Month: October 2022

AI in healthcare: What awaits the future of the industry?

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AI is known to perform tasks faster than humans while being more efficient. The application of AI in healthcare is growing into a phenomenon to look forward to as it is making waves across the healthcare industry.

The use of AI in healthcare can help ease the lives of doctors, patients, and healthcare providers alike. These are quality-of-life additions to the healthcare industry and are highly capable of predicting trends using analytics and data, leading to medical research and finding innovation. Combined with patient data and predictive algorithms, it is now possible to identify cancer in its nascent stages and heart attacks beforehand.

Robotics with AI isleveraged for surgery owing to their superior precision and can even perform actions best suited for the medical scenario.

On the administrative front, intelligent healthcare solutions bring a lot of structure and efficiency to day-to-day operations for healthcare companies.

The global AI in healthcare will see a CAGR of 37.1% from 2022-2023!

So, it’s evident that AI in healthcare is brimming with potential. Here are some of the benefits of AI in healthcare:

  • Efficiency in clinical research, diagnosis, and treatment
  • Precision in advanced surgeries
  • Optimizing costs for healthcare organizations
  • Streamlining processes and administration for healthcare companies
  • Improving patient-doctor and patient-healthcare provider experiences

Contrary to popular opinion, using AI in healthcare will not replace humans but will make their lives easier. It will facilitate an optimal team effort scenario, streamlining the process and obtaining maximum efficiency, which is favorable for healthcare providers and patients.

Centralize Patient Information and Streamline Operations with AI in Healthcare

The accelerated shift towards the online ecosystem on all fronts is now a reality. It’s not just eCommerce businesses; even healthcare companies require an online presence nowadays to capitalize on patients. Healthcare providers use advanced medical devices, and with the current norm of connected technology, there is an inflow of an immense amount of data.

The Bigger Challenge?

While some organizations have solutions to manage data and generate patient information, the challenge lies in bringing structure to the data.

Healthcare organizations are left with a plethora of unstructured data, sometimes from multiple sources. Even top healthcare companies lack the proper means and solutions to manage data ranging from patient information and medical transcripts to medical records. Efficiently streamlining data from various information sources is a significant challengeandcannot be performed with relational databases.

The Universal Customer Data Platform is Affine’s AI solution for healthcare providers that combines multiple data sources and pools the information, creating a universal data lake.

Healthcare providers can leverage insights from this and create a universal patient profile that can be accessed worldwide. They can also personalize their efforts for customer reach and engagement more efficiently, owing to the centralized data ecosystem.

Ai In Healthcare to Optimize Costs And Increase Revenue

Healthcare prices stem from various factors. The United States is notorious for its ridiculously high healthcare costs, which spells a significant setback in terms of revenues for healthcare providers. The USA spent a whopping $4,124 Billion on healthcare in 2020! Modern-day inflation has made everything high-priced and expensive healthcare is a deterrent to many patients who ideally should take regular tests and visit practitioners. In the long run, this is an unsustainable model for healthcare companies.

Healthcare providers can create packages and plans that patients can subscribe to, ensuring business while providing value to patients both service and cost-wise for a sustainable operating model in the long run.

The Intelligent Pricing Solution is another Affine solution for healthcare providers that creates a uniform pricing model for patients. This smart solution only recommends required tests and procedures thanks to the patient information, thus making it possible for the companies to offer great prices while providing quality healthcare service.This is vital in developing a sustainable patient relationship while improving engagement and helps increase the ROI in the long run.

Use Of AI In Healthcare Is Essential for A Sustainable Future

The above solutions are just a glimpse of what AI is capable of for healthcare providers. According to this report, ML in the healthcare industry is estimated to generate a global value of over $100 Billion. In the future, we are looking at AI-powered predictive healthcare, where anomalies in human health and chronic diseases are identified with historical patient information, and preventive measures can be taken in advance to save lives.

People are embracing travel post the pandemic, and organizations are encouraging a work-from-anywhere culture. Healthcare needs a connected tech approach, and providers must opt for centralized AI solutions that can provide patient information oncommand. Not only does this make for an efficient, but it also improves the patient experience.

For healthcare providers, AI and ML-based solutions help engage and motivate patients, improve their lives, assist them in their day-to-day activities, and handle the inflow of customers smoothly.

This may sound quite simple, but we all witnessed what happened when COVID-19 hit the USA, and the healthcare system got choked handling the sheer number of patients. Despite having one of the most advanced healthcare systems in the world, the country was brought to its knees during the pandemic. When I mentioned earlier that AI assists humans and does not take over their jobs, I couldn’t find a better example than the healthcare industry. Healthcare employees are among most overworked, burnt out, and underrated.

