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🚀 How Can Marketers Trust AI Without Falling into the Trap of Data Bias? 🤖💡 In a compelling discussion by marketing expert Helen James, the hidden dangers of AI-driven marketing are highlighted—specifically, the risk of data bias influencing marketing strategies. Helen points out that while AI can offer powerful insights, these can only truly benefit marketers if they are both accurate and unbiased. 📊 The Problem? AI algorithms might be designed or unintentionally skewed to prioritize certain data points over others, potentially leading to unfair and misleading outcomes. This can stem from biased training data or algorithms not crafted with transparency. 🔍 Why It Matters? Imagine crafting a campaign based on these biases! The results? Misguided strategies that could alienate potential customers and harm your brand. 👩💻 During my early days in digital marketing, I witnessed a campaign falter because the data fed into our AI tools wasn't diversified, reflecting only a segment of our target audience. It was a tough lesson on the importance of data inclusivity and checking algorithmic bias. ✅ Here’s a Solution: Marketers must use AI responsibly by implementing fairness controls: 1. Ensure diverse and comprehensive training data. 2. Regularly test and audit AI algorithms for any biases. 3. Transparently disclose how AI insights are derived. 🔬 Research supports the urgency—studies from organizations like the National Institute of Standards and Technology and the University of California, Berkeley, underscore ongoing concerns about AI and data bias. So, what's your take on this? ➡️ As marketers, how do you ensure your AI tools aren’t misleading your strategies? ➡️ Are there specific measures you’ve implemented to combat data bias in AI? Share your thoughts and experiences below! Let’s ensure AI serves us all fairly and effectively! #Marketing #AI #DataBias #DigitalMarketing #EthicalAI #TransparencyInAI

AI Powered, Actionable Synthetic Data Can Revolutionize Marketing Research To an extent that it has the power to put together a winning Marketing Strategy for you As a marketer, I believe it's essential to stay ahead of the curve and leverage the latest innovations to drive better results. The recent advancements in synthetic data are a game-changer, offering faster, more accurate, and cost-effective solutions for market research. This disruption is not just limited to market research industry but has significant implications for the entire value chain, including brands, marketing leaders, and businesses. In the CPG industry, for instance, where customer preferences are constantly evolving, using synthetic data models trained across our preferred sample of buyers, and consumers of brands, helps gain a deeper understanding of their needs and preferences. This has the potential to increase #agility in #marketingstrategy in my opinion. Taking this analysis a notch higher, AI models one day will be in a position to suggest marketing strategies with a very low %age of deviation as the models have an apatite for tens of 1000s of variable and scenarios. Compare this with a few scenarios based on which decisions are made today. The author says that AI generated strategy will play out sooner that one would expect. However, I would to love learn more on how synthetic data models are trained across my preferred samples before exploring them in greater detail as this is a foundation for all the good things to come. While some may worry about "AI replacing humans", the author believes it's a misconception. The real battle is between AI and shoddy marketing processes. AI can help us streamline our efforts, eliminate inefficiencies, and make data-driven decisions. As a marketer, I'm excited about the potential of AI to augment our capabilities and drive better outcomes. Read more about the future of market research and how synthetic data can transform marketing strategy: https://lnkd.in/gEcqW82t #AIinMarketing #DataDrivenDecisionMaking #MarketingStrategy  #MarketingLeadership

Following up on the AI Summit hosted by CMO Alliance last week. There were many good presentations and Lara Shackelford's session on using AI to drive your GTM Strategy is one that resonated with me. Her message focused on how AI must be considered a strategic component vs a mere tool that enables your teams to do more with less. A few points I walked away with highlight AI plays a role in the strategy: – by improving the Customer Experience from first touch (in Brand & Demand Marketing) to adding Raving Fans to your community (Product & Customer Marketing) and extend across the organization to Customer Success and Support. – by finding the right balance between the need to personalize content vs scaling delivery across the buyer's journey – by closing gaps in your Data strategy.  Data is essential to AI and therefore companies need to have strong governance, clear and transparent ethics around its use, and the ability to synthesize for improved signaling Click through below to see Lara’s full slides and check out the comments to see the many other great sessions shared last week.

Most marketers believe AI is crucial, but many lack the training to use it effectively. This is where the AI Marketing Technologist comes in, bridging the gap and ensuring success. Learn more:

We provided a use case workshop, and then attended the ANA AI for Marketers Conference last week in Hollywood, Florida (yes, morning beach runs were fantastic!). Here are our big five takeaways from conversations with enterprise marketers: 1) We're moving from hype to real use cases: Yes, there were some very enthused sessions about the general promises of AI. But, most marketers wanted to get down to brass tacks based on experience. 2) More brands are adopting, but it's still early. The good news was that there were more use cases to actually discuss with best practices to offer. That being said, most enterprises are still experimenting with personal generative AI tools, and not enterprise implementations. It's still early. 3) ML drives enterprise AI adoption: AI hype surrounds generative AI, but the use cases we saw at ANA and discussed in private conversations almost always incorporated some form of machine learning and data analytics. 4) AI is a team sport! To successfully identify, create, and implement AI models, marketing leads need to achieve alignment with their peers to adopt AI successfully. That means strong relationships must be forged with the CEO, CSO, CTO, CIO, and general counsel's office. 5) Guardrails are the first showstopper. Guardrails are the first barrier to overcome in any enterprise AI project, marketing included. It is necessary to build legal and data security guardrails. You can read the full insights here: https://lnkd.in/eNUBx7hb

