The smart retail glossary.

What customers paid on average for each item sold. It is one of the four components of the Eyez Score, which deducts price rises from it, so a higher price alone never counts as an improvement.

Formula Average item price = revenue ÷ items sold

What each purchase is worth on average. It breaks down into items per transaction times the average item price.

Formula Average transaction = revenue ÷ transactions

What the system learned and what the manager taught it, with research on your segment and its opportunities and challenges. Together they shape every insight and answer from the advisor.

A day with sales and no visitors is recognised as a counting fault, not a closed day. It never skews conversion or the comparisons, and the Eyez Score skips it.

Every campaign is measured against a baseline calculated from the history before it, to know how much revenue it added above normal. Its goal can be a percentage above the usual average, a sum for the period, a daily goal or no goal.

How many of the people who walked past the store came in, for example 20 of every 100 who passed. It is measured in stores with an outside sensor.

Formula Capture rate = came in ÷ walked past × 100%

Goods that sit in the store but belong to the supplier until they sell. It is the supplier's money, so EYEZ never counts it as the business's money stuck in stock.

How many visitors bought, for every hour, day and period. It tells you whether a drop in revenue came from fewer visitors or fewer buyers.

Formula Conversion rate = transactions ÷ visitors × 100%

Couriers, suppliers and pickups are corrected in the conversion base, as a fixed percentage or for a specific date. The displayed count stays as is.

How many days the stock on hand will last at the sales pace. You see it for the whole stock and for every supplier.

Formula Days of cover = stock at cost ÷ cost of sales per day

A 0 to 1000 score that shows what every unit of an employee's pay brings back. It is built from 4 components: output per cost, profit per hour, sales per hour and value trend.

A 0 to 1000 score that compares every store only with its own history, with 750 as the store's normal level. It is built from four components, visitors, conversion rate, items per transaction and average item price, and shows how much each one contributed.

Up to 3 time ranges, and whole weekdays, are taken out of the visitor count only. Revenue never changes.

The Eyez Score of a young store without a year of history yet. A new store gets it after just 3 months of trading, and the network score includes it too.

A daily goal checked during the day against the store's hourly curve: the share of a typical day that is usually behind you by this hour. The goal gets a state, on pace, behind, at risk or achieved, with no verdict before 20% of a typical day.

Formula Expected by now = today's goal × share of a typical day already behind you

How many items each purchase holds on average. It is one of the four components of the Eyez Score, and the simulator works out how much more revenue a month 0.1 more items per transaction brings.

Formula Items per transaction = items sold ÷ transactions

The number of visitors without the people who only came to collect an order. It is shown beside the total visitors and the number of pickups.

Formula Net visitors = total visitors - pickups

One Eyez Score for the whole chain, weighted by revenue and including young stores. The network view shows it beside each store's 30-day Eyez Score.

The hour of the day when the most visitors come in. A day-by-hour heatmap shows it for every store and for the whole chain.

A 0 to 1000 score for every employee, built from 11 components, among them personal conversion, contribution to the store and performance under load. Each component is measured per hour against the average of the employees in the same period, and a warehouse worker is never judged on sales.

People who came into the store only to collect an order. They are counted apart, so someone who only came to collect never skews the picture.

A target and a forecast for every day of the month, against what actually happened. The plan locks on the 1st, so you always compare with the real plan, and you can look back up to 24 months.

Takes one or more of 8 segments, such as children, out of the visitor count. Revenue never changes.

The label the daily SMS carries on Fridays and holiday eves, when the numbers are not final yet. If the numbers move by more than 5%, an update follows at 10:00 the next day.

A ready monthly order list: what, how much, from which supplier and on what budget, without breaking the turnover goal. Items are sorted into five urgency levels, from immediate to as planned.

How much a campaign brought back beyond what it cost. The system takes the gross profit on the extra revenue above the baseline and sets it against the campaign's costs, of ten types.

Formula Return on investment = (extra revenue × gross margin - campaign cost) ÷ campaign cost × 100%

The money that came in at the till. EYEZ breaks it into three factors, visitors, conversion rate and average transaction, and tells you exactly which one moved.

Formula Revenue = visitors × conversion rate × average transaction

Expected revenue to the end of the month and of the year, based on the same weekday last year, the same holiday and the store's actual pace. One engine computes it, so the page, the network table, the advisor, the SMS and the email always show the same number.

How much of the goods sold: the units sold in the period out of everything there was to sell. It sits in the stock picture beside days of cover and annual turnover.

Formula Sell-through = units sold ÷ (units sold + units in stock) × 100%

A deletion, ownership transfer or emptied data at the source is held aside until approved, so years of history never vanish by mistake. It works beside an independent data mirror and a nightly encrypted backup.

How many working hours are planned for a store: a weekly, monthly or daily standard, or a formula of one employee per so many expected visitors an hour. The system compares actual hours with it and checks whether going over it paid for itself.

How much stock to hold right now at your sales pace. The ceiling moves with sales and shows whether you are above it or how much room is left.

The share of stock, at cost, that has been in stock for more than a year. The screen shows it as a percentage and an amount, beside six age tiers.

Formula Stock over a year old = cost of stock older than a year ÷ cost of all stock × 100%

How many times a year the stock is sold and replaced at the sales pace. The replenishment report builds the order list without breaking the turnover goal.

Formula Stock turnover = 365 ÷ days of cover

A comparison of two stores or two groups that separates volume (visitors and revenue) from efficiency (how well the traffic was used). It also shows what would happen if one side reached the other's level.

What the system learns about the team: how many employees each level of traffic needs, when load hurts conversion, busy hours with too few staff, and which pairs of employees sell better together.