Mall Analytics: Mall Traffic, Proximity Traffic and Capture Rate

Shopping malls are not dead. They are evolving due to the disruptive trends in how people buy. The data tells us what shopping malls, and retailers, should do to survive, and thrive.

Mall-To-Store Purchase Funnel

To increase sales in mall stores, we manage each step in the process to purchase. In the Mall to Store funnel, we use KPIs of Mall Traffic, Proximity Traffic, and Capture Rate.

The relationship between the mall and the store is two sided. The mall gets leasing fees, which often include rent plus a percentage of sales.

In return, the retailer expects the mall to generate traffic for the store. In essence, the reason to lease a store in a mall is sales leads.

Thus there are three steps in the Purchase Funnel.

Mall Visitors

The first metric to define demand is the sum of mall visitors, per period of time. In the same manner that we measure Arrivals and Exiting in the store, we count the number of visitors to the mall.

Another area of interest is the traffic flow through the nearest entrance to the store. We seek a correlation between the mall’s entry point and the people passing by the store. This is about the proximity of mall traffic to the store.

Some of the shopping centers are huge and we can see a direct link between traffic in an entrance and a specific store. This is also the reasoning beyond Anchor Stores.

For example, Sawgrass Mall in Florida is one of the largest malls in United States. It takes an hour to walk in a constant pace from one side to another. If a visitor entered the Target store, they are unlikely to get to Marshall’s on the other side.

The analogy to online metrics is Cold Traffic.

Having 10,000 daily visitors in the mall is akin to cold traffic to your blog.

Proximity Rate = (Passing by the Store) / (Mall Visitors)

Proximity Rate is sometimes used in the same manner as the Capture Rate. We use Proximity in the context of measuring demand close to the store.

The analogy to Proximity Traffic is akin to your website’s Warm Traffic.

We get the number of people passing by either from the mall or from the store tracking solutions. Either way, the Proximity Rate is the percentage of the people passing close to the store divided by the sum of mall traffic (per period of time).

One of my favorite case studies is the impact of the Apple store on an upscale Mall. When the Apple store opened on the third floor, it changed the flow of traffic in the shopping center. Before, few people visited the 3rd floor. Afterwards, the stores enjoyed the most lucrative location inside the mall. The Apple Store increased their Proximity Rate in double digits.

Capture Rate = (Store Visitors) / (Passing by the Store)

The Capture Rate measures the success of the store to entice people to visit the brand.

The analogy to the online world is taking the first Call-to-Action. In a blog, it will be ‘to subscribe’. In eCommerce, it will be to ‘add to shopping cart’. The point is action.

A good case study is a jewelry store in a busy mall. The store sits in the corner between two major arteries of mall traffic. And it has open case displays which people can access from both sides.

The number of people passing by each entrance was similar. But the data showed that most customers entered through one entrance. The second entrance has many people walking nearby but almost no visitors.

Turned out the reason for the low traffic is that the entrance faced the food court. The high traffic entrance was set in the main path of the mall. The Capture Rate told the story and the store took action.

Sales Conversion {Visitors, Transactions}

When we talk about sales conversion, we attribute it to the store. In such, conversion is a function of the store traffic and transactions.

We can expand the definition of visitors to mall traffic. Since those conversion rates are small, they are almost never used by retailers. But this is a good analogy between online and offline analytics. In the data, we see the warm traffic (people passing in proximity) versus cold traffic (mall visitors).

Analytics of Mall Stores

To quantify the value of the mall to the retailers, we take a closer look at the Proximity Rate and Capture Rate. The metrics describe the mall visitors’ intent to buy.

But first, a conversion about quality and accuracy of data is in order.

Sensor vs. Device Tracking

A point of caution comes from the data. Many shopping malls deploy WiFi, GPS and Beacons technologies for Location Marketing. For the mall owners, this is the solution to judge the quality of promotional content. Along the corridors, the malls often install digital screens in various sizes and forms. We can compare traffic flows week to week, and period to period, and judge the effectiveness of marketing.

But data from tracking devices has its challenges. Regardless of vendor providers and signal frequency, the data is a sample. And yet, with only 50% to 70% of actual traffic the marketing agency can search for insights.

In Location Analytics, the challenge to device tracking is data consistency. It is better to deploy sensors for people counting in malls and stores. And yet, the tracking data from devices is better than no data.

Proximity Rate is the value of “Warm Demand” Traffic

The first factor of the analysis is how the patterns of traffic inside the mall relate to our store. Proximity Rate measures the “close enough” demand to the store.

Entrance Traffic: The question here is does it matter where, and when, people enter the mall. The data provides mixed answers. Either way, there is benefit to test for demand quality in context to the mall entry point.

InMall Traffic: There are two categories of flow patterns. The first has to do with mall traffic, such as the case of the jewelry store. The second comes from the location and nature of the store.

Take the number of entrances as a factor in the analysis. There is a difference between stores with a single entrance and those with two or more. In such stores, the traffic flow includes people who enter and exit the parking lots. This irrelevant traffic will lower the sales conversion.

Events Traffic: To increase traffic, malls do their own events and promotions. As a retailer, we test for quantity and quality of the change in traffic. A caveat in events traffic is that massive crowds tend to push away the shoppers.

Capture Rate measures the ability of the store to attract visitors

Proximity Rate tests for mall patterns. The Capture Rate measures the ability of the store to attract traffic from people in proximity.

In Capture Rate, the two factors are the number of people passing by and the number of people who entered the store.

How close is close: When we setup sensors, the challenge is in the field of view. The tilt of the sensor can be adapted to 1 or 3 feet. Thus, the tracking solution should define the concept of “proximity traffic”.

Stay Time at Window: There is a debate if Stay Time validates the success of a store window displays. Some say that the only “success” factor is when people stop and look at the display. But visual display has subconscious affects. This is true for windows, mannequins, and display cases.

Marketing Signage: When stores put signage outside the store, the intention is to entice people into the store. But displays impact the flow of people outside the store. Sometimes, signage creates obstacles to entry.

Lease line: the traffic sensors count the people who cross the lease line as visitors. Sometimes, stores have displays where customers can stand outside the lease line.

In jewelry stores, people can stand outside the store for most of the sales process. In such situations, the system may be inaccurate in counting the number of visitors or stay time. This can remedied with tilting of traffic sensors toward the aisles of the mall.

Bringing It All Together

Mall stores are an important weapon in the arsenal of retailers. For retailers, the value of a mall lies in its ability to generate traffic. And mall analytics must evolve as well.

The Mall to Store Funnel measures the Mall Traffic (cold traffic), Proximity Traffic (warm traffic), and Capture Rate (Call to Action). These 3 Key Performance Indicators quantify the relationship between mall and store. And together with InStore Funnel, the analytics method is robust, productive, and profitable.

Ronny Max is the founder of BehaviorAnalytics.Academy. We provide online courses, workshops and corporate training on growth methods for the physical store. Want to Increase ROI from the Technologies to Track People? Enroll for FREE.