AI in healthcare can aid organizations, patients, and healthcare employees at capacity and their absolute limit, helping them bypass various tasks.

What does Affine bring to the table?

Affine is a pioneer and a veteran in the data analytics industry and has worked with giants like BSN Medical, Optum, AIG, New York Life, and many other marquee organizations. From game analytics and media and entertainment to travel and tourism, Affine has been instrumental in the success stories of many Fortune 500 global organizations; and is an expert in personalization science with its prowess in AI & ML.

Learn more about how Affine can revamp your healthcare business!

Decision Intelligence: The Next Big Milestone in Impactful AI

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As businesses take a global route to growth, two things happen. First, the complexity and unpredictability of business operations increase manifold. Second, organizations find themselves collecting more and more data – predicted to be up to 50% more by 2025. These trends have led businesses to look at Artificial Intelligence as a key contributor to business success.

Despite investing in AI, top managers sometimes struggle to achieve a key benefit – enabling them to make critical and far-sighted decisions that will help their businesses grow. In an era of uncertainty, traditional models cannot capture unpredictable factors. But, by applying machine learning algorithms to decision-making processes, Decision Intelligence helps create strong decision-making models that are applicable to a large variety of business processes and functions.

The limitation of traditional AI models in delivering accurate decision-making results is that they are designed to fit the data that the business already has. This bottom-up process leads to data scientists concentrating more on data-related problems rather than focusing on business outcomes. Little wonder then that, despite an average of $75 million being spent by Fortune 500 companies on AI initiatives, just 26% of them are actually put into regular use.

Decision Intelligence models work on a contrarian approach to traditional ones. They operate with business outcomes in mind – not the data available. Decision Intelligence combines ML, AI, and Natural Language queries to make outcomes more comprehensive and effective. By adopting an outcome-based approach, prescriptive and descriptive solutions can be built that derive the most value from AI. When the entire decision-making process is driven by these Decision Intelligence models, the commercial benefits are realized by every part of the organization.

Decision Intelligence Delivers Enterprise-Wide Benefits

Incorporating Decision Intelligence into your operations delivers benefits that are felt by every part of your business. These benefits include:

  1. Faster Decision-Making:
    Almost every decision has multiple stakeholders. By making all factors transparently available, all the concerned parties have access to all the available data and predicted outcomes, making decision-making quicker and more accurate.
  2. Data-Driven Decisions Eliminate Biases:
    Every human process data differently. When misread, these biases can impact decisions and lead to false assumptions. Using Decision Intelligence models, outcomes can be predicted based on all the data that a business has, eliminating the chance of human error.
  3. Solving Multiple Problems:
    Problems, as they say, never come in one. Similarly, decisions taken by one part of your operations have a cascading effect on other departments or markets. Decision Intelligence uses complex algorithms that highlight how decisions affect outcomes, giving you optimum choices that solve problems in a holistic, enterprise-wide way, keeping growth and objectives in mind.

Decision Intelligence: One Technology, Many Use Cases

Decision Intelligence tools are effective across a multitude of business applications and industry sectors. Here are some examples of how various industries are using Decision Intelligence to power their growth strategies:

  1. Optimizing Sales:
    Decision Intelligence can get the most out of your sales teams. By identifying data on prospects, markets, and potential risks, Decision Intelligence can help them focus on priority customers, predict sales trends, and enable them to forecast sales to a high degree of accuracy.
  2. Improving customer satisfaction:
    Decision Intelligence-based recommendation engines use context to make customer purchases easier. By linking their purchases with historical data, these models can intuitively offer customers more choices and encourage them to purchase more per visit, thus increasing their lifetime value.
  3. Making pricing decisions agile:
    Transaction-heavy industries need agility in pricing. Automated Decision Intelligence tools can predictively recognize trends and adjust pricing based on data thresholds to ensure that your business sells the most at the best price, maximizing its profitability.
  4. Identifying talent:
    HR teams can benefit from Decision Intelligence at the hiring and evaluation stages by correlating skills, abilities, and experience with performance benchmarks. This, in turn, helps them make informed decisions with a high degree of transparency, maximising employee satisfaction and productivity.
  5. Making retail management efficient:
    With multiple products, SKUs and regional peculiarities, retail operations are complex. Data Intelligence uses real-time information from stores to ensure that stocking and branding decisions can be made quickly and accurately.

