Conversational AI is boosting performance in the healthcare value chain

We’ve all become used to interacting with the conversational AI (CAI) capabilities built into our phones, tablets, and laptops.

This voice-enabled technology has become part of our everyday lives as it answers our questions, controls IoT devices, makes purchases or, just by asking, serves us the content we want.

It’s unsurprising, therefore, to find that CAI is also revolutionizing the commercial world. A recent study by McKinsey found that 56% of businesses use AI in at least one of their operational areas.

Many firms first saw the benefits that enterprise-level CAI tech could bring as they learned to cope with the impacts of the Covid pandemic.

For example, when lockdowns necessitated working from home, remote access to cloud-based company info helped keep the commercial world afloat. Now home workers can make a full contribution by using a digital assistant to access formatted data from their company’s legacy systems over secured broadband or mobile networks.

Perhaps this is why the value of CAI is becoming increasingly apparent to the healthcare sector, which now recognizes the potential of this tech as an enabler throughout their value chains.

By deploying enterprise-level CAI technology for use in sales, research, regulation and administration, healthcare firms will see a marked increase in accuracy, productivity and profitability.

End To End Process Improvements

Our recent blog outlined the critical differences between chatbots and CAI digital assistants. The following examples demonstrate just a few ways in which a true AI solution brings tangible performance uplifts in healthcare.

Speeding up essential administration. Healthcare sales reps, for example, are required to add data to CRM databases to support their sales activity. This work soaks up valuable time, which reps could use to make extra sales or find new prospects. Voice-enabled CAI can auto-fill pre-defined templates, and using dictation; sales staff can populate free form sections, thereby speeding up necessary but low-value admin.

Simplifying Online as well as Offline research processes

CAI tech is adept at speeding up and simplifying research processes. Healthcare firms habitually rely on research data to produce their products and services. This process necessitates the ongoing review of complex clinical, technical or academic papers. CAIs can undertake offline assessments of downloaded PDFs and other document types, condensing and compiling the content into the format requested by the user.

Firms can deploy CAI applications to undertake ‘social listening’. By integrating this tech with social media channels, areas such as patient comments, brand mentions, reporting adverse events, and competitor moves can be monitored.

Allied to the above, CAIs can perform online content reviews from platforms like PubMeds. This information will usually be lengthy, highly technical, and take a long time to review. Instead, users can ask a digital assistant to extract the main information points from these sources and present them concisely and accurately. This allows for greater comprehension of the content and enables follow-up work to start expediently.

Reporting is made easy

The APIs of a CAI digital assistant is most usefully integrated into all a firm’s legacy data sources. When reporting data is required from several datasets, a CAI will efficiently gather information from each location in a single request. As a result, the time to compile a sales, financial, or marketing report is significantly reduced. In addition, the output can be refreshed by the CAI on an ongoing basis for subsequent versions.

In addition, over time, the CAI will be able to recognize and collate emerging trends and patterns in the data, improving the report’s overall impact.

The CAI Edge, in the era of “contactless”

The potential of CAI technology to enable information and process efficiencies is only just beginning. Data processing mediated through a voice-enabled AI will transform the post-pandemic healthcare sector, where the demand for new ideas, innovations, and products will accelerate.

In designing, our CAI, Ariya, the phamax team used their extensive industry experience to develop a domain-trained digital assistant for health sector firms.

Our team has configured Ariya’s machine learning and natural language processing to meet the healthcare industry’s precise needs. This helps to optimize operational efficiencies and develop new competitive advantages. All while achieving a market-leading ROI for your investment in CAI technology.

CAIs like Ariya is already boosting the performance of companies in the healthcare value chain. Is now the time to look at how a CAI can do the same for your healthcare firm?

If you’d like to meet Ariya or would like more information on our conversational AI or data solutions, complete our contact form or email us at ariya@phamax.ch, and one of our team will be in touch.

The Role of NLP (Natural Language Processing) in conversational AI

Chatbots are everywhere in our daily online lives. Most of these chatbots are rule-driven, following a predetermined workflow that responds to text-based queries. However, there is never any sense that we are dealing with another human when we interact with a rule-driven chatbot. Any deviation from the expected response results in ‘Sorry, can you please repeat that?’ or termination of the process.

AI-driven chatbots are very different. Their responses seem more dynamic and flexible, even empathetic. This is because they leverage NLP (Natural Language Processing) and Machine Learning to understand what the user is searching for. Within its predefined limits, an AI-enabled chatbot or Conversational AI is trained to mimic human conversation.

A conversational AI-enabled digital assistant is even more sophisticated.

Read about Conversational AI in our previous blog

Conversational AI can do everything that AI-driven chatbots can do but also initiate and lead personalized conversations that feel entirely natural to humans. They seem to understand the context and get smarter with every conversation. Conversational AI is the driver guiding the advanced chatbot or virtual assistant in its interactions with human users. Let’s take a short look at NLP, to understand why it is such a game-changer and how it makes digital assistants more ‘conversational’.

NLP, NLU, and NLG: What do these Acronyms really mean?

Natural Language Processing (NLP) is the engine that translates the user’s message for any type of digital assistant. This translation into machine-friendly language allows the assistant to understand the user’s intentions.

NLP, NLU and NLG: What do these Acronyms really mean?

So, what is NLP composed of? Natural Language Understanding (NLU) and Natural Language Generation (NLG) are the two indispensable elements in any NLP system. NLU deciphers the meaning of the text (or speech) that users input, while NLG generates the engine’s response.

NLU + NLG = NLP

Consider this simple equation for better understanding:

NLU + NLG = NLP

Let us give a practical example to show these processes at work.

When a busy account manager who needs quick access to numerical data or essential information consults an advanced digital assistant, NLP springs into action.

