The Buying Concierge

The next competitive advantage in hospitality marketing will not come from reaching more people. It will come from identifying the future guests most likely to buy what hotels most need to sell, and activating that insight with precision, speed and scale. rnJune 2026

For the past two decades, travel and hospitality brands have invested heavily in digital commerce. They have built websites, apps, booking engines, loyalty portals, campaign platforms, revenue management systems and customer data capabilities. Yet for many travellers, the digital shopping experience still feels surprisingly transactional. The customer enters a destination, date and party size. The system returns a list of rooms, flights, rates, packages or experiences. The customer filters, compares, hesitates, checks reviews elsewhere, opens more tabs, searches again, and eventually either books, abandons or defects to an intermediary that makes the decision feel easier.

That model is reaching the end of its useful life.

The next generation of digital retailing in travel and hospitality will not be defined by a prettier booking engine. It will be defined by the ability to understand customer intent, interpret context, inspire with relevant content, surface trusted recommendations, configure dynamic offers and make the path from idea to booking feel effortless.

This matters because the front door to travel demand is changing. Generative AI is rapidly becoming part of travel inspiration and planning. Nearly 40 per cent of U.S. travellers used generative AI tools to plan trips in 2025, an eleven-point increase in a single year, while traditional search engines declined from 51 per cent to 36 per cent as the primary trip-planning resource over the same period.¹ At the same time, travellers are becoming more demanding: they expect relevance, transparency, flexibility, proof and speed.

For executives, the implication is clear. Digital retailing can no longer be treated as a channel enhancement. It is becoming a core commercial capability that connects brand, customer insight, product, content, price, inventory, service and fulfilment. The winners will not simply be the brands with the most inventory or the lowest price. They will be the brands that make the right offer feel obvious, trustworthy and easy to buy.

From Booking Engine to Buying Concierge

Traditional travel retailing was built around availability. The customer stated where and when they wanted to travel, and the system responded with what could be sold.

Next-generation retailing starts from a different question: what is this customer trying to achieve?

A business traveller is not buying a hotel room; they are buying a productive, low-friction stay that supports a meeting, conference or client visit. A family is not buying a resort; they are buying confidence that the children will be entertained, the sleeping arrangements will work, the transfer will be manageable and the trip will feel worth the money. A traveller disrupted by a cancelled flight is not buying accommodation; they are buying reassurance, speed and certainty.

The role of the digital retail interface is therefore changing. It must move from being a passive shelf of products to becoming an active buying concierge. That concierge needs to understand intent, guide choice, explain trade-offs, reduce uncertainty, recommend relevant enhancements and complete the transaction with minimal friction.

This is a major shift. It requires a new retailing model built around context, purpose, language and dynamically assembled value. As explored in Demand Orchestration, the more commercially productive question is not who the customer is, but what they are trying to achieve and whether the demand they represent matches what the business most needs to sell.

Personalisation: From Segments to Situations

Personalisation has long been one of the most overused words in travel marketing. Too often, it has meant recognising a returning customer, inserting a first name into an email, presenting a loyalty rate or retargeting an abandoned search. That is no longer enough.

The next generation of personalisation will be situational rather than merely segmented. It will not simply ask whether the customer is a leisure traveller, business traveller, family traveller or loyalty member. It will ask: what is the customer trying to do right now, in this moment, under these conditions?

A traveller may behave as a business customer on Monday, a parent on Friday and a luxury leisure customer in the summer. A loyalty member may be price-sensitive on a short domestic trip but willing to pay more for certainty on a complex international journey. Personalisation must recognise these shifts.

Generative AI changes the scale and economics of this challenge. The same property, flight or package can be presented differently depending on the traveller’s purpose, origin market, party composition, season, loyalty status, budget, previous behaviour and journey stage. For a business traveller, the emphasis may be workspace, invoice support and proximity to the meeting venue. For a family, it may be room configuration, pool hours, child-friendly dining and cancellation flexibility.