Incorporating Decision Intelligence into the Solutions Architecture

CTOs and solutions architects need to keep four critical things in mind when incorporating a Decision Intelligence into their existing infrastructure:

  1. Focus on objectives:
    Forget the data available for a bit. Instead, finalize a business objective and stick to it. Visualize short sprints with end-user satisfaction in mind and see if the solution delivers the objective. This approach helps technical teams change their way of thinking to an objective-driven one.
  2. Visualize future integration:
    By focusing on objectives, solution architects need to keep the solution open to the possibility of new data sets arising in the future. By keeping the solution simple and ready to integrate new data as it comes in, your Data Intelligence platform becomes future-proof and ready to deliver answers to any new business opportunity or problem that may come along.
  3. Keep it agile:
    As a follow-up to the above point, the solution needs to have flexibility built in. As business needs change, the solution should be open enough to accommodate them. This needs flexible models with as few fixed rules as possible.
  4. Think global:
    Decision Intelligence doesn’t work in silos. Any effective Decision Intelligence model should factor in the ripple effect that a decision – macro or micro – has on your entire enterprise. By tracking dependencies, the solution should be able to learn and adapt to new circumstances arising anywhere where your business operates.

Machine learning and artificial intelligence are niche technologies, and companies have started thinking about or utilizing these technologies aggressively as part of their digital transformation journey. These advancements have changed the demand curve for data scientists, machine learning, and artificial intelligence technologists. Artificial intelligence-driven digital solutions require cross-collaboration between engineers, architects, and data scientists, and this is where a new framework, “AI for you, me, and everyone,” has been introduced.

To Sum Up

Decision Intelligence is a powerful means for modern businesses to take their Artificial Intelligence journey to the next level. When used judiciously, it helps you make accurate, future-proof decisions and maximize customer and employee satisfaction, letting you achieve your business objectives with the least margin of error.

E-Commerce, AI & the game of customer experience

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Exceptional customer experience through personalization is the elixir of online shopping. 95% of companies increased their ROI by 3X with personalization efforts. There is always the debate about privacy and handling of data, but the younger next-generation of shoppers are open to it, and the future is set to see data-backed hyper-personalization across multiple touch points in E-Commerce platforms, in my opinion.

The challenge for E-Commerce businesses with personalization is multifold. Customers seek a device-agnostic experience in online shopping, so a uniform shopping experience is a basic need. On top of that, there is a plethora of data inflow, which makes for great potential but only if it is leveraged aptly by E-Commerce businesses. With the prowess of AI, the possibilities are many and colorful for E-Commerce businesses.

There is an immediate need for a centralized solution, considering the omnichannel nature of shopping amongst online customers. With data inflow from various sources, the alternative is just a large amount of unstructured pile of data that does not provide value for the business.

This is where AI will rewrite the rules and set the foundation for a new type of unparalleled customer experience in E-Commerce.

Data & AI-2 sides of the personalization coin for E-Commerce

Personal opinion -I’m willing to share data for a no-nonsense experience on the internet. Eventually, with connected tech and synced accounts becoming a norm by the day, online shoppers will opt for the same, considering the benefits. In my opinion, we’re too co-dependent on the internet for our day-to-day activities and sharing data for a better shopping experience is a valid tradeoff.

3d product previews & virtual try-on are the tips of the iceberg of what AI has in store to revolutionize the customer experience and write the future for E-Commerce companies.

AI in movies is mostly dystopian, about rogue software taking over the world, but in the real world, there is a drastic contrast to the applications and potentials of AI in day-to-day use cases. AI isn’t anymore a niche tech reserved for a few organizations.The infusion of technology in E-Commerce has made life easier for people, and the data shows. Just take a look at the worldwide sales, the growth is unprecedented and projected to spike through the roof in the coming years.

So, naturally, as someone working in close quarters with AI experts and E-Commerce veterans, I couldn’t help but speculate about the future of the marriage between the two.

Next level personalization for exceptional user experience

I remember the good old days of AOL messenger, Yahoo-Mail & My-Space. The internet at its cusp was pure, and people just hung out and wondered at the marvel of this infant tech and its dynamic capability.

With great power comes great responsibilities, and the internet opened the gateway to access various types of data; this, paired with the eventual shift towards online shopping, would work wonders for businesses. This was inevitable as the monetization of the internet was bound to happen. When anything is free, you’re the product.

I’m spoiled by the Apple ecosystem and can’t get enough of the seamless interaction and experience when I use any device, be it my laptop, mobile, or iPad. Imagine this for E-Commerce businesses on a gigantic scale.

For E-commerce companies, AI technologies can vastly improve product selection and overall user experience, which becomes a crucial part of the customer lifecycle.

Big data offers a plethora of opportunities for E-commerce personalization. Segmenting and customizing the experience is made possible by analyzing historical data. Even the messaging is personalized to the core, ensuring the relevancy factor is preserved.

