Most shoppers make up their minds before they reach a store. A McKinsey and ICSC survey of 3,004 US consumers found that 85% of shoppers do some form of online research before visiting a store. They check product availability, compare prices, review selection, and look for coupons, so the store visit is often the end point of a buying journey that started on a phone.

That shift changes what retailers have to get right. The shopping journey now runs through websites, AI assistants, and reviews long before an associate says hello. Every gap in product data, pricing, or inventory accuracy costs the retailer a visit it never sees.

BSPK, the Customer Intelligence Platform powered by AI clienteling and first-party data, helps brands turn that research into store visits, sales, and lasting customer relationships. This article covers what shoppers validate before a trip, what retailers must make discoverable and reliable, and how first-party customer data connects online research to the in-store customer experience.

Five key takeaways show where the shopping journey now begins

• 85% of shoppers research online before a store visit, according to McKinsey and ICSC, so the store more often confirms a decision than starts one.

• Shoppers validate availability, price, selection, and promotions before the trip, and 37% rank reliably finding what they want among their top three reasons to choose a retailer.

• AI is now part of the research stage, with 62% of consumers in McKinsey's ConsumerWise survey using AI to compare brands, models, prices, or reviews.

• Retail businesses need accurate, machine-readable inventory, pricing, and policy data, because Adobe's July 2026 analysis found 39% of retail homepage content could not be read by AI models.

• Informed customers raise the bar for associates, and first-party customer data is what lets a store team turn a validated trip into a long-term brand relationship.

The retail customer journey now starts before the store visit

For years, the retail customer journey was drawn as a funnel that began with awareness and finished at the register. That picture no longer matches how people shop. McKinsey reports that more of the shopping journey now happens before a consumer enters a store or opens a retailer's app.

The result is a shorter, more decisive store visit. Customers walk in having narrowed their options and confirmed the trip is worth making. In McKinsey's words, the store becomes a place for fulfillment and confirmation rather than first exploration.

This is true across generations, though younger customers lead the change. In the ICSC consumer survey, 48% of Gen Z and millennial respondents described their shopping as a blend of online and in-store, compared with 25% of baby boomers. Shopping online and shopping in a store are now two halves of the same decision.

For marketing teams, this changes where budgets work hardest. Market research and media plans built around the store as the starting point miss the moment early in the journey when customers decide on a brand. The retail journey now has to be planned from the first search onward.

Shoppers validate four things before they make the trip

McKinsey's market research with ICSC points to four checks shoppers run before leaving home. Each is a question that a retailer's websites, listings, and apps need to answer clearly and correctly.

• Whether the product is in stock at a nearby store, in the size, color, or model they want.

• What it costs, so they can compare products and prices across retailers and channels.

• How much selection the store carries, which tells them whether the trip is worth the time.

• Which coupons or promotions apply, since those change the final price.

Getting these answers wrong is expensive. In the ICSC survey, 37% of respondents ranked reliably finding what they want among their top three reasons to choose a retailer, and 33% cited convenient store locations. A stock-out after a shopper has already validated the trip breaks trust faster than almost anything else.

AI tools now handle the early stages of research

Generative AI has moved into the research step of the customer journey. McKinsey's ConsumerWise survey found that 68% of consumers used at least one AI-enabled tool in the past three months. Sixty-two percent use AI to compare brands, models, prices, or reviews, and 55% use it to learn about a category or product.

Those AI-assisted customers are worth winning. Adobe Analytics data for July 2026 shows AI-referral traffic to US retail sites grew 62% year over year, converts 60% higher than non-AI traffic, and generates 53% more revenue per visit. The same data shows AI-referred visitors add items to their cart 28% more often than other shoppers.

These customers arrive having done their own market research. They know the features, the price range, and the alternatives, so a vague product page or an uninformed answer in the store pushes them toward a retailer that can match what they already learned.

Convenience and discovery trips follow different customer journey rules

McKinsey sorts store visits into two missions: convenience and discovery. Both start with research, but the customer's experience inside the store has to match the reason they came. A retailer that runs every location the same way risks a store that half-serves both missions.

Convenience shoppers arrive with a decision already made

Convenience trips are about speed and certainty. McKinsey found that 78% of respondents prefer help from an associate only when they ask for it, and 68% are extremely interested in faster checkout. These customers have done the work already, so friction at the shelf or the register is what they remember.

Returns and channel handoffs carry the same weight. About 90% of shoppers across generations cited easy returns and seamless omnichannel continuity as important parts of the in-store experience. If the website promised same-day pickup and the counter cannot find the order, the shopper's research was wasted.

McKinsey's case studies show how retailers are responding. Some are narrowing assortments to improve in-stock reliability, and others are testing checkout-free formats such as Amazon's Just Walk Out technology, which uses computer vision and RFID so customers can leave without scanning items. The common thread is a store that delivers exactly what the shopper validated online.

