Website usability audit on 1C-Bitrix: where leads are lost
A website usability audit is not a cosmetic review of markup, but a step-by-step analysis of the customer journey: from search entry to order confirmation. We look not at “like it or not,” but at the point where a person stops and closes the page.
We measure each step by the share of abandoned actions — then the argument about tastes is replaced by a list of conversion loss points with clear priorities.
The first group of such points usually lies in checkout. A form with twelve fields where three are enough, mandatory registration before shipping calculation, cost and timelines hidden on a separate page — these are typical checkout barriers. We test them on real scenarios: one-step purchase, repeat order, order without a manager call.
The second group — catalog navigation. When there are thousands of items, filters overlap so that some products are unreachable in two steps, and breadcrumbs don't return to the desired selection.
A usability audit of an online store separately calculates depth: how many actions to the target product and how many dead-end branches in the menu.
The third group — interface response. A slow filter, a cart with delayed recalculation, a pop-up over the “Checkout” button — the user reads this as a breakdown and leaves.
On 1C-Bitrix, this is more often a consequence of caching settings and overloaded templates, not the platform itself: it is fixed selectively, without rewriting the site.
Then we compile findings into a map: step, share of losses, cause, what we change. From it you can see what to fix first — that's what our engineers do.
What changes after removing barriers in the customer journey
The first measurable shift — shortening the path to a lead. We count not “it became more convenient,” but how many steps and required fields separate the visitor from submitting the form: in typical 1C-Bitrix templates there are seven or eight, after edits three or four remain.
The share of those who complete the form grows immediately, without changes in advertising channels or prices.
The second slice — abandoned carts. A customer leaves more often not because of price, but because they don't see delivery terms, timelines, and payment methods before checkout.
We move these blocks above the button, show cost and timing before payment, rewrite error texts in fields — the cart stops being a dead end, and losses at the payment step noticeably decrease.
The third effect — load on support service.
When order status, approval stage, and rejection reason are visible in the personal account, the customer doesn't call with the question “what's happening with my order.” Clear hints in fields remove typical doubts before contacting, the flow of identical emails drops, and the freed-up time goes to complex cases.
Separately, we look at repeat customer requests. If the path to a lead is predictable, and order and document history is in the account, the person returns for the next service in the same interface, rather than searching again where to leave a request.
We check all edits on the same analytics slice before and after — this way, conversion growth after usability edits is visible separately from seasonal fluctuations.
Review formats: express, full cycle, ongoing control
The review mode is chosen by two parameters: how deep you need to dig and how quickly you need the result. We take measurements before starting work — otherwise, after edits, it's impossible to understand what exactly produced the effect.
Comparison of modes
| Format | When it fits | Limitations |
|---|---|---|
| Express usability review | Need to quickly remove obvious losses in key scenarios | Won't show causes deep in the funnel, hypotheses are not tested on people |
| Full usability audit cycle | Rework of sections and order logic is planned | Requires access to analytics and product owner involvement, takes longer |
| Review with user testing | There are controversial hypotheses, decision needed before release | Need to recruit respondents from the required segment, timeline depends on them |
| Ongoing interface control | The site is live: releases, promotions, new forms | Works as a procedure with regular measurements, not a one-time campaign |
You can start with an express review: it shows where losses exist now and gives grounds to decide whether a full cycle is needed. We fix the plan and scope of work before the start, so the scope doesn't creep during the process.
How the work proceeds: from taking metrics to checking edits
A usability audit of a website on 1C-Bitrix begins not with expert opinions, but with taking metrics: we look at which steps the visitor leaves at and compare this with user behavior recordings.
This way we get a list of loss points from facts, not general considerations, and formulate edit hypotheses for them.
- Taking metrics. We record the current funnel indicators: the share of those who reached the order, view depth, sources. This is the baseline for comparison — without it, there is no way to prove the effect of edits.
- Recording user behavior. We look at where the cursor freezes, which form fields are abandoned, which filters are not noticed. The recordings show the moment when the person gave up — it is not visible in the numbers.
- Prioritizing edits. We sort findings by impact on the target action and implementation effort. We take first what removes losses in the most common scenarios.
- Testing hypotheses on a prototype. We assemble a working version of the controversial block and give the user a task: did they reach the goal, how many extra steps did they take. We cut weak solutions before development.
- Implementation. We make edits in parts, preserving previous template versions and the ability to roll back: a complete replacement of the interface on a live site is too risky.
- Post-release control. Two weeks and a month after release, we take the same metrics. If the indicators haven't moved, we return to the hypothesis rather than leaving the edit “just in case.”
What remains with the client: maps, reports, procedures
The engineering result of the audit is not a presentation, but a set of artifacts that remain in the project repository and documentation. Six months later, they show why a block is structured this way, and the next edit doesn't break what was found.
- User journey map for each key scenario: from search entry to form submission or order placement, with the steps where the visitor leaves.
- Report on loss points with priorities: hypothesis, expected effect, edit complexity, and verification method — from field validation to the order of blocks on mobile.
