President and Chief Strategist
September 18, 2019
Artificial Intelligence — Super Hearing for Healthcare Marketers: Real-World Examples of Creating Value for Commercial Organizations
A Gartner study published in June 2019 reports that 34% of life science chief information officers (CIOs) value AI as a “top technology game changer.” However, organizations struggle to effectively leverage AI. Most CIOs (63%) cannot find a use case, create a strategy, or secure funding for an AI project. Nearly half of the CIOs cite confusion in selecting vendors as a hurdle to applying AI. Gartner recommends that CIOs study examples of AI-related commercial successes. To support this, Gartner listed agencies, including Arteric, that are building value by applying AI technology in commercial operations.1
The Arteric team created this slide presentation and supporting commentary to provide healthcare commercial, clinical development, and corporate communication leaders with practical examples that may help them make wise choices about whether to apply AI, and if so, how. The examples illustrate how AI accelerates identification and validation of critical market insights. You’ll also learn what actions to take today to succeed in a future driven by AI, natural language processing, and voice interfaces.
If you have questions about the presentation or how to determine if AI would enhance your campaigns, the Arteric team is happy to answer them. Call us at 201.558.7929 and ask for Hans.
Signals. Patterns. Insights.
[Slides 1-5] I love exploring the underwater caves in Madagascar. Learning about Madagascar’s history and spending time with the populace doubles the pleasure. Slide 3 was taken during a trip in 2015, when villagers asked us to bring English-to-French dictionaries, which they plied extensively. When we returned in 2016 (slide 4), cellphone towers had appeared, and villagers had replaced their dictionaries with cellphones. Technological change was evolving as rapidly for villagers in Madagascar as it was for healthcare marketers in corporate headquarters.
[Slides 6-7] AI’s ability to evaluate multiple variables within massive volumes of marketing data enables this technology to detect weak behavioral signals that evade human analysis. AI’s processing power then extracts patterns of audience needs and behaviors that analysts convert into insights to guide brand strategy.
Marketers aren’t alone in leveraging AI’s signal-detection and pattern-recognition capabilities. In April 2018, the FDA approved the first AI-powered medical device for commercial use. IDx-DR is an AI-based diagnostic system for the autonomous detection of diabetic retinopathy (DR), a leading cause of blindness.2 DR-induced blindness is preventable, but only half of the at-risk population pursues diagnosis from a specialist. By providing general practitioners (GPs) with augmented diagnostic capabilities normally reserved for an ophthalmologist, IDx-DR moves specialized care closer to the people who need it. The expectation is that more people with diabetes will be tested for DR if they are examined during visits with their GPs. The FDA has since approved several more AI-powered medical devices.
Voice search increases the complexity of SEO and SEM campaigns
Search is moving to voice
[Slides 8-12] In our examples, AI’s utility revolves around signal detection and pattern recognition. To appreciate why AI is so frequently discussed as a marketing tool, we have to discuss the technology in the context of the rapid changes underway in online search. Voice-driven search is replacing keyboard-entered search. Gartner predicts that by 2020, 30% of all Web browsing sessions will be done without a screen or a keyboard.4 Advances in voice recognition technology and the ubiquitous presence of smartphones — 1.38 billion units shipped worldwide in 2018 — are fueling this paradigm shift.5 Though 1.38 billion represented a 1.9% decrease in shipments year over year, Internet traffic on smartphones continues to increase significantly. By 2022, smartphones are predicted to generate half of all Internet traffic.6
Healthcare professionals (HCPs) and consumers aren’t waiting for 2020. Almost 1 in 4 HCPs in the US (23%) are currently using a voice assistant for professional reasons. Of this 23%, more than three-quarters (78%) use search for critical information on treatments, dosing, diagnoses, disease, and other clinical information.7 Overall, 17% of EU5 physicians utilize voice assistants; in Spain, 24% leverage voice.8 Consumers are also migrating to voice search. Twenty percent of all mobile queries are made by voice, and this number will likely increase rapidly given the dramatic global growth of voice assistants.9 In the US, 41% of consumers own a voice-activated speaker.10 In Europe, the Middle East, and Africa, year-over-year growth increased 1126.7% during Q3 2018.11
Ranking at position zero replaces ranking on page 1
[Slides 13-14] Voice-driven searches produce 1 spoken answer winner, not 10. This winning search position is called position zero. Currently, voice commands to scroll through a list of audible search responses that follow position zero do not exist, because the average human working memory isn’t capable of evaluating a long, complex list. Combine this with Gartner’s prediction about screenless devices and it’s clear that marketers face an imminent future where being the featured search response will be essential to getting their content heard.4
Brands have an additional incentive to ensure that their content is featured at position zero. Research indicates that 2.6% of Google’s rich-snippet search answers are incorrect or irrelevant. Ensuring that brand content isn’t superseded by imperfect third-party information is a key challenge that brands face.12
Natural language inquiries dominate
[Slide 15] Google reported in 2016 that 70% of all voice searches entered into Google Assistant were expressed as natural-language questions.13 Natural language, or conversational language, is how people speak with other people. “How much aspirin should I take?” is an example of a natural-language voice search. Typing the keywords “aspirin” and “dosage” into a Google search window is the antithesis of natural conversation.
