Why a Seamless Cross-Channel Journey Matters

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Imagine a customer who has a tailored experience on your site, but then receives a completely unrelated email offer – jarring, right? Consistency is key. Brands that connect the dots between web, email, and SMS enjoy big benefits. For instance, companies with strong cross-channel marketing strategies achieve 89% customer retention on average (versus only 33% for weaker multichannel efforts)​

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Top-performing retailers like Sephora exemplify this: they rank #1 in personalization because they use data to personalize and connect the customer experience across channels – email, website, mobile app, and even in-store. Sephora meets customers where they are and how they like to shop — winning them over with personalized recommendations that keep them coming back. (Read our Growbook that shows how to predict these moments and respond with on-page experiences​)

The lesson is clear: when every channel “knows” the customer, it feels like a unified journey and customers respond with greater engagement and LTV.

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Personalization + Recommendations (Better Together)

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To achieve personalization, you should combine two powerful approaches: segment-based user personalization and catalog-based product recommendations. Think of it as who the customer is + what products/content they’d love. Here’s a breakdown of each and why combining them yields the best results:

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Segment-Based Personalization: This approach targets “who” the user is (or what group they belong to) to tailor the experience. It uses user attributes and behaviors to create segments and predictive scores. For example:

• RFM Segmentation: Grouping users by Recency, Frequency, Monetary value of purchases. This helps identify lifecycle segments like “Champions” (most loyal customers), “At Risk” (previously good customers now fading), “New Customers,” etc. Each segment gets different treatment. (Is a shopper high-value and recent? Roll out the red carpet with exclusive offers. Lapsed? Send a win-back offer.)
  
  
• Next Best Action Predictions: Using AI to predict what a user is most likely to do (or need) next, and tailoring offers or content for that. For example, if a customer has a high likelihood to churn vs. to purchase, the next best action will differ (perhaps a retention offer vs. a personalized item offer). This ensures you’re always guiding them optimally, not blindly.
  
  
• Behavioral & Profile Attributes: These include things like product category preferences (e.g. beauty shopper interested in skincare vs. makeup), brand affinity, location, retention tier, etc. Segmenting by such attributes lets you show relevant content. (If Jane consistently browses skincare, your homepage banner could highlight the latest in skincare for her, not the standard top sellers in all beauty.)

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Catalog-Based Recommendations: This focuses on “what” products or content to show each user, usually via algorithmic recommendations. It leverages your product catalog data and user behavior. Key recommendation types include:

• Affinity Recommendations: Items related to the user’s previously demonstrated interests. For example, if on Sephora Jane has shown an affinity for K-beauty skincare products, the site might recommend other K-beauty skincare items or new arrivals in that category. These recs align with her personal tastes.
  
  
• Similarity Recommendations (Content-Based): Showing similar items to ones the user viewed or purchased. (“Liked that face serum? Here are similar serums or products with comparable ingredients.”) This helps customers discover products in the same style or function.
  
  
• Collaborative Filtering: “Customers who bought X also bought Y.” This mines the wisdom of the crowd. If many people with similar behavior as Jane ended up buying a certain product, it’s likely relevant to her too. Classic examples are the “Frequently Bought Together” or “You Might Also Like” sections on product pages. Sephora uses this by suggesting items that pair well with what’s in your basket (e.g., a primer to go with the foundation you’re viewing).

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Using both personalization layers together is where the magic happens ✨. Segment-based rules set the stage (who is this user and what do they need?), and recommendation algorithms fill in the specific (which products or content?). For example, if a user is in the “At Risk” segment (hasn’t purchased in a while), your site might automatically show a banner like “We miss you! Here’s 10% off on items picked for you”. The products shown in that banner would be generated by a recommendation engine – perhaps a mix of items related to their past favorites (affinity) or popular sale items to entice them.

Conversely, a high-value “Champion” customer might see a personalized homepage module highlighting new premium products in their favorite category, using an affinity or similarity algorithm without needing a discount. The segment dictates the strategy (e.g., special offers or VIP exclusive), while the recommender picks the perfect products to display. This one-two punch dramatically increases relevance and conversion.

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On-Site Personalization: Every Visit Feels Like “Made for Me”

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Your website (or mobile app) is where the journey typically starts. Here’s how segment-based personalization and product recommendations unite to make each visit feel bespoke:

• Personalized Content & Layout: Depending on the visitor, you might change hero banners, headlines, or calls-to-action. Example: Sephora’s site might greet a logged-in Beauty Insider loyalty member with a “Welcome back, [Name]! Your 500 points can get you a free gift 🎁” message, whereas a first-time visitor sees a standard welcome or a sign-up offer. If you know a user’s favorite category is “fragrance,” the homepage could prominently feature a perfume promotion for them.

