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Retail Growth Objectives Part 1 – Traffic and footfall

Sydney, 10.03.2016

Norrelle Goldring from GfK introduces a new series on principles of retail profit, growth, store execution and customer experience.

In previous articles in the ‘Retail Rules’ series we discussed some retail profitability measures. Now we’re moving on to the 3 ways to grow in retail that translate into 5 retail growth objectives.

These are more shoppers (traffic, basket penetration), spending more (spend, average weight of purchase), more often (frequency). Here we’re going to discuss traffic or ‘footfall’ as a retail growth driver.


Traffic or footfall is the number of shoppers crossing the store, department, aisle or category threshold in a given period (hour, day, week, month, year).

Traffic is a critical retail driver so the aim is to grow it. Assuming purchase conversion rates remain constant, and increase in traffic can equate to an increase in one or more of frequency, AWOP, and spend.

Essentially, there are two kinds of traffic: new and repeat. Traffic might be repeat to the retailer, but new at a store level, or new to a category but not to the store as a whole.

Traffic is linked to the drivers of individual store selection. Shoppers typically choose stores based on proximity, range, ease of shopping, overall value (not just lowest price), service & knowledgeable staff, occasion shopping for, shopping trip type (mission), and special offers.

Proximity – how close your store is to a shopper’s work or home - can’t be influenced, but the rest can, and all do, influence traffic.

Improving store range and shopping experience is a long term retail goal and may result in increased store traffic over time driven by consumer preference.

Retailers need to understand which categories and brands are destination or traffic driving categories, whether on or off promotion.


It’s one thing to get the footfall, it’s another to convert it. Not all traffic, or every shopper, results in a purchase. Here it is important to understand your traffic-browse-buy ratios. If you have a low traffic-browse but a high browse-buy ratio in a category it is likely that that category is an intentional destination purchase, but for only a few shoppers. Conversely, if you have a high traffic-browse but a low browse-buy ratio either at a store level or at a category level you are doing a poor job of converting shoppers. This could be for any number of reasons but typically to do with range (don’t range it or out of stock means don’t have it), space & layout (can’t see or find it, which is tantamount to don’t have it) or price (too expensive). Not buying an intended product for one of these reasons is called ‘abandonment ‘– the shopper has abandoned the category or purchase. (In the online space abandonment means shoppers filling their virtual carts but then failing to check out).

But it might not be all your fault.

Shoppers might not be in the store to buy, they might be there to research. Particularly if it’s a higher involvement, higher spend and/or more complex category like consumer electronics. (Less likely with chocolate bars in a convenience store). Or if they are in a bottleshop looking for premium whiskies or vodkas as a gift, for example.

Shoppers might also be browsing a category to see if one of their brands just happens to be on special whilst they’re actually in the store for something else. We see this in supermarkets with some regularly bought categories. Shoppers know that the supermarkets just rotate the big brands around on frequent promotion every week or so, so they might check a category like dry pet food or the health and beauty aisle to see if one of their brands happens to be on special while they are in the store shopping that week. If not, then they leave the category and aisle – but it’s not really abandonment, because the purchase wasn’t necessarily planned or on the list.

Or they might be ‘boomeranging’, which is when they don’t shop an entire aisle or category, they simply go to the part of the aisle where their category is located, pick up what they wanted and leave the way they entered, without shopping the rest of the aisle.


It’s important to understand your traffic numbers at store, aisle and category levels – both the benchmark or baseline, and promotional period traffic. There are a number of ways to capture this:

Traffic counters assist in measuring footfall and can be compared to your transaction numbers to understand your overall traffic/buy (conversion rate, without the browsing stage) at a store level.

  • Your POS and loyalty card transaction data will help you understand your current converted (purchased) store traffic levels, with transactions as the proxy. It will also give an indication of converted category level traffic, depending on how many instore locations a category has. However, transaction data won’t tell you who is not traversing an aisle, or who/how many are abandoning, or how many are simply researching without purchasing, or traffic/browse/buy ratios.
  • To understand these, you actually need to observe shoppers. This is also helpful because you can see your product level traffic/browse/buy ratios … how many products in a category shoppers look at, touch, pick up – in what order – versus what they put in the basket. Shopper observations can be done by installing video cameras which are great for lower traffic categories because the cameras operate 24/7. Or you can get field researchers to physically watch shoppers for a week or two. (Although a cheap way out, using your store’s existing CCTV cameras aren’t generally helpful because they only look at a certain portion of the store, or there aren’t enough to observe all categories, or might not be located near the ones you want to observe).

At any rate, if you install video cameras or get researchers to observe shoppers you’ll also be able to get additional data such as gender, approximate age and dwell time – how long they spend in the category or the store.


• Traffic to store: yes, promotions. But also targeted personalised offers to shoppers using the customer data on them that you have captured. You may be communicating with them digitally or on their mobile phones. It’s not just about price based catalogue specials. Loyalty programs and rewards schemes can be used for special offers at traditionally slow times of day and days of week.

• Traffic to aisle/category: cross promote with other categories. Loyalty programs and rewards schemes can be used to drive traffic to certain categories by increasing the number of rewards obtained by shopping certain products in certain categories. Noise around new product releases, particularly for desirable brands. Apple iPhone springs to mind as an example.

So that’s a bit about traffic. Next time around we’ll look at the conversion side of it known as ‘basket penetration’ - ways to get the item in the basket.

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Norrelle Goldring is Head of Shopper Insight & Retail Strategy at global consumer research and retail datahouse GfK. She has 20 years’ experience in retail across manufacturer, retailer and agency roles with companies ranging from Diageo to Coca-Cola to Vodafone Stores. Norrelle helps improve shopping experiences by understanding how and why people buy things.

Call Norrelle on 0437 335 686 or email norrelle.goldring@gfk.com.au.

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Norrelle Goldring
Norrelle Goldring
Australia and New Zealand