Natural-language inquiries require search analysts to extract context and intent, not just keywords, from marketing data. In addition, people can ask the same question in many different ways. Both characteristics increase the volume and complexity of data processing required for search analysts to extract insights from marketing data (eg, pay-per-click data and analytics data from the Google Search Console tool).
This increase in data volume and complexity encounters the limits of human-based data analysis quickly, making it impractical to scale personalized content and experiences.
AI accelerates identification and validation of market insights
[Slide 16] Arterics objective is to position our clients for success today and 18 months down the road. To accomplish this, we pay close attention to what Google is saying. Google has stated that it may give priority in the search results to content that is relevant and authoritative and that answers a question or enables the searcher to complete a task. Arteric analysts scour brand marketing data to find insights that enable brands to create content that satisfies these factors.
Insight discovery without AI
[Slides 17-19] To assess the effectiveness of a brand’s content strategy, Arteric analysts evaluated data from 55,000 Google searches. We identified 1,700 brand-related questions, of which 235 were appropriate to be addressed by the brand’s content and that we believe would pass medical, legal, and regulatory review. We performed deep analysis of the search engine result pages (SERPs) by evaluating 175 of these questions to determine if Google identified and served an accurate answer from the brand’s content. The results: brand content appeared in the search results 114 times but answered only 4 questions with relevant, authoritative content.
[Slide 20]Uncovering this content gap was an essential insight, but it was only half the battle. The next step was to execute on what we had learned.
[Slides 21-22] Ironically, the brand had created and published accurate answers to many of the questions on their websites. However, Google didn’t identify the correct pages to serve to match the user’s query intent. To address the asymmetry between the query intent and the ranked content, we implemented and continually optimized a content strategy to develop highly targeted, detail-rich content. We crafted custom content that mirrored the audiences’ behavior and preferred lexicon. The result was that traffic and engagement increased significantly. Applying state-of-the-art SEO practices to the new content, as well as to existing content, further closed the gap, increasing organic site-wide search traffic by 202%.
AI scales. Human research analysis does not.
[Slides 23-27] It took 80 hours of analyst research to identify this huge customer experience gap. Being software engineers as well as healthcare marketing strategists, we’re always asking ourselves if there’s a technology solution that would enable us to work smarter and faster. Arteric analysts are as good as they come; but like all humans, they have limitations when it comes to data analysis. It’s challenging to cost-effectively analyze much more than 50,000 to 60,000 data points. And human beings can evaluate only so many variables within the data simultaneously.
These issues limit humans’ ability to detect trends, especially when signals are weak and scattered. We sought a technology to overcome these limitations. This brought us to AI.
A leading manufacturer of homeopathic OTC remedies for colds and cold-related ailments asked us to help drive engagement, boost signups to their email list, and increase revenue. We then searched for ways to improve on these results. Based on the available pay-per-click and Search Console data, the strategy we selected would require analyzing a minimum of 250,000 data points. This would require at least 300 hours of human data analysis.
We applied Arteric’s proprietary LGF* AI platform to uncover how audiences in the United States were inquiring about cost and other issues related to the brand. We analyzed 250,000 searches in 2.5 minutes, a nice speed boost compared with the 80 hours required to evaluate 55,000 data points in the past.
As the speed at which we could interrogate data increased, we invested more heavily in tuning the algorithm and scrubbing the data. Overall, there was a net benefit in performance and insight discovery.
Previously, we invested 80 hours to investigate 1 hypothesis. Now we are investing that time to investigate many hypotheses.
Freedom to experiment
Surfing is a perfect metaphor for the application of data science and AI in healthcare digital marketing. If you paddle in too early ahead of the wave, you get caught on the inside and crushed. It takes you forever to paddle back out, and you miss lots of opportunity. If you paddle in too late, the wave passes you by and you have to go to the end of the lineup and wait your turn, thus missing lots of opportunity. But if you paddle in at exactly the right moment and match your speed to that of the wave, then you catch the ride of a lifetime and you can take advantage of all of the opportunity.
AI and ML give us the opportunity to paddle into many more waves and match our content to our visitors’ behavior. These technologies enable us to compress the collect > analyze > execute cycle. This means that your brand will have more opportunities to identify and catch the perfect wave.
Two AI tools. Two answers to increase engagement.
[Slides 28-31] The LGF AI platform extracts from marketing data an essential insight that Arteric strategists leverage to increase online engagement. Arteric’s proprietary LGF AI tool uses latent semantic analysis, which is a form of natural language processing, to calculate the similarity of verbatim search data. This enables our analysts to group like searches and build maps of our audiences’ preferred lexicon. It also enables us to identify anomalous language that may present an opportunity for the brand to achieve competitive advantage. Simply stated, the LGF helps us to understand exactly how people search for topics and the type of reflective language required to drive engagement and rank in position zero.
