On Hawaiian, I have distinct memories of
stir-fry (whether chicken or beef, which always came with a generous helping of red pepper),
chocolate cake, and little plastic packages of butter shaped like a flower. On Alaska Airlines, I’d be served an omelet breakfast with
reindeer sausage, giant ice-cold muffins, or lasagna with those little semi-rigid paper tubes of salt and pepper, and the inevitable
prayer card containing a verse from the
Book of Psalms (Alaska faithfully distributed the prayer cards on their meal trays right up until 2013).
You could invariably smell the meals cooking before that magical announcement: “Ladies, and gentlemen, we’ll be coming through the cabin to serve a hot meal shortly…”
It was never lost on me that the technology to serve a tray of food to a diner in a pressurized metal tube, seven miles up, hundreds of miles from where the meal was originally assembled and cooked.
But how do they do that? We’ve all seen the carts and the plastic meal trays and the funny-looking scissor trucks that load the food and beverages in the airplane, but how about the rest? I talked with a couple of airlines, and even visited one of their catering facilities to learn a bit more.
Meal Planning
Alaska was once known for over-the-top onboard meals. In the late 1970s, they were a tiny regional airline just expanding south of
Seattle for the first time, and in order to compete with larger airlines, they introduced a lavish dining concept they called
Gold Coast Service. If you were a coach passenger flying from
San Francisco to Anchorage via Seattle, you’d have a lovely
prime rib dinner on the two-hour flight up to Seattle. You’d change planes, and then, if you wanted, you could have a second massive helping of prime rib on the flight up to Anchorage.
Alaska was so committed to better meals that, when it came time to order new aircraft, it opted for a seating configuration on its
MD-80s that allowed for larger galleys to accommodate its elaborate dining.
The early 1990s recession hit the airline industry hard, and competition on the West Coast heated up. In response, Alaska progressively
trimmed back its onboard meal service before finally switching to a buy-on-board meal model in 2006.
I chatted with
Todd Traynor-Corey, the Managing Director of Guest Products at Alaska Airlines, about how Alaska plans meals for its passengers. Alaska still plans meals somewhat differently from many airlines, he says. Alaska likes to infuse seasonal flavors into its dining, so it still has a quarterly menu-planning session, compared to other carriers that might plan their menus for an entire year with just one or two cycle changes. A sample summer dish, he shared, would have
strawberry rhubarb ice cream from the
Portland, Oregon-based Salt & Straw, with
cinnamon crumble.
The planning session comprises 100 to 175 dishes for
First Class and Main Cabin, from snacks and lighter meals to full breakfast, lunch, and dinner entrees. The team evaluates how they look on the plate, taste, and importantly, how complicated it would be for caterers to source and load, and the ease of serving for the in-flight crews.
Flight Attendants used to spend more time plating dishes in-flight, which he said could be difficult on shorter flights or during turbulence, so they worked with their catering partners to create dishes that required less prep time in-flight.
He also noted that some development goes on in the air. The team will take samples of coffee and wine onboard and test them in the in-flight environment, because the aircraft’s dry air and pressure mean food tastes differently than on the ground.
For a glimpse behind the scenes, I visited the
Cathay Dining facility at
Hong Kong’s Chek Lap Kok International Airport. They take sanitation very seriously at the facility—we were swaddled head-to-toe in white jumpsuits, shoe covers, and face masks to be allowed in, and we couldn’t take any photos or videos while in the facility (because catering instructions from customer airlines—posted all over the facility—are proprietary).
It’s a massive facility, and it’s more than just a kitchen. There are also huge storage facilities for frozen, chilled, and dry goods, and washing facilities. When aircraft from Cathay Pacific or one of Cathay Dining’s contracted airline customers come in, the carts are offloaded on the big scissor trucks directly from the aircraft galleys. Trash from inbound international flights is heated before being disposed of to kill any foreign pathogens, and the carts and dishes are separated and sent through industrial washing machines to be cleaned and staged for their next flights.
