Conversion rates are a crucial metric for retailers to measure location performance and make necessary staffing and marketing adjustments to increase sales.

It’s important to analyze conversion rates over time against the same store as opposed to store vs. store, since different types of shopper or browser traffic affect how many visitors make purchases and how many walk out empty-handed. Here’s how to analyze conversion rates and optimize around trends.

What is a conversion rate and how do I calculate it?

Conversation rate is the percentage of visitors that “convert” to customers by making a purchase, enabling you to see how effective you are at driving sales from foot traffic. For instance, if 200 people visited a store and 40 made purchases, that store’s conversion rate would be 20 percent (40 divided by 200). In order to make strategic decisions using this key metric, stores need to measure foot traffic accurately.

This key metric can be used to determine store performance but only when taken in context. As a standalone data point, conversion rate can be misleading. In order to make strategic decisions using this key metric, one should always view it relative to storefront location and revenue.

Opportunity versus destination locations

A store in Times Square naturally has higher foot traffic because of built-in tourism draw, while a strip mall in a rural area relies on cars and has little or no organic foot traffic. This is the difference between opportunity and destination locations; whether the storefront is located in a high-opportunity area with plenty of foot traffic, or a less-trafficked location that requires customers to travel to a destination.

High foot traffic will result in a mixture of casual browsers and potential customers at an opportunity location, whereas destination location visitors usually make the trip with a specific purchase in mind.

Assuming comparable revenue streams, a store in Time Square will have a lower conversion rate than a strip mall, because the high foot traffic will result in a mixture of casual browsers and potential customers, whereas visitors to the strip mall usually make the trip with a specific purchase in mind, resulting in a higher conversion rate.

Retailers in both opportunity and destination locations can raise their conversion rates and revenue by staffing around visitor traffic and marketing toward these different types of shoppers.

It's important to factor in location type when looking at average conversion rates across regions or store types. The top ten converting stores in a company may only be high-converting because they’re destination locations, where top-selling stores may have a lower conversion rate due to a high volume of opportunity foot traffic. Factoring in these variables empowers retailers to evaluate their store performance more accurately.

The top ten converting stores in a company may only be high-converting because they’re destination locations, where top-selling stores may have a lower conversion rate due to a high volume of opportunity foot traffic.

Improving conversion rates by location type

To improve conversion rates across store locations, retailers should sort their stores into opportunity and destination locations, then analyze foot traffic, conversion rate and revenue alongside each other in order to optimize each store’s performance. Below are some examples of what retailers can do to shift the balance and increase revenue.

Destination location

Example: If foot traffic and conversions at the strip mall are up, but revenue hasn’t increased, then customers are making smaller purchases. Train staff to upsell add-ons to increase revenue.

Foot Traffic Conversion Rate Revenue Action
Up Down Flat Schedule staff for predicted high foot traffic periods to meet demand and convert more visitors to customers.
Flat Flat Flat Increase foot traffic and conversions by increasing marketing efforts and train staff to convert that marketing-driven foot traffic.
Down Flat Down Increase marketing spend to drive traffic and train staff to increase dollars-per-sale by encouraging add-ons.
Flat Down Up Focus marketing spend on driving traffic. Staff is excelling at add-on sales but additional staff may be required during peak hours.
Up Up Flat Look into what’s selling and identify ways to partner that item with other products in-store for additional revenue.

Opportunity location

Example: If foot traffic into the Times Square store increases, but the conversion rate decreases, and revenue also decreases, store staff isn’t adequately meeting increased demand. Adjust staffing and increase training to see a higher conversion rate and more revenue.

Foot Traffic Conversion Rate Revenue Action
Flat Up Up Increase targeted marketing to raise foot traffic and staff appropriately to meet the increased need.
Flat Flat Flat Flat isn’t always bad. Once you find the optimal level for staffing and marketing, an opportunity location “flat” will mean the plan is working. To increase revenue, increase marketing spend incrementally.
Down Flat Down Review staffing levels against foot traffic for this location to ensure adequate staffing. Look for trends in marketing and weather to indicate why foot traffic is lower than usual.
Flat Down Up Focus marketing spend on driving traffic. Staff is excelling at add-on sales but additional staff may be required during peak hours.
Up Flat Up Consider increasing staff during peak hours so customers receive more attention and convert at a higher rate.

Start using data to drive operations

Retail growth happens when real data drives the decision-making process. This is why Dor works with retailers to provide accurate foot traffic analytics, including conversion rate and missed sales opportunities.

Dor makes it easier than ever to get your traffic data and start making better business decisions.

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