Podcast – Great promotion of the capabilities of chatbots for healthcare – many user cases, digest it here…

In this episode of the SeamlessMD Podcast, Dr. Joshua Liu, Co-founder & CEO at SeamlessMD, and marketing colleague, Alan Sardana, chat with Greg Johnsen, CEO of LifeLink about A.I. Chatbots for Healthcare. See the full show notes below for details.

Guest(s): Mr. Greg Johnsen (@Gregjohnsen), CEO at LifeLink

Dr. Joshua Liu (@joshuapliu), Co-founder & CEO at SeamlessMD

Episode 40 – Show notes:

[0:04] Introducing Mr. Greg Johnsen, CEO of LifeLink;

[1:02] Why Mr. Johnsen built a health tech company after exiting his previous company GT Nexus due to his passion for solving big problems;

[3:46] Why Mr. Johnsen believes now is the right time for digital patient engagement and chatbots for health systems due to the culmination of digital technologies across all industries;

[7:49] How Lifelink determined its core use cases by identifying workflows that require rote instruction that is labor-intensive and expensive at scale, considering three key criteria:

1. Is it high-value?
2. Does the workflow have a significant administrative burden?
3. Would the consumer prefer asynchronous communication?

[12:22] How Lifelink engages patients using two main modalities:

Passive: A chatbot that is inactive until engaged with (e.g. chat button on the website);
Proactive: A chatbot that reaches out to the consumer usually through SMS text message containing a “magic link”, which is a personalized URL key that leads to a browser-based, HIPAA-compliant, automated chat conversation;

[15:19] How asynchronous communication (i.e. communication that is not limited by time and space) improves the patient experience by allowing consumers to engage at their own pace, eliminating social friction;

[25:05] How COVID-19 put immense pressure on health systems to innovate and why the pandemic made it easier for LifeLink to fundraise their Series A as COVID became part of its story;

[27:17] How LifeLink acquired its first customers by thinking big and aligning with strategic, forward-thinking health systems willing to take a chance on a big shift as opposed to incremental progress;

[32:51] How LifeLink’s “virtual waiting room” workflow extends the waiting room to the consumer’s home or the parking lot, enabling patients to fill out required forms ahead of time while setting accurate expectations on current wait time;

[35:18] How LifeLink measures success focusing on patient experience metrics such as NPS scores, happy or not scores, as well as technology-interface scores such as Activation rate (% of patients that click through, authenticate, and engage with chatbot) and Engagement rate (how often patients stay in the conversation / go through the workflow);

[42:28] Fast Five / Lightning Round Questions:

Q1: What is your favorite book or book you’ve gifted the most?

A1: “Conversational Design” by Erika Hall

Q2: How has an apparent failure set you up for greater success?

A2: “In my last company (GT Nexus), we merged with this cloud-based platform (in the early 2000s) before cloud was mainstream. I spent my days selling into cheap procurement deals to heads of supply chains and I would be quite frequently met with reluctance from customers hesitant about putting their purchase orders into the cloud, even though it is the common standard now. It felt like rolling a boulder up a hill… In retrospect, it taught me that things do take time and if you have a great idea, grit is important.”

Q3: Would you rather have Super strength, super speed, or the ability to read people’s minds?

A3: “Probably super speed; I think speed is really, really powerful.”

Q4: What is something in healthcare you believe that others might find insane?

A4: “The sheer amount of money and complexity involved in setting up back-end EMR systems within healthcare systems. Although highly necessary, an extraordinary amount of time and money has been spent on developing these systems; the grip these systems have is also quite insane; the restrictions of the use of data within these systems is quite insane.”

Q5: What is 1 hobby or activity you’ve gotten into since the pandemic?

A5: “We have a lot of birds in the area near my office, so I’ve become a bit of a bird expert!”


This article is written by seamless and originally published here

AI-Powered Marketing: Leveraging First- & Third-Party Behavioral Data To Improve AI & Organizational Effectiveness

Artificial intelligence (AI) is an invaluable aspect of modern marketing, with many organizations leveraging AI-powered solutions to help collect higher quality data, deliver better buyer experiences and more.

One of those data sets is behavioral data, which enables B2B organizations to identify buyer preferences, their stage of the buyer’s journey and purchasing intent for optimal outreach, engagement and deal closing. Naturally, B2B organizations are leveraging behavioral data to inform their AI-powered solutions and marketing strategies.