When a user submits a query, ‘Which rep achieved the highest sales for product x?’ the system’s NLU immediately identifies the user’s intention is to “identify” the entity ‘representative’ in relation to ‘product x’ and compare “sales”.

NLU + NLG = NLP

Chat vocabulary:

-Intent: What users want to do or know

-Utterance: Different ways a user can ask the question or order action

-Entity: Objects or values for the intent

Thus informed, it connects to the relevant data sources, fetches required information, and generates an appropriate response through Natural Language Generation (NLG) and Dialogue Management

An advanced assistant’s NLU capabilities can identify and relate these intentions even when the enquiry is phrased in another way. This classifies under “utterance”.

For example, the enquiry ‘Name the best performing rep for product x?’ will elicit exactly the same information from the assistant as the first enquiry.

This flexible understanding of spoken or written inquiries is what distinguishes an advanced chatbot from its simpler cousins. Even if the account manager phrases his question in obscure or idiomatic language, the digital assistant’s NLP can decipher the message, extract the key identifiers, relate the identifiers, and deliver the correct response.

How Healthcare Digital Assistants can leverage NLP

The NLP used by an advanced digital assistant is ‘domain trained’. This means it can identify industry-specific terms relational to the business domain viz medical terms, business names, and other keywords which stand outside the universal directory of normal NLP code.

Training an advanced digital assistant to understand context is also crucially important to Conversational AI.

Although training the digital assistant to understand the user’s exact needs can be a long and complex process, it is absolutely indispensable for an effective Conversational AI.

Similarly, a domain and context-trained NLG (Natural Language Generation) can swiftly understand specialist queries. Because it understands context as a human does, it can deliver appropriate responses to obscure questions within its given domain of enquiry. It can even structure data and text into coherent narratives or pithy synopses.

While it can seem a bit abstract or obtuse, NLP is central to delivering an optimal user experience for users of digital assistants. With appropriate training, an advanced digital assistant can become an empathetic and indispensable friend to the busy sales representative or marketing manager. No more lengthy calls back to head office for the latest research or sales data — a quick chat with your phone, tablet, or laptop will return trained and relevant responses in a matter of seconds.

Applying NLP to benefit users in the Healthcare Industries

Applying NLP to benefit users in the Healthcare Industries

At phamax, we have successfully applied advanced ASR (Automatic Speech Recognition) and NLP to improve our digital assistant’s conversational skills. This is why Ariya is able to deliver conversation users would expect from a friendly colleague. Responses are dynamic, relevant, and above all spontaneous. It works faster, more flexibly, and more efficiently than traditional methods when accessing and processing information. With Ariya, frantic phone calls or lengthy waits for relevant information are a thing of the past. In fact, Ariya has been delivering effective solutions for clients in the health industry for some time, with many use cases in the pharmaceutical field. Users in sales, marketing business support, finance, law, procurement, and medicine are all piloting Ariya’s advanced NLP capabilities to deliver better conversational AI. Here are a few use case examples:

  • Efficient conversations: With its advanced and domain-trained NLP, Ariya extracts and delivers the information you require in mere seconds. It understands the context of your enquiry and responds to your specific needs and conversational style — in short, it is the friendly, competent personal assistant you always wanted.
  • Save time in data and information discovery: Ariya’s continual accretion of data via API allows it to crawl huge amounts of data, monitoring it for emerging themes. Apart from saving huge amounts of research time, a CI-trained digital assistant capable of ‘social listening’ is the perfect solution for innovative companies who want to keep abreast of their competitors and ahead of the curve.
  • Capture data and information: According to research, salespeople regularly lose up to 19% of their time on administration duties. Potential use cases are being developed for Ariya to autofill forms and CRM by dictation alone, eliminating the need to manually fill in pre-defined templates.
  • Easy and simple access to information: Ariya is the ultimate tool for business users serving the healthcare industries, regardless of their role or department. This dynamic solution offers the opportunity to save time and improve efficiency by empowering employees and setting new standards for accessing and processing information.

Conclusion

Conversational platforms are rapidly transforming the way people interact with the digital world and user expectations are rising all the time. Digital assistants equipped with conversational AI apply the latest NLP advancements to enhance user experience with humane, productive, and flexible conversations.

To know more about Ariya write to us ariya@phamax.ch

What personality traits qualify Ariya as a “WOMAN”

Ariya is an AI-enabled conversational digital assistant who is smart, intelligent, and progressive, clearly all the characteristic traits a woman possesses. Breaking the bias, she is set to make history in technology advancements and bring a revolutionary change in the way information is accessed and proccessed. Her technological skills and personality traits make her sophisticated and reliable. As a young aspirant, she is learning and adapting to make future reinforcements in our everyday work life. Here are a few personality traits of a woman we identify Ariya with.

1. Is empathetic, and cares for you

Chat or talk to Ariya just like you would converse with your colleague. Ariya’s advanced ASR(Automatic speech recognition), and NLG(Natural Language Generation) engine make conversations more humane. The responses are dynamic, meaningful and spontaneous, and not scripted.

2. Understands what you intend

Ariya undergoes intense intent training to meet all your information needs at work. Her extensive domain knowledge makes it a superior digital assistant for your everyday business information needs.

3. Is a keeper of information

Ariya acts as a keeper of information repository. She organizes, manages and stores all the information in one place. She knows where the intended data is kept and can either guide or access it for you.

4. Does the heavy lifting

Ariya uses sophisticated algorithms and AI techniques to take care of complex analytics, data, and information processes. Adding process automation to the mix, Ariya makes it all the more simple for you to infer.

5. Can multitask

Ariya is multi-skilled to collect, simplify, report and leverage information to make you shine. Choose from the list of skills that Ariya can perform and personalize to meet your needs.

