Data tells us what’s happening. Stories tell us why it matters in the moments that matter.  AI can generate content and personalize experiences in real time. Genuine connection comes from human experience, perspective, and emotion and not algorithms.

That matters because storytelling remains one of the most effective ways to build trust, engagement, and growth. Story-driven marketing can increase conversions by as much as 30%, while 81% of consumers say trust is essential before making a purchase. Consumers are also far more likely to engage with brands whose stories resonate with them personally.

The Art: building authentic connections

Effective storytelling is built on trust. A brand’s narrative must reflect the experience it delivers and the values it represents. As customer journeys become more complex, storytelling must be consistent across every touchpoint and channel. When people connect with a brand’s story, they are more likely to become advocates who share with, and influence others. 

The Science:  why stories drive impact

Our brains are wired to respond to stories. Stories create emotional engagement in ways facts alone cannot. Without them, brands struggle to cut through noise, build loyalty, and differentiate themselves from competitors.

Yet the most important ingredient remains human: authenticity.

Next chapter: AI, video, and immersive experiences

Technology is expanding how stories created, accessed, and delivered.  Video remains a preferred storytelling format for marketers, with AI enabling more personalized experiences by adapting content to individual preferences and behaviors.

Marketers can connect effective storytelling with omnichannel digital orchestration by using centralized data and modular content systems to deliver a unified, evolving narrative across every customer touchpoint in a consistent manner, tailored to different audiences. This requires an insight led and data driven approach internally and with external agency partners.

Setting up for success: pairing effective storytelling with efficient, compliant enablers

Having a great narrative isn’t enough. Brands must also think through, and align, how to harness the right MarTech stack including data, AI, and analytics and then pair this with the right internal governance and externally facing media / omnichannel customer engagement plan. A few critical successes factors include:

• Identity resolution: use a Customer Data Platform (CDP) for identity resolution to recognize users across devices
• Digital asset excellence: store modular creative assets in a central repository pushing consistent messaging dynamically
• Mapping narrative roles to channels: assign specific parts of your brand narrative and conversion stage to core channels
• Automate context-aware personalization: adapt the storyline based on user actions, preferences via AI and real-time data
• Enforce brand governance: define and align messaging playbooks / standards and automated rules with delivery platforms

Center of gravity: the customer / consumer / patient

The future of storytelling isn’t human versus AI. It’s human creativity amplified, curated, and rendered more efficient by AI. The brands that win will be those that use technology to scale relevance while remaining grounded in authentic experiences, genuine values, and stories people actually care about. AI can help tell the story, but only humans can make it matter. Part of this is ensuring that internal stakeholders and external partners have an aligned view of customer insights and brand customer experience vision, and how that ladders to the brand’s goals and objectives.

Over 59% of searches now end without a click to a website (aka, ‘zero clicks’ trend). The search landscape is undergoing its most significant shift since the rise of Google. As AI-powered search experiences increasingly deliver answers instead of links, visibility is no longer determined solely by rankings—it’s determined by whether your content is selected, synthesized, and cited.

For marketers, this means the conversation is moving (has moved) beyond traditional SEO toward Generative Engine Optimization (GEO). Success is no longer about winning a keyword; it’s about becoming a trusted source within an AI-generated answer – garnering significantly stronger engagement and conversion from the traffic they do receive.

Hair loss illustrates this shift perfectly. Consumers are moving from simple searches like “best hair loss treatment” to nuanced questions about efficacy, safety, and outcomes. AI engines increasingly answer those questions directly, pulling information from multiple sources and presenting a synthesized recommendation. Brands that are absent from that answer are effectively invisible.

At the center of this change are tokens—the building blocks AI systems use to process information. In an AI-first buying journey, content must be designed not only for humans, but also for machine interpretation. Structure, clarity, and authority have become competitive advantages.

For healthcare brands, the implication is clear: content strategies must evolve from keyword optimization to answer optimization. The winners will be organizations that create authoritative, evidence-based content that is easy for AI systems to understand, trust, and cite.  In the hair loss brand example, this may include:

• Structuring content for machine consumption. Clear headings, tables, FAQs, bullet points, and schema markup help AI systems quickly understand and extract key information. (e.g., How much shedding is normal? What are the main causes of hair loss?)
• Answer questions directly. Content that provides clear, authoritative answers early, and demonstrates topical expertise is more likely to earn citations in AI-generated results. (e.g., which treatments are FDA approved? Which products are safest to use?)
• Build around real consumer concerns. Create content that addresses the questions people are actually asking, not just the keywords marketers want to rank for. (e.g., Does finasteride affect blood pressure? Can topical minoxidil cause a racing heart?)
• Consider a ‘bimodal’ website approach.  Create content that matches the stage of Search and minimizes potential GEO bottlenecks (e.g., visuals) in the early-stage content.

In a world of AI-generated answers, being found is no longer enough. The new imperative is to become the source.

