Shoppers don’t come to your app or site to “explore your catalog.” They come to find something that fits, fast. When discovery feels like work (scroll, back, filter, repeat), people bounce or settle for whatever’s easiest. The good news: you can make product discovery feel more like a guided shortcut than a maze, especially on mobile.

Product discovery breaks down when shoppers have to do all the work. They land on a category page, start scrolling, open a few PDPs, go back, refine filters, and repeat. On mobile, that loop is even more painful: small screens, slow back-and-forth, and filter UIs that are easy to ignore. Improving product discovery is mostly about removing that friction and helping people reach the right shortlist faster.

Interactive formats like Storyly stories and banners are built for this kind of guided flow. Instead of expecting shoppers to navigate a complex catalog on their own, you can offer a lightweight path: ask what they’re looking for, let them tap into a relevant set, and route them to the right collection or PDP. Those interactions also create consented, zero-party signals (what shoppers explicitly tapped, chose, or saved). Over time, those signals can power smarter personalization and make discovery quicker.

This post focuses on practical ways eCommerce product, growth, and CRM/marketing teams can use interactive formats and experimentation to guide shoppers to relevant products faster and improve outcomes like PDP click-through rate, wishlist adds, and conversion.

What “better product discovery” means (and how to measure it)

Better product discovery means shoppers find relevant items with fewer steps and less second-guessing. It’s not “show more products” or “add more filters.” It’s helping people move from browsing to a solid shortlist quickly, especially on mobile, where endless scrolling is expensive.

In practice, better discovery looks like guided navigation: shoppers get a clear next step (tap a preference, choose a use case, pick a category), and the experience responds with a tighter set of products. Tap-based formats are a natural fit for these moments, because they replace long, unstructured browsing with quick decisions.

To measure whether discovery is improving, focus on “speed-to-relevance” and intent:

• PDP CTR: Are your discovery modules actually sending people to product pages?
• Wishlist adds: Are shoppers finding items worth saving, even if they’re not ready to buy?
• Conversion: Does the guided path lead to purchases, not just engagement?

If you want a broader view of what to track (and how to interpret it), it helps to align on a consistent set of critical eCommerce metrics so discovery tests don’t get judged on clicks alone.

For example, add a Banner on a category page that routes shoppers into “New in,” “Best sellers,” and “Under $50,” then measure whether PDP CTR increases compared to the same page without the Banner.

Or, run a Story that asks shoppers to pick a preference (for example, “lightweight” vs. “warm” vs. “all-season”), then deep-link to curated sets. Track whether those taps lead to more wishlist adds than the default category browsing path.

Build guided discovery funnels with stories and banners

Guided discovery funnels are structured paths that help shoppers narrow down options without feeling boxed in. The point isn’t to force a quiz on everyone. It’s to offer an optional fast lane that cuts scrolling and helps people self-select into the right set.

Think of stories as the multi-step flow and banners as the quick entry point. A banner can invite the shopper into a path (“Find your match,” “Shop by need,” “Build your routine”), while a story handles the decision tree: a few taps that lead to a curated collection, a shortlist, or directly to PDPs. This is especially useful when your catalog is broad, or when shoppers don’t know the right keywords to search.

For example, on mobile, add a banner at the top of a category page that says “Shop by occasion.” The Banner opens a story with three options: “Work,” “Weekend,” “Event.” Each choice routes to a curated collection page or a set of PDP links.

Or use stories on the home page to highlight “Trending now,” “Back in stock,” and “Staff picks,” but make each tile interactive so shoppers land in a relevant sub-collection instead of a generic category page.

These funnels also create explicit interaction signals. When a shopper taps “Weekend,” that’s a clear, consented preference, not a guess based on scroll depth. If you’re building toward personalization, it’s worth grounding your approach in first-party commerce data: what you collect, what it means, and how to activate it responsibly.

3 guided paths to reduce choice overload

Discovery often fails because of choice overload: too many products, too many filters, and not enough direction. Guided paths fix that by offering a few meaningful starting points, based on how shoppers actually think.

Path 1: Shop by intent (need-based).

Start with what the shopper is trying to do, not product specs. A story can ask one question (“What are you shopping for today?”) and offer a few intent options. Each option leads to a curated set. Less comparison fatigue, faster shortlist.

Path 2: Shop by preference (attribute-based, but simplified).

Instead of exposing every filter, ask for one or two high-signal preferences. Keep it minimal. One tap per step, only attributes that truly change the set. The output can be a pre-filtered list, a curated collection, or a PDP sequence.

Path 3: Shop by social proof (best sellers, new in, trending).

A lot of shoppers want reassurance. Starting with “Best sellers” or “Trending” is a low-friction way to help them choose. You can run this as a Banner that opens a story featuring top picks with direct PDP links, or as a story rail that routes into curated collections.

For example, on a high-traffic category page, present three entry points in a banner: “Best sellers,” “New in,” and “Giftable.” Each opens a story with a small set of items and a “See all” link to a curated list.

If you want more inspiration for what these story modules can look like in practice, this roundup of Story ideas to engage and impress your audience is a useful starting point.

