Walter Dosh

🏁 Marketplace Q1 Earnings Roundup: Instacart Instacart (CART) reported its first Q1 earnings as a public company. They announced an exciting partnership and continue to invest in advertising and AI. More below. 🚩 Instacart 📊 Financials ------------- - Gross Transaction Value (GTV): $8B; +7% y/y - Revenue: $820M; +8% y/y - Advertising & other Revenue: not mentioned, but approx ~30% of total revenue (from Q4 2023 earnings) 💡 Highlights -------------- ✅ Instacart announced a partnership with Uber to integrate hundreds of thousands of restaurants with an aim to boost customer acquisition, engagement & retention, and boost the value of Instacart+. The partnership will generate incremental revenue from affiliate fees. ✅ Uber is making advertising platform enhancements for better marketing efficiency (ROAS) and attribution. They're investing in in-store advertising with smart "Caper Carts" for brands to interact with shoppers in grocery stores. ✅ AI remains forefront with investments in AI-powered tools for stock prediction, personalized recommendations, and efficient in-store navigation If you found this helpful please like or share. If you have feedback on the format contents, length, topics please comment below

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I mentioned that I would be sharing a series of practical tips and recommendations about the role #analytics can play in accelerating a business, best practices for building a high-performing analytics team, and other lessons learned from the last decade at DoorDash. Today, you can find the first article I’ve written for First Round Capital: a deep dive into how to start an analytics function and what analytics can look like at different stages. In addition to the #lessons I’ve learned over the past decade building up the data science and analytics function at DoorDash, this post was inspired by my work as an investor and advisor to #founders. I frequently get questions about the right time to start an analytics team, who to hire, and what to expect from that team. I hope that anyone reading this article will walk away with something of a playbook and some guidance to help decide whether it’s the right time to start an analytics org–– and, if so, how to get started. https://lnkd.in/dNa58pC7 A big thank you to Jessi Craige Shikman and Julianna Marchant from First Round Capital for their support. I’d also like to thank Abigail (Homer) Reider, Carla S., Kshira Saagar, and Ali Musa for their feedback. And lastly, DoorDash Analytics team members (past and present) who have made the last decade such a meaningful adventure.

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The HR and talent tech market often falls short, largely due to the complexities surrounding people related processes, diverse company procedures, and unique team hiring rituals. I’ve encountered very few products that truly address the biggest challenges in hiring. BrightHire is one of the few that solve meaningful customer problems! Their AI functionality is game-changing, revolutionizing traditional recruiting habits and bringing transparency to hiring. We're excited to partner with Brighthire and leveraging such innovative technology to enhance our hiring processes. #rollthetape #TalentTech #Innovation #HRTech Rokt are hiring; https://lnkd.in/e9-p2biE

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Good McKinsey & Company article on how and why to rewire CPG companies around digital and #AI. 💰 Understand where the value can be created with existing technologies. Consumer insights and channel & customer management have biggest ROI in a lot of categories (see diagram). 👀 One beverage company that embarked on a digital and AI transformation unlocked 18 percent EBITDA uplift over two years 🚪 The importance of creating an innovation culture with cross-functional pods and phase gate processes for innovation funding 🎓 Upskilling your people through tailored learning curricula including on-the-job learning, formal training sessions, and individual coaching. 🔢 The importance of standardizing data pipelines, create reusable data platform products, elevating data product owners https://lnkd.in/ekWTUCHg

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Practical insights at Groceryshop 2024 on scaling AI responsibly from Ramesh Kollepara from Kellanova and Sabrina McPherson from Publicis Sapient . 1. Enterprise GenAI is a team sport - not just a tech game, but one that requires active participation from business stakeholders and end users 2. Create an ecosystem to bring the best in the industry - large and emerging players alike 3. Approach GenAI with a learning mindset - experiment multiple ideas with an understanding that not every use case will reach the end of the funnel

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Shout out to my brilliant friends Helena Cho and Diena Lee Mann!! I am not a data person, but I do appreciate good analytics. In my line of work, when we are identifying target audiences and the stories that could resonate with solving their problems, great data analytics share so much insight. 💡 Check out her interview!