This morning Sam Davies sent me an intriguing Marketing Week article by Mark Ritson about synthetic data in market research, essentially AI-generated data manufactured algarithmitacally mimicking real consumer insights. This leap in market research offers remarkable efficiency and accuracy, almost on par (90%) with traditional human-derived data. When refined and applied effectively it has the potential to revolutionise market research by reducing research time and costs, while providing deep market insights. However, it raises a key question for anyone working in strategy: can AI genuinely grasp and communicate the emotional complexities inherent in human behaviour and opinions?    Maybe it can Maybe it can't Maybe it can't…yet.   I get excited when I see innovation like this in our industry and think there's plenty of reasons to be utilising AI-driven tools, even in their infancy. As AI reshapes content creation and trend prediction in advertising, it's important to balance tech innovation with the irreplaceable human element in brand strategy and research. As Ritson's article puts it, we may be heading towards a future where "marketers don't have to go to the market once with research," but just keep asking AI questions? My challenge to that is that the better that AI gets at giving us the answers, the more important asking the right questions becomes.    #BrandStrategy #SyntheticData #ArtificialIntelligence

Data is the currency of marketing. Not so long ago, we called people working with data "marketing data analysts" or "data analysts." But ... with the rise of generative AI, this field has evolved, and we now refer to it as #marketingintelligence Why? AI and generative AI have made marketing intelligence more crucial than traditional data analysis. While data analysis reviews past data, marketing intelligence uses AI to generate new insights, predict trends, and guide decisions. It combines data with advanced algorithms to offer deeper, actionable insights for better marketing strategies. At Women Love AI Marketing, we define marketing intelligence as: **The process of collecting, analyzing, and interpreting data related to marketing activities, markets, and consumer behaviors. It includes analytics, data and insights, performance measurement, research, monitoring, predictive modeling, ethics, and data protection. This information supports strategic decision-making in marketing**. We didn’t create this definition randomly. It’s based on the remarkable achievements, research, and insights of these 12 outstanding women: Erika Bahr Arina Curtis Emmanuelle Galou Tina Huang Adrienne ROSTAING Alex Irina Sandu Dona Sarkar Joya Scarlata, MBA Jaime Teevan Rachel Woods Yvonne Li Ruchika Singh To understand how we transitioned from data analysis to marketing intelligence and how to apply it in your role, follow their work - closely. #aimarketing #womenloveaimarketing #womeninai Side note to Benoit: here is an amazing first series of bright women who have contributed so much to AI marketing growth ;). Poke Laura, Isabelle et Delphine.

You're looking for an AI solution, but don't know where to start... 🤔 There are so many options out there & between buzzword acronyms like LLMs, LAMs & NLPs it's a mess trying to wrap your head around this whole AI surge right now. Let alone compare vendors. 🤯 Luckily - Edelman did the heavy lifting & put together a report qualifying 187 vendors. This list of criteria points included elements such as model data, ethics, user-friendliness, and data safeguards. With the end goal of implementing AI to save time. You can download the full report below & cut the hassle of your evaluation. #AI #dataanalysis #reporting #analytics #sociallistening #listening #communications #PR #publicrelations #datastructuring

AI in Marketing is a journey not a destination. In many of our conversations with both Adtech vendors and brands, we get asked how AI can help them. at Alligator Solutions we often help these organisations devise the right journey to get them to where they need to be, as many are overlooking the crucial foundational steps. As with anything in life, taking a metaphorical short-cut will rarely help you in the long-term. Focusing solely on the destination can lead to costly missteps. Getting the fundamentals right matters in order to build out a more sophisticated use of data and tech to deliver great marketing. examples of getting the foundations right include (but are not limited to): -Centralising data across a range of sources: Fragmented data hinders AI's ability to learn and make accurate predictions. While AI might fill in the gaps, if those gaps are gaping holes in your dataset, you have a problem. This data input must be underpinned by a strong taxonomy and naming convention -Siloed operations: Information barriers restrict AI's potential for holistic insights. Make the data accessible and democratised to a wider group than your own department. Using someone else's product (e.g Pmax) may provide short term gains, or success through vanity metrics, but your org will gain little in the way of insight and learnings. -Centralised understanding of your customer: If you have failed to set-up the tech to connect and centralise the identities of your customers across channels, segments and stage of the purchase funnel, then AI cannot help leverage relevant content and messaging, or prediction (e.g. likelihood to churn or propensity to convert) By laying a strong foundation and the necessary steps to sophistication, enterprise marketers can take the right journey towards effectively utilising AI and achieving marketing maturity and sophistication. #marketingtechnology #AI #marketingmaturity #datastrategy

It seems every time I open up a news feed there's another article or report on the potential of AI for businesses. My interest lies in what it means for procurement. McKinsey's latest article sheds light on how companies are leveraging AI to transform the procurement processes.  It seems that companies have started to drive measurable impact in four ways: 1) Generating content by automating document creation to reduce manual work such as automating document creation such as requests for proposals (RFPs) and contracts, reducing manual work significantly. 2) Enabling synthesis or the exploiting the unparalleled capabilities in retrieving, summarising, and deriving insights from vast and diverse unstructured data sources. It has the ability to quickly generate comprehensive strategies and identify suppliers based on specific criteria, streamlines processes, enhance accuracy, and expand the scope of available data, leading to more informed and efficient decision-making in procurement. 3) Augmenting engagement by enhancing interactive engagement, particularly through the use of chatbots that facilitate smoother conversations, fosters better relationships, and aids negotiation strategies by providing tailored talking points and evaluating various scenarios, ultimately optimising negotiation approaches for success. 4) Accelerating software programming by bridging disparate systems and accelerating tool adoption. Gen AI significantly reduces manual work and expedites technology roadmaps, leading to greater automation and analytic capabilities. The full article can be found at the following link : https://lnkd.in/gfbZxY5x I have no doubt AI will change procurement, it's just a case of when, not if, and affordability. Are you already using AI for procurement? Share your experiences—I'd love to hear from you! #procurement. #costmanagement. #ceo #cpo