Discovery shoppers want a customer experience worth the trip

Discovery trips work differently. Customers come to explore, see new products, use in-store services, and talk with someone who knows the category. More than 87% of respondents rated associate friendliness, product knowledge, guidance, and quick issue resolution as at least moderately important.

These customers respond to personalization, within limits. Respondents showed interest in tailored promotions and product recommendations, but less interest in any approach built on heavy online-to-offline tracking. Relevance has to come from data customers share willingly with a brand, which is where first-party data and clienteling fit.

McKinsey's case studies include fashion brand Sézane, whose boutique "appartements" host events and curated collections that give customers a reason to visit beyond the purchase. According to the report, Sézane has reached double-digit compound annual growth rates in recent years. Discovery stores earn the trip by giving customers a brand experience that research alone cannot match.

Discoverable product data decides which stores make the shortlist

When 85% of shoppers research first, a store that cannot be found or trusted online loses the visit before it starts. McKinsey's guidance is direct: clean catalog feeds, accurate local availability, and live pricing determine whether a store appears as a credible pick-up-today option. That applies to shoppers and to the AI agents searching on their behalf.

Many retailers are not there yet. Adobe's July 2026 analysis found that 39% of homepage content across a broad set of US retail websites was not machine-readable by large language models. A product page an AI assistant cannot parse never makes the shortlist, and the retail customer journey ends before it starts.

Agentic commerce raises the bar again. McKinsey estimates that agentic commerce could generate up to $1 trillion in US B2C retail revenue by 2030. Yet in a McKinsey survey of 50 executives, 45 had considered an agentic commerce tool and fewer than five had a board-aligned strategy for it.

Our guide to what agentic commerce is explains how AI agents search, compare, and buy on a shopper's behalf. Retail businesses that fix data gaps early will be easier to find as AI agents take a bigger share of the market.

The checklist below covers the information customers and AI agents look for during research. Each item should be accurate, current, and consistent across every channel a customer might use.

• Store-level inventory that updates in real time, so a search result matches what is on the shelf and in the cart.

• Current pricing and promotions that match across ecommerce, apps, marketplaces, and the store.

• Return, pickup, and delivery policies, plus in-store services such as fittings or repairs, that a shopper or an agent can read in seconds.

• Appointment booking and associate contact options for higher-intent discovery visits.

• Structured product details, such as sizes, materials, and compatibility, written in plain language.

Merchandising also needs to move faster. McKinsey notes that planning assortments once or twice a year no longer keeps pace when search trends and AI-assisted discovery can shift demand in weeks. Real-time demand signals and local sell-through data should guide what each store features and stocks.

Ecommerce shopping has trained customers to expect instant answers, and they bring that expectation into every store. A business that updates in-store data as quickly as its website keeps the shopping journey consistent from search to shelf.

A retail customer journey map should start with online research

A retail customer journey map is a visual representation of each step a shopper takes, from first search to repeat purchase. Many maps were drawn when the store was the main venue for research, so they skip the steps that now happen online. Rebuilding the journey map around research gives teams an accurate view of where sales are won and lost.

To create the map, start by listing the key stages: online research, validation, the store visit, the purchase, and follow-up. Then add the journey touchpoints inside each stage, such as search results, AI assistant answers, product pages, messages from an associate, and post-purchase outreach. The in-store customer journey is now the shortest part of the map, and it carries the most weight.

Data for the map should come from ecommerce analytics, marketing insights, and store reports. Quantitative tracking and market research show where shoppers drop off, while qualitative feedback from interviews, reviews, and mystery shopping shows why. Teams can learn more from combining the two than from either one, because numbers show the gap and qualitative insights explain it.

McKinsey recommends a richer store file, an approach that follows behavior instead of store size. Beyond sales, it should show how far customers travel, whether visits are planned, which categories inspire trips, how often customers return, and how store visits connect to digital research. That view turns a retail customer journey map from a slide into a source of insights teams use every week.

Owners matter as much as data. Each stage of the shopper journey should name a team responsible for it, whether that is ecommerce, marketing, store operations, or customer services. When no one in the business owns the step between online research and the store visit, that part of the journey is where shoppers fall out.

Associates and first-party data turn validated intent into sales

When customers arrive informed, the associate's role changes. McKinsey's case studies and executive interviews describe the goal as moving associates from transaction executor to trusted adviser, supported by AI tools that provide real-time inventory, customer context, and next-best actions. As one retail executive put it in the report, "Providing intelligence to humans is the most powerful CRM on the planet."

That intelligence depends on first-party customer data. A shopper's past purchases, preferences, wishlists, and conversations with an associate are signals no ad platform can sell back to a brand. Clienteling puts those signals in the associate's hands so they can build relationships, and a retail CRM built for retailers keeps them organized for every team.

The data also has to outlast staff changes. McKinsey notes that frontline attrition is often driven by unclear roles and limited support, and when an associate leaves, what they knew about their customers usually leaves too. A system that records each interaction as brand-owned data keeps those relationships with the business.

