Artificial intelligence and analytics holds much potential for companies to utilize in order to grow, yet both terms tend to throw some people off. Even in 2020, people misunderstand the capabilities of AI and fear the common misconception that robots are coming to take their jobs.
We’ve previously discussed how agility is necessary for the entrepreneurial journey, as well as the fact that the entrepreneur approach can help companies increase digital business. Now, we’d like to examine how entrepreneurial-minded businesses can scale operations and increase ROI by paying close attention to analytics and the many ways AI can be leveraged in daily business operations.
Every business shares the same ideal – transforming ideas into operational business propositions. Yet, these ideas cannot be based on mere conjecture. Influential data insights coupled with presumption allow for businesses to approach their goals more accurately. Indeed, companies that have incorporated data-based insights into their operational functioning and processes tend to report more success than companies that do not. To inspire measurable results and redefine decision-making, you can create an information-driven business strategy that is paired with tangible objectives. Objectives coupled with beneficial data delivers valuable information regarding the competitor’s position, consumer patterns and future prospects.
Further, entrepreneurs need access to data sets in order to train machine learning algorithms. Companies can cut costs by thinking like an entrepreneur and starting with publically available data sets, though these are limited in scope. Getting a hold of data can inspire collaborative thinking within organizations, with entrepreneurially-minded employees working together to get a hold of data sets quickly, providing solutions faster than in prior decades.
Here are the following ways data analytics can enhance your entrepreneurial approach:
Aacording to an article published on Entrepreneur, data analytics demand has increased by 4X and data visualization by as much as 25X. Both business intelligence and data analytics allow entrepreneurial-minded employees to use patterns related to customers. When analyzed, these unique patterns linked to separate customer segments allow the analyst the opportunity to pinpoint cross-selling and up-selling business opportunities.
Reviewing brand sentiment is necessary when selling services and products to customers spread across different business verticals. Business intelligence and data analytics allow understanding of the customers’ preference for a specific service or product. Gaining an understanding of these factors behind customer experience allows analysts to improve the customer experience while also exploiting opportunities for cross-sell and up-sell.
Data analytics allows you to get a view of customers’ purchase history and an insight into what they are not buying. When combined with user surveys, the focus point required to sell the right product can be deduced. Data analytics further can help analysts get to the bottom of the why behind customer behavior, answering questions like “Which promotions are performing the best and which promotions are converting? What parameters improve the performance of marketing efforts and how can they be improved for future opportunities? What are the obstructions faced by customers at different touch-points and how can these obstacles be removed? What factors are stopping customers from making purchases – price, complexity of the website or the marketing copy?
Don’t go into your industry blind. Knowing the business propositions, performance, and patterns of other entrepreneurs, competitors, and industry leaders assist in increasing business intelligence. This, in turn, allows for the setting of accurate objectives and pathways to reach said objectives. In addition, brainstorming sessions can be enhanced by data-based information, allowing for improvements to be made to the product or service.
Don’t gamble with the business strategy. Data analytics allow for the analysis of the key influences of customer impact, business, and market verticals. Using this information, it is possible to accomplish data-based future predictions and decisions, allowing your business to be future-ready.
Advanced data analytics and business intelligence allow the user to gather crucial information and automate the processing of data-sets. Pinning down data insights, achieving correlations and industry trends enable business success and understanding the business through every vertical allows for faster decisions to be made in a shorter turnaround time. Ultimately, improve the decision-making process and reduce latency by utilizing these valuable insights.
As more advanced AI systems are developed, there will always be more of a need for more safeguards, advanced training and controls. While developing safety, validation and verification of AI systems pose a challenge to organizations, they also present significant opportunities. This is due to the fact that AI systems are currently transitioning into the real world, controlling technologies that have ever-more consequential bearing on human lives, such as the case of autonomous vehicles. While making a mistake with a chatbot might be inconsequential, making a mistake with a driverless vehicle can have a more significant bearing on human lives. These types of systems of checks and balances will become more important as AI increasingly enters into the physical realm of human life.