Affine’s AI-powered Hyper Personalized Marketing Experience is one such solution that leverages customer behavior data, segmentation data, and cohort analysis at scale

What do customers gain from this?

As an avid online shopper, I appreciate the personalized shopping experience on an E-Commerce platform. Getting to see the products with utmost relevance is a positive shopping experience rather than being spammed with random recommendations; at least, that has been my experience so far.

When E-Commerce businesses leverage data properly, it creates an exceptional shopping and customer experience and results in return customers. We all have our favorite shopping websites, and personalization has played a crucial role in them.

What do E-Commerce businesses gain from this?

First things first: – a centralized workhorse robust personalization ecosystem,minimal data leak, and making sense of every customer move and converting it into a quality-of-life add-on with personalization, targeting, and segmentation.

Such a sophisticated solution makes it possible to identify the most feasible customers and target them with hyper-personalized efforts. The data is the only limitation to the possibilities here. Not only does this net the best possible customers for the business, but it optimizes the marketing efforts making the whole targeting process efficient. Ad budgets are kept in check while ensuring superior ad display and performance.

I’ve spent fat budgets on marketing only to receive lukewarm prospects. I’ve also spent conservatively with proper data-powered personalized marketing initiatives that have resulted in excellent conversions. Centralized AI solutions provide complete accountability for marketing spend, helping E-Commerce businesses measure every dollar spent per lead.

Automation is seamless with AI

Contrary to popular opinion, AI is not about taking over human jobs; it is more about making our lives easier. Customer support is one of the most tasking efforts in the E-Commerce business. I’ve had my fair share of endless calls with customer support with language and technical issues. I know you’ve all been a part of at least one such instance in your lifetime.

The potential for customer support automation via chatbots is a fast-tracking of the entire process and is already seen with giants like Amazon.

E-Commerce businesses, small or large, can leverage AI to automate mundane tasks and basically run your online store to an extent without human intervention and take care of the overall processes in their day-to-day activities.

Be it automating marketing efforts, support, customer engagement, or advertising, AI has the clout to not only handle but also excel in outperforming manual labor while casually being time and cost-efficient in the process. Automating the marketing process also brings up a 451% increase in qualified leads.

Combat fraud activities with AI’s security prowess

We’ve all known of someone who has fallen prey to online fraud and I know I do. With the convenience of seamless transactions, there is also the vulnerability of fraud in E-Commerce transactions. A research shows that online payment fraud could lead to a global merchant loss of up to $343 billion from 2023 to 2027.

Despite security measures, these instances call for drastic innovations in verification tools and authentication processes. AI and ML algorithms are the only effective option to combat online threats at such a higher scale in the count of millions of transactions, with predictive analytics to detect behavioral patterns and suspect behavior resulting in fraudulent transactions.

Brand loyalty, repeat business, and ROI

A gazillion data points are analyzed so that customers can get the best shopping experience and keep coming back for more. Sure, but E-Commerce businesses have the most to leverage from intelligent AI algorithms running through a plethora of data points. As I mentioned earlier, the possibilities are immense and lucrative.

I have my go-to sites for shopping, and I have valid reasons for that. So do customers, hence the need for AI in E-Commerce platforms. Personalization may make it sound like the customer is reaping all the benefits, but that’s the intention.

80 % of users saw an increase in lead generation, whereas 77% saw increased conversions when using automation.

The spend more get more is outdated, and efficiency is the need of the hour. Inefficient business operations cause a major dent in business revenues

Conclusion

The era of big data is here. Digital dominance is set to take over the world, and E-Commerce sites are more or less the new convenience stores in the digital age. I see a lot of competition; I see a lot of potential.

75% of businesses already use AI and are on the right track in the long run. Having run a startup myself, I understand the qualms about the cost of implementing AI. But the big picture justifies it and how.

AI in E-Commerce is not even a novelty anymore; it is a must-have. An online E-Commerce is a global marketplace, and the standards are already set. It’s excel or be expelled. A proper flow to guide your customers through their buying experience is the basic requirement to sustain and perform in the long run.

What does Affine bring to the table?

Affine is a pioneer and a veteran in the data analytics industry and has worked with giants like Warner Bros Theatricals, Zee 5, Disney Studios, Sony, Epic, and many other marquee organizations. From game analytics and media and entertainment to travel & tourism, Affine has been instrumental in the success stories of many Fortune 500 global organizations; and is an expert in personalization science with its prowess in AI & ML.

Learn more about how Affine can revamp your E-Commerce business!

Manas Agrawal

CEO & Co-Founder

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