- List of edits by templates linked to page addresses: which components and output rules we change so the edit doesn't spill over to neighboring sections.
- Edit mockups for key screens: state before and after, field behavior, error and hint texts.
- Release verification procedure: list of checks before deployment — scenarios, forms, analytics goals, cart and authorization behavior.
- Interface documentation: template map, purpose of custom fields and settings, integration points with the accounting system.
- Change rules: who approves the edit, which branch it lives in, and what is checked before publication.
With this set, the client's team makes changes themselves or hands them to us — in both cases, there is no need to figure out again how the scenario is structured and where it breaks.
Case study: share of completed orders and time to lead
What was before the edits
An online store on 1C-Bitrix with growing traffic: the share of completed orders held around a quarter of carts, and checkout took an average of 4 minutes 20 seconds.
Funnel audit identified three bottlenecks — mandatory registration before delivery selection, manual address entry, and a payment form that reported an error without indicating the problematic field. Support received over 300 requests per month, two thirds of them — “the order won't go through.”
What was changed and what became
Checkout was shortened from five steps to two: registration moved to the end and is auto-filled by phone number, address is determined by postal code, and fields with errors are highlighted along with the reason.
As a separate stage, we rewrote button and hint texts — the abstract “Continue” was replaced with a specific action, and order status was brought to the first screen.
After the edits, the share of completed orders grew from 24% to 41%, checkout time dropped to 1 minute 40 seconds, and support requests about checkout decreased by two thirds.
A class of repeats also disappeared: previously 12% of orders were created twice due to repeated form submission; now there are practically no duplicates.
Measurements were taken on comparable periods and a single traffic source, so as not to confuse the effect of edits with seasonality.
How usability differs from web analytics
Analytics answers the question “where”: how many people reached the cart, at which checkout step they dropped off, how the bounce rate changed after edits.
This is the quantitative layer — it reliably shows the scale of loss and its place in the funnel, but is silent about the cause.
A usability review answers “why”: a person doesn't find a field, doesn't understand the wording of a condition, doubts the delivery time, and leaves before the system recorded the failure. The counter sees the fact of leaving, but doesn't see the doubt that preceded it.
Observation and surveys give different things. A survey records what a person thinks about their behavior, and often diverges from reality: they will say they didn't find the button, although they missed it three times.
Observation shows the actual route — where they look, where they freeze, what they try to click, and why they abandon.
The question “is a review needed if there is web analytics” is resolved simply. Analytics narrows the search to a specific step; the review explains why the step isn't completed.
Quantitative data without qualitative gives a list of problems without priorities, while observation without numbers — a set of individual opinions. The combination works: numbers point to the loss point, observation and surveys explain the user's decision.
Common doubts: forms, cache, templates, integrations
Before the start, the same technical questions usually come up: what is needed from the client, whether work can be done on a copy, whether edits will affect integration with the accounting system. We answer before work begins so the review proceeds without risk to the production environment.
What accesses are needed and can a copy be sufficient?
For the audit, a copy of the site on a separate environment is enough: we take the database and template files, deploy locally, and work there. Access to the admin panel is needed to check form settings, caching rules, and real order scenarios.
We don't touch the production environment until edits are approved — the exchange with the accounting system continues to work as usual.
Will edits break the exchange with the accounting system?
Edits in templates, markup, and form scripts don't affect the exchange — they live separately from export handlers.
If an edit concerns places that pass orders to the accounting system, we first run the scenario on a copy with a test export: compare the field composition, exchange logs, and behavior on repeated submission. We transfer to production only after the data composition matches.
Why after an edit is the old version of the page visible?
Some pages are assembled from cache, so changes may not display immediately. Before deployment, we record which caching rules and components are affected, and clear them in a targeted way by section, not the entire site — otherwise the load will increase.
After that, we check forms and order placement end to end: from adding a product to confirmation, in different browsers.
Let's discuss the task: what we will show and in what form
The conversation begins with your task, not a template list of services.
To return with a substantive assessment, it's enough to have access to analytics, a list of scenarios where you observe leads being lost, and a short description of what you've already tried to change in the interface.
This is enough to discuss the usability task substantively and name realistic review timelines, not averaged ones.
What we will show at the meeting and in what form we will return with a plan:
- Map of conversion loss points: where exactly in the funnel the user leaves — by lead submission steps, forms, catalog pages, and cart.
- Analysis of user paths on live traffic and session recordings, indicating which step breaks the scenario and on which screen it happens.
- Estimate of review timelines: how much time each stage will take and what data it depends on, so you can plan the work.
- Edit plan after the review — with priorities by impact on conversion and a split into quick changes and template rework.
- Scope of interface work: which components and forms we touch, what we do on the template side, and what on the logic side.
- Set of metrics before and after edits, so the effect is measured rather than discussed in words.
Describe the task in a convenient form — send a link to the site and in two or three paragraphs tell us what is unsatisfactory. We will return with an assessment and work plan: what we do first, what can be postponed, and what result you will see at each step.