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The upcoming shopping season is not just about offering discounts – it’s a strategic opportunity to fine-tune promotional efforts and analyze competitors. Delving into Black Friday and Cyber Monday strategies, I had the privilege, to share insights in a recent article by E-commerce w Praktyce . The piece explores standout campaigns and tactics driving results in this high-stakes period. 🔍Plan Smart, Execute Sharp Tight timelines? No problem—precise scheduling ensures nothing falls through the cracks. 💾 Data Is Your Secret Weapon Boost ROI with advanced remarketing and smart CRM segmentation. 🔑 Stay Transparent Shoppers are savvy—genuine deals build trust and drive sales. A full article with more insights waits in the comments section Insightland. Everyone has data, we have insights. #datadriven #blackfriday

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I have a great time spinning up our own delivery data in Omni, to the point that it deserved a write up on how easy is to use and the instant insights that we get from it! Check it out in our blog!

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Great 30-minute video from a dozen retail experts (incl me) talking about the impact of #AI on #retail #marketing. Here are my top insightful takeaways: - Microsoft's Sedhu Krishnamurthy talking about new opportunities to process large scale data and #NLP to understand shifting customer and market needs. FYI checkout Stan Sthanunathan's i-Genie.ai for next level CPG Consumer Insights. - Joyce Gordon of Amperity talking about how AI provides opportunities for challengers to be more competitive, opening up capabilities that previously could only be subsidized by large scale players. - Kathie Johnson of Sitecore talking about #GenAI removing the "soul-draining" tasks that take away from ideation and creativity - Melissa Minkow of CI&T about how #AI can help marketers navigate conflicting research data and presentations into coherent visions - Hayan Ortega of @Microsoft on AI's role changing focus from sales enablement to buyer empowerment and truly scalable 1:1 hyperpersonalized shopper journeys - Me talking about how AI changes the ROI economics of data platform investments, the ability to process even larger scales of internal and external data, accelerating the already increased #CMO focus on data. - Michael Klein on new intelligences that can fulfill the holy grail of multi-touch attribution in an increasingly distributed touchpoint world, and me chiming in on the exponential increase in data complexity we can now process and pattern match. - Christine Russo on how CMO's become a chief deployment officer, thinking about balancing quick wins with longer term infrastructure - Greg Buzek of IHL Group on the crucial differences in AI adoption strategies depending on whether you are a big or small company. Enjoy all the great insights from RETHINK Retail! https://lnkd.in/ebGvvXxY

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Check out the article below to see how Skechers was able to drive stronger customer loyalty by partnering with ActionIQ and Databricks!

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Building a Career Around Data Products: Using Product Mindset with Analytics Today, I had the pleasure of catching up with Vineet Batra from Chubb, who heads their analytics team. Vineet is a passionate leader in building intelligent data products with his strong background leading products and data teams at OYO and BNY. We discussed the future of analytics and products, focusing on the creation of data products and noting that awareness around this topic is still quite limited. Many might wonder, what are data products, and why do we need them? Simply put, data products represent the next level in analytics, embedding data insights into core products and daily lives. While, traditional analytics often involves ad hoc analyses presented in PPTs, Excel sheets, or dashboards. In contrast, data products leverage these insights on a larger scale, integrating them into everyday tools and processes with strong use of cloud technology. But it requires a strong product approach. Here are some examples of how data products touch our lives: •⁠ ⁠Credit Bureaus: Organizations like CIBIL, Transunion use data from our payment and credit histories and transactions to create credit scores, providing a snapshot of our creditworthiness. •⁠ ⁠Payment Networks: Companies such as Visa and MasterCard utilize vast amounts of transaction data to build data insights solutions and indexes to help network banks and merchant. •⁠ ⁠Health Apps: Applications like Fitbit and Apple Health collect and analyze data from our daily activities, offering insights into our fitness levels and health trends. Personally I had the opportunity to build some very useful data products during my career, including the automation of audits, marketing automation and global procurement to drive supply chain synergies. These experiences have shown me firsthand the transformative power of data products. The next big thing in AI and products will be embedding AI and analytics into everything, building very cool data-driven products. Google Maps is a prime example of how data and AI help us navigate our world efficiently, which has also enabled innovative solutions like Uber. What are some data products that have touched your life? Share your experiences and thoughts in the comments below ! If you are someone who would like to explore learning about building data products, do comment or DM either of us. #dataproducts #career #analytics #product