This is personalisation as intelligent publishing. The brand must be able to assemble the right message, image, proof point, product attribute and offer in real time. That does not mean allowing AI to invent marketing claims. It means grounding AI in accurate, structured and governed product, policy, price, inventory and service data.

“The opportunity is not to create more content. It is to create more useful content. Brands that ground AI in accurate, structured product data will earn relevance. Those that do not will generate noise at scale.”

Context, Purpose and Language Are the New Relevance Layer

Travel products are complex because the same product can mean very different things depending on context. A hotel near a railway station may be a convenience benefit for a late-arriving business traveller, a safety concern for a family, or an irrelevant detail for a resort guest. A non-refundable rate may be attractive for a budget-conscious leisure traveller but unacceptable for a corporate traveller with uncertain plans.

Next-generation digital retailing must therefore interpret customer context, trip purpose, location, commercial conditions and journey stage simultaneously. Language is the bridge between customer intent and product configuration. Customers do not think in supplier terminology. They do not wake up wanting a “semi-flexible rate plan” or a “deluxe king room”. They express needs in human terms: “somewhere quiet”, “good for teenagers”, “easy after a late flight”, “romantic but not formal”, or “a trip where I can work in the mornings and explore in the afternoons”.

The ability to translate this language into searchable attributes, comparable options and bookable offers will become a defining retail capability.

Localisation Must Go Beyond Translation

Many travel brands still treat localisation as a language and currency exercise. Next-generation retailing requires a broader view. It means adapting the proposition to the expectations, behaviours and needs of different source markets and customer missions: language, imagery, payment methods, service norms, proof points, local recommendations and merchandising logic.

Travel and hospitality brands have an opportunity to become curators of place, not just sellers of rooms, seats or packages. A hotel brand should not simply sell a room in Lisbon, Tokyo or Chicago. It should help the traveller understand which neighbourhood fits their trip, what can be done nearby, which experiences are authentic, how to move around, and which add-ons make the stay better.

This matters commercially because local relevance increases the brand’s role in the trip. The more useful the brand becomes in shaping the experience, the more opportunities it has to increase direct engagement, ancillary revenue, loyalty and customer lifetime value.

Inspiration Must Become Purpose-Driven Content

Travel shopping often begins before the customer has a clear destination, product or budget. Generic destination content is no longer enough. Beautiful imagery and broad copy may create desire, but they rarely reduce decision friction. Purpose-driven content does both.

Instead of publishing content around internal categories, brands should organise inspiration around customer missions: city breaks for food lovers, resorts where teenagers have independence, hotels suited to hybrid work trips, weekend escapes by train. This type of content is commercially valuable because it acts as both brand storytelling and retail navigation. It inspires the customer while guiding them toward relevant products and offers.

Generative AI can help scale this publishing model, but editorial strategy remains essential. Without it, AI-generated content risks becoming generic. With it, content becomes a retail asset.

Natural Language Search Will Reshape Travel Shopping

The search interface is moving from form-filling to conversation. For years, travel websites have asked customers to translate intent into rigid parameters. Natural language search reverses the relationship: customers describe what they want in their own words and the system interprets, clarifies and responds.

A customer should be able to ask for a hotel near good restaurants but not in the most touristy area, or family-friendly beach resorts in October where the transfer is under 45 minutes, or a complete three-day itinerary around art and local food with hotels that fit. Filters will still matter, but they should become contextual and dynamic, surfacing the attributes most relevant to the customer’s purpose rather than the same long list for every enquiry.

The aim is not to add more features. It is to reduce the effort required to find the right choice.

Easy to Shop Means Easy to Decide

Travel is difficult to shop because products are hard to compare. Customers often make decisions with incomplete information: the practical difference between two rate plans, the real value of an inclusion, the connection risk on a flight, or whether a resort experience is appropriate for their group.