There’s an entire room dedicated to fruit—and it smelled delightfully like it. Workers were clustered around tables speedily hand-slicing watermelons (to spec, of course) from a massive crate of them marked “imported from southern China.”
Another delightful-smelling room was the bakery, where bakers worked producing breads, muffins, pastries, and cakes for various airline customers, or staged pre-packaged bakery items for the airlines that preferred to source their own and send them to the facility instead of having them baked onsite.
Perhaps the most interesting process was the
omelet machine, which can make about 6,000 omelets per day. The machine is a circular table lined with oiled frying pans, with eggs added as the table slowly turns. The omelets fry for about 60 seconds, then are flipped out of the pans directly into the thin metal casserole dishes, where they’ll be heated and served onboard. They’re also only cooked to about 75% done, so they won’t end up overcooked, since they’ll be chilled and reheated again before serving.
In another part of the facility, conveyor belts help workers assemble tray setups. Each worker might add cutlery, a bread roll, or a dessert to the tray before the worker at the end of the conveyor belt loads it into the cart. There are also conveyors for the casserole dishes themselves. We watched workers assemble breakfast dishes for
MIAT Mongolian Airlines flights the next day, and I found myself thinking the meals looked so good it was almost an excuse to fly with them someday.
We were also led past cooking stations where chefs tended what seemed an army’s worth of food. At the massive grill station, a chef turned steaks over expertly, with the grill marks so neat they looked painted on. He was an expert with the tongs, working quickly on each steak, for he had several dozen to get through. At a nearby stir-fry station, another worker tossed a massive amount of shrimp noodles.
Many of the meals were for other airlines, but Hong Kong is also the main hub for hometown carrier Cathay Pacific, and their meal standards are exacting. In the airline’s earlier days, standardized menus were the aim, focusing on the cuisines of Hong Kong and
Great Britain, which counted Hong Kong as a colony until 1997.
Once the carts are loaded, Cathay Dining has an automated system. The cart is picked up on a ceiling-mounted hanger system called Power & Free, which keeps the carts chilled and moves them to the staging area where the trucks are loaded to take them to the aircraft. All told, the system can move 12,432 meals per hour.
Once onboard, meals are heated in
convection steam ovens in virtually all cabins, although there are facilities for cooking eggs, toast, and rice to order onboard
Cathay’s First Class cabins. The airline also offers on-demand dining between meal services, and more than a few flight attendants onboard mentioned that the airline’s
burger, one of the available “anytime” items in Business Class, has its own devoted following among the airline’s frequent fliers. I even overheard several of the regulars ordering the burger instead of the regular Business Class meal.
Of course, there are logistical issues to deal with. Just accounting for the dishes is difficult enough, and airline meal planning takes that into account as well. If one of your tray setups includes a reusable hot beverage cup for coffee (like on a breakfast tray), then a tray setup on the return flight must be identical—even if it doesn’t exactly make sense for the meal period—otherwise your coffee cups start to pile up somewhere.
An Inflight Repast
Airline meals can be big business—especially for airlines like Cathay Pacific and Alaska Airlines, which use them as a point of differentiation. Cathay’s focus on meals is necessitated by its extensive long-haul network and fierce competition among Asian carriers—particularly on the quality of their food service. Alaska Airlines is also growing into the international long-haul market and will likely offer free hot meals in the Main Cabin on those flights—the first free hot meals to be served in Main Cabin by Alaska in nearly 20 years.
It’s almost a small miracle if you think about it. While you’re checking in online and getting your bags together for the flight, a team is busy preparing meticulously planned meals, putting together globally sourced ingredients onto plates that have just arrived from far-flung locales, been washed, and put right back into rotation to offer a restaurant-style meal thousands of miles away, seven miles up.
It’s kind of a feat—and oftentimes a memorably tasty one.