For marketers to execute on this insight, a brand’s content must exhibit sufficient quality and authority signals for Google’s algorithms to conclude that the brand’s content is more authoritative and more informative, and thus more likely to satisfy the specific query intent of the audience.
In order to understand the relative authority and relevance of websites in a competitive search space, Arteric developed a second AI-powered tool, the WEE Word Embedding Analysis Engine. The WEE compares the relative authority of a brand’s website content with that of its competition. The WEE tool measures word frequency and co-occurrence of words and phrases to simultaneously determine the relative authority of multiple websites on all topics they include content about. Arteric’s analysts use the output of the tool to determine the topics that need to be strengthened in order for our customers to dominate a topic in search and to drive increased engagement with the target audience.
By analyzing (1) audience search behavior and (2) our clients’ content and that of their competitors, we build a bridge between audience behavior and brand content to maximize audience engagement.
It takes a team
Multiple talents are needed to develop, apply, and optimize an AI solution. Brand business owners and strategists, data experts, software developers, and a visionary strategist to connect the dots comprise a complete team. The common thread that binds the team is that every participant — internal or external service provider — must have expert-level familiarity with the nuances and intricacies of the business problem that the AI solution must solve. Since 2016, Arteric has been assembling that team.
Continue the AI conversation
I discuss these and other elements of AI success in the podcast “How Artificial Intelligence Can Dramatically Improve Your Pay Per Click Campaigns,” presented by Life Science Marketing Radio. AI as a tool for marketers is in its infancy, but the Arteric team is optimizing its use in healthcare campaigns. We’re here to answer your questions about AI or other marketing technology, so don’t hesitate to call us at 201.558.7929.
- Gandhi A. Life Science CIOs Can Accelerate Commercial Effectiveness With New Applications of Artificial Intelligence. Gartner Research website. https://www.gartner.com/en/documents/3935365. Published June 2019. Accessed September 16, 2019.
- FDA permits marketing of IDx-DR for automated detection of diabetic retinopathy in primary care [press release]. Coralville, IA: IDx Technologies. April 12, 2018. https://www.eyediagnosis.net/press-releases/press-release-fda-permits-marketing-of-idx-dr-for-automated-detection-of-diabetic-retinopathy-in-primary-care.
- Carfagno J. 5 FDA approved uses of AI in healthcare. Docwire website. https://www.docwirenews.com/docwire-pick/future-of-medicine-picks/fda-approved-uses-of-ai-in-healthcare/. Published July 18, 2019. Accessed September 16, 2019.
- Levy HP. Gartner predicts a virtual world of exponential change. Gartner Research website. https://www.gartner.com/smarterwithgartner/gartner-predicts-a-virtual-world-of-exponential-change/. Published October 18, 2016. Accessed September 16, 2019.
- Scarsella A, Stofega W. Worldwide smartphone forecast update, 2019–2023. Framingham, MA: IDC. https://www.idc.com/getdoc.jsp?containerId=US45235019. Published June 2019. Accessed September 16, 2019.
- Cisco visual networking index: forecast and trends, 2017–2022 white paper. Cisco Systems website. https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html#_Toc529314188. Updated February 27, 2019.
- Paging Dr. Siri. Decision Resources Group website. http://www.drgdigital.com/ebooks/paging-dr-siri-physicians-and-the-rise-of-voice-assistants. Published August 16, 2017. Accessed September 16, 2019.
- Siri and Alexa are already changing how Europeans get health info, DRG Digital | Manhattan Research data show. Decision Resources Group website. https://www.prnewswire.com/news-releases/siri-and-alexa-are-already-changing-how-europeans-get-health-info-drg-digital--manhattan-research-data-show-300612321.html. Published: March 12, 2018. Accessed September 16, 2019.
- Meeker M. Internet trends 2019. Bond website. https://www.bondcap.com/report/itr19/#view/title. Published June 11, 2019. Accessed September 16, 2019.
- Smart speakers ‘reach critical mass’ with 41% penetration. Inside Radio website. http://www.insideradio.com/free/smart-speakers-reach-critical-mass-with-penetration/article_e18576c4-124c-11e9-85b9-2bd2f048ecc9.html. Published January 7, 2019. Accessed September 16, 2019.
- Smart speaker sales explode in EMEA with more than 3.3 million devices shipped in 3Q18, according to IDC. IDC website. https://www.idc.com/getdoc.jsp?containerId=prEMEA44576018. Published December 20, 2018. Accessed September 3, 2019.
- Nicas J. Google has picked an answer for you—too bad it’s often wrong. Wall Street Journal. November 16, 2017. https://www.wsj.com/articles/googles-featured-answers-aim-to-distill-truthbut-often-get-it-wrong-1510847867. Accessed September 16, 2019.
- Huffman S, Chandra R. Your Google Assistant is getting better across devices, from Google Home to your phone. The Keyword blog. https://blog.google/products/assistant/your-assistant-getting-better-on-google-home-and-your-phone. Published May 17, 2017.
Category: Opinions and Insights