Training shapes adoption. According to McKinsey's State of Fashion research, cited in the report, 47% of US consumer goods and retail employees say training is the most important factor for gen AI adoption, yet nearly half receive only moderate support or less. Tools that are simple to learn get used, and tools that get used produce the data the rest of the business depends on.

Measurement should follow the store's mission. McKinsey suggests discovery-led locations track appointment conversion, average order value, and repeat-visit rates, while convenience stores track pickup wait times and issue resolution. Both need the same foundation: a connected record of each customer that store teams, marketing, and business leaders can act on.

BSPK, the Customer Intelligence Platform powered by AI clienteling and first-party data, can help

BSPK turns first-party customer data into repeatable customer growth. As AI changes how shoppers discover and compare brands, BSPK gives retailers a way to capture the high-value interactions that happen in stores, over messaging, at appointments, and during services such as styling or consultations, then act on them one customer at a time at every point in the journey. In the age of AI, a brand's real advantage is the customer data it owns and how intelligently it uses it.

The platform works in three steps. BSPK captures each interaction as structured data tied to a persistent customer identity, unifies signals from POS, ecommerce, CRM, inventory, and engagement into a single omnichannel customer view that syncs in real time, and activates that profile through AI agents and associates working together. Every interaction improves the next one.

Most marketing systems were built for campaigns sent to cohorts. In an AI-shaped market, generic marketing messages get ignored or filtered out, while personal and timely outreach gets read. BSPK helps marketing teams move from segment thinking to relationship thinking, with insights from every store conversation shaping the next action.

Across the stages of the customer journey, BSPK works like this:

• A single customer view brings purchase history, preferences, wishlists, notes, and engagement into one living profile, with insights every team and agent works from.

• Acquire Agent reads first-party signals such as browsing, wishlists, and abandoned checkouts, scores who is most likely to buy, and turns that intent into store visits, appointments, and event attendance.

• Engage Agent spots relationships that are going quiet, drafts outreach in the advisor's voice, and works across SMS, WhatsApp, email, and the other channels clients use.

• Convert Agent briefs the advisor before a client arrives, curates matching products from live inventory, and automates the thank-you and next action after the visit.

• Campaign Agent turns launches and brand moments into personalized one-to-one outreach instead of mass blasts, then measures what each moment drove, including client feedback.

• Skills Agent coaches associates in the flow of work with in-the-moment suggestions and feedback, so every associate can sell like your best one.

• Client Ideabook and Slices let teams create curated collections of products, lookbooks, and videos that associates share through a private branded page where clients can wishlist items, leave feedback, and request appointments.

• Analytics turn outreach, conversions, repeat purchases, and attributed revenue into insights by store, region, and associate.

Associates stay in control. Agents prepare and suggest, and the associate approves before anything sends, so the conversation stays human. When staff change, customer knowledge stays with the brand, because every interaction lives in BSPK instead of on a personal phone.

BSPK layers onto existing systems instead of replacing them, with one-click Shopify integration, an open API, and integrations with platforms such as NetSuite and Klaviyo, so businesses keep the tools they already use. Marketing and store teams finally work from the same customer record, which moves the business from cohort campaigns to one-to-one relationships. To see how this works on the sales floor, read what clienteling is and how it builds loyalty.

These frequently asked questions cover what retailers ask most

What is the shopping journey?

The shopping journey is the full path a shopper takes from recognizing a need to researching, buying, and coming back for more. Most of that path now happens online, with 85% of shoppers researching before a store visit. The store visit is increasingly where a decision gets confirmed.

What do shoppers research online before visiting a store?

Before visiting a store, shoppers most often check product availability, compare prices, review selection, and look for coupons, according to McKinsey. A growing share use AI assistants for the comparison step, so that information needs to be accurate everywhere it appears.

How do you create a retail customer journey map?

To create a retail customer journey map, list the stages from online research to repeat purchase, then add the touchpoints, data sources, and team owners for each one. Combine quantitative tracking and market research with qualitative feedback so the map shows where shoppers drop off and why they leave.

How is AI changing the customer journey in retail?

AI is moving research and comparison earlier in the customer journey, and agentic commerce lets AI tools complete some purchases for the shopper. Retailers need machine-readable product, pricing, and inventory data so AI assistants can find and recommend their stores, and marketing teams need first-party data to stay relevant once customers arrive.

How does clienteling improve the in-store customer experience?

Clienteling improves the in-store customer experience by giving associates insights such as past purchases, preferences, and earlier conversations, so they can advise shoppers who arrive already informed. Platforms like BSPK add AI agents that suggest who to contact and what to share, while the associate approves every message.

Retailers that make research reliable will win more store visits

The 85% finding is a signal for retail businesses of every size. Customers decide online, then come to the store to confirm, collect, or explore, and they leave quickly when the store does not match what they found. Retailers that build accurate product data and a connected view of each customer will earn more of those visits and a larger share of their market.

BSPK helps brands capture every high-value interaction, unify it into one customer profile, and act on it with AI agents and associates working side by side. Request a demo to see how BSPK can turn your brand's first-party customer data into repeatable growth across the full customer journey.