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With the rise in investment in Direct to Customer (D2C) channels by CPG firms, the question arises: How will this impact the Retail-CPG relationship? Considering potential scenarios and assuming the worst, the next question would be: Is investing in D2C still a viable option at the expense of a crucial relationship with retail? Here are some key reasons why companies might opt to invest in D2C channels: - Cost Efficiency: Deloitte's research suggests that adopting D2C channels can cut costs by up to 30% through streamlined operations and improved margins. - Investment Growth: A recent McKinsey report shows that 70% of CPG companies are ramping up their DTC investments to align with evolving consumer behaviors. - Consumer Preferences: A Nielsen survey reveals that 60% of consumers prefer buying directly from brands, prompting CPG firms to prioritize DTC strategies. - Enhanced Data Insights: Direct engagement with consumers allows CPG companies to collect valuable data on purchasing behaviors, resulting in enhanced product offerings and personalized marketing tactics. - Sustainability Focus: DTC models empower CPG firms to highlight sustainability in their operations, appealing to eco-conscious consumers. Understanding the benefits of D2C channels and evaluating their potential impact on the retail-CPG relationship is crucial. Feel free to share your thoughts on this matter and engage in an enriching conversation. It promises to be an intriguing discussion. #CPG #Retail #Analytics #DTC

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🚗 Ever experienced the seamless transition of driving a car with automatic headlights that activate in the dark, or windshield wipers that spring to life at the first hint of rain? These aren't just convenient features—they symbolize a smarter, more intuitive driving experience. 🌟 At Amazon Pay, we're on a parallel journey to revolutionize your everyday transactions, making them as intuitive and effortless as your smartest car features. 🎥 In our latest campaign featuring the charismatic Ayushmann Khurrana, he showcases just how smart he feels using Amazon Pay. It’s not just about making payments; it’s about enhancing the entire experience to be more intuitive and user-friendly. Watch it out. 👏 A big shout out to the relentless efforts of the team who obsess over refining and perfecting the customer experience every day. Their dedication is making the smarter way to pay not just a possibility, but a reality. Kalyan Chitumalla, Venkatesh Harsha Nandula, Ratnakar Mani, Bhavik Sankesara, Chandan Chatterjee, Hariharan K.R, Tanmai Vully,Chandru R, Abhishek Attal, Jatinder Khurana, Anshul, Kunal, Aasif, Sankalp Talwar, Shubham, and more. Shout-out to the leadership of Mahendra Nerurkar, Anuradha Aggarwal, Rahat Patel, Vikas Bansal, Nirav Kamdar, Amit Jain to continually push the boundaries of what's possible in digital payments. Join us in celebrating this leap towards a more intuitive future. Because with Amazon Pay, it's not just paying. It's upgrading to a smarter way of life. #AmazonPay #Innovation #DigitalPayments #SmartTechnology #CustomerExperience #AyushmannKhurrana

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You’re in Q4. Forecasts look shaky. Market volatility is at an all-time high. Your team is scrambling to adjust pricing, relying on traditional forecasting models built on static, historical data. But these models don’t capture real-time market shifts, leaving your team reacting after the fact instead of anticipating change. How can AI improve this scenario? AI can leverage real-time data sources from customer behavior, market trends, and competitor pricing to provide up-to-the-minute insights. Instead of reacting after the fact, AI enables your pricing strategies to adjust dynamically as market conditions evolve. Additionally, AI’s predictive analytics can forecast potential revenue risks months in advance, allowing you to address problems before they impact your bottom line. This shifts your approach from reactive to proactive decision-making and gives you greater control over pricing and risk management. By automating these processes, AI allows your team to focus on strategic, high-value decisions rather than constantly firefighting. I’m considering hosting a session on how to adopt AI strategically, shifting from reactive approaches to proactive transformation. If this sounds valuable, let me know and I’ll share more details.