Sonder initiates Chapter 7 liquidation
https://www.hotelinvestmenttoday.com/Financials/Debt-and-Equity/Sonder-initiates-Chapter-7-liquidation?
SAN FRANCISCO – One day after Marriott International terminated its licensing agreement with Sonder, the apartment-style rental hospitality company announced it will wind down its operation and initiate a Chapter 7 liquidation of its U.S. business. Sonder also intends to initiate insolvency proceedings in the international countries in which it operates.
At the same time, Sonder took a parting shot at its former partner, Marriott, stating its integration was substantially delayed “due to unexpected challenges in aligning our technology frameworks, resulting in significant, unanticipated integration costs, as well as a sharp decline in revenue arising from Sonder’s participation in Marriott’s Bonvoy reservation system.”
Sonder Interim CEO Janice Sears added, “These issues persisted and contributed to a substantial and material loss in working capital. We explored all viable alternatives to avoid this outcome, but we are left with no choice other than to proceed with an immediate wind-down of our operations and liquidation of our assets.”
In response to Sonder's comments about Marriott's alleged role in its downfall, a Marriott spokesperson told Hotel Investment Today, "Marriott is aware of Sonder’s intention of a U.S. bankruptcy filing. We have worked tirelessly to remain informed about Sonder’s financial situation and develop action plans so that we can work to meet the needs of our guests, which remains our priority. Sonder operates its properties and has made independent business decisions. Marriott does not agree with the characterizations expressed in Sonder’s release and will respond further at the appropriate time."
Late Sunday, Marriott abruptly ended its licensing agreement with Sonder Holdings Inc. initiated last year due to what it called Sonder’s default on its agreement. With the removal of ~7,700 Sonder apartment-style rooms (142 properties) from Marriott’s system, Marriott’s net rooms growth for 2025 is now expected to approach 4.5% (reduced about 45 bps).
Sonder agreed to go public in 2021 with a SPAC backed by billionaire investors Alec Gores and Dean Metropoulos and a $2.2 billion valuation in 2021. It is now reportedly valued at $6.8 million. More recently, it told the SEC it was concerned about its future.
Sonder said in its release about winding down its business that it made comprehensive efforts to evaluate all financing and other strategic alternatives, including a sale of its business and operations, to improve its financial condition.
Sonder said it engaged numerous strategic and financial parties but ultimately was unable to execute a viable going concern transaction for its business and operations or obtain additional liquidity.
Inside Chimera’s ‘sniper-like’ approach to deals
https://www.hotelinvestmenttoday.com/Development/Owners/Inside-Chimeras-sniper-like-approach-to-deals?
The newly formed family firm announced its first acquisition last week. Deno Yiankes talks about the firm’s targeted approach to growth.
NAPLES, Florida — Chimera Hospitality was formed earlier this year as a three-headed family operation with a targeted “sniper-like” approach to acquiring assets.
The Naples, Florida-based hospitality firm, formed by industry veteran Deno Yiankes (who has spent over 30 years at White Lodging) and his sons, Alex and Eric, announced its first acquisition, the voco Sarasota in Florida, last week.
Deno Yiankes said the firm is operating from a solid thesis and has a great idea of what it is and what it isn’t.
“We think this is the right time to be looking,” he said. “You’re not going to see us buy a portfolio of 50, 30- to 40-year-old properties along an interstate… We’re going to be more laser-focused. I call it sniper-like, and we really pick off a few things that we think have high potential. I find that liberating, frankly, versus if I were running a fund right now and having to do some things that maybe aren’t in our best interest from an investment standpoint.”
Yiankes, who sat down with Hotel Investment Today after the announcement, stepped away from his role of president and CEO of investments and development at Merrillville, Indiana-based White Lodging in 2020, with this company formation as the destination. But he said he wanted his sons, who had just graduated from college, to first go out in the hotel investment world for a few years.