I was thrilled to collaborate with Nancy Phelan, SVP Customer Engagement at Trinity Life Sciences, on this post! We had impassioned conversations about this over a few dinners, and decided to work on this post (reprinted here) as part of Trinity’s “One Chapter Ahead” blog series.

As Punxsutawney Phil’s groundhog prognostication nears on February 2nd, I thought it fitting to focus on ‘the shadow’ (org) conundrum which for many re-occurs as its own vexing ‘groundhog day’.

Perhaps one of the sure-fire signs of looming gloom & doom (and potential failure), is the shadow organization.  This can take several forms from passive to aggressive, from good intentions to being a harbinger of ‘death’ for teams, tasks, and organizations. I’ve rarely seen a positive outcome from shadow orgs or efforts.

WHAT is a shadow org? A shadow organization is a hidden part of an organization that is not widely known / discussed or necessarily aligned to. It can be made up of informal relationships, unwritten rules, and hidden influencers. And/or, they can be large scale efforts that are embedded formally in ways of working or possibly in parallel to current (and likely duplicative) processes and operations. In all cases, they often include alternative systems, ways of working, and talent or solution providers.

WHY are they employed? Aside from confidence issues, generally shadow orgs exist because results, speed, or alignment are lacking (or all three) and are often spun-up with consultancies working ‘on’ and not ‘in’ the business, often for exorbitant costs and resources. On a smaller scale, specific people, teams or functions may use non-sanctioned partners or technologies to circumvent barriers to achieve goals. Again, this can be for good results/intent and not necessarily bad, such as standing up what ‘good looks like’ or achieving urgent go-to-market / launch needs. It is critical to make the distinction from pilots, which are vetted, aligned, and ideally embedded initiatives designed to prove out a use case and solidify KPIs, strategy, and operational imperatives for adoption and scale.

The WHO…is often the key problem. Unlike pilots or tests, shadow orgs can be fatally flawed for many reasons rooted in inadequate management and governance, which is a derivative of people:

• Insufficient (or non-existent) alignment, process / workflow design, or talent
• Not reporting to the appropriate functional lead/team
• Lack of vetting, inclusion, and traction with key stakeholders
• Being designed by consultants or groups lacking in org or capability expertise
• Murky commitment or understanding of what it takes to be successful, and how long that may take

HOW are shadow orgs disruptive? Without thoughtful design, governance, and proper management shadow organizations can be disruptive to company life, performance, and culture – not to mention impact. ‘Negative norms* can run rampant within companies as a result, often undermining company culture, performance, and potentially talent retention. As boundaries are crossed, and functional roles and systems are duplicated, a ‘downward spinning spiral‘ can emerge, mystify, and cause complexity. At a simplistic level, the existing or origin function or process can become obscured or lost – and ultimately may conflict with the shadow org intent.

WHEN to take action: The best ‘Rx’ is to contract within teams and leadership to avoid this pitfall and know when to spot shadow orgs or dynamics early and diffuse or contain them with systemic and sustainable solutions.  Urge leadership to have confidence in, and support, the longer-term picture with an ‘above the line’ path to get there with proper resources. This may indeed require outside support (not substitution) and change which is by far less scary and likely more effective in having a desired impact ‘stick’ and scale.

Transformation and ‘change resilience’ requires people working openly with a collective success, grounded in data-driven performance. This includes identifying and upskilling the talent that will operationalize and scale the capability or function. Not doing so may bring, in groundhog-day terms, may bring more long winters than early springs, as well as that ‘groundhog day’ deja vu!

One of the most annoying Cx ‘leakages’ I find is not connecting to existing value – which is more than a missed opportunity, it is unrealized impact. After focusing on the right questions to solve for the business and customers, it is vital to connect (all) the dots along the customer journey.  One of my top non-pharma offenders, which is also one of my top personal brands, is BMW.  This is a brand with a high lifetime value, ample resources, and enduring if not hallowed brand love – so why can’t they get out of their own way and have a consistent and connected customer journey?  

A recent example:  people are literally blown away that my BMW credit card reward points can be applied to car payments (brilliant!) – we haven’t had to actually make a payment in two years!  A friend actually purchased a BMW for the first time because of this, but when she went to several dealerships for test drives – no one knew about it and she literally had to ‘Google it’.  BMW does very little cross-marketing of this, not even at the point-of-sale, much less as an acquisition driver. The credit cards are (in theory) a shining example of product relevance – tailored offerings for cars vs. motorcycles, discounts or credits on service, offers for performance driving courses or classes, but the potential is obscured and under-realized.

Other personal examples:

• Promo mailers for service about cars no longer owned.
• Financing offers on cars purchased outright.
• Knowing (far) more about a new model than dealership staff.
• BMW loaner cars only being given after purchasing a new BMW, and not after used BMW car purchases with higher mileage and in need of trade-in (even though my husband has restored and/or bought about 50 BMWs).  
• Dealerships not knowing about or understanding European delivery (no longer offered), even though it is/was one of the highest forms of brand love and (fantastic) immersive brand experience.
• When asked to test drive a manual (stick shift) car, the sales reps replied, “Oh you don’t want that, it’s a lot of work”, even though I brought up the BMW ‘art of motoring’ brand narrative.

