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Application of Generative AI in Product Management

By Amit S – Assistant Vice President – Growth & Strategy, Accenture

In product management, generative AI has emerged as a very powerful tool for revolutionizing many of its aspects. From market analysis, segmentation, persona development, and personalization to analyzing the competitive landscape of a product, generative AI has been very helpful to product managers. It can improve many aspects of the product process like personalization according to customers’ needs, time used in product development, and automating repetitive tasks.

Key Takeaways:

  • Generative AI is categorized into 2 broad categories- generative and transformational models. 
  • The first one, generative alternate, is where you have a text or image input into the Generative AI model and it in turn generates a creative video or images in response. The other one is a transformational model. It is generally generated from the text input. 
  • Generative AI can give an overall landscape of what the competitors are doing, how they are utilizing the use cases, or what products they are selling.
  • Generative AI can help product managers in market analysis and segmentation. It can help in understanding the customer better and devise the sales strategy. 
  • Identifying buyer persona can help product managers in terms of defining and crafting their product offerings in a more innovative way. It is another one of the functions of Generative AI.
  • Generative AI can help product managers analyze the competitive landscape of their products.
In this article
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    Introduction to GTM with Generative AI

    As an introduction, Generative AI is not a new concept. It has been evolving since 1958 when we started having machine learning calculations. It has gained prominence with a lot of large language models coming into the picture starting with AI2 Elmo or Google’s Bert. It has evolved with the introduction of GPT3 in 2020. It has evolved to thousands of use cases in every industry wherever possible to automate content generation.

    Broadly, Generative AI is categorized into 2 broad categories- generative and transformational models. The first one, generative alternate, is where you have a text or image input into the Generative AI model and it in turn generates a creative video or images in response. The other one is a transformational model. It generally generates from the text input. It generates a relevant outcome that you are looking for. These both can be trained on either supervised or unsupervised learning depending on where the end applications would be. 

    Generative AI has different applications like market and customer research. It can give an overall landscape of what the competitors are doing, how they are utilizing the use cases, or what products they are selling. We can utilize it in terms of data strategy or the optimized input products that are going to create finished goods for us. This is because it does not only limit the technology product, there could be a physical product that we have to deliver and we would need certain raw materials or goods that we would first process and deliver to the customer. So giving us an optimization in terms of the various factors of prices, it can help us gain more value in terms of the money that we save in purchasing or procurement. 

    It helps in the overall customer journey mapping where there is a turn, where customers are dropping off in the entire customer journey. Based on this, product managers can plan their future campaigns. They can define the content strategy, not just limited to the content but also identify which particular media is giving them better or higher results vs what they should target in terms of content. It can also help in terms of content production and management of the content.

    Market analysis and segmentation

    On the basis of an attribute a customer or market would have, product managers can analyze or plan their market strategies. So identifying segments based on the customer purchase history, the customers’ buying patterns, understanding how is the customer interacting or what are all the pages the customer follows, the product searches a customer does, his prior search history; based on these product managers can personalize the recommendations to the customer. They  can also help in understanding the customer better and devise the sales strategy. They can also microsegment those and identify the common interests of the customers. Based on this information, you can create brand creatives, target ad campaigns, marketing collaterals and brochures. It can also help in terms of automating the entire email flow that the customers would have in the entire customer journey.

    Persona development and personalization

    Persona is basically a semi-fictional character that illustrates the behaviour or need of the individual that will form our target audience as to what age group that person is from, what is the demography, what are their pain points or challenges, what is their purchasing power, what are their satisfaction requirements and so on. Product managers can tailor make their product based on the target persona. So persona identification is important in a way to define your product offerings. Those who have been associated with a product or business would know that we create a persona and identify needs. So persona used can be created by both manual or Generative AI processes. Generally, as product managers, we identify who the person is, what is the essential tasks they do, what are their different pain points, what are the barriers for them to buy our product, and what are their aspirations. So identifying buyer persona would help us in terms of defining and crafting our offerings in a more innovative way. 

    Identifying a persona can be challenging because you need a lot of data and assessment research, you need to speak to a lot of people, carry out the feedback mechanism, carry out the market research and so on. Generative AI can also be utilized for this process. 