6. Has your back when you feel lost

Be it during a discussion, generating a report, or making decisions, Ariya is always ready to support you with any data point you need.

7. Prompt: Understands the urgency of your needs 

Get information in the blink of an eye, as and when you need it. You can ask Ariya as many questions as you want, and she will remain unfazed.

8. Is reliable

Ariya’s conversational AI applies a “confidence score” to give you the best possible answer, making her all the more reliable.

9. Ability to learn and adapt quickly

The ML technology keeps Ariya up to date. Ariya learns from experience. With each interaction, she improves her ability to understand, predict and respond with accuracy. She gets smarter with each use case applied.

Conclusion

Everyone is dependent on information for knowledge, discussion, meeting, or performance reporting. But there are always instances where either information is not available the way we need it when we need it the most, or as easily as it is expected. Ariya is trained to be your everyday assistant for information needs anytime, anywhere. Ariya removes all the complexities around the information process. Schedule a demo to explore Ariya. Write to us at ariya@phamax.ch

Conversational AI: What it is and how you can benefit?

These days, you get greeted by a chatbot on every website you visit,“Hi, how may I help you?”

The growing popularity of chatbots has become a fact. Since the early 1960s, people have been interested in developing a robot that can converse with humans. From phone calls and texts to messaging applications, we’ve come a long way. Companies have come to realize the importance of chatbots in assisting numerous industries to reach and engage with customers in ways never seen before.

Going one step ahead, the evolution of Artificial intelligence (AI) has helped step up the game in the world of chatbots. It is now possible to create conversational virtual agents that can understand and respond to a variety of questions, commonly referred to as Conversational AI or Conversational Artificial Intelligence.

Chatbots and Conversational AI are frequently used in the context of Artificial Intelligence (AI) interchangeably. They might sound the same, but they are not.

Most individuals and enterprises are confused between these two buzz words.

So, let us get down to understanding them.

What is a Chatbot?

At the most basic level,

A chatbot is a computer program that allows humans to interact with the computer using a variety of input methods like voice, text, gesture, and touch, 24/7/365.

Chatbots can be extremely basic Q&A-type bots that are programmed to respond to preset queries. Most of us are familiar with bots for customer service in our personal lives, and also with popular chat and messaging platforms like SMS, Facebook/LN Messenger, WhatsApp, banking help bots, etc.

So far, chatbots have gained popularity to enhance customer experience and business efficiencies, now they are even being utilized for employee assistance.

Chatbots are broadly classified into two types, rules-driven and AI-driven.

Rules-based chatbots follow a predefined workflow, a simple tool capable of understanding and responding to text-based commands. It can only work on a single channel and operates as a chat interface. Usually navigational, it works on a pre-determined chat flow.

AI-driven chatbots leverage NLP (Natural Language Processing) and ML (Machine Learning) to understand what the user is asking or looking for. It is more conversational, performs complicated multi-turn conversations, and executes judgment-intensive tasks, just like us- humans.

What is a Conversational AI? 

Conversational AI is a higher-level concept of a chatbot.

Conversational AI is the communication automation technology based on advanced robotic solutions. Unlike chatbots, conversational AI is a digital assistant that can lead natural conversations with humans.

It combines AI technology with other technologies (natural language processing (NLP), machine learning (ML), secure integration, process workflows, dialogue state management (DSM), speech recognition, etc.) to deliver a more personalized user experience.

Think of conversational AI as the ‘brain’ that powers a virtual assistant or advanced chatbot.

How does Conversational AI work?

To assist someone, you basically need to understand what help they need. A machine should first identify the “need” or “intent”. In conversational AI, the brain has to translate human language into something a machine can understand and respond to in a humanlike manner.

Let’s take an example where this can be applied.

In a scenario where a sales rep makes a query to a digital assistant to find out his performance:- What is my sales (intent) in April ’21 (entity)?

Imagine a robot built to mimic humans.

Same as us, the technology uses Automatic Speech Recognition (ASR) to function as humans’ ears to hear and convert voice into text.

Natural Language Understanding (NLU) functions as a brain to interpret what’s being said.

Natural Language Processing (NLP) helps understand and assimilate text and spoken words in much the same way human beings can.

Output is generated through Dialogue Management to serve as brain cells. During this step, the application formulates a response based on intent. Natural Language Generation (NLG), a part of NLP, orchestrates and converts the response into a human-understandable format like speech.

Proprietary algorithms also play an important role in enhancing the overall NLU capabilities of a digital assistant. In the case of the Ariya, the conversational AI interface, phamax has trained the supporting framework to understand business nuances and terms used in the context of healthcare and can be scalable to train the assistant to understand organizations context (product names for instance).

Conversational AI still needs humans to train them.

Conversational AI-based digital assistants can work their best only if they have both a trained team and implementers who can make the most of these technologies behind them. As digital assistants answer more questions and AI trainers assist in increasing their knowledge, conversational AI becomes smarter. Conversational AI learns new variations for each intent and how to improve its responses.

How is a Conversational AI different from a Chatbot?

To make it easier to understand here is a summary of some of the typical features* of a conversational AI application versus a basic chatbot.

*not all these features are necessarily part of a conversational AI solution

There is a wide range of conversational AI applications currently being used across all industries. From customer service to marketing and security, these intelligent programs are helping businesses connect with customers and employees in innovative ways. In fact, conversational AI has become an integral part of many organizations’ digital transformation in the wake of the global pandemic.

1. Customer service support:

Conversational AI for Customer Service, such as online chatbots and voice assistants (VAs), is increasingly being employed by contact centers to mimic human employees as part of customer support service automation. The customer service digital assistants can be deployed across channels, providing brands with the opportunity to create an omnichannel customer experience. AI-powered digital assistants are capable of delivering service, 24/7 which means that there’s always someone to respond to customers’ queries!

