Understanding your ideal customer and your closest competition are crucial for success in the QSR and retail space, especially for brick-and-mortar locations. Companies need insight into current and potential storefront locations to understand who has a foothold in the area, along with the customer journey and visitor intent.
The Spectus Data Clean Room was built to provide the tools, data, and infrastructure needed to expedite the development of custom location data-based solutions in a privacy-focused way.
One of the first steps in a competitive analysis is to assess which of your competitors have footholds in the markets or neighborhoods you’re evaluating. Even in a market you already operate in, you need to continuously monitor your competitors’ presence.
The pandemic has had a major impact on brick-and-mortar locations for both retail and quick-service restaurants (QSR). Retail vacancy rates hit a seven-year high in 2021. Major retail chains closed more than 12,000 stores in 2020, resulting in more than 150 million square feet cleared out. These closures have resulted in rent price changes, as well as opportunities for strategic growth. Beyond just knowing the competition in the area, you need to understand how visitors are interacting with their locations.
- How much time are individuals spending in the store?
- Where are they going before or after their visits?
- What socioeconomic groups are visitors associated with?
Addressing these questions informs you of the health of your competitors’ locations, as well as the health of the area as a whole. Our POI data gives you a solid foundation for the competitive analysis process. The capability to dig into specific POIs and the mobility data associated with them identifies competitors’ footholdings in areas of interest – giving you a clearer picture of potential opportunity. You can also analyze foot traffic patterns, dwell times, and visit frequency in order to gauge areas most primed for location expansion or closures. Users also have the ability to upload their own list of POIs to our Data Flow Studio and gain access to historical and ongoing data.
Spectus POI data also plays a role in the self-evaluation process. When conducting research on a new or existing market, you need to evaluate evolving migration patterns, changing foot traffic trends, visitation data, and external attractions.
It’s no secret that Covid has drastically changed the physical restaurant and retail industry. As retail space occupancy rates decrease, restaurants have struggled while third-party delivery services have skyrocketed. In addition to that, companies have continued to be remote or hybrid. This indicates a need to reevaluate current physical locations and allocate resources to new market expansion.
Layering our POI data with our Stops data, you can understand which location(s) is seeing consistent foot traffic and dwell times. Monitoring dwell time at you and your competitors’ location(s) allows you to understand customer loyalty, shopping, and visitation behaviors. A study found that increasing an individual’s dwell time by 1% leads to a spending increase of 1.3%. Understanding these metrics and your customers informs the operational needs and structure of your location to maximize your customers’ potential spending power.
Visitor purpose for QSR
When it comes to analyzing the competition and health of a QSR market, you need to understand the foot traffic patterns and trip purposes of a location. There are myriad potential trip purposes, like drive through and takeout customers, dine-in guests, gig workers for companies (such as GrubHub and DoorDash), and restaurant employees.
GrubHub, the national food delivery service, saw a 35% increase in customers between August 2020 and August 2021. More orders means more third-party delivery workers entering restaurants. This array of visitor purposes requires restaurants to allocate resources, implement new operational processes, and invest in technologies to best serve each person coming to your location. This could be something as simple as setting a curbside pickup window for carry-out customers, or dedicating team members to fulfill the orders.
By analyzing customer journeys and dwell times, you can gain an understanding of the purpose of different trips. Individuals who spend more than an hour in the restaurant are most likely dining in, while shorter dwell times imply carry-out customers or third-party delivery drivers. Layering dwell time with trajectories data allows you to distinguish between different visitor intent.
Customer trips & habits
Differentiating visitor personas means understanding their behavior and movement around their stops. For example, a gig worker’s trip would be from a restaurant pickup to the delivery location, and back to the restaurant, whereas a carry-out customer would travel from home to the restaurant and back. With Spectus Stops and Trajectories data, you can build a model of visitors to your restaurant and the purpose of their visits by evaluating their behavior around their stop.
The Spectus Trajectories dataset allows you to dig deeper into visitors by analyzing how they are getting around. Trips data allows you to analyze the complete trip, but Trajectories allow you to see the mode of travel. Understanding the predominant mode of travel in an area can help you draw conclusions about larger transportation trends. For example, a study by Transport for London found walkers and cyclists visit stores 50-100% more per month than drivers.
Spectus Trajectories provides the tools to analyze modes of travel and build upon custom trends around your locations, informing inventory forecasts, employee headcount needs, and fluctuating foot traffic over time.