• Product Recommendations on Key Pages: Strategic recommendation widgets on the homepage, product detail pages, cart page, etc., keep the customer discovering relevant items. On the homepage, a “Just For You” carousel might blend affinity picks and trending items. On a product page, a “Pair With It” section might show items often bought together – for Sephora, viewing a foundation might show the matching primer and setting powder commonly bought with it. In the cart, a “Don’t forget these” suggestion could upsell accessories (e.g., makeup brushes) that others added before checkout. (Read our Growbook, which covers predicting each user’s most likely next purchase categories and targeting them via email, SMS, and on-site banners)

• Real-Time Relevance: As the user browses, you can even update content. If they show interest in a certain brand or category in that session, the site can respond. If Jane clicks on several K-beauty products today, the site might instantly feature a K-beauty recommendations widget in the next page she visits. The goal is to seize on in-the-moment intent.

This level of relevance has a big impact. When customers feel like the site “gets” them, they explore more and buy more. And it’s not only about product pitches – it can be informational too. Sephora, for instance, knows if you are a skincare enthusiast vs. makeup newbie and can tailor educational content accordingly (like linking to a skincare routine guide vs. a makeup tutorial on the homepage). Everything aligns with the shopper’s profile.

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Extending Personalization to Email & SMS (Continuing the Conversation)

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Personalization should not stop when the user leaves your website. Email and SMS are your follow-up champions – the means to re-engage and continue the journey off-site. The key is to carry the context from the website into these channels so the experience stays cohesive. Here’s how to do that:

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Triggered Emails Based on Behavior: Instead of one-size-fits-all email blasts, send emails reacting to what the customer just did (or didn’t do) on the site. Classic examples:

• Cart Abandonment Email: If Jane added items to her Sephora cart but left, she should receive an email reminding her of those exact items, possibly with a gentle nudge (e.g., “Your favorites are almost gone 😯 – complete your purchase and enjoy a giftcard!”). Including product images and even reviews or offers related to those products can entice her back.
  
  
• Browse Abandonment: If she browsed product pages or categories but didn’t add anything to cart, an email highlighting a few of those items (“Still interested in these?”) along with similar recommendations can recapture her interest. Often, just showing “you looked at this, here it is again” along with “you might also like these” does the trick. You can see how to craft a smarter cart abandonment recovery journey here.
  
  
• Post-Purchase Follow-up: After a purchase, don’t send a standard “Thank you”. Instead, personalize the next email with product care tips, how-to videos, and recommended complementary products. Sephora excels here – if you buy a mascara, you might get an email with a tutorial on application and a recommendation for a cleanser to remove it, tailored to what they know about your skin​, they even include the exact item you bought in the email when asking for a review, making the message feel 1:1​. (Source)

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Personalized Newsletters/Promos: Even your regular campaign emails can be segmented. Instead of one blast announcing a sale on skincare and haircare, and makeup to everyone, you might send Alice (a skincare fan) an email featuring the skincare sale, while Bob (who buys cologne) gets an email highlighting the fragrances on sale. Additionally, you can embed product recommendation widgets in emails – e.g., a “Recommended for you” section that pulls in items via an algorithm at send time.

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SMS with Relevance: SMS is a more personal, immediate channel – so be even more thoughtful here. It’s great for timely, concise touchpoints. For example, Sephora sends SMS alerts that are personalized and location-based: if you opt in, they might text you when a promotion is happening at your local store or if a product you loved online is back in stock nearby​. (Source) The beauty of SMS is the high open rate – if you make it relevant (not spammy), it grabs attention. Use the customer’s name, reference their recent activity or preferences, and include a clear CTA link that brings them back to a personalized landing page. (Nothing’s worse than clicking an SMS link that dumps you on a standard homepage – it should feel like a continuation of the conversation, not a restart.)

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Unified Messaging & Deep Linking: Ensure your promotions and messaging align consistently across all channels—web, email, and SMS—to reinforce your campaign’s impact and maintain customer trust. Use deep linking to create continuity, directing users from emails or SMS directly back to relevant personalized experiences on your website. This approach prevents confusion, boosts conversions, and keeps the customer journey seamless.

In essence, treat email/SMS as extensions of your site. They’re not separate campaigns, they’re steps in the same journey. When a customer moves from site to inbox to phone and back to site, it should feel like turning successive pages of the same storybook, not jumping between different stories.

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Sephora’s Seamless Personalization in Action

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Unified Customer Profile: Sephora leverages its Beauty Insider loyalty program to collect customer insights, including skin type, favorite brands, purchase history, and even personalized quiz results (like finding the perfect foundation shade). This unified data allows for consistent, relevant personalization across every channel.