If the customer support query is complex or beyond the scope of the digital assistant, there is a seamless process to hand off the query to a live agent based on their skill sets and current workload.

2. Communication channel:

Chatbots have become a vital part of messaging platforms’ ecosystems. In 2015, the top 4 messaging platforms exceeded the 4 biggest social networking apps in the number of monthly active users, according to Business Insider. Since then, AI-based digital assistance has become an integral offering at every platform, we land, aiming to create more personalized and meaningful conversations. 

3. Enterprise support:

The difference between chatbots and an AI-based conversational experience lies in the integration of back-end systems to provide information to users. When you use AI to ingest systems like your SAP, CRM, or ERP, you may have direct transactional dialogues with customers without the need for a business person.

Advanced AI chatbots can integrate with an organization’s data source or back-end systems, such as inventory management or customer relationship management (CRM). Today, Conversational AI-enabled digital assistants like Ariya have the potential to support the sales force to drive greater efficiency. The AI-enabled digital assistant interface is designed and domain trained to assist sales reps to quickly access phone numbers, extract competitive and performance updates, even make a CRM entry instantly. The potential of conversational AI to simplify processes is enormous.

4. Everyday digital assistants at work:

With information and data overload, it is quite impossible and unfair to expect your employees to remember or have enough time to extract the information they need. An everyday assistant who can be present with all the information one needs can motivate them to perform better.

In customer service, for example, reps don’t have to waste time seeking information, or depending on tools and colleagues to help them, which cuts down the waiting time to respond to customers due to a knowledge gap. Additionally, it enables reps to locate answers significantly faster, resulting in shorter encounters and higher first-contact resolution rates. All of these are well-known markers of consumer satisfaction.

5. Unlocking knowledge:

Most businesses now keep massive amounts of data and information which go unused. Organizations are aware of their accumulating data, but their processes and systems for accessing and utilizing the data are hampered by outdated or less efficient practices.

If a decision-maker is looking for sales figures, for example, the first step is to approach a member of the sales team, who may have to pull from multiple systems and reports to answer a single, yet complex question. Which might be stressful also consumes a lot of his time.

With the new advancements in technology, AI provides the scope to extract unused data while handling massive data warehouses effortlessly. Conversational AI can act as an assistant that can quickly extract and process data in a meaningful format. Organizations worldwide have started leveraging these across functions and hierarchies.

Conversational AI is the next evolutionary step:

With increasing popularity, Conservational AI is here to stay. Training the technology with domain knowledge can open greater opportunities towards enhancing organizational and employee efficiency. Eliminating all tedious steps throughout the information journey is a thing of the past. Gone are those days when you had to depend on your colleague or have the technical skills to get information.

Conversational AI assistant like Ariya is one of the revolutionary examples of transforming the traditional ways to process and access information.

How to successfully launch an internal app – a guide in eight steps

Launching an internal app is exhilarating, but equally stressful. You want to ensure high adoption rates, but you are concerned employees might reject your app. Thankfully, there are several steps you can take to fuel adoption and engagement. 

Nothing beats seeing your hard work come together as employees embrace the app you made to make their jobs easier. This article will take you a step closer to that feeling with eight key steps for a successful internal app launch.

Let’s jump in!

How do you launch a product internally?

Launching an internal product requires clear objectives and target audiences, value propositions, frictionless onboarding, and a lot of hype. You can do a pre-launch that encompasses four parts to achieve these things.

Pre-launch steps to get people on board

Your journey starts with a pre-launch. A pre-launch will help assure app readiness with a pilot programme, collect feedback, create hype and boost product visibility, ensuring that everyone in your company is on the same page.

A pilot programme is crucial to app success, helping you collect feedback and identify problems before your app reaches users. You can use your findings to improve the app and establish best practices to prime your app for adoption.

Create a beta group to test drive your app and enlist product champions to market your app and drive interest in the product. Invite volunteers to try your app and collect feedback to improve your application before release.

Success rests on the way you communicate the change to employees. You need to be concise and communicate the benefits of your product so that employees understand why you are making the change and how it helps them.

Avoid generic words like “revolutionary” and phrases like “a better way to do things” because these can turn people away. “A new tool that will make your job easier” is better than “a new tool that will transform how you work”.

Company leaders should play a lead role in this, communicating with the department to share how the new technology is beneficial.

Also, don’t neglect external communication. PR plays a big role in internal app launches because it publicly backs up internal communication. Showcasing the change to the outside world is a great way to get people on board.

Segmenting users that fit specific criteria to create target audiences will ensure your messaging and app features resonate with users. It also serves the practical purpose of letting you fine-tune your messaging by department.

For example, you can tell sales that your app saves them time on paperwork, you can tell marketing that it saves them time on campaign management, and you can tell HR that it saves them time on hiring new people.

You can also take individual features, such as cloud uploads and in-app collaboration, and use workflow examples to get different departments on board.

Hype is the engine behind every successful app launch. It will ensure your employees not only know about your app but want to download and use it.

There are several ways you can create hype:

  • Start a countdown
  • Share sneak peeks and teasers
  • Share your brand vision and how the product fits in
  • Take your team through the product with visuals
  • Create teaser videos
  • Offer a beta version of the app to department heads
  • Work with department heads to communicate the benefits

Ensuring a smooth, successful launch 

With hype in full swing and confidence in your product, it’s time to launch. The risk following launch is low adoption rates as only the most engaged employees use it, but there are several ways you can reduce this risk.

Invite all your employees to an event celebrating the launch of your product. You can increase attendance by letting people attend in person or remotely via video link, and those who miss it can watch it afterwards.

An event could be as simple as a get together at work, or you can book a big screen with a stage like a Steve Jobs announcement for Apple.