    Speaking of a buyer persona, there are a few key points to be considered- Who is the buyer, what does he buy, where does he buy from, style of purchase, past history, hobbies and lifestyle. This requires thorough research. Product managers can keep on refining these buyer personas as well. 

    Hyper personalization is targeting the exact user base that helps you optimize your campaign life cycle. Product managers need to have details of what are the devices used and what are the search engines that the customer is targeting. Data collection is then ingested into the CRM system. E-commerce sites are used to ingest the data in data engines. What it gives in turns is we can cross-sell or upsell the same customer additional products or supplement products that the customer does not potentially realize we would be requiring.

    Competitive landscape with Generative AI

    Generative AI empowers product managers to stay ahead of the competitive landscape by providing insights into the strategies and innovations of rival companies. This can be segmented into 3 large categories- what the large tech companies are doing, what established technology platforms are doing, and what emerging startups are doing. 

    Large tech companies all have their established customer data platform and personalization platform. For example, when it comes to Adobe, they are very creatively utilizing Experience Cloud and also Photoshop to enhance customer experience. 

    In established tech platforms, salesforce’s Einstein AI powers Salesforce products for lead scoring and marketing campaigns. In emerging startups, persado live provides feedback on marketing copy as it is being written, for better engagement and conversations.

    What are some Generative AI tools that can be utilized for our overall go-to-market strategy?

    1. Taskade 

    There is a tool called Taskade that can give you a go-to-market plan. So market research, product positioning, pricing strategy, sales and distribution strategy, market and promotions strategy, and product launch strategy, all are aspects that you can add to your board. You can define further subtasks in it, assign it to your team, track your progress, set up calendars etc. You can ask further queries in terms of -creating a plan for designing and campaign, for social media marketing campaign. You don’t need to put everything by yourself. You can get a starting point, of course, you can refine it, and you can further work on it to enhance it by either prompt or manually. It also saves time. 

    2. Anyword

    It is a platform that creates text on the go and you can create it to manage your social media. It has other use cases as well. You can create product descriptions, and product titles, and create an appealing information page for Amazon Flipkart or any other e-commerce site. You can assess the click-through rate to the products or postings you have done through the tool. So that way it comes in very handy, you don’t need to write all those textual inputs by yourself. It gives you a very good starting point. It comes with features like content improvement, social media post writing, ad creations, landing pages, emails, product listings, or general writing. 

    3. Adobe Firefly

    In Adobe Firefly, you have to define what you are looking for. It will generate creative images. Based on responsive AI, it also has a tag or metadata attached to it that helps us control the usage or fair usage of the content. You cannot use somebody else’s pictures in the backend because it will still have those metadata tags.

    Hence, generative AI is a groundbreaking technology that can change the way product management works in the evolving market. It can help product managers in various ways, ranging from understanding customer personas, market analysis, market segmentation and analyzing the competitive landscape of their products. By strategically utilizing the power of generative AI, companies can make better product decisions and drive product success, shaping the future of product management in the coming future.

    Frequently Asked Questions

    Generative AI can help a product manager in understanding customer personas, market analysis, market segmentation and analyzing the competitive landscape of their products.

    Using generative AI in product innovation and development has many benefits like coming up with product solutions that are not possible with traditional methods. It can help in automating repetitive tasks and save a lot of time. It can also help product managers tailor their products to specific user preferences, which enhances the personalization aspect of the product.

    Generative AI can utilize customers’ browsing history, purchase history, and lifestyle preferences and make highly personalized recommendations, which significantly improve customer satisfaction and product sales.

    Taskade, Anyword and Adobe Firefly are some generative AI tools that can be used to improve go-to-market strategy.

    In Adobe firefly, product managers have to define what they are looking for. It will generate creative images. Based on responsive AI, it also has a tag or metadata attached to it that helps them control the usage or fair usage of the content.

    Persona development is an important aspect of product management that can be significantly utilized through the use of Generative AI. By analyzing vast datasets and customer feedback, AI models can create semi-fictional representations of target audience segments, outlining their characteristics, preferences, and pain points. This can help product managers in tailoring their products according to specific audiences and get better satisfaction from them.

    About the Author:

    Amit S – Assistant Vice President – Growth & Strategy, Accenture

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