Ketch’s Post

There’s a widening gap between how marketers and consumers feel about brands collecting data and tracking customer journeys. According to The University of Cambridge Psychometrics Centre, 77% of marketers believe their organization should invest in predictive data and 71% of consumers believe that brands with access to personal data are using it unethically. Marketers and consumers don’t see these “lines” the same.  Consumers expect content, ads, and offers to be personalized and relevant.  And yet much of the data tracking that would help personalization and relevance is seen as creepy and invasive.  As privacy regulations tighten and consumers become more aware of data usage, zero-party data is emerging as a more ethical, transparent, and valuable data source for companies to build customer relationships and deliver personalized experiences. Zero-party data is information that customers intentionally and proactively share with a company or brand, typically through surveys, quizzes, preferences, or other direct interactions. This data is highly valuable because it provides explicit insights into customers' interests, preferences, and intentions directly from the source. Customers are fully aware they are sharing this data, eliminating privacy concerns.    Zero-party data and third-party data are fundamentally different in terms of how they are collected and their value for marketing and advertising purposes.    The key differences are:     1. Source: Zero-party data comes directly from customers, while third-party data is obtained from external sources without the customer's knowledge or consent.     2. Accuracy: Zero-party data provides explicit and accurate insights into customer preferences and intentions, whereas third-party data is often less reliable and accurate.     3. Privacy: Zero-party data is shared willingly by customers, eliminating privacy concerns. Third-party data collection and usage raise significant privacy issues.     4. Value: Zero-party data is highly valuable for personalization and targeted marketing, as it offers a direct understanding of customer needs. Third-party data is becoming less valuable due to privacy concerns and regulations. One Creation Corporation

Spot on post Jim Schofield, I see a lot of post touting 1st party data + 3rd party data and it reminds me of the definition of Insanity, “Insanity is doing the same thing over and over again and expecting different results”. Why as an industry to keep falling back on status quo? It's time to think differently, treat customers like humans, ask them what they want from your brand, incentivize them to share their data, be transparent and most of all, Build Trust with them! #Insanity #customerdata #digitalmarketing #buildtrust #justask

Accelerating time to value (TTV) is the goal, and the new Ketch Partner Program is designed to reduce TTV and improve customer satisfaction, retention, and ROI. 👇🏼 Calling all consulting firms, law firms, tech platforms, and marketing agencies: Today, we officially announce the Ketch Partner Program, arming you with the next-gen tools to enable privacy and drive data activation in the AI era. Ketch empowers partners with tech that simplifies privacy ops and unlocks the permissioned data for business growth. Companies select Ketch for our modern approach, including: 👏 Automates key compliance workstreams, like consent signals and DSRs 👏 No-code, intuitive interface designed for non-technical users 👏 Powerful APIs and extensive integration options Why partner with Ketch? ✔️ Incentivized pricing and commissions ✔️ Dedicated partner management ✔️ Hands-on implementation support and guidance Our partners are already seeing the benefits: “Bounteous x Accolite clients who use Ketch value its ability to connect consent preferences seamlessly across their data ecosystems,” says Jonathan Weber, SVP of Data & Analytics at Bounteous. “The Ketch APIs reduce complexity and help automate key tasks, driving efficiency and ROI.” “Together, Myna and Ketch are building innovative solutions that put customers first,” says Eric Dieterich, Founder and Managing Partner at Myna Partners. “Our partnership thrives on a shared commitment to customer success and truly listening to client needs.” Ready to elevate your clients’ privacy game and unlock new revenue streams? Let’s get to work. Dive into the Ketch Partner Program below ⬇️ Bounteous Myna Partners Red Clover Advisors Wyng Assertiva S.A. Boltive Americaneagle.com 85SIXTY VeraSafe Kelley Drye & Warren LLP Kelley Drye Advertising Law Transparent Partners Saint Hugo CrossCountry Consulting Jigsaw #marketing #data #artificialintelligence super{set}