“There’s more awareness of what behavioral data is and how you can use it,” said Steven Casey, Principal Analyst at Forrester, in an interview with Demand Gen Report. “There’s been an arc in the development of the martech, with marketers using this kind of data to solve relatively simple problems. Solutions have also been using AI for a while to make recommendations for marketers and sellers, and behavioral data can only enhance that.”

In a recent report from Forrester, Casey highlighted the changing landscape of marketing with the consolidation of AI-powered solutions and the rise of behavioral data, and how it has given way to a new form of AI-powered B2B marketing. The report also explores the importance of data management and how solid data sets can help an organization’s AI tools improve operational efficiency and align marketing and sales strategies.

AI-Managed First-Party Behavioral Data Improves Operational Effectiveness

According to the report, the key to successful behavioral data and AI synergy is the quality of the organization’s first-party data. However, many organizations still struggle to find ways to keep their AI informed and optimized, with 32% of global marketers citing bad data as a hindrance to effectiveness.

“The typical problem people run into is data management,” Casey explained. “They just have too much bad data from too many sources. It’s not clean; it’s not unified. Until you’ve cleaned up the data, it’s just bad fuel for your AI.”

The report highlighted some data sets for organizations to focus on to overhaul their behavioral data, which would allow them to improve their team’s effectiveness, including:

  • Assigned data – By assigning AI to record firmographic and demographic data sets, organizations can identify buyer preferences, needs and goals for a more personalized buying experience;
  • Observed data – Recording specific buyer statements and actions while interacting with a brand’s website, social media page, etc. can improve marketing and sales effectiveness, as AI records key information and provides recommendations for successful buyer interactions; and
  • Inferred (intent) data – This prediction-based data set leverages assigned and observed data to automatically provide predictions and recommended actions to take, allowing organizations to determine buying intent and make strategic decisions accordingly.

“AI-powered marketing thrives on these data sets,” said Casey. “The data shows a behavior, and it helps you see if people at an account did something, or maybe an account or a company did something, and act on it. With this first-party data, I can say ‘Okay, I’m gathering first-party behavioral data, and I’m getting a much better picture of buyers’ true intentions.’”

Expanding Third-Party Data Sets For AI-Powered Initiatives

Third-party behavior data also plays a critical role in AI-powered marketing, enabling organizations to rely on a holistic data strategy to engage buyers.

When building up third-party behavior data for AI-powered marketing, Casey explained that having AI solutions that cast as wide a net as possible is essential. The report highlights how AI can track unique behavior data signals, such as published content and review websites, and provide marketing and sales professionals with an external database that is constantly refreshed and ready to use for email campaigns, ABM engagement, programmatic advertising and more.

AI-powered marketing also encourages organizations to survey their third-party sources to make sure their AI-powered strategies are using behavior data that is accurate, up-to-date and relevant to their marketing initiatives.

“It’s an opportunity for marketers to think more broadly and comprehensively about all the data they gather about their customers,” said Casey. “There are lots of different processes and methodologies for leveraging third-party behavior data. But at its core, it’s a mindset of thinking about what I can learn from the landscape around me that would give me an indication of how best to engage with my own buyers.”

AI & Behavior Data Strategies Encourage Internal Alignment

Casey also made clear that AI and behavior data synergy with specific teams was essential for successful AI-powered strategies, as marketing, sales and customer experience teams will ultimately share and implement the data and solutions.

Various teams can share behavior data among their peers using AI, allowing the solutions to inform marketing, sales and customer service processes using the same, unfettered insights. By leveraging the first- and third-party behavioral data gathered by AI, teams can create a universal truth about buyers that encourages them to collaborate on campaigns and sales deals, optimize workflows and improve decision-making at the employee-level.

“Marketing can raise its profile and overcome some of this old behavior by using AI to make recommendations and surface insights for sellers,” Casey explained. “Leveraging observational data and gathering more insights using AI allows teams to make recommendations based on what your AI has learned while gathering data on similar situations.”

Ultimately, AI-powered marketing is only as good as the data organizations have at their disposal, as the AI solutions, as well as marketers and salespeople, heavily rely on accurate data to support their operations. Behavior data is an interesting and effective alternative to inform AI’s researching capabilities and can help B2B organizations improve internal operations and data gathering from internal and external signals.