Next-generation retailing must make products easier to compare based on relevant attributes. For hotels, that may include room size, view, bed configuration, workspace, cancellation rules and guest review themes by purpose. For airlines, total journey time, connection risk, flexibility and disruption support. For resorts, transfer time, kids’ club ages, sustainability credentials and activity schedules.

The key is not to expose every attribute equally but to surface the ones that matter for the customer’s purpose. The best digital retail experiences will reduce cognitive load, helping customers compare, choose and book with confidence.

Trust Becomes the Conversion Engine

As AI becomes more involved in travel planning, trust becomes more important, not less. More than 90 per cent of consumers trust AI-generated travel information. Yet only 2 per cent are currently willing to give AI full autonomy to make or modify bookings without human oversight.² Travel is high stakes. A poor recommendation can waste money, damage a holiday or disrupt a business trip.

Trust must therefore be designed into the retail experience. Reviews need to become more useful: not average scores, but review intelligence that relates to the customer’s specific purpose. AI can summarise review themes, but it must be transparent and evidence-based. A stronger recommendation is not “recommended for you”. It is: “Recommended because it is close to your meeting location, has strong reviews for quiet rooms, includes breakfast, and offers flexible cancellation.”

The next generation of retailing should use nudges to help customers make better decisions, not pressure them into decisions they later regret.

Recommendations Must Follow the Stage of Journey

Retailing does not end at booking. Customer needs change throughout the journey. At the inspiration stage, the traveller needs ideas and reasons to care. At research, they need comparison tools and proof. At booking, they need clarity on price and flexibility. Before arrival, they may want transfers, upgrades or dining. During the trip, local recommendations and service support. After the stay, loyalty recognition and personalised rebooking.

Too many brands concentrate retailing effort on the booking path. Customers are often more willing to buy relevant add-ons once the core trip is confirmed and the details become concrete. The commercial opportunity lies in matching the recommendation to the moment. The right offer at the wrong time is still the wrong offer.

Merchandising Moves From Static Display to Intelligent Guidance

Next-generation merchandising will use customer intent, product attributes, behaviour, availability, pricing, journey stage and commercial objectives to guide choice rather than display inventory. Prompts such as “travelling with children? These rooms give you more space and include breakfast”, or “this rate is lower than typical weekends in this period”, or “add late checkout for a more relaxed final day” are techniques retail has used for years that travel has underused because product data, pricing, content and fulfilment are fragmented.

Effective merchandising should make the customer feel better informed, not manipulated. Scarcity and urgency messaging must be accurate. Value claims must be explainable. Personalisation must feel helpful rather than intrusive.

Cross-Selling and Upselling Must Become Experience Design

Cross-selling and upselling are often treated as ancillary revenue tactics. In the next generation of digital retailing, they need to become part of experience design. A generic upsell says “upgrade your room”. A relevant one says “for your anniversary stay, this room adds a view, more space and late checkout”. A generic cross-sell adds breakfast. A relevant one explains that nearby cafés are limited before 9am and the family are travelling with children.

The best strategies are based on trip purpose, party composition, arrival time, length of stay and destination context. They ask not what else can be sold, but what would make this trip work better for the customer and create value for the business.

“Poorly timed or poorly matched recommendations feel like friction. Well-designed ones feel like service. The difference is not the technology. It is whether the offer genuinely serves the trip.”

Atomic Inventory and Pricing Are the Foundation

The next generation of digital retailing depends on a more granular view of the product. Atomic inventory means breaking the travel product into components that can be described, priced, combined, recommended and fulfilled: room attributes, views, bedding, floor level, connecting-room status, check-in times, cancellation terms, seats, bags, meals, flexibility and experience time slots. Atomic pricing means pricing these components dynamically and transparently based on availability, demand, context, channel, timing and value.