Unlock the power of secure data collaboration! In today’s competitive landscape, having real-time insights into your marketing performance across various distribution channels and gaining a deeper understanding of customer behavior provides a significant edge. However, sharing data with retail partners can be a sensitive issue, particularly when it comes to protecting customer privacy, creating a number of challenges. Companies collect vast amounts of customer data every day, but sharing this data can quickly become problematic due to strict privacy regulations like the General Data Protection Regulation (GDPR). Yet, gaining these insights is highly valuable. For instance, consider a soft drink supplier selling its products through supermarkets. When the supplier launches a new campaign, having real-time insights into its performance is extremely beneficial, allowing for immediate adjustments and campaign optimization. A new, privacy-compliant solution for securely sharing this data between companies is the data clean room. A data clean room is a secure environment where sensitive data can be analyzed without compromising individual privacy. It uses anonymized or pseudonymized data to maintain confidentiality. The publisher (the party sharing the data) can enforce strict privacy rules for the subscriber (the party accessing the data), and both parties can share data in a controlled manner. This setup allows partners to explore overlapping audiences and customer segments, gaining valuable aggregate insights without exposing any underlying data. Data clean rooms provide several key advantages for both suppliers and their retail partners: 📈Real-time insights for campaign attribution and optimization: By enabling real-time insights, data clean rooms allow companies to monitor campaign performance as it happens, making it possible to adjust strategies and tactics immediately to maximize impact and results. 📚 Deeper customer understanding: The shared data environment offers more comprehensive insights into customer behaviour and preferences, helping companies better tailor their marketing efforts and product offerings. 🤝 Opportunities for co-campaigns: Data clean rooms create the foundation for collaborative marketing initiatives, enabling suppliers and retailers to run joint campaigns. These co-campaigns allow both parties to deliver more personalised and targeted offers to their shared customers, enhancing customer satisfaction and loyalty. Want to know more about the possibilities of Data Clean Rooms? contact us at Springbok Agency! 

"Automate your email marketing with AI," they said. "It'll save time and boost performance." But what they didn't say? Mismanaging customer data with AI could lead directly down the privacy violation rabbit hole. Why? Because AI can mishandle sensitive data, leading to compliance issues and, ultimately, eroding customer trust. The #1 mistake people make? Believing AI is infallible. Assuming AI will inherently handle data responsibly without oversight is naïve and risky. You can't just set and forget when it comes to automation, especially with customer data involved. Why isn't this hands-off approach the best? Because ignoring the complexities of data management leaves you vulnerable. AI decisions need human oversight to navigate the intricate web of data privacy and regulations effectively. So, what's the better way forward? Maintaining transparency and complying with data regulations should be at the forefront of any automation strategy. The goal is to create value through trust and not risk it by being careless. Here's how to do it: ✅ Understand Data Regulations: Know regulations like GDPR or CCPA inside out. Tailor your AI systems to respect these guidelines. ✅ Audit Your AI Systems: Regularly review AI processes for data handling. Spot and correct any inaccuracies in data processing swiftly. ✅ Implement Robust Consent Mechanisms: Before automating communications, ensure you've clear consent from your users. Design a transparent opt-in system. ✅ Prioritise Data Encryption: Encrypt data collected and processed by AI tools. This additional layer of security protects against data breaches. ✅ Educate Your Team: Regular training on data privacy and AI ethics is critical. Make sure your team understands the importance of data protection. When it comes to email marketing and automation, trust is your currency. Mismanage it, and you'll end up bankrupt. But manage it well? You can now build stronger relationships with your clients while ensuring you're compliant and trusted. Remember, automation isn't the enemy—mismanagement is. Keep your AI strategy aligned with transparent, data-respecting practices, and set your business up for long-term success. Follow us for more daily tips on conquering email marketing challenges!

Dear agency owners, this one is for you. If you are an agency in a tactical way (e.g. email marketing, digital ads, SMS, content, etc) extend your agency to provide database marketing services. Here's why 1. You can sync data from Shopify, Google Analytics, and Klaviyo from those sources to Google Big Query in about 1 hour. 2. A $25MM annual retailer will have a data file that is about 65GB of data - over 10 years. The data is EXCEPTIONALLY SMALL. Not including images. 3. You are already segmenting with Klaviyo and their rudimentary tools - unleash the power of querying and analysis and your segmentation will improve 100% in a short period of time. 4. Attach a BI tool and you are now rapidly answering business questions on consumer performance and becoming the go-to authority on marketing and sales for the retailer. They listen to you because you can analyze everything. 5. It's stupid cheap to build ~ $1500 a year. 6. If you attach ChatGPT to the BigQuery instance, you can train an agent to analyze the data and produce aggregates and in-depth analysis without knowing any SQL. 7. Longevity - you create stickiness and longevity and a huge amount of value by being able to analyze customer data and help drive marketing, sales, assortment planning, etc. If this is not on your radar, it should be. You can set up authentication procedures with low code and no code tools and move that data using Fivetran, Paragon or others. Make sure you secure the data structures, chatGPT can give you an assist on what to build. And architect standard functions that run standard segmentation and reporting services so you are not writing them every day. Now you have a core offering of highly targeted incremental performance and consumer database marketing services that will relate to your customers and create long-lasting, profitable relationships.