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Personalized Web Experience: When Jane logs into Sephora.com, she immediately sees customized messages like “Recommended for you, Jane – New skincare arrivals,” based on her past browsing and purchasing habits. She also encounters recommendation carousels such as "Customers also bought," populated with items relevant to her interest in K-beauty serums and moisturizers, guided by affinity and collaborative filtering algorithms.

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Contextual Email Follow-up: Later that day, Jane receives an email directly referencing the products she recently viewed, such as “Still thinking about Glow Serum X?” along with complementary items like moisturizers and sunscreens suited to her preferences. Sephora cleverly includes dynamic content highlighting her loyalty point balance, reinforcing engagement and motivating further action. Additionally, if Jane made a purchase, Sephora sends timely replenishment emails precisely when she's likely to need a refill.

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Immediate SMS Engagement: Because Jane has opted into SMS communications, Sephora sends her concise, personalized texts offering timely offers, like “Hi Jane! Enjoy 20% off your favorite GlowCo products this week!” They also leverage location-based marketing, inviting Jane to visit a nearby store for a free sample of the serum she recently viewed online, effectively connecting her digital experience to an in-store interaction.

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Consistency Across Channels: Sephora maintains cohesive messaging across web, email, and SMS, reinforcing themes and promotions consistently. Jane receives the same promotional details across all touchpoints, eliminating confusion and enhancing her overall customer experience.

It’s no wonder Sephora has been a Retail Personalization Index topper multiple years running​. They exemplify how segment-driven personalization and great recommendations extend across channels. The good news is you don’t have to be Sephora (or have their budget) to do this – you just need the right strategy and tools.

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Bringing It All Together

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You might be thinking, “This sounds fantastic, but also a lot of moving parts… How do we actually do this?” Traditionally, marketers cobble together various tools: one for on-site personalization, another for product recommendations, another for email automation, maybe another for SMS – plus a customer data platform to tie data together (and let’s not even start on connecting in-store data!). Integrating and maintaining all that can be a nightmare – data silos, inconsistent segmentation, latency issues, high costs, you name it.

This is where an all-in-one growth platform like Intempt’s GrowthOS can be a game-changer. (Disclosure: that’s our platform, built from seeing these pains firsthand.) GrowthOS unifies website/app personalization, product recommendations, and cross-channel customer journeys in one place. Here’s how it simplifies the job and amplifies your capabilities:

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• Unified Customer Data Platform (CDP): GrowthOS consolidates data from your website, app, and eCommerce store into a single customer profile, giving you real-time insights and ensuring consistent personalization across channels.

• AI-based Real-Time Segmentation: Easily create detailed segments (e.g., RFM scores, customer lifecycle stages) without needing technical expertise. GrowthOS continuously updates these segments in real-time, allowing immediate and relevant marketing actions.

• AI-Driven Product Recommendations: Implement sophisticated recommendation strategies like affinity-based suggestions, trending items, or collaborative filtering. Customize, test, and adapt recommendations to align with your business goals, such as promoting high-inventory items or popular products.

• Visual Omnichannel Journey Builder: Use the intuitive, drag-and-drop journey builder to seamlessly coordinate experiences across web, email, and SMS. For example, you could automatically trigger a personalized email when a customer becomes inactive, followed by an SMS reminder, enhancing customer engagement effortlessly.

• Consistent Cross-Channel Personalization: Maintain cohesive messaging and offers across all channels using the same unified data. Customers consistently receive relevant, personalized experiences wherever they interact with your brand.

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In short, our philosophy (and differentiator) is ditching the data/app silos and giving you one GrowthOS to rule them all. Marketers can work in one platform where data flows freely, triggers are real-time, and every channel stays in sync. This not only makes execution easier (fewer manual processes and workarounds), but it also directly improves customer experience.

Curious? Watch how we use Intempt to bring customers back.

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Conclusion: One Journey, One Customer (Make It Count)

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Today’s eCommerce customer expects a personalized, cohesive experience. They don’t think in terms of channels – to them, interacting with your brand is one continuous relationship, whether it’s on your website, in their inbox, or via text, or in a physical store. 

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By combining segment-based personalization (e.g. knowing who someone is, what they’ve done, and what they need) with smart catalog recommendations (offering what they’re most likely to want), you create relevance. By extending that relevance across channels with consistent messaging and timing, you create trust and convenience. The key is to start thinking holistically: break down the silos between your web experience and your messaging campaigns. Plan them together, fueled by the same customer data and logic.

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So, next time you’re setting up an email campaign, ask: “What did this user just experience on our site, and what will they see when they click through?” Make sure all the pieces connect. With the right strategy (and the right platform to support you), you’ll turn disparate touchpoints into one harmonious journey – and your customers will notice the difference.

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