This is where the technology challenge becomes a commercial strategy challenge. As explored in The Next-Generation Commercial Engine, the central reservation system was built for a world of stable room types, fixed rate plans and limited distribution channels. That world no longer exists. Product information, content, pricing, customer data and fulfilment logic sit in different places. The result is a customer experience that cannot always explain, configure or deliver what the brand wants to sell.

The product catalogue becomes the commercial foundation. Without it, AI-powered retailing will remain superficial. With it, brands can create more relevant offers, improve conversion, increase ancillary revenue and strengthen direct relationships.

The Rise of AI-Influenced Demand

AI is becoming a source of qualified demand. As consumers increasingly use AI assistants for trip planning, brands must consider how they appear in AI-generated recommendations. More than 60 per cent of travel businesses are now experimenting with or scaling agentic AI,³ and the competitive gap between those investing in the right foundations and those deferring is widening.

AI systems need accurate, structured, accessible and trustworthy information. Brands that provide thin, inconsistent or generic content will be harder for AI systems to interpret and recommend. The future customer journey may begin with a traveller asking an assistant for recommendations or a complete itinerary, with the assistant shortlisting options before the customer ever visits a brand website.

That means brands must win twice: first inside the AI-assisted discovery environment, then again at the point of booking. As examined in The Battle for the Consumer, the brands that will retain commercial control are those that invest in direct relationships, content quality and data infrastructure before platforms complete their work of intermediating the guest entirely. The best defence is not to resist the shift, but to make the brand’s direct channels more useful, more trusted and easier to transact with.

What This Means for Travel and Hospitality Executives

Digital retailing is becoming an enterprise capability, not a digital department project. It requires coordination across marketing, revenue management, distribution, e-commerce, loyalty, technology, operations, data, brand and customer experience.

The questions executives should be asking are not about improving the booking engine. They are about which customer purposes the brand wants to serve better than competitors, where the current shopping experience creates uncertainty or friction, whether the data structure supports natural language search and dynamic offers, whether upsell and cross-sell offers are genuinely relevant to the trip, and what it would take to become the easiest brand in the category to shop, compare, trust and book.

A Practical Roadmap

The transition does not need to happen all at once, but it requires a deliberate sequence. Audit the customer journey by purpose, not just by channel. Improve the product data foundation so that attributes are structured, governed and reusable. Build modular content around customer missions and trip types. Introduce natural language discovery starting with high-value use cases. Redesign merchandising around relevance, testing by customer purpose and journey stage. Connect cross-sell and upsell to experience design. Integrate retailing with operations so that digital promise and fulfilment are aligned. Prepare for AI-mediated discovery by ensuring product information, policies, reviews and price signals are accurate and machine-readable.

Measure retailing performance more broadly. Conversion matters, but so do margin, ancillary attachment, direct share, trust, repeat behaviour and lifetime value. The future is not a better booking engine. It is a buying concierge: intelligent enough to understand intent, commercial enough to create value, and trusted enough to earn the booking.

About PACE Dimensions

PACE Dimensions is a research and consulting firm founded in 2010 with deep industry experience and a practitioner’s expertise in helping Travel and Hospitality companies excel through strategic clarity and operational excellence. The firm specialises in translating market insights and strategic imperatives into practical initiatives that deliver measurable performance improvement. Its consultants bring proven track records of success working with hotel groups of all sizes across upscale and luxury segments, combining rigorous analysis with pragmatic implementation approaches that drive sustainable results.

References

¹ Phocuswright (2025). Search Slips, AI Surges: Travel’s New Front Door? https://www.phocuswright.com/Travel-Research/Consumer-Trends/Search-Slips-AI-Surges-Travels-New-Front-Door

² McKinsey and Skift (2025). Remapping Travel with Agentic AI. https://www.mckinsey.com/industries/travel/our-insights/remapping-travel-with-agentic-ai

³ Phocuswright (2026). Budgets, Barriers and the Race to Agentic AI. https://www.phocuswright.com