“By using behavior data and AI, you are helping your teams be successful,” said Casey. “You are letting your teams know what their customers are doing so that you and your other teams are informed. This is the end goal of AI-powered marketing strategies, as you can leverage first- and third-party data to give marketers an AI partner with that will provide relevant data throughout the buyer’s journey.”


This article is written by Michael Rodriguez and originally published here

How is AI (Artificial Intelligence) Changing the Digital Marketing Game?

Artificial intelligence has taken the digital marketing world by storm. This post sheds light on how AI has impacted digital marketing, with the help of its prominent use cases.

Artificial intelligence (AI) was just an ambiguous term in the realm of digital marketing a few years ago. Today, when AI is delivering exceptional results, marketers no longer feel hesitant to embrace it.

In a survey commissioned by MemSQL, out of 1600 marketing professionals, 61% of them considered machine learning and artificial intelligence as crucial data initiatives. Another 2018 Salesforce survey revealed that an impressive 84% of marketers have already adopted AI — up from 29% in the preceding year.

This year-after-year growth has surpassed other emerging technologies such as marketing automation and the Internet of Things (IoT) that marketers continue to adopt.

Join us as we take a deeper look into how AI is revolutionizing the digital marketing game, as we know it.

Improved User Experience

Great user experience is the mark of a successful digital marketing campaign. Prospects are more likely to convert when they can resonate with the content. It is what turns loyal customers into brand evangelists. And this is where AI can help enhance customer experience.

Marketers can analyze AI-generated data to determine which form of content is the most relevant for their target audience. Factors such as past behavior, historical data, and location can be used to recommend the most valuable content for the users.

An example of this capability can be observed in online shopping experiences. We all know how Amazon shares relevant products to buyers based on views, purchases, and previous searchers. That’s artificial intelligence at work!

Another app has gone above and beyond, allowing users to virtually “try on” clothes without actually visiting the store. This not only translates to higher engagement, but also lower product returns, and less disgruntled customers.

Predictive User Behavior

Artificial intelligence can not only examine past customer behavior but also predict the future behavior of existing and new users. Through data management platforms (DMPs), it can gather third-party data across the internet and not just from the company’s website.

Therefore, businesses can apply these insights to personalize their digital marketing strategy and campaigns. Apart from that, AI can help identify the leads with the most potential to convert. Businesses can then devise compelling digital marketing strategies for their highly qualified prospects.

With new algorithms, the accuracy of data is anticipated to get more efficient. Predicting the ROI and determining sales forecasting will inevitably become a lot more convenient in the future through these innovations.

Real-Time Customer Support

Quick resolution of problems and queries is what drives customer support. For this reason, many companies have introduced AI chatbots on their websites and social media channels to communicate with hundreds of thousands of visitors simultaneously.

According to a Business Insider report, almost 40% of internet users across the globe prefer interacting with chatbots compared to virtual agents. Incorporating chatbots in the digital marketing strategy would allow companies to reach potential customers as well as retain existing ones.

Some of the simplest queries such as order status can be managed by AI chatbots. By reducing the wait time, businesses can considerably increase overall customer satisfaction.

Optimized Email Marketing

As established earlier, personalization is a critical aspect of digital marketing. With the help of AI, brands can run personalized email campaigns. Creating engaging, relevant emails by including product recommendations based on user behavior is a tried and true recipe for success.

AI can help predict what type of images, design, subject lines, and messaging would generate better results during the campaigns. Not just that, brands can deliver the right message to the right users at the right time by leveraging artificial intelligence in email marketing.

Content Marketing

By embracing AI in content marketing, companies can obtain the desired ROI. The technology allows them to determine the type of content that resonates the most with their targeted demographic.

As a result, companies can allocate more resources into creating that form of content. For instance, a study indicates that 40% of millennials engage with video content the most. Hence, if the target audience is dominated by millennials, video content should be the primary focus.

According to the same study, video marketing comes next to blogs, where the latter remains the most prevalent form of content marketing.

Wrapping Up

With the greater accessibility of artificial intelligence, more and more brands are embracing it within their digital marketing strategy. The fact that AI provides timely customer service, relevant recommendations, and enhanced user experience is irrefutable.

For businesses, it offers valuable insights that are key to making informed decisions.


This article is written by Ruhi Van Andel and published here