Because your product is for employees, the event should be too. Put on food and drinks and generate lots of buzz about your product and brand.

6. Training and demos 

One of the most significant barriers to app adoption is training. Your employees are more likely to use your app if they know the basics; however, delivering in-person training is slow and risks alienating many employees.

The solution? Training and demo videos. A series of training and demo videos that are always accessible will deliver knowledge and skills efficiently, ensuring that your employees are ready to use your app after adopting it.

Publishing videos on the cloud is the best way to guarantee access, and you can turn them into a series with tutorials and demos covering different areas.

Post-launch steps to fuel engagement

Following the launch of your app, adoption rates will explode and then gently fizzle out as employees use it. Your job now is to maintain user engagement and ensure everyone gets maximum value from the app.

Despite your best efforts, early-stage excitement in your product will wane. The key now is to maintain engagement and keep people enthusiastic.

Internal product advocacy is essential, but the product manager can only do so much. Internal advocates are vital to ensuring that your product’s vision and goals continue to progress and deliver value to employees.

The job of product advocates is to focus on and clarify the benefits of the app and the problems it solves. In other words, product advocates maintain focus in your app so that users continue to see and find value in it.

One of the biggest mistakes businesses makes post-launch is letting the app sit there and stagnate. Your internal app has to evolve and continue providing the best possible user experience to maintain engagement and user satisfaction.

Here are a few ways to keep things exciting:

  • Let users request features
  • Let people vote for the next new feature
  • Survey users to collect performance feedback
  • Produce tips and tricks videos and articles
  • Test new fonts and layouts with beta versions
  • Keep adding new features that enrich the user experience

Conclusion 

Efforts like these will help ensure a smooth app launch and significantly increase adoption and engagement rates. However, the biggest challenge is ensuring your product’s vision and goals are met over time.

A chain is only as strong as the weakest link. You need a product strategy that encompasses pre-launch, launch, and post-launch cycles for app success. Taking a systematic approach is the best way to keep users around for the long haul.

How is a Virtual Assistant different from a Chatbot?

One of the hottest topics in the tech world these days is conversational AI. How can a machine talk to or chat with a human in a relevant way, correctly addressing the content of the conversation? This is a hugely complex task but in the recent past technological breakthroughs have been achieved.

With these, new buzz words emerged, starting from the already familiar “chatbot” to the more holistic “virtual assistant”. In this blog, I am reviewing the key differences between the different technologies and the benefits they grant users.

What is a chatbot?

A chatbot is a text-based, programmed set of dialogues that can simulate a conversation with a user in natural language through messaging applications, websites, mobile apps, or phone calls. It uses an interface for the interaction with humans. More advanced chatbots can use a question-answer system, leveraging simple Natural Language Processing (NLP) to further emulate real conversations. They are often used to automate and streamline interactions between people and services to enhance the overall customer experience.

But as sophisticated as they might appear, a chatbot is programmed to deliver only scripted responses to pre-determined user inputs.

Despite this “shortcomings”, according to Forbes, the chatbot market is forecasted to reach $1.25 billion by 2025.

Benefits of chatbots

  • Cost savings
  • Collect consumer data
  • Effectively operate in global markets
  • Better customer engagement

What is a virtual assistant?

A virtual assistant (also known as an intelligent virtual assistant or intelligent personal assistant) is a sophisticated interactive interface that is designed to comprehend meaning and context using artificial intelligence based on Machine (Deep) Learning.

It can assist in simple to complex dialogue structure activities, with options to predict and prompt. Some virtual assistants even attempt to understand the user’s behavior and emotions, in order to deliver a human-like interaction experience.

VAs increasingly leverage voice capabilities. Voice recognition first came into play in the early 2000s through IVR (interactive voice response) systems and quickly gained popularity for its ability to understand human speech.

A sub-group of virtual assistants are the so-called voice assistants which can take inputs in the form of voice commands and communicate to the user audibly. Popular examples are Siri, Alexa or Google Assistant.

Now that we have a basic understanding of chatbots and virtual assistants, let’s dive deeper into the key differences:

In case you consider implementing a machine-based conversational tool, the choice between a chatbot and virtual assistant will depend on your objectives

For simple to medium complex conversations (i.e., more directing the user, with less choices on questions), a chatbot can be very useful. End users can interact with the chatbot via different messaging and social platforms, simulating a conversational experience to a certain extent. But ultimately chatbots are constrained by having to work off a limited script.

Virtual assistants can create a better user experience and deliver higher value to the end-users but require a deeper understanding of the related tech domain.

In the near future we will see the rise of virtual assistants who can truly serve the user over a wide range of tasks, like data localization and visualization, analytics, providing predictions and ultimately supporting decision-making by making recommendations based on data. Virtual assistants will enable organizational-wide performance improvements, by empowering employees to take better decisions through-out the day by providing the right knowledge, anytime, anywhere.

6 Time-Saving Techniques for Pharma Marketers

Being a marketer in a field that is set to hit $1.17 trillion by 2021 can rapidly become stressful. 

Dealing with significant budgets, a highly competitive market, a tough industry reputation and complex regulations… That’s the daily life of a pharma marketer.

Making products stand out or justifying a ROI aren’t easy tasks in such a challenging environment. Especially when we consider that brand loyalty doesn’t really exist in that market. 

And as if the life of pharma marketers wasn’t difficult enough, most teams have another challenge to add to their burden: time. Or rather, the lack of time due to bottlenecks and an inefficient organization within the company.

The good news is: There are many ways to improve the situation of your pharma marketing team. 

We’ve gathered 6 time saving techniques that will tip the scales when it comes to the success of pharma marketers.