Where to place discovery modules across mobile and web

Placement matters because discovery is contextual. Shoppers need help at the moments they’re most likely to get stuck: entry (home), exploration (category/search), and decision (PDP).

• Home page: Act like a concierge. Use stories to present a few clear paths (“Shop by need,” “New in,” “Best sellers”) and make the next step obvious.
• Category pages: Reduce endless scrolling. A banner near the top can offer a shortcut into a mini-funnel (one or two taps → curated list). Category pages are also great for testing because traffic is steady and downstream metrics (PDP CTR, wishlist adds) are clean.
• PDPs: Prevent back-button fatigue. Use stories for “Similar styles,” “Complete the look,” or “Alternatives,” and deep-link straight to PDPs so shoppers stay in a forward flow.

If you’re leaning into short-form, swipeable UX patterns, you’ll also want to think about how those patterns translate to owned channels. TikTok-ification breaks down what to borrow (and what not to) when you bring that experience into your app or website.

Run a product discovery experimentation playbook

Discovery isn’t a one-time redesign. Catalogs change, seasons change, and shopper behavior shifts. You need a repeatable way to test, learn, and roll winners into the default experience.

Interactive formats make experimentation easier because you can change the content and the decision tree without rebuilding navigation. You can test:

• different guided paths (intent vs. attribute vs. social proof)
• different entry points (home rail vs. category banner)
• different landing destinations (curated collection vs. PDP sequence)

Start with a single hypothesis tied to a real friction point. For example: “Mobile category shoppers scroll but don’t click into PDPs because they can’t narrow options quickly.” Then test a Banner + Story funnel with three clear paths. Measure PDP CTR for shoppers who engage with the module vs. those who don’t, and watch downstream wishlist adds and conversion.

For example, run an A/B test where Variant A shows a banner (“Find your match”) at the top of a category page, and Variant B does not. Inside the story, test two different first steps:

• A1: intent options (“Work,” “Weekend,” “Event”)
• A2: attributes (“Slim,” “Regular,” “Relaxed”)

Compare which structure drives higher PDP CTR and wishlist adds.

If you want a deeper framework for running these tests (and avoiding common pitfalls), Storyly Experiments and A/B testing is a solid reference.

Keep the playbook tight:

• One change per test. Don’t swap creative and funnel logic at the same time if you want clean learnings.
• Measure the full path. Story/Banner engagement → PDP CTR → wishlist adds → conversion.
• Treat wishlist adds as a core discovery KPI. Not everyone buys in-session, but saving is a strong “you helped me find it” signal.

Use pre-sale wishlists to accelerate discovery and demand capture

Pre-sale wishlists turn discovery into demand capture. Many shoppers browse ahead of a launch, a drop, or a seasonal refresh. If they can’t buy yet, intent disappears: they leave and may not come back. A pre-sale wishlist flow gives them a clear next action, and gives you a measurable signal of demand.

The idea is simple: use stories or banners to showcase upcoming products or collections, then let shoppers tap to save what they like. It’s faster than “remember this and search later,” and it creates a clean, consented signal that the shopper explicitly wants that item.

For example, before a new collection launch, run a home page story featuring upcoming items with “Add to wishlist” interactions. Each tap saves the item, and you can route shoppers to a Wishlist page or a “Notify me” experience depending on your setup.

Or on category pages, add a banner that says “Preview what’s coming next” and opens a story of pre-sale items, letting shoppers wishlist directly from the story.

To keep pre-sale wishlists effective, keep the flow short. The best experiences feel like browsing a small, curated rack: tap through, save, done. The moment it turns into a long quiz or a heavy form, you lose the speed advantage.

Turn interaction signals into navigation and merchandising decisions

Interactive discovery isn’t just a front-end layer. The real payoff comes when you use interaction signals to improve navigation and merchandising.

When shoppers tap story options, choose guided paths, and add items to wishlists, they’re telling you what they want, clearly and on purpose. That’s different from passive signals like time on page or scroll depth.

For example, if a “Shop by need” story consistently shows a large share of shoppers tapping “Giftable,” that’s a merchandising signal. You might elevate “Gifts” as a top-level navigation item during key seasons, or create a more prominent gift entry point on the home page.

Or, if shoppers frequently tap “Lightweight” in a preference-based story but don’t click into PDPs, your curated set may not match what “lightweight” means to them. That’s a cue to adjust the product set, the labeling, or the landing destination.

You can also use these signals to improve placement. Strong engagement on the home page but weak engagement on category pages might mean category shoppers are in mission mode and need a more direct banner, or that your module is simply too far down the page.

Improving product discovery is an ongoing loop: build guided flows, run focused experiments, capture intent with wishlists, and use interaction signals to refine navigation and merchandising. When discovery becomes a measurable system, not a guessing game, shoppers get to the right products faster, and your key metrics follow.

Closing thoughts

Product discovery doesn’t need more complexity, it needs better shortcuts. Start with one high-traffic page, add a single guided path, and measure what changes. Once you find a flow that lifts PDP CTR and wishlist adds, you’ll have a repeatable pattern you can roll out across categories, seasons, and campaigns.