What do entrepreneurs running startups desire from AI/ML advanced marketing campaigns?

As an AI engineer, I’m interested in finding underdeveloped spheres of digital marketing where AI can have a big influence and making it available to the general public. I’m opposed to only a small number of organisations having access to this technology.

What do you have in mind that has not yet been created? What do you want to see created? Which current AI/ML-based services do you think could use tweaks or improvements?

I am proficient in a variety of machine learning algorithms, including supervised learning methods (such as linear regression and support vector machines), unsupervised learning methods (such as dimensionality reduction and clustering algorithms), and reinforcement learning methods (such as Q-Learning and Deep Q-Networks).

  1. What issue are you trying to solve?

  2. Why is this a problem, exactly?

  3. What is your solution, ?

  4. Has anyone else attempted to solve this issue?

  5. If you can solve this issue, who will give you money?

These are some of the significant queries that come to mind at the moment. As you can see, none of these have anything to do with “how” you want to proceed.

But you simply discussed how you would carry out those. I have to admit that this seems more like “you have a hammer, you see everything as a nail.” like that.

Before incorporating your own startup, you need to start asking the correct questions. Additionally, I would strongly advise working with a startup before striking out on your own.


Just to answer for the hell of it though (Im not actually selling these technologies, hence my comment below)

What issue are you trying to solve?

Companies that need advanced digital marketing campaigns at scale with complex & efficient ways to get new customers but potentially dystopian methods to increase sales & engagement.

Why is this a problem, exactly?

Companies need marketing…

What is your solution?

Complex innovative AI/ML solutions for advanced digital marketing campaigns that leverage technology and complex algorithms to increase sales and engagement, customer retention and grabbing new customers in ways that blow traditional marketing out of the water & dont rely on humans.

Has anyone else attempted to solve this issue?

Yes. As I said to the other redditor, ‘apple music, spotify, soundcloud, youtube music, pandora, deezer, etc. All music apps doing the same bullshit, and they’re still all giant companies.’ ‘multiple companies doing the same thing confirms there’s market validation for you, just come in with a specific niche & dominate it. The market cap for the AI industry is too large to even consider them as a competitor. I hope you don’t proceed with great ideas you may have then abandon them because you see other companies doing it, that’s not the way to go.’

If you can solve this issue, who will give you money?


These are some of the significant queries that come to mind at the moment. As you can see, none of these have anything to do with “how” you want to proceed.

I’m not coming at you when I say this, but with all respect I think you dont understand the terminologies I was using to describe those ideas. Ex: ‘to examine users’ social media engagement, interests, and digital behavior, generating comprehensive psychographic profiles for more accurate ad targeting and personalized content suggestions.’ That does explain how it would ado it.

But you simply discussed how you would carry out those. I have to admit that this seems more like “you have a hammer, you see everything as a nail.” like that.

I know, as I stated I was not creating a startup… I wanted this community thoughts on what they think should be created, I just listed ideas as inspiration.

Before incorporating your own startup, you need to start asking the correct questions. Additionally, I would strongly advise working with a startup before striking out on your own.

I worked at multiple startups, and I worked at Scale AI & Braze, but again I’m not creating a startup or selling anything.


Identifying underdeveloped areas in digital marketing where AI can make a significant impact and democratizing its accessibility aligns with the goal of empowering small businesses and startups. Here are a few areas where AI can potentially make a difference:

  1. Personalization at scale: Many businesses struggle to deliver personalized marketing campaigns to their customers due to resource constraints. AI can help automate and optimize the process of tailoring marketing messages, offers, and recommendations to individual customers, enabling startups to engage with their audiences more effectively.
  2. Content generation and curation: Creating compelling content consistently can be a challenge for startups. AI-powered systems can assist in generating content ideas, writing blog posts, and even automating video creation. AI can also aid in curating relevant content from various sources to share with target audiences.
  3. Customer sentiment analysis: Understanding customer sentiment and feedback is crucial for startups to improve their products and services. AI-based sentiment analysis techniques can analyze customer reviews, social media posts, and other sources of feedback to provide actionable insights and identify areas of improvement.
  4. Customer segmentation and targeting: AI algorithms can help identify distinct customer segments based on various parameters, such as demographics, behavior, or preferences. Startups can leverage these insights to tailor their marketing strategies for different customer groups, thereby optimizing their campaign effectiveness.
  5. Social media monitoring and engagement: AI-powered tools can assist in monitoring social media platforms, identifying relevant conversations, and engaging with customers in a timely manner. These tools can help startups manage their online presence, address customer queries, and build brand loyalty.
  6. Optimizing advertising campaigns: AI can enhance the effectiveness of advertising campaigns by automating ad placement, optimizing bidding strategies, and identifying the most relevant target audience segments. This can help startups maximize their return on advertising spend and reach their marketing objectives efficiently.

