The Business of Voice search And Its Potential Commercial Applications

Voice search is basically a feature in smart devices that enables users to perform internet searches through a voice command. Being a dialog system, it can be accessed by activating the feature and speaking into the microphone. The device picks up the voice and searches the internet for whatever the user demands. In the simplest of examples, a person driving a car who can not use a device because of being on the road presses a single button and speaks for whatever is required.

Why does voice search matter?

Humans have been seeking comfort since the advent of time. Moving from caves and jungles to skyscrapers and highly civilized societies, a lot of comforts has been achieved through the centuries. Communication developed over time and an era of smart devices was entered into.

Laptops, tablets, desktop computers, and smartphones began to be considered essential to existence. They bridge the physical gap of thousands of miles with the click of a button. Features in these devices provided further ease and convenience to users by integrating new technologies into them. One such technology is voice search.

How does voice search work?

The device is configured in such a way that it first recognizes the language the user is speaking and then picks the keywords which the user speaks. After that, an internet search is initiated by the device and the results are obtained. In case a screen is available, the device displays the results. It can also be configured to speak out the results to the user. If a screen is not available, the results are simply read out to the user like in the previous scenario. 

To make sense of what the user is trying to say, the device must be equipped with a language understanding capability. The basic English language is found in a majority of the devices given it is an international standard. However, many devices are also able to recognize different languages and perform searches accordingly.

Due to the wide range of where these devices are operated, the language issue is something that will be completely eliminated in the future. Smart devices having voice technology add to the convenience of the users and enhances the user experience.

More and more devices are being integrated with this technology and their use is also becoming widespread. As customers shift towards this trend, it indicates a change in the strategies that businesses need to employ in order to remain on track. 

The evolution of search

Businesses have online websites where they present their products and services. Due to the shift towards online modes of shopping or even obtaining information, a large number of websites have surfaced all over the internet. To remain relevant and make sure the website pops up when the users search using particular keywords, websites use metrics to ensure they are among the top results.

This is done through a process known as Search Engine Optimization (SEO). Search engines rank websites according to a predetermined ranking system. This is achieved through an algorithm that uses a lot of metrics in assessing which websites should be displayed first to enhance user experience. Unlike paid ads, search engines cannot be paid to get higher rankings. The only option for businesses is to design their websites in such a way that they remain relevant and are able to compete with other websites after a user search is initiated.

According to Google officials, twenty percent of the total searches on Google are now initiated through voice search. Among youngsters, the percentage is even larger. For better optimization, businesses have strategies in place. However, with the increasing use of voice search, the metrics need to change or be updated. When a user types, it is mostly keywords, which initiate the search being conducted by the search engine.

The search engine finds the most relevant websites and ranks them for the user to choose from. This is no different from what happens when a user generates a voice search. The search engine follows the same pattern of picking what the user said and search the internet for possible results.

The only thing different now is the fact that typing is different from speaking. While the user might type keywords, due to the interactive nature of voice search assistants like Siri and Alexa, the search is conversational. For example, while typing a person might search “nearby restaurants”. These two keywords will guide what the search engine displays. In the case of voice search, the person might ask “which restaurants are offering dinner right now?” The difference in the number of words used or how the sentence is structured might produce different results from what was displayed through the search performed by typing.

The future of voice search

Due to this shift in the way users now search and interact with their devices, search engine algorithms might display different kinds of results. The built-in strategies that businesses have employed currently to stand out might now need a shift of focus since those were text-based and now there is an increasing shift towards voice-based searching. To successfully maintain or achieve higher rankings by the algorithms, businesses now need to develop new strategies.

These strategies should not only have the capability of dealing with the existing search methods since the majority of searches are still typing based. Besides, businesses need to utilize the market that exists due to the use of voice searches when users interact with their devices. With further development and enhancement of technology in smart devices to be able to make sense of different languages, more and more traffic will move towards voice-based searching.

