E-commerce businesses of all sizes around the globe are scaling with Statsig.

Statsig supports e-commerce companies ranging in scale from Whatnot, the largest livestream shopping platform in the United States, to regional powerhouses like Flipkart and Hepsiburada, and innovative startups like LAAM.

E-commerce companies face unique complexities as they scale:

• Handling large volumes of visitors—and consequently, vast amounts of data—making it challenging to cut through the noise.

• Catering to diverse user segments, each with unique behavioral variations.

• Capturing limited attention from users in a crowded market.

All this makes it challenging to prioritize growth efforts and ship features that positively impact core metrics (and don't inadvertently tank them).

Four products, one platform

Statsig helps E-commerce companies at every stage of the buyer journey with four core products within a single, integrated platform:

• Feature Flags: Help with precise targeting of users, turning features on and off, and automatically converting every rollout into an A/B test.

• Experimentation: Lets you test hypotheses, drive learnings, and positively impact core metrics.

• Product Analytics: Dive deep into your metrics, identify opportunities, and make data-driven decisions throughout the development lifecycle.

• Session Replay: Gain contextual, qualitative insights by watching how users interact with your product.

Driving growth at every stage of the customer journey

The e-commerce buyer journey can be segmented into four distinct steps: Discovery → Research → Checkout → Retention.

Each stage offers tremendous opportunities at both the front end and back end to drive core metrics. Below, we'll look at examples of customers leveraging Statsig to drive growth at each stage of the customer journey:

1. Discovery

The first step in the e-commerce customer journey is discovery. When users visit a site for the first time, how do you grab their attention quickly before they bounce?

Key metrics to track here include bounce rate, pageviews per session, time spent per session, and new user sign-ups.

A common approach is to try different homepage banners, layouts, CTAs, etc., to drive the desired actions, such as product searches and adding to cart. But this only scratches the surface.

We see customers tailoring the new user experience based on contextual elements like the traffic source (ads, referral, or organic search) or the visitor's country to resonate with the users better and grab their attention.

Customers like Cider were able to tailor localized experiences as they scaled across 160+ countries globally and ensured that they could deeply engage their users — using experimentation to learn user preferences and iterate.

2. Research

Now, as the user starts to explore the products/services on the platform, how do you engage with them deeply, empower them with the right information, and nudge them to make a purchase?

Key metrics to track here include: Add to cart rate, Conversion rate from product page, Click-through rates from recommendations, engagement with reviews/Q&A

A common strategy is to drive impulse purchases by providing a special offer or discount code, but this may not always be an option, especially if it has already been used multiple times in the past.

We see our customers achieving success when fine-tuning the search and recommendation algorithms to provide a better experience that delights users as they browse the platform.

LAAM optimized their homepage design and listing page rankings, leveraging data from Statsig. They also tested a wishlist feature to allow users to save items — which ultimately resulted in acquiring new users and more products added to the cart.

Here, as with every stage of the customer journey, Statsig's Product Analytics helps you understand what is working versus what isn't and how users are engaging across core product workflows. You can also define highly specific user cohorts and analyze their engagement. For example, you can look at users who looked at a product but didn't add it to cart.

3. Checkout

Optimizing the checkout process is a classic experimentation use case, filled with opportunities to make the experience as frictionless as possible.

Here, Statsig’s Funnels help you identify the exact points of drop-off so you can focus your efforts where they are most needed. The tight integration of experimentation with Product Analytics means you can not only pinpoint problems in the funnel but also quickly test ideas to solve them.

LAAM reduced the number of steps in their checkout process from five to one for logged-in users and two for logged-out users. They were able to quickly understand drop-off rates between steps and optimize various elements of the funnel by running A/B tests on Statsig.

Similarly, Cider created a one-step checkout to simplify the process for first-time buyers without accounts. They used Statsig to test a one-time code option, eliminating the need to sign up during checkout. This change ultimately drove higher sales and led to a 20% increase in new user registrations.

4. Retention & upselling

The customer journey doesn’t end after a user makes a purchase. The real value in an e-commerce business lies in driving long-term loyalty and maximizing the customer's lifetime value (LTV).

OfferUp iterated on various features like search and filters on their selling page to drive sustained engagement in their marketplace. By setting up layers, they could implement more experiences in shorter development lifecycles, ultimately increasing free trial subscriptions by nearly 4% and targeted CTA clicks by 11%.

Similarly, boosting customer lifetime value (LTV) through upselling is a key driver of revenue growth for Cider, with personalized recommendations playing a pivotal role. Cider uses Statsig to continually fine-tune its recommendation algorithms to maximize upselling opportunities without negatively impacting long-term retention.

Going from achieving quick wins to driving continuous learning

We've observed that customers initially achieve quick wins by identifying low-hanging fruit, which increases key metrics and builds trust and momentum for their experimentation culture.

As the culture spreads across the organization, we see our customers becoming more hypothesis-led when building products and significantly increasing their experimentation velocity—often by 10/20/30x. For example, Whatnot migrated to Statsig Warehouse Native, achieving flexibility, trust, and agility as they scaled.

By choosing Statsig, you are partnering with a platform that is equipped to scale with you from your early days to having millions of active users.

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