Reduce the number of agencies you’re working with

We get it, your pharma marketing team has already plenty of work trying to stand out in front of empowered patients and hard-to-reach physicians. 

But do you really need to externalize marketing activities to so many different agencies?

Let’s take the example of a digital campaign: if you’re having one agency for your content, another one for design purposes and a third one for digital media buying, you’re more likely going to face miscommunication and your marketing team is probably spending too much time on coordination.

And at the end, this might be doing more harm than good to your team.

Instead, try to find agencies covering several needs. And if this doesn’t seem possible, or if you don’t want to cut an agency loose, ask that agency to find partners that can bid together on offers! 

You can negotiate a single point of contact for both agencies.

That way, your marketing team will save a lot of time on coordination, and having to talk with one agency only will considerably reduce the risks of miscommunication!

Use a digital assistant for easy information retrieval

Market researches, brand plans, disease-related content or training documents are essential for your marketing team. Whether it is for a product launch, product training or just to answer some customer query, the information should be easy to find. 

Data is power, especially for an industry where “patient experience” is becoming the number one element of marketing strategies.

But that power is often lost due to the difficulty for marketers to find the information they need. In fact, according to a report by McKinsey, more than 30% of time is wasted at work… looking for information! 

There are plenty of reasons behind that struggle to find relevant in-house data. It can be a lack of transparency, bottlenecks, data silos, disconnected information or dependencies…

You name it.

And often, those obstacles lead to the marketers not being willing to look for the information in the first place! And it’s understandable.

Data access is the first issue. But let’s address the elephant in the room. Even when a marketer manages to find the right dashboard or spreadsheet, she still needs to spend time trying to understand and draw inputs from that raw data. And often she will end up reaching out to the owner of that document anyway. 

The key here is to provide your marketing team with a fast and simple way to find the info they need, whenever they need it.

A way to do so is to invest in a multi-platform digital assistant such as Ariya. This tool has been developed especially to help marketing teams to find the information they need, using natural language. You ask, it answers.

Local vs global teams

This tip is mostly for international companies, with separate marketing teams in the headquarters and locally. 

To save time and avoid double work, it’s important that you have a clear split of responsibilities between local and global teams. 

In a few words: what should be done globally, and what must rather be done locally?

For example, if your company is present in 5 countries, what is your web strategy going to be? Should you go for a single multilanguage “.com” domain, or for 5 local domains?

And if you end up with 5 local domains, who is going to be responsible for the content? Is the global marketing team in charge of the whole content plan, or is each local marketing team taking care of its own content?

And this doesn’t only apply to digital marketing. Let’s say your company organizes a congress in France. Who’s going to be in charge of the organization? Is it going to be the French team or the global team? And if this is an international event, should it be a joint effort?

All those questions seem rather logical, but decisions are often taken spontaneously and not well communicated, when they should be taken way upstream. And this situation easily creates some confusion across the different marketing teams of the company.

Foster synergy between brands

Once again, this might be obvious, but ask around and you will be surprised how difficult it can be for a marketer to get information on other brands from the same pharma company.

During a new brand launch, for example, boundaries between projects and brands are often preventing marketers from learning from the mistakes and experiences of previously launched brands. 

By fostering a synergy between brands and making the information easily accessible to marketers, you’re not only going to save your marketers a lot of time, but you’re also giving them the possibility to reuse successful strategies and previously gathered data such as market studies, competition analysis or customer reports.

Less meetings, but more structure

Don’t understand us wrong, meetings can be positive as they allow all-level employees to communicate, brainstorm, and align. 

The issue we’re trying to highlight here is the lack of structure of these meetings. 

In a survey conducted by Harvard, in 2017, 65% of surveyed senior managers admitted that meetings keep them from completing their own work, while 71% agree on how inefficient and unproductive meetings are.  

And when we know that, on average, companies are holding 8 meetings per week (across all employee types and company size), it’s easy to see how time consuming and unproductive it can get for marketers (well, for everybody, actually).  

The goal of this article isn’t to explain how to throw productive meetings, but just to remind you of a few basic rules that can save you a lot of time.

Meeting organisers should start by clearly defining in advance the objective of each meeting, and the topics to be discussed, as well as making sure the right persons are invited to the meeting. Whenever possible, documents should be sent (and read) in advance.

Then, once the meeting takes place, less time will be spent giving context or reflecting on things that could have been prepared in advance.

Also, if the information is shared smartly across departments, couldn’t the need for meetings be reduced?  Our point is that meetings are often organized to make sure everybody is on the same page, and as we explained above, easy access to in-house data plays a big role in that matter. 

Work hand in hand with healthcare professionals

Marketing drugs to physicians is hard. 

As thoroughly explained in this article by Digital Authority, physicians are not easy to find, their attention is difficult to catch, they expect rationalized marketing and marketers have to come up with clever marketing approaches to stand out. Even more so during the COVID pandemic.

Yes, physicians are clever, and they are dealing with consumer health on a daily basis. They take their job very seriously and have little spare time to deal with marketers.

There isn’t much space for trial and error in the pharma industry and having a healthcare professional from your target group close to you might be the missing card in your marketing team’s hand. 

And we’re not talking about asking some physician friends for information when needed. By being close, we mean having a healthcare professional on payroll, whom your team can work hand in hand with. 

Let’s say your team is building a digital strategy targeted at dentists. They have tools to study the market and target group, but a strategy based solely on analytics is time consuming and not 100% reliable. Wouldn’t it be much faster and reliable to understand where dentists really consume digital information, through the inputs of a dentist himself?

Sometimes, you do have a market study made with your target group, but the communication ends there. 

The same goes with Google and other search engines. To reach a target group, your marketers first need to understand how that target searches for specific information on those search engines. If not planned properly, your team will spend hundreds of dollars advertising on keywords that are actually missing the target. Once again, working with a physician from your target group will help your team understand what his peers are really looking for.