Yiankes remains a board member and paid senior advisor for White Lodging. He said he had planned to leave that role by now, but things changed when his mentor, White Lodging founder Bruce White, tragically passed away in 2023 after a battle with cancer, and Yiankes extended his consultant role.
Chimera was founded earlier this year. Yiankes said the company isn’t raising capital but using its own equity and sourcing partners to finance deals. The company wants to be at least 50% on each deal and find a partner like Monroe, Louisiana-based InterMountain Management who went 50-50 on the voco Sarasota. InterMountain will also manage the property.
“Our goal is to be a minimum of 50%. We may be more, but the point is, it’s our own money,” Yiankes said. “We evaluated doing the GP-LP [model] and raising a fund and we convinced ourselves that… we’re going to be capital constrained. One thing I’ve learned is that sometimes it’s better not to have too much money. It’ll force a discipline for us.”
Chimera will grow slow and steady, Yiankes said, with a plan for three to five deals over the next five years.
“That’s our vision and then we’ll see where it goes from there,” he said. “Then it’ll be up to my sons how aggressive or not aggressive they want to go after that.”
Yiankes said the company doesn’t need to scale fast. He just wants to pick the right deals.
“Our cost of capital is fairly favorable, even though we are a startup. We were pleasantly surprised at the three different financing options we got on the [voco Sarasota],” he said.
When asked how Chimera will win deals, Yiankes said it’s more about picking off the right deals.
“It’s not so much how we’re going to win over the next guy. It’s that we only have to pick a few,” he said. “We just want to pick three to five. So, I’m very confident, just based on statistics, that we’ll be able to find them.”
Yiankes said the main driver for forming Chimera was his desire to work with his sons. Both of his sons worked for brokerage firms and then with independent owner-operators until this year. Now he said they are serving as vice presidents of acquisitions and are tasked with finding and underwriting potential deals.
The name is rooted in Greek mythology, with Chimera being a three-headed monster.
Chimera Hospitality completed the acquisition of the voco Sarasota in Florida on October 29.
Inside the Sarasota deal
Yiankes said the trio has been working on the voco Sarasota deal since April and it finally closed on October 29 (the seller and price were undisclosed). He said they love the market dynamics in Sarasota, especially the lack of new supply over the next few years, which easily aligns with the company’s thesis of acquiring high-quality, differentiated properties in a growing market that the company believes are not operating at optimal levels.
“We don’t need to be in the top 50 MSAs. We just want to be in the MSAs that we feel have a little spurt over the next couple of decades,” he said.
“There are only seven hotels in downtown Sarasota, and one of them, a 300-room Hyatt, is in the process of being demolished to be replaced with a Ritz-Carlton-branded residential. So, you have literally 20% of the room inventory going out with no hotels under construction. We have at least a three-year run here, probably more like four, where there’s going to be limited to no supply growth.”
Yiankes said the thesis stems from the belief that there will be muted new supply in most urban markets in the coming years due to the high cost of development.
“Part of our analysis was considering whether we do ground-up development,” he said. “I can think of 20 reasons why, from an investment standpoint, I’d rather buy an existing hotel today, with the right criteria, than go out and build a ground-up.
“If the property is well constructed, if it’s good real estate and it’s in a market that has solid growth metrics, that tells me that I’m probably going to invest in something that’s going to see greater appreciation and faster appreciation than most. That’s what led us to the voco and what we’re going to use as a driving force for our next investments.”
Yiankes said he feels liberated about Chimera’s flexibility with potential investments.
“We’re going to stick with what we consider to be premium-branded property,” he said. “So, you’re probably not going to see us doing independents… We think with soft branding and lifestyle branding today, you can have your cake and eat it too.”
Working with family
The collaboration between father and sons is going very well, Yiankes said, thanks to their unified vision.
