Conversion rate is a ratio. Any ratio improves if you shrink the denominator. That is the whole problem, and almost every incentive built on conversion rate ignores it.

I saw a discussion recently about queuing outside stores, centred on whether luxury brands should be queuing under the banner of scarcity and exclusivity. That debate usually stays at the top of the sector. What goes unnoticed is that plenty of premium brands and stores have queues outside as well, and often their head offices do not know it.

In many cases, the reason for doing so is to support conversion rates.

In stores, the holy grail of KPIs is often and still considered conversion rate. Score high and you do well. Score low and you are clearly doing something wrong as a store. Some premium brands even go as far as to incentivise it, awarding structural bonuses for achieving conversion rate targets.

The problem is that stores can get into the habit of acting to increase their conversion rates at the expense of their top line, and even of the enterprise bottom line.

Where the cost actually lands

Traffic and sales are highly correlated in stores. Just as importantly, marketing departments invest huge sums into getting customers to those stores.

Marketing costs usually are not distributed across store P&Ls. So stores do not see the impact on their own profitability when they queue and filter customers out. But it is essentially this simple: marketing spends to get customers to the door, and when customers get to the door, the door is closed. In turn, marketing often has to increase spend to get customers to the door, and the cycle continues.

Customer acquisition cost goes up. Sales generally do not increase, or at least not to the full potential of the store. And store managers and teams get rewarded for their great conversion.

What it does over a longer period

Extend the pattern over time and the problem compounds:

Traffic numbers are interpreted as fact. Traffic may appear stagnant in reports, while in reality demand is higher than perceived and people simply are not willing to queue.
Everything around the store is then planned accordingly: forecasting, buying, allocation, staffing, marketing.
When those are planned on that basis and stores do decide to let more people in, the product is not there and the staffing is not sufficient. Potential is missed again.
Make adjustments, create a queue again to boost conversion, and now you are overstaffed and over-allocated. You need to reduce prices on too many products, decreasing gross margin. All because store teams are driven to deliver the highest conversion rate rather than sales.
Marketing costs increase. Prices may be raised, which pressures conversion further through price elasticity. Staff may even be cut to protect profitability.

The arithmetic

Simple maths shows queuing will not necessarily fix the top line through better quality of sales either.

Consider a store with 5,000 visitors in a day, at 10% conversion and an average transaction value of €200. That is €100,000 for the day.

Now queue, and let in 20% fewer people. That is 4,000 visitors. Boost conversion by the same 20%, from 10% to 12%, which is not a given. Assume ATV holds at that scale. That is €96,000 for the day, down 4%.

This means you need to outperform your conversion rate against your traffic decrease. For every customer you let in less, you need to convert at 25% more just to stand still. And even then it does not account for the people who could have experienced the brand but never got the chance, or were not willing to wait.

"But queuing raises basket size"

This is the strongest argument on the other side, and it deserves a straight answer: if the customers who wait are higher intent, surely they spend more, and ATV rises enough to cover the lost traffic.

Run it through the same example. At 4,000 visitors and 12% conversion you have 480 transactions. To reach the same €100,000 you now need an ATV of €208.33. So you need a 20% lift in conversion and a 4% lift in ATV, simultaneously, simply to end the day where you started. Anything less and you are down.

There is a second problem with the assumption. Queues are used most heavily during peak trading, and peak is precisely when baskets are already elevated and when time pressure caps how much anyone browses. The headroom for an ATV lift is smallest exactly when the queue is longest.

And the customers most likely to wait are the ones who were always going to buy. You are not adding spend from them. You are removing the marginal visitor who would have added incremental units.

"They were not serious customers anyway"

Many store leaders are convinced the 1,000 people who avoided the queue were simply not serious. There is no way of knowing that, and it is a risky assumption.

The customers who were not willing to queue will not magically shop in your online store instead. They may just buy from a competitor who left the doors open.

People who visit and leave without buying provide data too, positive and negative. Stores are commercial engines, but they are also brand touchpoints. A customer may have liked what was in store but found their size unavailable. They tried a different product, and now they know their size. They will buy the right size online later. At the very least they leave with a positive feeling about the store and the brand, and become a return visitor and in time a customer, because they were able to experience the store from the inside.

In that scenario the acquisition cost is not wasted. The store manager may not see direct revenue from it, but the enterprise will. Queuing for conversion does not do that.

Shrink is a different argument

Shrink is often raised here, and the case can be well made that filtering people out and raising the entry barrier does keep some people with bad intentions away.

But that is focusing on a symptom, just as much as focusing on conversion rate is.

Shrink is calculated at cost. Products are sold at ask. Marginally decreasing shrink at cost, at the expense of selling product at ask, is not a viable business model.

The cost to everyone around you

More holistically, and already visible in certain city centres and shopping and outlet centres: if multiple stores in a dense area queue at the same time, the appeal of a day out to shop decreases.

If people need to queue in traffic, queue for a parking space, queue for multiple stores, and then, depending on how well a store is run operationally, queue for a fitting room and a till, that customer comes back less often. That reduces lifetime value not only for the brand and store in question, but for every other store around it.

Stores have a big role to play in the attractiveness of shopping areas. Many of those same stores and brands increasingly talk about the pressure caused by online retail. Having people queue outside to boost a KPI no one outside your company cares about may just make that a self-fulfilling prophecy.

What conversion is actually for

Conversion should be viewed as an outcome of many things. Some are rightly in the control of store teams. Many are not related to them at all.

Conversion is a combination of demand created, product availability, price elasticity, and environment and experience. To get a real perspective on what it means, and on the potential of a business, everyone willing to enter needs to be able to enter. Only then is scaling to full potential possible.

There are exceptions. Sometimes health and safety is a genuine concern and crowds need to be let in in a phased way. Sometimes staffing or operational processes simply cannot cope with the numbers arriving. Even then, that should be treated as data to act on: invest in staffing, which is usually cheaper than acquiring or reacquiring customers; optimise processes; in time, look for a bigger building to balance supply and demand.

But that is crowd control. It is not artificial queue management to protect a conversion rate.

Instead, retailers should incentivise the things that matter to the bottom line and that are directly understandable and actionable for teams. Units sold during the non-sale window, for example. Conversion should be worked with exclusively as an outcome of what happens when all traffic comes in, to support the data needed for sustainable growth. That improves decision making at store and enterprise level, and creates alignment across departments instead of self-sabotage.

Conversion rate has an incredibly important place in stores and in retail. But ironically, the brands most focused on conversion rate in itself risk being the ones furthest from converting to their full potential.

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