What’s the fix? The brilliant basics, but across and inclusive of all touchpoint silos internally and externally. This means: thorough content audit and customer journey mapping, and in particular – aligning your data into a cohesive data lake with a well thought our analytics / AI model. This takes: a champion with visibility and ideally governance across silos, capabilities, and Cx engagement planning inclusive of content execution and ongoing optimization.

Look, I love this brand and even almost worked there so I could tackle these challenges.  Consumer goods customers should in theory never expect to know more about a product offering than the front-line sales representatives.  Looping back to the patient perspective, patients don’t generally expect to know more about products and conditions than physicians or pharma co’s, so we have to work much harder as an industry to help them and to connect the dots to all the value we can provide beyond the product itself.    

Why is Customer experience (CX) so allusive? Why has the healthcare industry always lagged in connected end-to-end CX outcomes? Which companies or brands are fearless in CX actualization and innovation, and what can we learn? Why is sustained and systemic organizational change so hard?

Of the 30% of companies that achieve the intended company or customer transformation, only 5% hit it out of the ballpark¹. Compounding this stark reality, according to BCG², “the share of innovation-ready companies was 20% in 2022; and was 9% in 2023”.  When patient outcomes are at stake, curating a personalized, meaningful experience in the micro moments that matter is an overdue cost of entry. Studies show that improved CX can lead to a 15-20% increase in sales conversion and up to 3x shareholder value growth. However, pervasive challenges impede progress, particularly in healthcare.

Eighty percent of healthcare professionals attribute impact to CX, but with 89% of U.S. patients turning to Google before consulting a doctor³, the importance of connected, meaningful customer experiences has never been more critical. Many organizations face relentless pressure to do more with less, underperforming campaigns, and an inability to scale. The pharma industry, for example, has consistently lagged in achieving end-to-end CX transformation.

I’ve experienced firsthand the never-ending barriers obstructing lasting progress: agencies often work on the business but not in it, underutilized technology systems, operational silos, ‘anti-bodies’ to organizational change, and talent challenges. To break through, leaders must embrace a holistic strategy combining talent, systems, and innovative capabilities to truly crack the CX code and drive results. Many companies do achieve success in Cx, but generally this may be partial (e.g., campaign or audience specific) or under-realized in impact.

I’m a continual learner, and seek to apply what’s working well and obsess in optimization. In starting this blog I hope to share (and learn) pragmatic, prescriptive, and precise customer experience paths in bite-sized, focused topics and examples. Let me know your thoughts!

Sources:

¹ McKinsey: https://www.mckinsey.com/capabilities/transformation/our-insights/common-pitfalls-in-transformations-a-conversation-with-jon-garcia

² BCG:  How Companies Can Get Their Innovation Mojo Back – https://www.linkedin.com/pulse/how-companies-can-get-innovation-mojo-back-boston-consulting-group-mtase/

³Eligility: https://ictandhealth.com/news/4-tips-for-doctors-who-see-patients-already-diagnosed-by-dr-google#:~:text=According%20to%20a%20report%20by,to%20do%20with%20medical%20knowledge.

Customer experience can be a bottomless pit of opportunity and complexity.  Getting to the bottom of it (or going in the right direction at least) is directly tied to asking the right questions early and often – so let’s start there. Using pharma terms, there is a ‘fair balance’ product label implied in the efficacy, side effects and adverse events that can come with large scale CX transformation:

• Efficacy:  What are the clear benefits? Did you conduct enough clinical trials and testing before launching? How will you measure or prove success? Will it keep working as intended?  Are people (companies/customers) taking it as directed? Is your team focused on outputs and not outcomes?
• Side effects:  Is there a clear, consistent understanding of what customer experience is and what it takes? Is the internal gauntlet of alignment or delivery preventing or delaying success?  Do you have a good plan or strategy but lack the funding, resources, or technology/data to deliver? Is right talent in place, and do they believe in the vision? 
• Adverse events:  Is the transformation required to achieve targets or needed change causing new symptoms or a fatal lack of confidence? Are key stakeholders or leaders developing ‘antibodies’ to the process? Are local market teams going ‘off-label’ and prescribing their own solutions or ways of working? Does leadership at the top see the tangible gains or is impatience germinating ‘org-design over-haul syndrome’?

So many customer experience moments and outcomes (good and bad) are shaped by the questions asked, or not asked, early on. The well-known Einstein quote applies here: “If I had an hour to solve a problem and my life depended on the solution, I would spend the first 55 minutes determining the proper question to ask… for once I know the proper question, I could solve the problem in less than five minutes.” Asking the right questions seems easy, but it’s the most common mistake I have seen from small to large companies – it is a skill set that takes EQ, and not just IQ, and hands-on experience.

Upcoming post topics:  change resilience, defining customer experience, marketing as a science, connecting the dots with data and technology, putting the customer at the center.