Using the power of AI for product management

There's a lot of buzz around Artificial Intelligence (AI) at the moment. The Prime Minister recently made a speech in which he said that “Artificial Intelligence is the defining opportunity of a generation,” and set out plans to use the technology to boost growth. In particular, he highlighted the opportunity for businesses to use the new AI tools for faster planning and record keeping.

Whilst the Prime Minister is right, the real strength of AI is its ability to analyse vast amounts of data almost instantly and provide summaries and conclusions. This makes it ideal for use in marketing, for the development of new products and just as importantly for enhancing and prolonging the life of existing products. Using AI tools offers several significant benefits for Small and Medium-sized Enterprises (SMEs). The most important is the ability to compete with larger companies that have far more resources and capacity.
 
Product management

AI tools can greatly enhance various aspects of product management, offering numerous benefits and efficiencies. Here are just a few areas in which we can use AI tools in product management, many of which may surprise you:
 
1. Market Research and Consumer Insights

  • Trend Analysis: AI tools can analyse vast amounts of data from market trends, social media, and consumer feedback to identify emerging trends and customer preferences.
  • Customer Segmentation: AI can segment customers based on their behaviours and preferences, allowing product managers to tailor products and marketing strategies to different customer groups.

2. Product Design and Development

  • Generative Design: AI algorithms can generate multiple design options based on specific criteria, helping product teams explore a wide range of possibilities and innovate more effectively.
  • Prototyping and Testing: AI can help in creating and testing prototypes, predicting potential issues, and improving designs for better performance and user experience.

3. Project Management and Workflow Optimisation

  • Task Automation: AI can automate routine tasks, such as scheduling, progress tracking, and reporting, freeing up product managers to focus on strategic decision-making.
  • Resource Allocation: AI tools can optimise resource allocation by predicting project needs and potential bottlenecks, ensuring efficient use of time and resources.

4. Pricing and Sales Forecasting

  • Dynamic Pricing: AI can analyse market conditions and competitor pricing to suggest optimal pricing strategies, maximising revenue, and market share.
  • Sales Forecasting: AI models can predict future sales trends based on historical data and market analysis, helping product managers plan effectively.

5. Customer Experience and Support

  • Personalised Recommendations: AI can analyse customer behaviour and preferences to offer personalised product recommendations, enhancing customer satisfaction and loyalty.
  • Customer Support: AI-powered chatbots can provide instant customer support, answer queries, and gather feedback, improving the overall customer experience.

6. Post-Launch Analysis

  • Feedback Analysis: AI tools can analyse customer reviews and feedback to identify areas for improvement and inform future product versions.
  • Performance Monitoring: AI can continuously monitor product performance, identifying issues and opportunities in real time.

7. Competitive Analysis

  • Market Intelligence: AI can track competitors’ activities, product launches, and market positioning, providing valuable insights for strategic planning.
  • Benchmarking: AI tools can benchmark a company's products against competitors, highlighting strengths and areas for improvement.

By integrating AI into product management processes, businesses can streamline operations, drive innovation, and create products that better meet customer needs, ultimately gaining a competitive edge in the market. Importantly these tools are now available at a fraction of the cost of traditional methods, and many tools are freely available.
 
I’d like to highlight two tools in particular, the first that members have used very effectively and the second one that was launched in January this year. These are just examples showing the opportunities that are rapidly developing.
 
Trendbaby

In terms of new product development and the management of existing ranges tools like the TrendBaby suite can help businesses find new product innovation and opportunities.
 
Made in Britain member Marshalls plc has been a long-term user of the trendwatching reports and tools. Head of Market Intelligence Sara Dawson believes that the market and consumer insights gained from these resources have helped Marshalls gain and importantly retain its competitive advantage: “Marshalls have used the Trendwatching.com resources for almost 20 years and they are an invaluable resource to inform and steer our marketing teams thinking on products and communications. The development of the AI tools takes this to the next level.”


Trendwatching have many free to use tools. They work by asking you to:

  1. Select the industry and organisation you want to innovate for.
  2. Select the consumer trend that you want to explore.
  3. Define your target audience to tailor the product ideas to their needs and preferences.
  4. Set your innovation goals and timeframe for the project.

The AI tool then generates ideas based on the selected trend, audience, and goals.
 
Once you have used these tools you may wish to go further, these tools are part of their membership fee but they do offer a free 14-day trial.
  
Tools such as these have three major benefits:

  • Speed: They can generate new product ideas in seconds, accelerating the innovation process
  • Relevance: They can ensure that product ideas are aligned with current consumer trends and market demands
  • Efficiency: They can reduce the time and resources needed for brainstorming and ideation.

MatterGen
 
Recently launched by Microsoft, MatterGen, is an AI model that can generate new materials with specific properties that your products need. This marks a major shift in how we can discover and design new materials.

The model uses a ‘diffusion architecture’ that simultaneously generates atom types, coordinates, and crystal structures across the periodic table.

The model can be fine-tuned to create materials with specific target properties whilst importantly considering the design's practical constraints, such as supply chain risks.
Tools like MatterGen be a game changer for manufacturers, the traditional trial-and-error approach to materials discovery is slow and expensive. By directly generating viable candidates with desired properties and dramatically accelerate the development of advanced materials.

Microsoft have made their model available to the public and have released the source code of MatterGen under an MIT license together with the training and fine-tuning data.
 
Once new products are developed and existing ones enhanced, the new AI tools can help even further; for example:

These aren’t recommendations, they are examples of what is possible so far…but with AI, the landscape is constantly evolving, and we have only scratched the surface of its potential.
 
The world of AI is developing so rapidly, the secret is to jump in, explore, test, test, and test again. What is certain is that if you aren’t using these tools, your competitors will be.

Professor Chris Harrop OBE is visiting professor in sustainable business at the University of Huddersfield Business School.

By Made in Britain 2 weeks ago | By Made in Britain

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