🔥 Excited to share my latest blog post on Remarkety: "Ethical AI and Data Privacy in Email Marketing". In this piece, I delve into the crucial balance between leveraging AI for personalized email marketing and maintaining the utmost respect for data privacy. https://lnkd.in/e2mqCcUJ As a passionate advocate for responsible AI (Generative AI) use, I believe it's our duty as marketers to ensure that innovation never comes at the cost of consumer trust. The article features real-world case studies showcasing the good, the bad, and the ugly of AI in our field. 🔗 Check out the full article here https://lnkd.in/e2mqCcUJ and let's start a conversation on how we can collectively push for ethical AI practices in our industry. #EmailMarketing #EthicalAI #DataPrivacy #DigitalMarketing #ecommercemarketing

The MarTech stack is more complex than ever. It's also more interconnected. This creates some hidden costs that many businesses, even small ones, don't realise until they committed. What's happening? At the root of most of it is data governance. Is the new system connecting with customer data and if so, how secure is it? Is it yet another copy of your data or does it just pull from a primary source? The last thing a team needs is yet another customer data source. The cost to prepare and move data can be relatively easy and a good vendor will have this service baked in. But sometimes, there can be costs if cleaning and re-working is needed. This can get pricey. Assess the data first. If the service has AI tools built-in, be sure to check the Terms & Conditions as they may have a clause allowing them to use your data, content, creative to train their AI tools. It's not just unfair, it puts your IP at risk. ** I'm Giles Crouch, head of marketing innovation at NordSpark | Marketing Innovation Lab I'm a neutral advisor helping companies improve their MarTech and marketing management. We don't sell or support any software.

TRE, maker of the cutting edge TRĒ CRM for professional services announced today that Todd Miller has acquired majority interest in the company. Miller, the founder and former CEO of gwabbit has also been named CEO of TRĒ AI. TRĒ is positioned to disrupt the traditional CRM industry with the world’s first and only turnkey AI-driven contact and relationship intelligence CRM for professional services with built-in eMarketing. TRĒ deploys in only 5-minutes and includes data quality management and data cleansing, eliminating the need for data stewards. “TRĒ was built for the Marketing and Business Development professionals who use CRM in law firms every day,” said Todd Miller, TRĒ AI CEO. “TRĒ’s AI sources the best possible contact and relationship intelligence content for its built-in eCampaign solution. Firms no longer need to wait months or years for results from their CRMs. TRĒ delivers instant value to firms and instant wins for the firm’s MBD champions.” https://lnkd.in/eAFKqHj6 #legal #legaltechtalk #CRM #AI #legaltech

🚀 AI spam cannons are good... but you're using them the wrong way. 🎯 The AI should be applied to targeting and timing, not messaging. 🤖 When used correctly, the AI spam cannon will help you connect with prospects who have a better chance of needing your services. ✂️ It will also whittle down your list — one of the best use cases for AI is taking an unstructured, unvalidated list of contacts or accounts and qualifying out bad fits. 🔍 Think about it like this: You have a CSV with URLs. You then use multiple scrapers to visit those URLs, gather unstructured data, and have AI analyze it. 💡 Is this person in your ICP? 💡 Do they handle what you're selling? 💡 Does this website have high traffic? 💡 What does the FAQ page say? Does it mention shipping time? 💡 Does the website code contain tools like Mailchimp or HubSpot? 🌐 There’s so much you can learn just by scraping LinkedIn, company websites, Google pages, Trustpilot, etc., and AI can help you analyze that data — something most people aren't leveraging. 🚫 Instead, most are just scraping LinkedIn, trusting AI to write a personalized line, and blasting away. Which often leads to horrible results like that cold email that referenced someone's LinkedIn post about their mom dying. It would be hilarious if it wasn't so fucked up. ⚠️ Nothing wrong with blasting, but don’t trust AI to write those lines unless you’re a pro (95% of people reading this are not skilled enough to program the AI correctly). ❌ Spam cannon = bad ✅ AI spam cannon = good ❌ Spam cannon ≠ AI spam cannon 📈 Downstream effects of this include: 📞 Better data for phone calls – your conversations are grounded in relevant insights. 💻 CRM with more relevant information – AI can provide more depth than ZoomInfo or Apollo alone. 🏢 Smarter decisions across the company – ads, SEO, and other investments are optimized because of a deeper understanding of your ICP's firmographics. 📊 Unbiased analysis of your Closed/Won deals – Using AI to analyze your deals gives a clear picture of a good-fit customer. Ask 10 reps, and they’ll all say something different. Reps lie. Managers lie. Numbers don't.