“We all see the opportunity and the ability to have different perspectives. The one huge benefit for me is working with two gentlemen that are in their late 20s and seeing and hearing their different perspectives,” he said. “They may defer to me on some things, just based on my experience, but they’re the future. So, for me to be able to be working and hearing their thoughts, I’m finding it very invigorating.”
He said his sons have changed his thinking on design issues, particularly when they walk through hotels, and especially on how to use social media to gain a great perspective on hotel development.
“Two years ago, I would have probably said I would be the gray-haired guy saying to slow down,” Yiankes said. “But I’m finding I’m actually a little more optimistic than they are… In some cases, they’re scratching their heads saying, ‘Why are we spending time on this? We already know the answer.’ And nine times out of 10, they’re right.”
In terms of hold time for assets, Yiankes said he’s cut more from a long-term perspective.
“We’re going to be opportunistic, with a bias toward holding longer rather than shorter,” he said. “Because, by definition, if we believe our thesis, why wouldn’t we?”
When asked about the biggest lessons he learned during his time at White Lodging, Yiankes mentioned his amazement at talking with other hotel investors over the years, who always focused on the art of the deal.
“You talk to them for 60 minutes and 58 minutes is about how they put this great deal together and this financing and this and that and they don’t want to talk about operations,” he said. “I learned from Bruce, that it’s an operating business.
“Your associates at the property level are the ones that drive the value. You don’t do it in your corporate office. You have to appreciate that your operating team needs to be able to focus on operating the hotel and you can’t create distractions for them with all your owner issues. Let them operate the hotels and do what they do best and give them the tools to do that… That’s where magic occurs.”
https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/next-best-experience-how-ai-can-power-every-customer-interaction?
Lars Fiedler is a partner in McKinsey’s Hamburg office, Nicolas Maechler is a senior partner in the Paris office, Andreas Giese is an associate partner in the Riyadh office, David Malfara is an associate partner in the Miami office, and Dominika Kampa is an associate partner in the London office.
By harnessing AI and gen AI to create the next best customer experience, front-runners could generate value for customers and themselves through increased conversion, retention, and upselling.
Imagine your company had an AI-powered engine that could detect when a customer needs help—before they even realize it. And was able to coordinate and sequence customer touchpoints while personalizing communications to get the right message to the customer in the right way.
Through our work with leading companies, we see that some are already using this approach—called next best experience—to impressive effect. With properly-calibrated AI models accessing integrated data sets that span the entire customer life cycle, companies can craft experiences that deliver real value.
The results are impressive: The AI-powered next best experience capability can enhance customer satisfaction by 15 to 20 percent, increase revenue by 5 to 8 percent, and reduce the cost to serve by 20 to 30 percent.
This article explores how the AI-powered next best experience approach addresses critical customer experience issues, details what it takes to build and operate it, highlights case studies that demonstrate its value, and outlines six practical steps for organizations to get started.
What is next best experience?
AI-powered next best experience is a customer experience capability that allows companies to proactively deliver each customer the right interaction at the right time in the right place. This approach differs from the more-common “push” approach, where a company essentially spams customers with offers or promotions.
The next best experience capability uses data and AI to answer the question “What does this customer need most in this moment?” It then delivers a seamless, personalized, and satisfying customer experience that builds loyalty and customer lifetime value (CLTV).1 The AI-powered next best experience approach relies on data analytics, machine learning (ML)- and AI-powered predictive models, recommendation engines, and gen-AI content generation and personalization capabilities (see sidebar for an illustrative example, “How next best experience works: A journey to satisfaction and delight”).
Tackling customer engagement challenges with next best experience
As customer experience has become increasingly digital, managing customer relationships has become more complex. Often, multiple functions—billing, customer experience, customer care, and marketing—interact independently with customers, leading to poor results.
For example, the customer insights team might send a customer survey at the same time as the loyalty team pushes an email to sign up for automatic billing. Marketing, meanwhile, sends a new upselling offer. The customer ends up feeling spammed by the company, potentially ignoring all proactive communications or opting out of marketing consent altogether.