This relationship will ensure that your marketers understand the needs of the other physicians from your target groups, and this will also considerably reduce the time spent in discussions between non-physicians about what physicians prefer. 

5 Essential Time Management Tips for Pharmaceutical Reps

If you’re a pharmaceutical or medical sales rep, panic triggered by running short on time is probably a familiar feeling.

With calls to prepare, doctors and clinics to visit, data to pull as well as admin work to finish, the tasks can feel endless as your to-do list grows longer and the day grows shorter. 

Unfortunately, you can’t add hours to your day, but there are some time-saving tips that sales reps can adapt to make their work week run a little smoother and improve productivity.

Even if you commit to one or two of these time management skills, your days will become less stressful and you’ll have more time and energy to focus on the important stuff like connecting with customers. 

1. Optimize Your Calls

Since visiting healthcare facilities often isn’t possible during the pandemic, it is important that your phone and video calls are impactful.

There are some tactics you can use to avoid wasting time making multiple calls to the same physician or spending days waiting for your call to be returned.

First, try scheduling your phone or video call with an email a few days before.

In your email, let the physician know the purpose of the call. If the doctor is informed on what product you will be discussing and how it helps their patients, they will be more apt to speak for a few minutes rather than taking a cold call where the purpose is unknown. Currently, physicians are very busy. When you do get your customer on the phone, be brief, know your facts and get to the point quickly.

Secondly, meet the physician where they’re at.

Whether they prefer FaceTime, Zoom, or a traditional phone call, make sure your virtual connections are done through a channel they are comfortable with. Ask them what they prefer and adapt. Don’t spend valuable time setting up a Zoom call, only to later realize your customer prefers a phone call. 

2. Get Quick Access to Data

When you spend too much time on administrative tasks and not enough time with your customers, performance can suffer.

Tasks like running reports, pulling product information or finding answers to customer queries can quickly eat up valuable time.

Though sales and marketing analytics are vital for you to be able to determine where you should spend your time and efforts, extracting the information becomes cumbersome, especially on the go.

Investing in Aryia, a text and voice-enabled application to pull analytics, has proven to be a major timesaver for medical and pharmaceutical reps.

You won’t have to mess with complicated dashboards, type in formulas or wait for an analytics specialist to answer your question via email. You can get instant answers to your data inquiries so you can move on with your day, equipped with valuable knowledge and data you need to satisfy your customer’s needs.

3. Intentionally Structure Your Day

A study published by InsideSales.com has shown that only 28 percent of sales reps follow a structured time management system.

Without a structured guide to follow, it is no wonder the majority of medical sales reps find their days slipping away from them. A structured, yet flexible, schedule is critical for completing important tasks.

We all know that “life happens” and we have to adjust and adapt our schedules, but having a tentative plan for the day promotes focus and intentionality.

Structuring your day in time blocks can be helpful.

Make a list of everything you want to get done in a given day.

Jot down about how many minutes (or hours) you think each task may take.

Block out that time on your calendar.

Now you’re committed to completing those tasks at a certain time of the day.

Word of advice, when timing your tasks make sure you factor in drive time and prep time.

Then, if there are any recurring tasks, like entering data into your CRM, make sure you automate the recurring task on your calendar so you don’t have to enter it repeatedly.

When structuring your day, consider when you are most productive and energized. Some people work best in the early morning, while others prefer the afternoon.

You’ll also want to consider your clients routine as well. Get to know your customers schedule, that way you know when to avoid the office and when is the best time to schedule a meeting.

4. Eliminate Distractions

Ringing phones, social media notifications, talkative co-workers and urgent emails can all nag for our attention.

But did you know that surrendering to these distractions can actually make you much less productive?

A study done by the University of California Irvine found that it takes an average of about 23 minutes to get back on track after attending to a distraction.

Gain minutes, maybe even hours, back in your day by eliminating distractions when possible. Close your email window when you’re working on a project with a tight deadline, turn off social media notifications and silence your phone when you need to stay focused.

Though not all distractions can be eliminated, they can be effectively identified and managed.

If you find it difficult to do by willpower alone, there are apps out there that can help you manage online distractions like Freedom and Mindful Browsing.

5. Utilize Templates

Emails and proposals to clients should always have a personal touch, but there is no reason why you can’t start them from a template.

Using pre-written templates for routine emails and documents can shave off some time in your workday and boost efficiency.

It may seem simple, but it is often overlooked!

Browse through your “Sent” email folder and recent documents. Pay attention to the kind of emails you routinely send to prospects and the documents you frequently create.

Write-up a template for each and copy and paste the template when you need it, but make sure to add in the personal details and times associated with that specific client or meeting.

No reason to start from scratch each time you send an email!

Final Thoughts

We’ve all heard the saying, “Time is money.”

The phrase was coined by Benjamin Franklin, a philosopher, statesman and inventor. He knew a thing or two about the value of time! Since every minute is precious, even saving a few here and there is worth it.

Follow a few of the tips and tricks we touched on to maximize productivity in your workday. You may even see a boost in your sales, and you can tip your hat to effective time management.

Modern Challenges Faced by Medical Affairs Teams

Let’s Give Medical Affairs Teams a Break

Within the complex workings of pharmaceutical businesses, the Medical Affairs Team serves as a cornerstone. Engaged in extensive research and analysis, these professionals play a critical role in defining scientific strategies and comprehending the intricate nuances of the pharmaceutical landscape.

Their responsibilities include understanding comprehensive research papers, clinical evidence reports, and various scientific journals, all to translate their findings into actionable insights, such as sourcing KOLs, orchestrating seminars, and identifying unmet patient needs.