While AI clearly offers a lot in terms of the work it can accomplish, allowing entrepreneurially-minded individuals the opportunity to become more creative, there are still businesses that are hesitant to adopt it. It seems that much of this hesitation is due to the fact that people don’t understand how they should be thinking about AI. Further, they don’t understand just how AI will impact their work or life in general, overlooking instances of “narrow AI” like weather forecasts and Google Translate.
While AI has “intelligence” in the name, the technology is still on its way to holding meaningful conversations or making complex choices. Instead, the focus should be on the immediate and mundane task of making AI function in real-world settings.
Further, AI can be challenging to implement into the workplace. To properly incorporate AI, what is needed is a more innovative, entrepreneurial and agile workplace in order to survive the technological revolution. Here, first-generation AI tools and applications can play a vital role by handling repetitive work, freeing up employees’ time to become more creative and entrepreneurial.
Bigger companies are more and more motivated nowadays to utilize AI to automate repetitive tasks, as they are encouraged by cost, productivity, and efficiency gains, as well as the increasing pressure of regulatory compliance. To remain competitive and relevant, companies need to engage in AI research, implement AI tools and applications, and introduce AI-based services and products. In order to make a mark in a hyper-competitive global market, companies are becoming more and more involved in AI as investors or acquirers.
AI can provide the impetus for employees to think more like entrepreneurs. There are many industries and occupations poised for immediate disruption by AI – those with tasks that machines can easily be trained to do. This includes industries like healthcare, security, finance, and transportation, with AI automating tasks like scheduling an appointment or ordering a delivery through natural language processing, surgical robotic assisting physicians and even autonomous vehicles.
From employee management systems and interactive search assistants to complex ambient intelligence and self-learning user segmentation tools, AI remains almost limitless in its potential. While AI has the ability to automate certain repetitive tools, it also has the ability to improve the effectiveness of business strategies.
How can entrepreneurially-minded business leverage AI strategies? Try the following:
Thanks to the latest AI integrations, search engines have become just as responsive in understanding user queries as pinpointing publisher’s intent when they upload content. Publishers are now tasked with generating higher quality content since rankings depend on how well content addresses its intent to the target audience. In turn, deep learning algorithms grade relevancy, reader-friendliness, and authenticity before displaying content, serving searcher intent more accurately. AI integrated search engines respond to user intent signals more confidently against predefined algorithms, with their machine learning capabilities allowing them to gather information and predict, influence, and anticipate trends in content consumption.
Improve engagement, extend retention, boost sales and customize user experience through personalization. One of these techniques you’ve likely heard of – SEO (search engine optimization). And we’re not just talking traffic. AI integration helps enhance its application on everyday online searches simply by personalizing online searchers’ experiences when interacting with the brand. AI in SEO can also efficiently respond to a brand’s KPIs (key performance indicators), while building a strong digital footprint in the market. Here, data also plays a part, with data building persona-based intelligence and harnessing the power of user individuality, designing the most fitting solutions for these personas’ preferences. SEO also has the advantage of costing a lot less for longer-lasting impact against traditionally high-dollar practices.
In the world of marketing, AI plays an imperative role in the advertiser-customer relationship by facilitating interaction through deep learning. It functions by capturing essential patterns and filtering out the most predominant characteristics, which can then segment your audience. For instance, when a customer from a specific segment interacts through a landing page, the chatbot will analyze the data to generate a response according to the user’s preferences, thus grading the quality of the lead. While AI holds much potential for business strategies overall, the worlds of sales and marketing have much to gain from AI implementation.
It is not enough to simply automate your processes. Today’s technology allows you to combine AI and data integration to take the next step forward, resulting in intelligent automation or the integration of AI, data, and automation. Not only does it improve efficiency for your routine, it can also revolutionize your business operations.
To stay competitive, you must be a step ahead of competitors both in customer satisfaction and in cost savings. In this sense, technological innovation needs to be intrinsic to your management process and not just present in specific and isolated areas. This is why Stefanini’s integrated approach, as well as our support for the entire process for intelligent automation, makes us your ideal Industrial Technology provider.
See more related content
Combining AI and Analytics hold much potential for your business. Ask our experts how.
Hi. Need help?