Next best experience can address these challenges by focusing on customer experience as a way to drive value, sequencing touchpoints, and using AI to drive personalization.
Refocusing on experience as the driver of value
The next best experience approach improves customer communication and engagement by providing a meaningful and personalized experience for existing customers. Deploying predictive analytics helps companies know when best to deliver the right messages.
Take, for example, a global payments processor that wanted to reduce attrition among its most valuable merchants: Using a next best experience approach, it built an advanced machine learning model to predict the likelihood of a merchant reducing business within the next seven days.
The model used a vast dataset, drawing on operational, financial, and customer information to build a digital twin of the daily interactions between the processor and each merchant. Once each merchant was scored, cluster analysis then grouped and prioritized the merchants by issue types (such as disputes) or opportunity (such as low working capital).
In the final step, the organization built a large library of interventions. These ranged from sales, such as introducing new products and features, to service, including fee forgiveness and technical fixes. It then mapped these actions to the clusters so that automated actions either protected revenue, reduced attrition, or capitalized on a client opportunity.
The result? The global payments processor estimated that the new system could reduce merchant attrition by up to 20 percent per year.
Sequencing touchpoints
By sequencing customer touchpoints more effectively, a next best experience approach can lead to more satisfied customers, potentially increasing revenue and reducing cost to serve.
For example, a telecommunications company in Europe decided to stop all outbound campaigns to customers who had open complaints, ongoing care journeys, or a high propensity to call regarding service-related topics. This simple act of ensuring that care activities took place prior to any outbound marketing had a positive effect: It drove the company’s net promoter score (NPS) to the same level as the market leader’s NPS and improved both cross-sell and churn rates.2
Deploying AI to drive personalization at scale
An AI-powered decisioning engine that governs decision-making across various use cases, such as new customer acquisition or personalized recommendations, can improve CLTV (Exhibit 1). Even better, an AI-driven next best experience approach improves with each new use case, as customer interactions are fed back into the integrated data set, making decisions more accurate over time.
A major US airline has harnessed AI for predictive customer insights to enable more personalized offers for high-value or at-risk customers. The customer service team did not previously differentiate between customers when offering compensation vouchers for flight delays or cancellations. However, by introducing machine learning models to inform recommendations, customer service agents could prioritize specific customer segments and tailor compensation accordingly.
In this way, the agents could differentiate, for example, between a frequent flyer who has faced three recent delays and a leisure traveler with no recent delays.
This AI-driven move led to a 210 percent improvement in targeting at-risk customers, an 800 percent increase in customer satisfaction, and a 59 percent reduction in churn intention among high-value, at-risk customers.
Constructing a next best experience engine
A next best experience engine can be built on an organization’s existing technology architecture, with an ecosystem of tech partners—including cloud, enabling technology, foundation models, and gen-AI solutions. The next best experience engine consists of four key components: data engineering, advanced analytics, gen AI, and a campaign delivery platform (Exhibit 2).
Data engineering
A solid data engineering foundation brings every customer record into a single repository, providing consistent insights. This process begins by pulling data into a data lake, gathering billing records, customer relationship management (CRM) entries, web analytics, mobile app events, and call center logs. Once ingested, these records are transformed into cleaned and aggregated tables using standardized scripts that prepare the data for analysis.
The tables are typically stored in modern data warehouses. Quality control processes are essential. Automated checks, for example, can detect anomalies (such as missing data or sudden drops in record volume). These controls are accompanied by data lineage tracking, which captures the origin, transformation, and update history of each data element, ensuring traceability for compliance and debugging purposes.
Advanced analytics
On top of the data foundation sits a series of models that predicts behaviors and recommends decisions based on the business context. These include three types of models: 1) propensity models that score how likely a customer is to upgrade, churn, or respond to a campaign; 2) channel models that determine whether email, text, in‑app messaging, or voice calls will be most effective; and 3) value models that calculate the lifetime value or near‑term revenue opportunity.
