Imagine walking through a dark room where everything you knock over costs your company $100,000. Urban site selection feels like this right now – dependant on out-of-date traffic studies, data aggregators with clunky algorithms, and best guesses from industry experts. But what if we could just flip the lights on, let real data lead, and remove bias from the site selection process?
Urban living is becoming the new normal — already 87% of people in the US live in urban areas according to the US Census Bureau. Brands want to be where people are, but suburban demographics and population data doesn’t hold true when expanding into urban market. So the urban site selection process relies on slivers of data to estimate the potential for new locations but does not give a comprehensive picture:
● DOT offers a snapshot of traffic but doesn’t count pedestrians.
● Hand Counting is only as accurate as the person counting is vigilant.
● Data Aggregators that pull data from everywhere they can: Twitter, Weather, DOT and Tarot Cards. Building black boxes put out nice reports but little of it verifiable.
What is this data-gap costing you?
One poorly placed location can wash away the success of others. A few poorly place locations can quickly turn a successful expansion into an expensive liability. So why do we still turn to these antiquated numbers? Because until now we were looking in the wrong place. It turns out, the key metric in urban markets is pedestrian traffic.
Companies that are able to benchline their pedestrian traffic by measuring external activity at storefronts are creating a new KPI that never existed: the value of a real-world impression. As we know, digital impressions track how many eyeballs see an ad. When compared to revenue, the value of an ad space can be quantified. And subsequently, a minimum level of impressions needed to reach a certain level of revenue can be identified. Taking this outside and into the physical world, companies can quantify the value of a pedestrian walking by and extrapolate the potential revenue of a new location. By pairing the counts with the average sale per customer, companies can create a new, data-based, and reliable standard for retail site selection modeling.
How Pedestrian Counts are Collected.
You need pedestrian counts. What can you do to get them? Send out an intern? Seems like an ok way, but what happens when it’s raining, or your intern gets hungry? Or when they are daydreaming about their next “big-kid job.” What about at night or early morning? Interns aren’t reliable counters. And they certainly aren’t scalable. That’s why Motionloft created the most advanced computer vision sensor on the market to collect counts and report on activity about anything your intern could, but without the pesky need for food, alertness, or work/life balance. Our sensors don’t record video of people; they track actions and relay what they see in the form of small data packages sent over the LTE network. This means we can install anywhere there’s a place for us to plug in.
Motionloft: Why Your Urban Expansion Efforts Will Fail.