Existing AI/ML-based services, such as chatbots, recommendation systems, and predictive analytics, can benefit from continuous improvements and refinements to enhance their accuracy, performance, and adaptability to various industries and use cases.

Remember to also consider ethical considerations, such as data privacy, transparency, and fairness when developing AI-based marketing solutions. Ensuring that the technology benefits a wide range of businesses and is accessible to all can contribute to a more inclusive and equitable digital marketing landscape.


My point might apply to writing papers or anything else; it was not specifically about startups.

I disagree that just a few companies have access to these technology. Facebook has made its “segment anything” function available. They created and published detectron2 and continue to offer more and more content. They all had access to LLaMa, which lets them all design their own llm models. Google developed Facebook’s Pytorch and TensorFlow. As a result, we can now create deep learning models in a matter of hours.

So many businesses share some of their work so that others can do their tasks more quickly.

The most, if not all, ML/AI publications are open access.


You must keep in mind that there is currently a ton of noise.

Someone trying to force another AI tool down my neck is of very little interest to me because I already don’t want any of it.

I believe that AI should be used as a value delivery layer rather than as the primary source of value. For example, if you use AI to give business insights via a chatbot, I want you to go beyond simply using the same data APIs that everyone else does.


@KaranTrivedi, Once again, the purpose of this discussion was to solicit user suggestions and ideas. You obviously missed that.


@DhirajMehta, Again, there isn’t much out there that this kind of investigation can find that hasn’t already been obsessively explored.

The recent advances have improved its quality and made it simpler for those without actual ML skills to integrate it into anything that makes sense for AI to assist with.

There won’t be anything that is both a brilliant idea and unsaturated that is simple to discover, find, or solve, therefore you need to be interviewing individuals who use the products to understand their workflows and shortcomings.


@KaranTrivedi, You make a valid point, and I value your opinion.


Sorry, what I intended to say with my last statement was that asking people for suggestions won’t give you anything to solve; instead, understanding workflows and weaknesses is where YOU might be able to discover areas where AI can aid in a way that people aren’t yet aware of, and that is where you can find something worthwhile to pursue.


My design agency engages in social media marketing. Due to the large number of clients, it is difficult. An AI-powered social media scheduler that lets you establish clients, learn about their backgrounds, objectives, and activities, and prepare posts for scheduling with relevant trending hashtags is something I’d want to have. The optimum time to post should also be considered (most do so at that moment).

The reverse engineering of competing brands in the market that are performing better by this AI, together with the presentation of reports and advice on how to increase the client’s reach and interactions, would also be wonderful.

Reach out to me if you have any ideas of such nature, and I’ll be happy to help.

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I understand your perspective, and I agree that simply using AI as a delivery layer without providing unique value is not sufficient. To truly harness the power of AI in digital marketing, it’s important to focus on creating innovative and valuable solutions. Here are a few approaches that can help in this regard:

  1. Domain-specific AI models: Instead of relying solely on generic AI models and data APIs, developing domain-specific AI models can provide more tailored and valuable insights. By training AI models on industry-specific or business-specific datasets, you can generate more accurate and relevant predictions or recommendations.
  2. Unstructured data analysis: AI can be particularly useful in extracting insights from unstructured data sources, such as social media posts, customer reviews, or multimedia content. By leveraging natural language processing (NLP), computer vision, and audio analysis techniques, you can gain deeper insights from diverse data types and provide unique value to your users.
  3. Predictive analytics: AI algorithms can go beyond descriptive analytics and enable predictive capabilities. By analyzing historical data and patterns, AI models can provide forecasts and recommendations for future marketing strategies. Predictive analytics can help startups optimize their marketing campaigns, anticipate customer behavior, and make data-driven decisions.
  4. Automated decision-making: AI can assist in automating decision-making processes, such as bid optimization in advertising campaigns or personalized content recommendations. By integrating AI algorithms into marketing platforms, startups can streamline operations, increase efficiency, and deliver real-time, personalized experiences to their customers.
  5. Interpretability and explainability: As AI algorithms become more complex, ensuring interpretability and explainability becomes crucial. Providing transparent explanations of how AI models arrived at their predictions or recommendations can build trust with users and help them understand the value being delivered.
  6. Ethical considerations: Consider incorporating ethical considerations into your AI-based marketing solutions. This includes ensuring data privacy, avoiding algorithmic biases, and promoting fairness and inclusivity in your models. Demonstrating a commitment to ethical practices can differentiate your offerings and add value to businesses seeking responsible AI solutions.

By focusing on these aspects and striving to create unique value beyond the standard AI applications, you can differentiate yourself in the market and provide more meaningful solutions for startups and businesses in the digital marketing space.