According to estimates given by Google, around 71% of the population between eighteen and twenty-nine years use voice search. Statistics indicate a far bigger percentage of overall searches to be voice-based. Businesses need to revise their strategies and ensure that both markets are tapped in properly for profit maximization and business sustainability. The future is changing and giving room for creativity, which should be prioritized by businesses, which want to remain relevant.

Key Takeaways

  • Voice search enables users to perform internet searches using voice commands on smart devices, making it more convenient for users, such as drivers who need hands-free access.
  • With the advancement of technology, voice search has become an essential feature in smart devices, offering users greater ease and convenience in communication and information retrieval.
  • Smart devices recognize the language spoken by the user, extract keywords from the voice command, perform an internet search, and display or read out the results.
  • Businesses use Search Engine Optimization (SEO) to rank higher in search engine results based on certain metrics. As voice search becomes more prevalent, SEO strategies need to adapt to conversational queries.
  • Around 20% of Google searches are initiated through voice, and this percentage is even higher among younger users. As voice search becomes more popular and smart devices improve language understanding, voice-based searching is expected to increase.
  • Voice-based searches may produce different results than typed searches due to the conversational nature of voice commands. Businesses need to develop new strategies to maintain or improve their rankings in search engine algorithms.
  • Businesses must adapt their SEO strategies to cater to both text-based and voice-based searching to tap into the increasing market of voice search users and stay relevant in the future.
  • Voice search is on the rise, with a significant percentage of young users utilizing it regularly. Businesses need to prioritize creativity and adaptation to leverage the opportunities presented by voice-based searching for sustained success.

Connected Business Frameworks And Analyses

AI Paradigm




Large Language Models

Large language models (LLMs) are AI tools that can read, summarize, and translate text. This enables them to predict words and craft sentences that reflect how humans write and speak.

Generative Models


Prompt Engineering

Prompt engineering is a natural language processing (NLP) concept that involves discovering inputs that yield desirable or useful results. Like most processes, the quality of the inputs determines the quality of the outputs in prompt engineering. Designing effective prompts increases the likelihood that the model will return a response that is both favorable and contextual. Developed by OpenAI, the CLIP (Contrastive Language-Image Pre-training) model is an example of a model that utilizes prompts to classify images and captions from over 400 million image-caption pairs.


AIOps is the application of artificial intelligence to IT operations. It has become particularly useful for modern IT management in hybridized, distributed, and dynamic environments. AIOps has become a key operational component of modern digital-based organizations, built around software and algorithms.

Machine Learning

Machine Learning Ops (MLOps) describes a suite of best practices that successfully help a business run artificial intelligence. It consists of the skills, workflows, and processes to create, run, and maintain machine learning models to help various operational processes within organizations.

Continuous Intelligence

The business intelligence models have transitioned to continuous intelligence, where dynamic technology infrastructure is coupled with continuous deployment and delivery to provide continuous intelligence. In short, the software offered in the cloud will integrate with the company’s data, leveraging on AI/ML to provide answers in real-time to current issues the organization might be experiencing.

Continuous Innovation

That is a process that requires a continuous feedback loop to develop a valuable product and build a viable business model. Continuous innovation is a mindset where products and services are designed and delivered to tune them around the customers’ problems and not the technical solution of its founders.

Technological Modeling

Technological modeling is a discipline to provide the basis for companies to sustain innovation, thus developing incremental products. While also looking at breakthrough innovative products that can pave the way for long-term success. In a sort of Barbell Strategy, technological modeling suggests having a two-sided approach, on the one hand, to keep sustaining continuous innovation as a core part of the business model. On the other hand, it places bets on future developments that have the potential to break through and take a leap forward.

Business Engineering


Tech Business Model Template

A tech business model is made of four main components: value model (value propositions, missionvision), technological model (R&D management), distribution model (sales and marketing organizational structure), and financial model (revenue modeling, cost structure, profitability and cash generation/management). Those elements coming together can serve as the basis to build a solid tech business model.

OpenAI Business Model

OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.


OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).

Stability AI Business Model

Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.

Stability AI Ecosystem


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