How Decision Science Boosts Artificial Intelligence: A Brief Analysis
In this modern world, computers are being leveraged to systematically detect data signals and patterns that can drive higher business revenues and better outcomes. This has led to a confluence of machine learning, predictive analysis, algorithms and artificial intelligence that can assist global leaders in coming up with business solutions that have been traditionally driven by human experience, intuition and intelligence.
This Confluence is known as Decision Science
It is a toolbox of quantitative techniques and approaches that go into conveying the ability of decision-making to the masses. At its very basic, the concept covers everything that can provide analytical solutions to complex problems. It encompasses a consistent and rational economic framework that comes with an objective system to make the most of each outcome by considering every risk and reward.
To put it in plain language, Decision Science simplifies the way decision-making should be carried out; in fact, it makes the process better. It allows us to take into account large quantities of complex data, identify and calculate all risks, dismiss all biases and pitfalls driven by emotions, and in the process, save time.
Decision Science and Artificial Intelligence
Decision Science has the potential to boost the power of Artificial Intelligence to the utmost. Especially, when it comes to ensuring the benefits and safety aspects of developing Artificial Intelligence for long-term use, it can play a crucial role in bearing the challenges and serving as the nexus between data science and cognitive science.
AI can go a step ahead of targeting the right consumers and predict their potential behaviour as well. However, with Decision Science, the critical aspects of such behaviours can be studied and the insights taken to figure out strategies to use them for business benefits. When it comes to making decisions online, AI shows us the best routes and Decision Science the right direction.
Enabling Personalised Experiences
Today, Artificial Intelligence is extensively used by businesses (to recommend products and services to their potential consumers. People on social media are now being ‘shown’ which product to buy based on their unthinking search habits and preferences. And then, they are ‘told’ what others bought along with those products. In short, the way we use the Internet is getting personalised.
This has gone beyond the eCommerce space and penetrated other industries such as healthcare and information technology as well. Thanks to Decision Science in AI, technology can now take in data from varied sources, analyse and interpret it to provide insights and throw light on the best decisions.
For instance, finding the best course of treatment for cancer is now easy. With more and more data being harnessed, the suggestions complement the exact need of the patient and thus, are worthwhile. Similar is the case in an HR department that looks forward to hiring the right talent, or in real estate, where realtors hope to generate leads and seal more deals.
Triggering Lead Generation
It is one thing to make suggestions according to consumer preferences and another thing to persuade them to accept the suggestions. This is also where Decision Science aids AI. It removes the barriers that keep potential consumers from converting and activates the right triggers to entice them. In other words, AI answers the ‘what’ in a consumer’s mind and Decision Science takes care of the ‘why.’
This is done with the help of ‘Behavioural Economics,’ which carries out economic analysis using psychological nuances of human behaviour to make sense of economic decision-making. Here, everyday irrational choices and unconscious search patterns are taken into account. Why? — Because these seemingly irrelevant choices deeply go into defining consumer behaviour in the long run.
The use of Behavioural Economics is well very pronounced in the area of eCommerce where potential buyers face two major barriers on their way to a purchase — ‘overchoice’ and ‘fear of regret.’
The first one is a cognitive phenomenon in which potential buyers find it difficult to make a decision because they are left spoilt for choice. Also, even if they make a decision, the outcome isn’t very positive. Also known as ‘choice overload,’ this happens due to too many choices presented to the buyers leaving them paralysed. The second one — fear of regret — happens when buyers feel dissuaded because they think they’d make a wrong choice.
Decision Science mixed with AI comes as a sign of relief. It helps in reducing the choices to a special few that align with buyer requirements to perfection, and bring in third-party approvals and social proof to help potential buyers decide right. This works in two ways — by sealing quick deals and increasing the basket size as well!
Minimising the Impact of Status Quo Bias
Change is the only thing constant, which makes it scarier. Most people dislike change and prefer things to remain the way they are. Such people perceive any change as a loss. This is known as status quo bias which directly affects decision-making and causes buyers to miss out on beneficial purchases. However, Decision Science used in combination with AI can help overcome this sticky situation along with fear of regret.
For instance, if specific choices are accompanied by another set of choices that support the former, it becomes easier for consumers to make a decision. Let’s say you are looking for glasses that would suit the shape of your face. If, along with a list of choices, you are also provided with an option to virtually try the glasses in 3D, it could help you decide quicker. Similarly, prompts like ‘try before you buy’ or ‘money back guarantee,’ too, can work like magic.
In Conclusion…
Decision Science and Artificial Intelligence when used together make a powerful tool for branding businesses and boosting sales. In fact, Decision Science is the key to effective AI that brings real success to the table. From personalised search to seamless purchases, the duo can create a clear path to hassle-free consumer experiences across varied industry verticals.