These models are interpreted through a decision orchestration layer that blends statistical outputs with real‑world operational logic. For example, a customer flagged as high-churn risk might be automatically removed from all promotional campaigns and instead added to a retention journey that involves loyalty offers or service improvements. Conversely, a customer with low-churn risk but high-upsell probability may receive a proactive upgrade message.
Gen AI—and agentic AI
Gen AI creates personalized content that powers the customer experience. Large language models enable dynamic message generation, which includes contextual references, such as recent transactions, service interactions, or usage trends. These messages can vary in tone and detail depending on customer preferences and can be tailored to the delivery channel (for example, SMS messages, personalized emails, or real-time chatbot conversations).
Initially, generated messages are typically reviewed by marketing or compliance teams. Over time, however, automated guardrails, template-based constraints, and learning loops will allow the content to scale with limited human oversight. More advanced implementations add agentic AI elements, where agents autonomously refine messages, predict impact, test different phrasing, gauge likely responses, and adjust accordingly. Agentic AI can move organizations beyond templated messaging to scalable, high-quality, personalized communication.
Campaign delivery platform
This final component ensures the delivery of messages through appropriate and timely customer channels, starting with integration into marketing automation systems that manage email sends, SMS notifications, and mobile push alerts. CRM systems and call center interfaces are also integrated, allowing human agents to view real-time prompts that reflect AI recommendations.
Using gen AI drives the ability to scale fast. It can be harnessed to create personalized content and be driven by recommendations from the central engine (for a company case study, see sidebar, “Using a next best experience engine to deliver an effective communication campaign,” and for an individualized case study, see sidebar, “Using AI to hyper-personalize customer communication”).
Despite the importance of getting the technology right, the successful implementation of a next best experience engine is never just about tech. It delivers value when it is embedded into workflows, supported by operational processes, and paired with organizational change. Even the most accurate model will fail if frontline teams do not trust or act on its recommendations.
How companies can get started on next best experience
Organizational leaders can consider six aspects when exploring the potential of a technology-enabled next best experience approach:
*- The data layer: Organizations can start by integrating key data sources—such as CRM, billing, or operational datasets—into an initial feature store or sandbox data lake, and then check data accessibility and quality using a proof-of-concept ingestion pipeline.
*- Advanced analytics: After selecting a high-impact use case, such as churn prediction or upsell likelihood, companies can train and deploy a basic predictive model in a pilot workflow. Performance can be monitored weekly to continually refine the model through feedback loops.
*- A robust technology ecosystem: Companies can consider investing in technologies such as MLOps (machine learning operations), DevOps (development operations), and MarTech to streamline model development and deployment. This approach also helps better connect analytics and marketing for improved customer engagement.
*- The operational model: Organizations can rethink their operating models, focusing on the importance of aligning incentives across silos. For example, a single contact policy across all teams can drive coordinated customer interactions across different departments, such as billing, customer experience, marketing, and sales. Implementation can include establishing a cross-functional working group with a unified contact policy and aligned incentives, such as shared targets, to drive collaboration.
*- Impact measurement: Companies can set up a universal control group and a universal target group. Comparing the two can reveal insights into customer behavior and transaction patterns. At the same time, control groups can be used for A/B testing of campaigns, while dashboards provide transparency into predictive model performance.
*- A two-speed approach: Companies can consider launching a small-scale lighthouse pilot while concurrently working on foundational capabilities, such as data lake architecture and cross-functional governance. This approach can drive rapid results alongside a scalable build-out.
The convergence of technological progress and heightened customer expectations has created an ideal environment for revolutionizing customer engagement. The next frontier of the customer experience—the next best experience approach—can now be unlocked, especially by front-runners who can effectively use AI and gen AI to enhance predictive capabilities and gain a competitive edge.
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