Giles Crouch, PhD-c’s Post

The D2C rush is over and not worked all that well except for a few brands. And now Wayfair is going bricks & mortar. We think digital changes everything, it does change a lot, but not what we think. Why? Consumers still want to experience buying many products. D2C relied on a marketing formula, mostly a certain style of video, that followed the lines of a trend and isn't, well, trendy anymore. Changing cultural norms and behaviours takes a long time and is never done by one brand alone. I think we can safely say the notion that going digital will solve everything in marketing is a myth. It's about balance and a mix based on listening to the customer. Not a management consulting firm. https://lnkd.in/g-evMW6J

Generative AI tools like Claude, ChatGPT4o etc., can be a great helper for marketing teams. But there are some common mistakes we see when we train marketing departments on using these tools. Avoid them. #marketing

Much of my work with businesses is helping them understand how consumers adopt technologies and how to market their technology innovations effectively. There's a problem with this poster. What is it? None of these are "new". They've all been on the list of technology trends for, well, upwards of 20 years. Web3 is right now, flat and on life support. cloud and edge computing goes back several years. Industrialising Machine Learning is very old news. Next generation software development is a meaningless term. Trust architectures and digital identity has been a trend for well over a decade and remains largely stagnant. Much of the hope for advancement in these areas is now being placed on Artificial Intelligence3 (AI). Which will disappoint. Be cautious of buying into technology trends without understanding their history.

Enjoyed being interviewed by Ana Melikian, PhD on the future of AI and being human in this time of change. AI can be wonderful and very helpful, and here I take a look at AI from a human perspective. https://lnkd.in/gKPHsuvM

There's an increased interest by some brands in using synthetic consumer marketing data. It can help and be a part of developing a strategy. But it should not be seen as an answer to consumer research. Why? Synthetic data tells you what happened. It doesn't tell you why and the why is far more valuable than the what or the how. The why helps you gain insights into the critical aspects of a purchase decision, which is context. Context can only be understood through qualitative research. Yes, it's expensive to actually talk to customers. But it's more expensive to rely on quantitative data alone as that will lead to lots of clicks perhaps, but less buying. Which makes advertising much more expensive and harder to attain real marketing ROI. Synthetic data may be cheap at the front end, but it's far more expensive on where it counts; driving revenues. Use it within the context of understanding where it helps and where it hurts. #marketing #management

A Sunday Thunk if you like. There's much talk about AI taking over humanity. What if instead, AI ended up making us more human? But how would we know that and what would be a benchmark to start from? https://lnkd.in/gBeuSQpJ

The first computer code was written by a woman. Ada Lovelace, in the Victorian era who wrote an algorithm for Babbages Analytic Engine to calculate the Bernoulli sequence of numbers. It is believed the first algorithm was written over 2,000 years ago.

These are the costs by the AI companies themselves to train their basic AI models (mostly LLMs), what isn't counted is how much it costs an average company to train the AI for their own systems. Why? Not only do they realise the model training cost, but it also creates a stark awareness of their technology debt. Especially with regard to their data management, governance and quality of data. Eventually, these issues will be dealt with. Maybe. Research is showing few companies are finding value from AI products sold by large tech companies. It's a Catch 22. The systems need to be trained, but the systems have to be in good order. Few are. This may be the real challenge and hurdle to overcome.

It's hard to kick bad habits. Like fussing over market share. It's a metric that doesn't really tell you much and isn't very helpful in creating strategy or measuring effectiveness of sales and marketing. Why? It doesn't tell you if your customers are using your product or service. It's good for stock trading (sort of), but not much more. It's a vanity metric for a brand. It doesn't help you understand why. Heavy Usage as an index does. The more customers actually use your product/service, the more likely they are to continue to. It can indicate where a product may be dropping. A warning sign to dig deeper. It works alongside CLV and CAC and helps you identify when and where competitors are slipping up. Which means opportunity for you. It's a signal for the performance of intangible assets like brand health. Kick market share to the curb. Evict it. Toss it onto the waste heap of wasteful metrics. #marketing #management