Amidst their demanding roles, the integration of AI technologies such as ML and NLP offers a promising solution, facilitating the handling of intricate pharmaceutical information and making their work more efficient and responsive.

Simplifying Data Management for Effortless Workflow with LLM

Harnessing the power of Generative AI, Medical Affairs Teams can accelerate data analysis, reducing the time required to review dense scientific documents, technical papers, and data summaries by up to 60%.

Leveraging this technology streamlines the document review and analysis process, allowing for a more effective and time-saving approach compared to traditional manual review methods.

Recent studies have shown that AI systems trained in natural language processing can swiftly summarize extensive medical records, significantly reducing the time and effort compared to manual review by humans.

Consequently, the integration of Generative AI for document review and analysis is a game-changer, significantly minimizing the hours or even days of manual work into mere minutes or seconds. The extent of time saved may vary depending on specific variables at play, underscoring the significance of utilizing AI for optimizing document analysis.

Conversational AI further streamlines complex search processes, enabling Medical Affairs Teams to swiftly address critical issues and focus on essential tasks such as business updates, initiating studies, providing key recommendations, and addressing stakeholder inquiries.

In establishing evidence-generation strategies, Medical Affairs Teams play a crucial role in providing a robust evidence base tailored to meet the needs of diverse stakeholder groups. Whether it’s providing support for clinical decision-making, reinforcing buying decisions, or addressing patient concerns, their evidence-based approach serves as a cornerstone in validating the efficacy and safety of pharmaceutical products.

Navigating Extensive Data in Evidence-Based Research

The magnitude of data required for building an evidence base is extensive, demanding meticulous collection and analysis efforts. Ensuring accessibility for both internal and external users presents another layer of complexity. However, the immense commercial and scientific value derived from this reservoir of quality information justifies the comprehensive data collection process.

The deployment of AI-powered search capabilities swiftly establishes a comprehensive and easily accessible catalog of medical assets and specific pathologies, streamlining the sourcing of Key Opinion Leaders (KOLs) for necessary support during product launches.

Integrating a digital assistant streamlines the access to updated evidence bases, eliminating outdated spreadsheets, departmental databases, and ad hoc documents. This centralized platform ensures seamless accessibility for all users, promoting efficient data utilization across various business functions and global locations.

Achieving Excellence from the Outset

In time-critical medical emergencies, the use of AI-enabled digital assistants aids in prompt client interactions, offering guidance and support without burdening the Medical Affairs Team. By simplifying complex technical information and streamlining query resolution processes, these digital assistants enhance first-time query resolutions and elevate overall customer satisfaction.

Utilizing AI to Enhance HCP Engagement and Information Accessibility

Beyond product launch, Medical Affairs Teams play a pivotal role in comprehending the distinct challenges and requirements that HCPs encounter, these teams can craft targeted strategies that effectively meet their evolving needs. Moreover, ensuring that medical information remains pertinent and easily accessible is paramount. By harnessing AI-powered tools and analytics, these teams can streamline the process of understanding HCP behavior, thus enabling the creation of targeted strategies that resonate with their specific challenges and requirements. AI can also facilitate the efficient dissemination of tailored medical information, ensuring its accessibility and relevance for HCPs. Furthermore, AI-driven insights into HCP preferences and frequently asked questions enable teams to optimize communication strategies, fostering stronger relationships and trust within the healthcare community.

Nurturing Patient-Centric Engagement with AI Integration

In the ever-evolving information landscape, encompassing academia, business publications, press coverage, and social media sources, AI plays a pivotal role in streamlining comprehensive information searches, enabling Medical Affairs Teams to swiftly direct necessary responses for their organizations.

Fostering Closer Patient Relationships

Given the prevalence of digital communication, AI-enabled Medical Affairs Teams have a unique opportunity to engage with patients in the digital realm. By leveraging Generative AI-powered chatbots, organizations can provide personalized, automated responses to patient queries, enhancing patient engagement and satisfaction while reducing the burden on healthcare professionals. This approach fosters improved patient education and care outcomes, cultivating stronger patient engagement and bolstering brand affinity within the pharmaceutical landscape.

Accelerating Efficiency with Conversational AI

Conversational AI catalyzes expediting various tasks within Medical Affairs, from scheduling meetings with KOLs to promptly addressing common inquiries and delivering product information. While specific percentage improvements may vary, the integration of Conversational AI holds the potential to substantially enhance operational efficiency, potentially saving Medical Affairs teams significant time on diverse responsibilities.

Pioneering Patient-Centric Innovations

For biopharma companies, leveraging wearable devices, apps, and data transfer protocols presents a wealth of opportunities for gathering clinical and experiential insights. With AI at the forefront, organizations can collect and collate these insights into an integrated product platform, allowing Medical Affairs Teams to monitor market-specific changes and drive data-informed innovations. By harnessing real-time data via advanced GUIs, wearables, and domain-trained digital assistants, these innovations facilitate continuous advancements and product enhancements.

Conclusion

The integration of process automation, generative AI, and conversational AI serves to expedite access to and dissemination of medical information, significantly optimizing time management for Medical Affairs teams. While Conversational AI acts as a virtual assistant, facilitating seamless communication, Generative AI streamlines the production of comprehensive scientific literature summaries and insights. Anticipated to yield substantial annual savings and foster growth within the biopharma market, these transformative technologies have the capacity to redefine the operational landscape for Medical Affairs professionals within biopharma companies. Embracing AI as a pivotal tool within their commercial arsenal can position businesses at the forefront of industry innovation and strategic advancement.

Overall, the integration of AI has the potential to afford Medical Affairs professionals more time, allowing them to focus on strategic initiatives that drive tangible business outcomes. This not only benefits their colleagues and peers but also contributes to enhanced service delivery for practitioners and customers alike.