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More Of The Same: Strong Q2, Driven by Advertising & Cloud Amazon delivered impressive second-quarter results, with net sales surging 10% year-over-year to $148 billion. The company’s net income experienced a remarkable upswing, showcasing improved operational efficiency and cost management.   Key Highlights Revenue Growth: Amazon's net sales climbed 10% to $148 billion, defying economic challenges and demonstrating continued market dominance. Profit Surge: The company reported a net income of $7.8 billion, a significant increase compared to the previous year, reflecting improved operational efficiency and cost management. AWS Expansion: Amazon Web Services (AWS) maintained its growth trajectory, solidifying its position as the leading cloud computing platform, with revenue increasing by 12% year-over-year. Advertising Boom: Amazon's advertising business continued its rapid expansion, generating substantial revenue and positioning the company as a major player in digital advertising thanks to newer offerings with brand building media. Advertising revenue jumped 20% to $12.77 billion. Prime Day Success: The annual Prime Day shopping event exceeded expectations, setting new sales records and driving customer engagement. Specific sales figures haven't been disclosed. International Growth: Amazon's international segment performed well in Q2 2024, with operating income improving by $1.2 billion year-over-year to $300 million. This was driven by cost reductions in established markets and expanded offerings in emerging ones. This meant the segment returned to profitability after several quarters of losses. Rx Pass: Whilst the report was light on new product announcements outside of AI initiatives, they did reveal that Amazon Pharmacy has expanded to include 60 popular prescription medications for just $5 a month with fast free delivery...

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To scale eCommerce growth, maximize revenue, and optimize spends, a strategic mix of analytics efforts needs to be applied across multiple fronts. While Attribution Modeling is key for improving campaign performance and a stronger ROI, Custom Attribution Models also pose the challenge of incomplete data trackability, discounting the negative impacts of channels and biggest of all, investment in expertise. Hence, one might find it better to utilize the in-built attribution models in GA4 and focus on these analyses for delivering greater ROI: 1. User Journey Analysis: Rather than looking at top-down, aggregated data, zoom in on how real customers navigate the site. Analyzing user journeys lets you pinpoint where people get stuck, drop off, or move forward. One can expect to unravel bottlenecks in the journey and even reduce in cancellations and churn. 2. CRO: CRO is an aggregation of ongoing strategies that compound over time by making a series of small, data-backed changes, from landing pages to product pages that cumulatively boost your conversion rate. This will have a huge revenue impact if you already have significant traffic volumes. 3. SEO Performance analysis: SEO performance analysis may feel like a slow burn, but it’s a powerful growth engine for eCommerce businesses. When you start ranking higher for strategic keywords, you’re boosting your organic traffic, and continuously depend less on paid marketing. SEO insights show exactly how customers are finding you which is invaluable for long-term scaling. With limited time and resources, a focus on User Journey Analysis, CRO, and SEO will lead to tangible, actionable steps. So, instead of spending months developing a complex custom attribution model why not test a new keyword strategy that could drive 30% more organic traffic? For most eCommerce brands, the real growth lies in getting closer to the customer experience and making quicker, more impactful changes that directly translate to revenue.

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The adoption of generative AI could unlock $160B to $270B in annual profit (measured in EBITDA) for CPG companies globally. The only problem is that many CPG companies lag in capturing digital and AI value, often stuck in pilot stages. McKinsey analysis shows that CPG companies are among the poorest performers in digital and AI maturity (see below), while retailers lead the pack. This is particularly concerning given the potential for a 6-10% revenue uplift and a 3-5 percentage point EBITDA growth over three to five years through digital and AI transformations. CPGs face two unique challenges: 🔸Data Proliferation: they face massive issues with data complexity and fragmentation across retailers, suppliers, manufacturers, and consumers. 🔸Organisational Change: Successful transformations require deep organisational change, not just technology upgrades. Companies must rewire their operations to fully harness digital and AI capabilities. The time to act is now. If CPGs are able to move beyond pilot projects and embrace comprehensive organisation-wide transformations, they can capture the significant value that digital and AI offer. Source: https://lnkd.in/ecp92Gqa #CPG #DigitalTransformation #AI #Retail

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Leaving aside the icky-ness of several hundred talented, hardworking people finding out they no longer have a job via a sentence in an earnings call, Oracle's quiet announcement that they are shutting down their ads business leaves a substantial hole in the market for users of their audience solutions- which are being used on actively running campaigns- with very little practical guidance being provided. If you find yourself in this situation, you should know that in addition to being a branded solution in Oracle, Proximic by Comscore's data powered much of Oracle's white labeled audience solutions, and that data is broadly available across all programmatic environments. Furthermore, our contextual solutions can help Grapeshot users seamlessly transition away from those solutions to our ID-less contextual audience solution, IAB category targeting, brand suitability etc. Please reach out if you need help or have been using Comscore data in Oracle and are not sure where to go from here. Lastly ( and most importantly) - If you worked at Oracle ads and are now job hunting, Proximic by Comscore is #hiring for a few different roles and we'd love to hear from you 💕

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