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Ecommerce optimization services use store data, customer research, usability reviews, testing, and implementation to identify and reduce avoidable friction in shopping journeys. By making it easier for shoppers to find products and complete purchases, these services can support more orders and sales—but no published benchmark or vendor case study can predict the result for an individual store.
What ecommerce optimization services do
Ecommerce conversion rate optimization (CRO) is a systematic process of improving a site so visitors can complete a desired action more easily. For an online store, that usually means examining the journey from product discovery through checkout, then using evidence to decide what to change and whether the change helped.
The work may combine several activities:
- Quantitative analysis: Review funnel and behavioral data to find where shoppers leave or struggle.
- Qualitative research: Observe or interview customers and run usability sessions to learn why problems occur.
- Benchmarking and audits: Assess the store’s experience, including product discovery and checkout, against usability principles or competitors.
- Prioritization and experiments: Turn findings into hypotheses, rank them by likely value and effort, and test suitable changes.
- Implementation: Make validated improvements, with the necessary design and engineering work.
These elements are not a universal service definition. For example, scandiweb describes consultation, store-specific CRO planning, benchmarking, data analysis, moderated user testing, experiment design, and engineering implementation as parts of its own program.
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Optimization can help when a fixable obstacle prevents an interested shopper from acting. A service investigates the store’s own journey rather than assuming that every possible improvement matters equally.
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Product discovery
If shoppers have difficulty locating relevant products or understanding product information, they may not reach the point of considering a purchase. Behavioral data can show where discovery breaks down, while customer research can reveal what people expected to find. A proposed change should address an observed problem and be evaluated against an agreed measure.
Checkout completion
Checkout is a reasonable area to investigate because complicated forms, trust concerns, payment friction, or unexpected costs can stop shoppers who otherwise intend to buy. These are possible causes to validate with the store’s own data and customers, not a checklist that applies in the same way to every business.
Cart abandonment also includes shoppers who are not ready to buy. Baymard Institute reports that 42% of US online shoppers abandoned a cart in the previous three months because they were browsing or not ready to purchase. That share is not evidence of a checkout defect a service can remove.
Measure changes against the store’s goals
Baymard defines conversion rate as conversions divided by visitors, multiplied by 100, and recommends ongoing measurement. Before comparing results, specify what counts as a conversion, which visitors are included, and which segments or time periods are being compared. Baymard also notes that a universally “good” conversion rate cannot be set across industries; a store’s own goals and relevant comparisons over time are more useful than a context-free target.
Why checkout gets attention—and what the numbers mean
Baymard Institute’s research overview, accessed October 7, 2026, reports a 70.19% global average cart abandonment rate, tracked across 14 years. This is an aggregate figure, not a forecast for a particular store.
In an article updated February 2, 2025, Baymard states that 17% of US online shoppers reported abandoning an order in the past quarter because checkout was too long or complicated. The same article estimates a 35.26% potential conversion increase for the average large-sized ecommerce site from checkout design improvements alone. Baymard’s current research overview also says its usability sessions indicate that the average large-scale ecommerce site could potentially gain a 35% conversion increase through better checkout UX, and identifies 32 unique checkout improvements on the average site. These are Baymard research-based estimates of potential, not expected or guaranteed outcomes for a merchant.
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Vendor-published examples are also specific to their cases. Shopify says its customer Stellar Eats saw a 3.5% conversion lift after switching to Shopify’s one-page checkout. scandiweb displays client-reported examples of a 12% increase in checkout conversion after a checkout rebuild in a regulated market, a 40% increase in checkout conversion following a separate multi-step checkout redesign, and a 73.32% increase in add-to-cart rate after another landing-page revamp. These are selected provider or platform case studies, not independent evidence of typical results or a promise of what another store will achieve.
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There is no established universal ranking or independent head-to-head comparison among providers in the sources cited here. Compare the proposed work and evidence, not just headline uplift claims.
- Store-specific starting point: Does the provider begin with your goals, analytics, and customer journey?
- Research depth: Does it combine quantitative evidence with customer research, rather than relying only on visual opinion?
- Prioritization: Can it show how findings become ranked, testable hypotheses?
- Implementation: Who builds approved changes, and how will technical risks be managed?
- Measurement plan: Which primary metric and guardrails will be monitored, for which segments, and over what period?
- Relevant evidence: Are case studies comparable to your business, and can their results be independently verified?
- Clear deliverables: Are the audit, experiments, implementation responsibilities, and reporting defined before work begins?
Ask providers to explain the link between evidence, proposed changes, and success criteria. That makes it easier to distinguish a reasoned optimization plan from a list of fashionable design changes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to expect from results
Optimization is incremental: a change may help, have no measurable effect, or perform differently across customer segments. Neither a research benchmark nor a provider’s selected case study establishes what your store will gain. Treat uplift claims as context, define success using your own conversion event and business goals, and judge changes with consistent measurement.
In Shopify’s vendor-published account, Everlane product lead Anna M. Peterson said: “With the Shop Pay experience, people are getting through checkout faster than with all of our other payment methods.” This is an attributed customer statement in Shopify’s context, not a general finding that applies to every store or payment option.
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