Ink #personalization #ai #emailmarketing

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Measuring the performance of promotions is critical for EVERY business. It's THIS EASY TO DO in Tableau with set actions. Want to learn how we did this in Monday's masterclass? Keep an eye on my feed FRIDAY for a very short window to purchase the recording and materials.

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In this week's episode of Boy Meets Data (link in the comments), I share a story about a challenging situation for data leaders. What happens when you take on a new role and your entire team leaves within your first few months? That happened to me many years ago. Data leaders have large aspirations about how they'll drive business strategy with data, make them "data-driven," and do all these wonderful things. However, if you don't have a strong team to lead, your actual job will be much different. These situations aren't discussed at conferences or webinars. Here are some key questions to ask when starting a new data leader job: ➢ Who was promised a promotion but wasn’t given one? ➢ Who applied for your role and didn’t get it? Were they told why? ➢ Who is frustrated with the way things are currently operating? Enjoy the article. If you like it, be sure to subscribe so that you can receive the new ones as they are published. #whatdidIsignupfor #dataleadershipstruggles

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This paragraph from Google's executive guide to generative AI is something everyone should clearly understand, or at least, keep in mind when working with this general-purpose technology: "Foundation [Gen AI] models are best thought of as probability engines that can be nudged and shaped by human input. Because they are probabilistic, they are fundamentally different from traditional software paradigms. When today’s apps need to look up product prices or validate customer information, they use deterministic functions that call a database. In contrast, foundation models use the patterns they learn during training and tuning to calculate the most probable output, such as the most likely answer to a question or an accurate caption for an image." . Garbage in, garbage out. #genai #digitaltransformation #thebasics

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I’ve often said TikTok was a train wreck clearly seen from years away that retail could have easily avoided Fashion's exec bros slept on it of course Still to this day dismissing the shared content of girls And now this... For the 3rd time in 3 weeks!! Luma AI dropped AI video generator "Dream Machine" overnight But unlike SORA AI , VEO, Vidu or KLING - AI Videos – it’s completely free to & available to anyone right this second The que is sooo long that it's taking a long time to generate my veeeeery on trend video Film maker Christopher Fryant released a new feature-length film project with it… He calls it nothing less than a sea change moment for AI video Remember when Tyler Pyler scrapped his $800M production campus? THIS is why I call it nothing less than a tsunami change for retail Imagine when women's sports catches on????? I do... Women earn 21X less than male athletes And get 90% less of the sponsorships Yet here’s a veeeeery interesting fun fact – They have 2X the engagement on social media with 1/2 the followers Pretty handy at a time when social commerce is the future THE ONLY WAY to close the pay gap is through non-competitive league products for the most engaged creator on the planet By gaining a deeper understanding of an athlete's community, a MASSIVE opportunity just appeared Women born on social media are driving a total market transformation And given the right tools we can spawn a new generation of value-based brands catering to a new market they understand natively finally breaking free from fashion's greedy gatekeepers & their sea of retail blandness!!! American brands are not only competing withbehemoths like SHEIN, you are competing with every kid on the internet who has more social media savvy b/c they were born digital Now she has the power of gen-ai to scale from 1 to hundreds of videos a week Btw, the fastest growing category of small businesses in America are content creators (Shopify) It's time to help our athletes scale with tools of community + creation It's also time for America to stop competing on discounts for fashion people don't want b/c it is created a year before consumer demand We must lean into Gen Z needs for entertainment, authenticity, content creation, collaboration, & community to reinvent retail IRL Oh AND!!!! Text to Sound Effects is here ElevenLabs generates sound effects, short instrumental tracks, soundscapes, & a ton of character voices Also available starting TODAY Bottom line – in discovery commerce, content is the product EVERYONE must be in the media and entertainment business before they can even think about physical products The democratization of AI video and audio is your final warning to wake up - a new generation of digitally-native entrepreneurs will destroy the market That's how teenage twins generated over $260k in 7 days #thegreatfashionreset #creatoreconomy #C2M #communitycommerce #contentistheproduct #tiktokisthestore

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#Shoppers will NEVER get behind #dynamicpricing until/unless they see that it provides them with cheaper prices at least 50% of the time. Textbook example of an #AI #commsfailure that prioritized the #tech and #industry messages over the #customerbenefits. We can and must do better #topretailexperts

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Today's technology news highlights a range of developments. Strava has implemented more stringent privacy measures by restricting third-party apps from sharing users' fitness data and banning its use for AI training. Niantic is leveraging Pokémon Go player data to create a "Large Geospatial Model" for enhanced spatial intelligence. Sony has begun beta testing cloud streaming on its PlayStation Portal, allowing select PS5 games to stream over the internet. Starlink is experiencing renewed demand, evidenced by a resurgence of waitlists in various U.S. regions. Additionally, there's news about a website discovering vintage YouTube clips, Alexa's potential enhancements via partnerships rather than AI, X Corp.'s lawsuit against Twitch regarding advertising, Apple blocking the Musi app, and Microsoft collaborating with Atom Computing on quantum error correction. This post provides a summary of key articles, aggregated, curated, and summarized by Mindlab’s AI Agent from trusted sources. For more in-depth insights, visit https://www.mindlab.news, or join Mindlab's LinkedIn Page: https://lnkd.in/gAM9bTYj The image below was created using MindLab's AI Agents, drawing inspiration from current technological developments reported in various online news sources. #GenerativeAI #AI #MindLab

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